I mean really use the tools. Ravage all the features. Exploit every possible button. Produce built-in visualization magic. Poke into the hidden crevices and discover exotic delights. Nourish yourself with the "info snacks" the tool's engineers and product managers cooked up.

This post is all about that.

When it comes to data analysis, you are usually more likely to see me share guidance on advanced segmentation or custom reports or advanced social metrics or controlled experiments or economic value or competitive intelligence or web analytics maturity or one of an infinite number of difficult, if hugely rewarding, things.

Not today.

Today is going to be about healing heartbreak. Ravaging data. Poking and prodding. Nourishing ourselves. And doing so with simple mouse clicks inside the standard tool interface (!) with the reports and features you can already access.

Here is a summary of the eight incredible recommendations in this post:

#1. Create a Customized Dashboard – Earn Love, Drive Change

#2. Leverage Custom Alerts – Let Data Kick Your Butt Into Action

#3. Use Table View Options (Comparison, Pivots, In-line Filters) – Faster Initial Insights

#4. In-Page Analytics – Re-imagine Traveling Through Data

#5. Perform Recency, Frequency & Pan Session Analysis: Fall in Love with People not Page Views

#6. Matched Query Type, Keyword Position, Day Parts: Sexier PPC Analytics

#7. Custom Report Filters, Tabs: Bring Deeper Relevance To Your Custom Reports

#8. Quit Google Analytics: Move Beyond Tool/Creativity Limitations

If you are an Analysis Ninja, focus on the mental model and approach used in each recommendation. If you are an Analysis Ninja in-the-making, close the door to your office/room – you are going to repeatedly squeal with delight.

Ready?

#1. Create a Customized Dashboard – Earn Love, Drive Change!

Who does not love dashboards? Humans love them. Aliens love them. HiPPOs adore them.

So why is it that we don't spend time creating customized ones for our stakeholders? After all, humans, aliens and HiPPOs have different needs.

Pledge to shift away from a one-size-fits-all data puke, and use your web analytics tool to create a customized dashboard.

One day, Google Analytics will default to be the Home tab when you log in, but until that blessed day arrives, just click on the Home icon in the orange top navigation. Then click on Dashboards, and what do you see? Oh yes! + New Dashboard. Click!

I love that phrase "Blank Canvas." So open. So full of possibilities. So much hope and wonder.

Now just because you can do anything does not mean you should. My process is to name the dashboard first. Seems odd, right? But by naming it, I am giving it a purpose; and a purpose requires asking questions and focusing. And great, relevant, dashboards spring from asking questions.

I named my dashboard: VP, Digital. It now has a specific audience and a purpose. Rather than data puking, I'm now forced to go talk to the VP of Digital and ask this question: "What are your business priorities for the next six months?" That will lead to: "And how will you know if we've successfully executed on priority x?" That will lead to: "Awesome, I know exactly which critical few Key Performance Indicators I'll be showing in our dashboard."

Boom!

Every element in the dashboard has a purpose and is tied to a business priority. She/he wants more Social traffic. You, the Ninja that you are, are showing all segments of traffic to give context (you rock!). She/he wants time on site, you have no idea why, but you add it (along with a sparkline that shows the trend – sweet!). It is a content site, so rather than silly things like page views you use Loyalty (more on this below) and you also show consumption of videos (events). Finally, you bring together Conversion Rate with the Goal Value delivered by the Social obsession.

Charming!

Pro Tip: Always, always, always let the Acquisition, Behavior and Outcomes framework be your guide. After you've created a dashboard, check to see that you have all three elements. If you don't, you are not showing the end-to-end picture. Without this you fail in your duty (and the data recipients will make poor decisions).

Create a customized dashboard for your Search team, one for your Display team, one for the folks doing onsite merchandizing, one for the nice lady that owns the ecommerce shopping cart and all the other key clusters of your audience. Give them hyper-relevant starting points, collections of "info snacks."

The cool bit is that in addition to standard widgets and simple tables, you can also bundle along your smarts into the dashboard and delight your users.

One way is to use the awesome built in inline Filters feature when you use the dashboard widgets, to show just the data that is relevant (did I already say less data puking? :).

In this case, I've done that by adding a filter to segment revenue to only show social value.

And it is not all social media, it is just the money made from the company's own social media efforts by using the right campaign parameter. I'm (secretly) trying to show the VP how much (or how little!) money our own efforts are generating. Smart widget, smart insights, smart decisions.

So go forth and multiply! Create a small cluster of hyper-relevant (secretly smart) dashboards!!

#2. Leverage Custom Alerts – Let Data Kick Your Butt Into Action!

Sometimes (actually frequently) it is not enough to rely on our own diligence in terms of remembering to log into SiteCatalyst and look at the right set of numbers (across a hundred reports!) to know what's up with the business. It is especially undesirable to be surprised about something awful happening to our digital existence.

We can't predict the unknown unknowns easily, but we can be magnificent at proactively identifying the known unknowns by leveraging the custom alerts feature in our web analytics tools. Here's a screenshot from Google Analytics:

These alerts will let you know if engagement on your website crosses certain thresholds or when the bounce rate spikes for traffic from Google or if there is a spike in conversions (praise the lord!). All things you know will happen, you just don't know when. Known unknowns.

With smart alerts set, you don't have to remember to check the data every eighteen seconds. An email, or a text message, will poke you into action. Your boss will be impressed at how you seem to always have your act together!

Here's one of my favorite custom alerts. I would like an alert when goal conversion rate for any day is greater than 25%. My normal is around 18%, so if it jumps up by that much I can get an alert and I can do deeper analysis to figure out what might have caused the spike.

You pick the period for comparison, your the necessary dimension and metric, add the condition, type a value and you're in business.

If you don't have at least five custom alerts set up, you can't call yourself an Analysis Ninja in training. At least not a serious one.

Five of my favorite alerts are in the second part of this blog post: Identify The Known Unknowns: Leverage Analytics Custom Alerts Here are more clever examples from the team at Google: Five Custom Alert Examples

Don't rely on yourself to remember to look for your site’s magic moments. Put yourself in position to be proactively informed when they happen.

#3. Use Table View Options – Faster Initial Insights!

Enough dancing around the outside of the tool. Let's rip off our clothes and jump into the cold inviting water!

It is very hard to quickly understand a lot of numbers when they are presented together. When you log into WebTrends or Google Analytics or CoreMetrics, you're lucky if the standard report does not contain five or seven metrics at the very least for every table row. Data puke!

Not only will you not see the forest, you'll be lucky to even see the trees.

My preferred path is to leverage the tool's built-in features for filtering/visualizing the data.

In Google Analytics there are a few super cute options. Click on the table like icon next to View. You can see five different ways to look at the data in any table: Percentage, Performance, Comparison, Term Cloud and Pivot. All exist to make your life easy.

My personal favorite is Comparison. This option takes the site average for a metric and compares the individual performance of every row to that average, and it visualizes the data for you.

For the top websites that refer traffic, I wanted to know quickly (without having to do the math) which source sends traffic that tends to see more than one page. AND I want to know contextual performance of every row with site average AND every other row. Hard? Nope. I simply choose Comparison. Then I choose Bounce Rate. And in two seconds…

Like every two-year-old child, I know that red is bad and green is good. GA is telling me is that Twitter (t.co) traffic bounces 14.59% more than site average. Ouch.

Scanning the rest of the table, remember I want contextual performance analysis, I can quickly see that I should love the GA blog, Linkedin and SEOmoz more and other folks a little less. :) But I am also now a lot more curious about Ycombinator. That is a lot of traffic. What post on YC did they come from? What content did they read here? Why might they not have cared for anything else? I can analyze and then identify an specific optimization/engagement strategy to reduce bounce rates.

You can literally do this for any metric in the standard tables in GA. Try to look at your top 25 campaigns and compare conversion rate. Or open the new search engine optimization reports in Google Analytics , for your Queries look at Impression and try Comparison for CTR.

Pretty cool. But that is not all.

I've always been partial to pivot tables in Microsoft Excel, hence it is not surprising that my second favorite view option in Google Analytics is Pivot.

Now I can create a lovely report, for example, to find "arbitrage" opportunities across search engines? Here's how you do it.

1. Go the keywords report (in Traffic Sources section). From View choose Pivot (as above).

2. Click on the box next to Pivot, type in Source, select it.

3. Click the box next to Pivot metrics and choose Visits (or whatever else you like, go crazy!).

4. Look at the performance. I typically look for anomalies. For which keywords do I get more traffic from Bing when compared to Google. Or Yahoo! compared to Ask, etc.

Every search engine's SEO algorithm is unique. For example I get twice the traffic for "digital marketing" from Bing than from Google. I use the data above to customize my SEO strategy for each search engine.

You can use pivot tables in pretty much every GA report.

In this case, I can more easily figure out which of my top pieces of content are delivering the micro-conversions that are valuable to me. I track these micro conversions as Events, here's my Pivot table:

Use your creativity when it comes to pivot tables and you'll be delighted at how wonderfully they help you answer hard questions.

One last bonus item when it comes to using tables in web analytics tools spectacularly: Use the in-line table filters. Just click on the link called advanced next to the magnifying glass on top of the table you are viewing (in any report).

Now, rather than looking at half a million rows and trying to find an answer, you can simply type in your question. In this case I only want the rows of data (keywords, campaigns, pages, products purchased, videos watched, whatever) only for those people who:

1. Saw more than 3 pages during their visit AND

2. Entered my website on the cluster of 900 pages about Aruba.

These people are of particular interest to me … I click Apply and, voilà, I have them cornered!

Using this strategy I can go to the standard table with hundreds of thousands of rows of data and quickly only look at data for my brand keywords or just for my email campaigns or just for people who visited more than 10 times or just for those who came via Yandex or just those that read a segmentation post or just those that donated or…. anything. And I can do it fast.

Why stare at a table, or worse just the top ten rows, wondering what to do? Speed up your time from data to information by using the Comparison view, Pivot tables and in-line Filters.

#4. In-Page Analytics – Re-imagine Traveling Through Data!

This is one of the hidden gems of Google Analytics, especially for traversing lots and lots of data in context of the web page itself. It is fantastic at communicating data, complex data, to people whose primary job is not data analysis.

The In-Page Analytics report takes all the data you would find in the Explorer and Navigation Summary reports (essentially all the links you have on a page and their performance) and shows it to you in an elegant visually appealing view.

There are two ways to get to this report.

1. Just go to Content > In-Page Analytics.

2. Go to Content > Site Content > Pages, then click on the URL you want (or use the in-line table filter mentioned above to find the URL), and click on In-Page at the top.

On top of the report you'll see the scorecard, or aggregate performance of the page via metrics like Pageviews, Unique Pageviews, Time on Page, Page Load Time (!) and Bounce Rate. Having the % of Total (grey text, small font below) provides great context.

Below that, in blue, green, red and orange I see the percentage of clicks on each link. I don't have to infer data in the table, it is all laid out for me nicely!

And note the orange bar at the bottom, it is particularly nice. It shows how many people click on links below the fold. The fold is defined by your browser size. As you resize the browser windows you'll see that number dynamically change. This data is extremely valuable for long pages, especially if you have valuable links below the fold. IF you're New York Times or Amazon, you want to know if people scroll!

This is so important if you are responsible for merchandizing. If you have a few different layouts of your web pages, this is a great way to know which links, promos, and annoying dancing banners are attracting the clicks.

But you don't have to watch clicks. Aren't clicks are the new HITS :).

You can click on the Viewing drop down (#1 below) and choose any goal. When you choose a goal, the display changes to show what percentage of people who click on a particular link go on to complete a goal in that same session!

In my case, below, 15% of the people who click and read the comments end up meeting my goal of going to Market Motive (and hopefully sign up for the Web Analytics Master Certification program!). But only 1.9% of the people who visit the Digital Marketing section of the blog do the same.

In this case you can also see that the links on the top are especially valuable for this goal. Only 9% of the people who ultimately went to Market Motive clicked on any links below the fold (and the fold here is pretty much the top of the blog post!). So I have to be particularly good at the information architecture on top of the page. Once they scroll, the chances for goal conversion go down dramatically.

I can do this type of "conversion click" analysis on any of my 8 goals. How awesome is that? With those insights, I can go and optimize my key pages for my individual business goals.

Imagine what you can do with your home page optimization if you know this. Now when everyone wants a link on the home page or the category pages you can show them which links your visitors are actually interested in and let data fight your political battles!

I rarely find anything really sexy (in an analysis context :) unless it comes with segmentation. You saw that in every single recommendation above. And my choice for this report is no different. You can segment like crazy.

When I use the In-Page Analytics report I don't want to look at all the traffic in one ugly bucket. I want to analyze groups of like type people, like type behavior. For example, I want to know how the behavior of search traffic is different from direct traffic. How hard is it? Three simple clicks…

1. I click on the Advanced Segments drop down and choose the standard segments (or one of my 50 custom segments).

2. I click on the In-Page tab to go to the report. (I was in the Pages report.)

3. I choose the metric I want. In this case I, selfishly, want to know if there is a difference the money I make (Goal Value) if Visitors from Search and Direct traffic click on the exact same link on the page.

4. Bam! Bam! Bam!

There is a substantive difference. When people come from search I make $142, on average, when they click on that link, but if they are direct I only make $58 (boo!).

Imagine what a gift this is when it comes to figuring out how to create the best landing pages. I know what the Search Traffic gravitate towards, I can now optimize their experience on the site rather than serving them random/generic links!

You can do this analysis for social media visits, for a particular keyword, for people who watch videos or download catalogs or, well, anything you can segment in Google Analytics (which is pretty much everything).

Forget tables. Be sexier. Let your site tell you what to do.

But there is one fly in the ointment.

The implementation of In-Page Analytics in GA is frustrating and silly. When you first go to see that report (if you are using Internet Explorer), you are going to see this insane warning:

If that box was not scary enough, the whole darn text is wrong. My ga.js (and most likely yours) loads from Google, and I have the snippet on my site. #aaaarrrrrhhhhh

In addition to the above you'll also see this at the very bottom of your browser window at the same time…

So, how do you make this report work?

It is supremely annoying that the Google Analytics team and front end does not make that clear.

But it is simple. Ignore the first error, and click the "Show all content" button on the second error. Magically, everything will work.

If you are using an older version of IE you might see this error:

Classic useless error. Don't click the default Yes – just click No and the report will work fine.

In Chrome, mercifully, it works fine with no errors.

While it is disappointing that the error shows up initially, the report itself, as you can see above, is quite valuable. I hope you'll give it a chance.

#5. Perform Recency, Frequency & Pan Session Analysis: Fall in Love with People not Page Views!

I'm a big fan of pan-session behavior. What happens across multiple visits by the same person? (And are there multiple visits at all in the first place?)

Having grown up in the traditional business intelligence and direct marketing world, I'm also a huge fan of RFM analysis .

In Google Analytics, you'll find them in the Audience Section under Behavior.

Here is a great example of the type of business-critical question you can answer with these reports. We are a photo-sharing website (think little sister of Flickr ). We make money on content consumption (via display ads) and premium subscriptions to the site. But we can only make money if other people come and upload their photos, and still others come to view those photos. Long-term success is achieved if our audience becomes loyal and we don't have to keep spending money on Google and MSN and Yahoo! renting traffic.

So, are they loyal? Check out the Frequency (count of visits) report. It shows how many people visited only once (42%) and how many 2 times and 3 times and… so on and so forth.

For this business the results are fantastic:

While a chunk of people come only once and never again, notice how bottom loaded the report is. 43% of the traffic comes to the site between 9 and 200 times in a month! That is loyalty! We can feel better about our marketing and engagement strategy.

How about for your site? Are you having one-night stands or building longer-term relationships with your audience?

Another nuance of loyalty is that you not only want people to come to the site multiple times, you want a shorter gap between two visits. You're looking for recency. This report show us how spectacularly we are doing for our photo site:

The vast majority of visitors visit the site every day! Analysis Ninjas know that the 83% number above includes new visitors to the site, so we should subtract that (why are web analytics tools so annoying some times!). But, it is still a huge number, and we should be happy.

How about for your site? Does the recency line up with, for example, the rate at which you publish new content/launch new products/execute new marketing campaigns?

Another facet of pan-session analysis is looking at the number of visits it takes to convert our visitors. Not everyone wants to marry you on the first date, right? (Yet almost all digital marketing and almost all landing pages are constructed as though this were the case. Sad.)

My favorite report to use to answer this question about customer behavior is the Path Length report in the new Multi-Channel Funnels section in Google Analytics.

In our case, around 23% of our conversions happen in the first visit, and then there is a long tail and then look…

OMG! 48% conversions that took 12+ visits to convert! We can specifically look at that segment of customers and figure out what combination of Google, Atlas, YouTube and Email Marketing (or whatever) it took to get that conversion!

We can use this data to create better experiences for our users. We can optimize the ads and marketing messages (across channels) it took to get these folks to come to our website multiple times, prior to conversions.

This is hard work. Most definitely senior Analysis Ninja work. But that is how you win big. When you skip this type of analytical effort, you doom your company to live on scraps. And really, who wants that?

#6. Matched Query Type, Keyword Position, Day Parts: Sexier PPC Analytics!

I've always been a bit miffed that most web analytics users are less than sophisticated when it comes to analyzing search/AdWords campaigns. So many companies spend so much money. Why not do some incredible analysis? Especially when our web analytics tools make it so easy.

My first example is a good representation of that.

Most people don't realize that when you view the keyword report in the AdWords section, you are looking at the key words/key phrases you bid on, not the queries that were typed by users into Google. If you base you AdWords success on just the keywords report, you might end up making substantially poor decisions.

For that reason, I love and adore the Matched Search Queries report (in the Advertising section). It shows what users typed into Google when your ad was served. The report is standard in Google Analytics.

All you have to do is click on the box next to Secondary dimension and type in Keyword. Now you are looking at both the word you'd bid on (right) and the word the user typed (left):

You can quickly see the differences between your bid and the matched query (#2 above). The next obvious step is to look at the performance and optimize your Match Type strategy based on the results.

In the screenshot above you can see that the keyword bid on was "calico critters toys." Those ads were matched to the user queries "little critters toys" and "calico critters cloverleaf manor." And there was a 9 points difference in the bounce rate (ouch!). Good to know. Go back, optimize your match types in AdWords and optimize your landing pages.

Fun right?

My second favorite? Keyword Positions report. Why? SEOs obsess about their rank on the search engine results page (SERP). That obsession is often valueless. But for your PPC campaigns? Obsession will deliver glory!

So why not analyze which position your ads show up in when it comes to AdWords?

A combination of your max bid, your quality score, match type will determine the position of your ad for every search query. Google Analytics will show you that information beautifully.

Here it is…

Just click on a keyword and the visualization on the right comes to life. Now you are better able to determine which position gets you the most clicks. Top 3 is better than Top 1 (the position your boss was obsessed about – "I WANT #1 RANK!!"), and neither can beat Side 1 (the cheaper position!).

Another lovely thing you can do with this report is look at the performance once those clicks (ok, people) land on your website. Just click on the down arrow and choose the metric you want, Bounce Rate in my case below:

You can see that every position has a bounce rate. Side 1 still has the best performance. You don't have to just use Bounce Rates. You can also use % New Visits, Time on Site and Pages/Visit as your metrics. The goal is still the same: find the position that delivers best performance.

If a position works optimally for you, then you can use AdWords Automated Rules to have your ads show up in particular positions.

You use your money wisely and get higher ROI. #winning

One small bonus tip: I love looking at the AdWords Day Parts report a couple of times a month. Most of the time, the data shows the normal trend, more clicks and conversions during the business day.

But every once in a while for certain keywords, or segments, I'll discover that the pattern is very different. For example, you can see below that the conversion rate actually peaks at midnight…

We did not know that people were searching for us late in the night, and they were highly qualified (!). Hence sadly our AdWords budget was capped at that time, we did not to "waste" money. Sad. Once we saw this data we loosened up the budget and picked up loads of extra conversions.

You'll discover other delights like this. In the view above I'm using the Compare Metric feature of Google Analytics. It is cleverly hidden in light gray text on white background on the top right of the main graph in every report. Just click on the drop down and choose the comparative metric you want.

If you spend money on AdWords, be smarter about the analysis you do. There is no better way into your boss's heart. If you spend money on other types of campaigns, I hope you'll find inspiration above to do interesting off-the-normal analysis.

#7. Custom Report Filters: Bring Deeper Relevance To Your Custom Reports!

It is hard to keep pace with all the changes that web analytics vendors make to their tools. I wanted to share two clever features in Custom Reports that make them even more super magnificent (and mandatory if you are a Ninja!).

The first one is the filters that are built right into the custom report you are creating.

I love custom reports because you don't have to data puke any more, you can just show the data that is needed. [Helpful post: Leverage Custom Reports For Better Insights]

Now you can focus even more by embedding the segments your leadership cares about right into the report!

Above is my awesome Visitor Acquisition Efficiency Analysis report (click link to get it). But if my leadership team is only interested in understanding how good the company is at acquiring mobile traffic, I can include a filter right into the report (see above) to just show mobile traffic.

And if they only care about USA (and why not?), I can limit my custom report to show just that. Why bug them with everything?

Now my custom report is not just relevant, it is hyper-personalized. I have shortened the distance between data and insights.

Your imagination is the limit in terms of the clever filters you can build into your custom reports.

Second tip on custom reports: Create micro-ecosystems.

I was not too pleased with the eight or ten standard mobile reports and their data views and all that. So, why not create my own custom report? Wait, not just a custom report but rather replace all the standard reports with my one Awesome Mobile Report? [Click to grab it!]

My primary strategy was to create three tabs. One for device drill downs and metrics, a second one for search performance, and a final one to understand performance of content:

Each tab has specific metrics relevant for just that dimensions (Device, Search, Page), and it is all in one place to give decision makers one go-to place for all their mobile performance needs.

Same outcome: Faster movement from data to insights.

You'll know you are an Analysis Ninja when you can replace 100% of your company's reporting needs with just five such micro-ecosystems. (Not 100% of the analysis needs, 100% of the reporting needs.) It is entirely possible, and think of how easy your life will be then…

And I have to tell you it is a tremendous amount of fun.

One final, surprising, way to do the data hustle with GA…

#8. Quit Google Analytics: Move Beyond Tool/Creativity Limitations!

Sometimes all the reports and features are simply not enough.

You can't understand why it is impossible to see Keywords in rows and a monthly count of Visits in columns. Weird, right?

You can't fathom why something so amazing and straightforward as tag clouds are so uncool and utterly useless in Google Analytics.

You are frustrated with the insane report/table formatting requirements by your business leaders. They want a particular font type, or your dashboard goes into the junk folder!

When you run up against the tool's limitations, weird implementations by tool vendor, or hard-to-please clients… quit the tool. Get the data out. Unleash your creativity.

It is, of course, possible to take data out of Google Analytics. The straightforward way is to simply use the Export button in the top nav.

The problem is the second image above. You can only download 500 rows easily, when you actually, in this case, have 122,397 rows of data. [And you all know how much I love mining the long tail by moving beyond the top ten rows of data! Not possible with 500 rows.]

Option one is simple, yet slightly painful: "Trick" GA into giving you all the data that you want to download.

Happy?

Now here's the caveat.

Using the method above it is possible to download all of the 122,397 rows of data. The challenge is that you might not have enough cache allocated to your browser. Or you don't have enough memory. Or you might have an older browser. Or one of so many things that will cause your browser, not the web analytics tool, to hang. It is just hard to get that much data rendered into a browser.

Of course where there is a problem, there is an incredible solution.

If you want to export all your data frequently just use the free Google Analytics API. It is pretty cool. [Tools like WebTrends and Adobe have APIs as well. WebTrends is free, for Adobe API pricing please call your Account Rep.]

If you want to have a quick naughty flirtation with the GA API, visit the Data Feed Query Explorer. If you enjoy that (and you will, because that is what naughty flirtation is all about) get more context about the Google Analytics Core Reporting API. End your journey devouring the handy dandy Dimensions & Metrics reference guide.

Now allow your inner geek to rejoice!

If, like a majority amongst us, you want to skip the flirting and jump to marriage, mosey over to the Google Analytics Application Gallery. Everything you can dream of is there. Data Warehouse integration? There. Business Intelligence? Got it. Campaign Management with a side of Email Marketing? Sure. Mobile Apps and Widgets and Gadgets? Absolutely!

It is pretty cool to use the API to integrate your offline phone call data with your Google Analytics data, understand the demographics, gender, income, etc. of people who come to your site, or overcome the sub-optimal standard GA Funnel report by using PadiTrack.

Going back to extracting data efficiently and making magic, three apps you'll find particularly useful are Excellent Analytics , Nextanalytics and GA Data Grabber.

Excellent is free (hurray!). Nextanalytics costs $199/year and GA Data Grabber costs $299/year. Both tools are full of pre-built dashboards, reports, cool visualizations and easy ways to collect data from tons of sites and pull it all nicely into one report. Both also contain loads and loads of automation capabilities. They allow you to shift from 90% data collection and 10% actual work, to 10% data collection 70% data analysis 20% social media time-wasting. What's not to love? :)

It may seem odd to spend money on a free tool. But not paying just one dollar a day to make your life better is most likely a Class 1 analytics crime. Don't commit crimes!

Regardless of if you use WebTrends or Google Analytics, the API allows you to do better reporting, smarter analysis (with offline data) and automate the mundane. Create a better life for yourself.

So that's it.

Eight simple ways you can hustle with data, convert skeptics, earn the love of your website visitors, and improve profitability of your web business. All without leaving the confines of standard reporting features already inside your tool (except that last tip).

I hope this post will accelerate your mastery of Google Analytics (or IBM or Yahoo! Web Analytics or Open Stats). And I hope it will mean less time spent wrestling data and more time taking action based on intelligent insights.

Good luck!

As always, it's your turn now.

Are the strategies outlined above already a part of your daily data hustle? Which recommendation surprised you the most? Which one do you think is most over-rated? If you are a GA power user, did I miss a feature or approach that you love a lot? From your experience, with any tool, do you have a tip to share with your peer readers?

It would be wonderful to hear from you. Please share your feedback, ideas and awesomeness via comments.

Thank you.

Google Analytics Tutorial: 8 Valuable Tips To Hustle With Data! is a post from: Occam's Razor by Avinash Kaushik

It is a lot easier to predict the present. So I'm not going to do that either.

Rather, I'm going to share a clump of realities/rules garnered from the present to help ready you for the predictable near future . Now here is the great part… if you follow these rules and act on these insights I believe you'll be significantly better prepared for the unpredictable future.

Awesome right?

Now here's another surprise: These rules/insights/mind shifts are not about data!

Here's important context (before we get into the rules for revolutionaries)…

The Fundamental Web Analytics Problem Is Not Data!

A huge part of the last few years for me have been about bringing more data, better strategies, more powerful tools, ever more impactful keynotes to people around the world.

One of my biggest learnings?

Most companies are astonishingly blasé about data and possibilities of measurement. Most web "analysts" remain glorified "data pukers" or glorified JavaScript taggers.

Why?

The problem, it turns out, is not data. The problem is only partly the data pukers or JavaScript taggers. The real problem is that our management teams lack imagination when it comes to the web, and our marketing executives continue to do TV on Twitter, catalogs on display ads, irrelevant shouting on search, etc.

That frustrating reality is the source of numerous problems for the company (and the web as a whole), but it also means Executives ask for unimaginative data. "Count Impressions, in real time!" "Show me Clicks and the count of Facebook Fans!" "My dashboard should have Page Views and Exit Rate!" Sad, unimaginative measurements of their sad, unimaginative campaigns.

If you are doing lame stuff, why try harder in an analytics context by asking for Economic Value or Visitor Loyalty or Conversation Rate or a thousand other super powerful and insightful metrics ?

The problem is not analytics or data (or your blood, sweat and tears). The problem is Marketing and lack of imagination in using the web/digital channels.

And here's the thing… if you are a "Web Analyst" in the broadest sense of that word, then this is your problem. Solve it or suffer the indignity of making decent money doing work that will have no impact on your organization. If you are a digital marketer then this absolutely is your problem. You're the massive, under-appreciated, hidden part.

In the last eighteen months or so, I've spent a lot of time trying to solve that problem. Get the senior-most people in the largest companies in the world to unlock their imaginations when it comes to their digital existence via impactful digital strategies. Convert them to be revolutionaries for their companies and customers.

I've discovered that if we can just get them to imagine a better existence, undertake serious risks, experiment with new better ideas, and spend money executing them… they will ask for more robust measurement! Because you need serious new good analysis to understand the impact of serious new good stuff!!

In the same spirit, if they don't do wonderful, beautiful, imaginative things, we people who play with data will continue to play a marginal, at best, role in most corporations in the world. Even if these unimaginative companies spend a ton of money on Omniture, IBM, WebTrends, Yandex Analytics and Google Analytics, we digital analysts will lead unimpactful puking tagging lives.

And no one deserves that.

In case you are reading this and you are the aforementioned Digital Marketer, then your life is sadder still. How good can it possibly feel to do unimaginative things that barely even worked on TV/radio/magazines/catalogs?

Whether you are the Marketer/CMO or the Web Analyst/Ninja, it is imperative that we unleash imagination.

Why doesn't everyone do that already?

I know that this sounds utterly simple but we, people and companies, don't always realize that the "rules" have changed. Our mental model has not shifted enough to the existing reality. This lack of internalizing the rules jeopardizes our current state to some extent, and our future to a significantly greater extent.

A lot of my work is making companies realize the implications of these rules on their company strategy and structures. You've probably seen these rules sneak into my blog posts. I want to share them below as a collection with the hope that it will motivate you to create a veritable primordial ooze from which new ideas (or indeed life) will spark for an imaginative digital existence.

7 Rules for Digital Marketing Revolutionaries!

These are my observations on changes already underway, changes that are dramatically affecting what marketing is and should be. You might have observed at least some of them in bits and pieces, but perhaps you have not considered them as a whole. Adapting to the implications will allow the creation of a more future-proof you.

#1 Customer expectations on the web are insane, will get super-insane.

We expect more.

High bounce rates show how horrible slow-loading websites are. Lack of loyalty shows simply re-publishing AP stories is useless. After 19 visits, www.bloomberg.com should create a home page around my interests, not their one-size-fits-all pimping to everyone. With an iPhone there is no friction between me being in your store or on your site (or, omg, getting a mobile geo-targeted coupon from your competitor for 5% off your price while I'm in your store!). There are 12 different alternatives to your site that provide free return shipping. Just because your site is B2B, you do not have the right to create a 1940s website and force visitors to type their name, precise GPS coordinates and underwear size to get a PDF that should have existed as a webpage in the first place (as HTML has been invented).

It is no longer acceptable to just meet past expectations. Alternatives to you are one click away, one Google search away, one tweeted recommendation away. Aim to meet super-insane customer expectations and you'll future-proof your business.

Oh and yes, I do get that this is hard. You have to rethink everything. Price of greatness, sadly.

#2 Multiplicity: Competencies, Campaigns, Systems, Everything.

This is something we are most unprepared for.

You can no longer be good at just one thing, or two. It is a 10-thing world now (and maybe a 20-thing world soon).

If you are a catalog company you have to be good at catalog marketing (as long as it continues to provide incremental revenue ), and you have to be good at NASCAR (as long as it provides incremental revenue), and you have to be good at Facebook, and you have to be good at email, and search, and YouTube and… a hundred other things. All while constantly optimizing your portfolio via controlled experiments .

You have to be good at sourcing your products and you have to be good at delivering them.

You have to be good at using clickstream and surveys and competitive intelligence and heuristic evaluations.

You have to be good on every device of every screen size in every country with a monetizable audience.

You have to be good at… many things all at the same time. For far too long we've been able to be successful by relying on our sheer strength on one thing. Catalog. Paid search. YouTube. Billboards. TV. With every passing day that strategy now ensures we are rejecting tons of revenue and tons of prospective customers.

It is hard to rewire the company's DNA to truly execute a multiplicity strategy. That's why you allocate 15% of your Marketing budget to getting good at multiplicity. All the time.

#3 One-trick ponies are going to be a liability.

This is a subset of the one above, but I wanted to call it out separately because I am madly, deeply convinced of its importance.

Increasingly, your people can't be one-trick ponies. Especially not people you consider stars.

If your Marketer is not savvy in basic finance and analytics and writing some html and creating mobile campaigns and tag clouds then you have a long term liability on your hands, and not an asset who is really, really, really, really good at writing copy for display campaigns.

The web demands immense agility and flexibility from every company. Having one-trick ponies can limit your capacity to think smart and move fast.

If you have an Analyst who is just good at Omniture and has never done an online usability study, and used Compete, and taken a whack at a rough digital P/L, then it is time to set them on a path to evolve, or get someone else.

If you have a Finance person for your web business who has never run campaigns on Facebook, and who doesn't understand the uniqueness of mobile applications, and a little bit about the insanity of ad exchanges then over time try to hire someone who does.

At one time, it was okay to be 100% good at one thing, and only one thing. But today companies with people who are 70% magnificent at one thing and have filled the remaining 30% with being good at everything in the periphery of their jobs will rule this world.

You want to change HR hiring practices now to nurture such 70/30 people inside your company, and to make that a mandatory condition for all new hires. Then you'll rule this world.

PS: Here's the raw brutal truth for you dear reader… no company is going to invest in you. The most precious Digital Folks are those who choose to invest in themselves, on their own time. Especially in the 30% area referenced above. Now you know.

#4 Attention is the most precious commodity.

We live in a hyper fragmented world with, quite literally, hundreds of TV channels, thousands of social connections and millions of websites. The single biggest gift any brand can get is attention. And not just the few seconds you get by showing 19 ads on one web page, or tweeting one relevant link in 1000, or showing the same ad for DirecTV six times while watching one 23 min program on Hulu, or showing up for a query for "flights to Sao Paulo" when you only offer flights to Europe, or… a million other ways.

Attention results from understanding the true strength of each channel and then engaging uniquely with your audience. Here's a good example. I bike ride a lot. I walk a lot. In general, I'm a big fan of exercise. I would follow Gatorade on Twitter with the exercise connection of that brand. But you know what they do on Twitter? They retweet other peoples tweets about them. The most lame thing you can imagine using Twitter for. (That is if they don't waste time with condescending tweets like "We've got your back xyz.")

How could Gatorade have my attention? With a Twitter stream about hydration. If their tweets supported their bio on Twitter: "Helping athletes get the most out of their bodies before, during and after activity." I could not find a single tweet of the 250 I reviewed that fell in that category. Why not try that? Why not go for grabbing my attention and then keeping it? Why not go from trying to have a Gatorade ad on every TV sports event in the hopes that I'm watching to doing that plus doing social media right and have a direct relationship with me?

Not one or the other. Both done exceptionally well. That's how you earn attention.

Or consider this example. Why do Priceline or Expedia mobile apps only do prices? Why do they not have a TripIt-like functionality built in? If they did, I would go having to remember which app to use to search for a hotel to having an app that is central to my life (and TripIt provides such value that it is) that I use all the time and that I will of course use when I have to think about booking any travel.

Get it? Attention. Via incredible daily utility.

One more example. With 55k RSS Subscribers and 110k Visits a month, this blog could make a few dollars with AdSense or Display ads or annoying interstitials offers. It could also make a few more dollars constantly pimping my two books in posts. Yet it does not. It simply gives you content (my goal: "incredible, relevant, of value"). You see, I don't want your AdSense clicks. I want your attention. And I know I can monetize that 100x all other things combined.

So what is your business shooting for online when it comes to digital marketing? What are you doing to earn, and keep, attention?

#5 Brand destruction is insanely efficient now. Beware!

United breaks guitars. Kenneth Cole goes too far with Egyptian protests. Gap logo. Bank of America everything. You can add 100 more examples in 100 seconds.

Those are big ones. But there are small ones too. I told 20 people that Nikon's site is slow and profoundly sub-optimal on mobile. (Guess what I had on hand when I saw their sexy ad on TV? A mobile device!) Now these 20 people will tell others. Small, silent brand destruction.

Yet so few companies have built organizational capabilities with this efficiency in mind. The distance between a story and an audience is six pixels (as my friend Mitch Joel might say). It is ever more important to live your values, walk the talk, deliver what you promise, not say stupid stuff, be real and accessible, and all those delightful things.

You see, the power that can so efficiently destroy your business, is also the power that can boost you to untold heights. And that's marketing money can't buy.

Oh, and you are right that people bought Kenneth Cole stuff even after the insensitive tweet because only a few people are on Social Media. The challenge is that everyone will be Social in ways they can't even imagine. Then we move from six pixels to two. Then what will you do?

Imagine a better future for your company.

PS: It is no longer optional for you to just create TV ads and not have the most brilliant, engaging and helpful mobile websites. In case you were wondering, the year of the mobile was two years go.

#6 Being good at the Long Tail matters just as much as the Head.

I've talked about the long tail on this blog, especially in context for Search. But the concept applies across all channels.

Here's a good example. You can spend all your money on the four standard channels on TV and get in front of 1000 people. But you can probably find 1000 people *relevant* to your brand and message by advertising on 28 *relevant* channels in the long tail (those after channel #14). Or the relevant 50. It is much harder to do, and much harder to explain to your boss who is still looking at GRPs, as GRPs for the long tail mostly don't exist. But if you do, you'll be more efficient, shout less, and deliver more value to your company and delight to your customers.

In every channel we have, Facebook or YouTube or Google or AOL or AdMob or pick your favorite, we have the capacity to shout at concentrations of irrelevant people, or show up for the dispersed hyper-relevant few. While I can't dissuade most Executives from the former, I try as hard as I can to help create strategies for the latter. I'm convinced it is the ability to do the latter that makes you future-proof.

Oh, and this is why Multiplicity matters (TV AND Catalog AND Mobile). This is why owing your own strong digital outpost (your own website) and being present in a space someone else owns (Facebook) matters. This is why having multiple trick ponies matters. They combine to get you really good at the Long Tail execution complexity and massive bottom-line benefit.

#7 Glory will come to the precious few who are willing to embarrass themselves.

We don't take risk and try things, imaginative (possibly glorious) things, because we believe the price of failure is so high. And it is in the real world. Consider creating a TV commercial or re-packaging a product or trying a new offer. First, it takes a very long time to actually try something (add longer plus infinity for risky things). Second, when you fail, you fail spectacularly. Heads roll. Companies get entrenched in what they know and end up constantly optimizing for what's always worked, meanwhile the world changes and these companies die, albeit slowly.

Now consider the web. You can have your most embarrassing idea for a redesign/new offer/product launch/whatever out there in one day. AND you can control for risk! You can only show the redesign to 1% of the site traffic. You can try the offer with just one affiliate or some Bing ads. You can launch the product to a selected group of opted-in customers (or only to people in New York). You can literally control for risk should everything blow up in your face. AND you can have analysis of your risk in almost real time to get an early read and in a few days with statistical significance!

And yet it is the rare company that is able to get over its mental model from the real (old) world and try imaginative things in the digital world where the rules are different and stacked in your favor. Yes, brand destruction is easy in our world, but we are not talking about destroying our brand. We are talking about taking controlled risks and optimization. What marketing program in the universe does not need that?

If you are an executive, encourage your company to check its old world thinking at the door. Consider rewarding people with new ideas. Allocate some of your aforementioned 15% budget to experimentation and testing. If you are a large company don't live without someone with strong Design of Experiments skills. Don't brush off Twitter or Google+ because you are B2B or A2K. Try. With 100% effort . Then do more of what works, or kill ruthlessly.

If you can't embarrass yourself, in controlled quantities, you can't become magnificent. and you can't future-proof your company.

Bonus: #8 Data is your friend.

You did not think I would miss this one did you? :)

This blog is about the joys of measurement and the transformative power of data. So I won't talk about it a lot more in this post.

Let me just say this… more of marketing is becoming algorithmically driven and a lot more decisions we make using reports today are being automated to be made faster, more efficiently, on our behalf. The ability to have a real analytical competency will mean the difference between winners and losers.

So do the 7 things above, but ensure you have a clearly articulated Digital Marketing & Measurement Model. Fill it with the best web metrics to measure success. If you partake in analysis, let that be at the intersection of custom reports and advanced segments.

Data + You = BFF = Business & Personal Success.

Eight simple rules for digital revolutionaries to follow in order to unlock the imagination of their companies and be massively successful in the future. Absorb them. Undertake the very hard task of slowly evolving your company to adapt to them. Monetize the opportunity presented, future-proof your company.

I wish you all the very best.

It's your turn now.

Do you agree with my learning that our primary problem is not web analytics/data but, rather, it is unimaginative web strategies? Have your own stories to share about brand destruction? Do you agree with the eight rules for revolutionaries above? Got your own?

Please share your feedback, ideas and awesomeness via comments.

Thank you.

The 2015 Digital Marketing Rule Book. Change or Perish. is a post from: Occam's Razor by Avinash Kaushik

In this blog post we are going to bring the sexyback. I am going to attempt to significantly simply your life by recommending the critical few metrics you should use to analyze performance of your digital marketing campaigns and website. You'll be able to quickly go from "omg what can I do!" to "omg what am I going to do with all the money and fame I'm earning!"

The approach I'm going to use is to 1. Use my Acquisition, Behavior and Outcomes framework to ensure an end-to-end view of important activity and 2. Recommend metrics / KPIs you can use based on the size of your company.

Each recommendation comes with hints on what analysis to perform once you have the data, and what changes you could make to your campaigns, content and overall digital strategy. [A summary in pictorial format is at the end of this post.]

Excited? Let's do this!

Best Metrics / KPIs for Small Business Websites

Small business websites are a very fragile ecosystem. People working hard to do the best they can on the smallest possible budgets. But not to worry. They have to start with just four simple metrics to start rocking!

Acquisition:

Clicks? Visits? Backlinks? Impressions? No. We have something magnificent.

Cost Per Acquisition.

Obsess about this metric. You have very little money. You need to know, obsessively, what you get for it. This metric delivers that insight. Oh, and everything has a CPA (not just your paid search or display/banner ads). If you are doing SEO then you are likely paying for someone. That's the cost.

Kill things that don't have an optimum CPA. Invest more in ones that do. Simple enough, right?

Tip: Remember this is just cost, not profit. If your product costs you $15 to make then, in the above scenario, you are shipping a crisp $5 bill along with every Social Media order!

Where is it? Most likely in Excel. For Search it is in your Google Analytics or Omniture Site Catalyst reports. But for most other programs (Affiliate, Email, Social, Display) your Cost is likely sitting outside your web analytics tool. So extract the # of conversions, import into Excel, add a column for Cost, do the math, sing or weep (based on what the data says!:)).

If you are paying someone to do web analytics and this metric is not on top of the dashboard they've created for you, it might be time to say sayonara to them.

Behavior:

Page Views? Time on Site? No. You can do so much better!

Bounce Rate.

I continue to be a believer in trying to prompt love at first sight. Okay, okay, I'll settle for delivering relevance. :) Bounce Rate helps you identify campaigns where you might be targeting wrong people (who then come to your site and leave right away) or sending relevant traffic to irrelevant (and often flash-filled hideous) landing pages.

Bounce rate helps you find campaigns and landing pages that need to be killed / improved. Everyday.

Where is it? Standard metric in every web analytics tool worth anything. Look at your All Traffic Sources report and your Landing Pages report.

Checkout Abandonment Rate.

I find the fastest way to make money is to take it from the people who have already decided to give it to you. Obsess about checkout abandonment rate (the percentage of people who click Start Checkout to those who complete that process).

Focus on checkout steps with the highest abandonment. Tweak like crazy. A/B & Multivariate tests are a good option. But you are a small business… so just take away as many fields as you can, play with where to show shipping cost (I vote for way up front), reduce the number of checkout steps if you can, ask for account creation at the end of the process rather than at the start. Try, test, measure, be rich.

Where is it? In Excel. Or if you use Google Analytics: In Paditrack for free. (Google Analytics' native funnels are pretty sub optimal, ignore that entire feature.) For other tools: In KissMetrics. Create a funnel just for the checkout process (from clicking Start Checkout to Thanks for your Order) and both these tools will give you the metric automatically. They also allow you to segment the data! Make love to it.

[Bonus: What is abandonment rate?]

Outcomes:

My favorite Economic Value? No. As a small business I recommend…

Macro Conversion Rate.

You are a small business. Obsess about conversion rates, and everything connected to improving them. What products are people buying? Every single day (okay week) look at the All Traffic Sources report and seek out the Conversion Rate metric. Ruthlessly punish sources that are not working well and reward the pretty babies. Be they Earned, Owned and Paid media – oh and have a marketing strategy that has each of those elements or as a small business owner you are not going to win a lot.

I love creating an advanced segment with just the people who buy twice the average order size. I call them the Whales. Look at sources, locations, product bundles purchased, keywords and campaigns and all that to learn where/how you can find more Whales.

Where is it? Standard metric in all analytics tools. Remember to look at both the rate and the raw number of conversions for context. People make silly decisions when they don't do that.

That's it!

You are a small sized business and these four simple key performance indicators will literally rock your world as soon as you start measuring them. Cost Per Acquisition. Bounce Rate. Checkout Abandonment Rate. Macro Conversion Rate. Don't look at any other metric until you feel you've mastered them.

Tip: If you've hired the right analytics talent/consultant to help you, they'll be measuring these fabulous four.

Best Metrics / KPIs for Medium Sized Business Websites

What if you are a medium sized business? What key performance indicators are optimal for you?

First, you are going to measure the KPIs mentioned above. But because you are running a bigger and more complex business you'll also measure…

Acquisition:

CPA

+ Click-through Rate

While CPA is a macro metric about your campaigns' bottom-line performance, Click-thru Rate (CTR) is a deeper dive into analyzing the creativity and relevance of your affiliate deals / search listing / blinky banner ads.

In the context of Search (Paid or Organic), the text in your ads, the number at which your listing is ranked, the match between the user query and your ad's intent all help you receive a higher CTR. And if someone comes to your site (and does not bounce!) then you get an opportunity to convince them of your product or service's glory.

Small tweaks to the subject line of your email campaigns can have dramatic improvement in CTR. Recency and Frequency capping of your display remarketing campaigns can have a huge impact. Changing demographic targeting options in your Facebook ads can work wonders. Etc., etc., etc.

Put another way… CTR helps you understand if you showed up at the right place for your first date. Are you dressed okay. And if you are smiling the right smile. Helpful to know, right?

Where is it?

Everywhere. Start at a campaign level. Drill down to individual creatives. Kill badness. Promote goodness. Rinse. Repeat.

Behavior:

Bounce Rate

Checkout Abandonment Rate

+ Page Depth

A very tiny percentage of visitors to your site will see more than a couple pages. That's the internet for you. As you improve the user experience, information architecture and relevancy of content on your site, it is important to keep an eye not on the rather useless metric of Average Page Views per Visit or Average Time on Site but rather on the distribution of page depth. Here's how that picture might look like (from a post I wrote in July 2006!)…

From the deep detail reported by your web analytics tool you can choose to aggregate into buckets you most care about (like mine above). Categorizing the visits into Abandoners, Flirts, Browsers, One-off-Wonders, Loyalists will dramatically change your view of content consumption. Over time, as you move to deeper consumption, you'll see direct business rewards.

The above image emphasizes a sale/conversion at the end, but even if you are a content-only website improving Page depth helps you because more pages equal (at the very minimum) more ad impressions!

Where is it? The final table will be in Excel. If you use Google Analytics the data you need is here: Audience > Behavior > Engagement > Page Depth tab. If you use WebTrends, Yahoo! Analytics, Coremetrics please click around to find the data. They all have it.

+ Loyalty (Count of Visits)

If Page Depth helps you optimize for a single session experience, Loyalty helps you optimize pan session behavior. Put another way… how good are you at getting the same person to visit your website multiple times? For ecommerce or non-ecommerce websites, loyalty can mean the difference between life of survival and raking in profits like crazy.

First set a goal for the % of site Visits you would like for people who've visited more than x times. [Set a goal for x too. :)] For ecommerce websites use your Days to Conversion report (more on this metric below) to set your goal. For content sites perhaps mirror your content update schedule. If you are the New York Times and you update the website 24 times a day then should the average person be visiting the site at least 90 times per month?

Your BFF, as always, is analysis and not just reporting the metric. Create this simple segment in five seconds…

Apply to your keywords and campaigns and referring sources reports and identify which sources drive loyal traffic. Apply it to your content reports and figure out which content drives Loyalty (Sports? Op Ed? International? Cat Stories?).

Where is it? In every web analytics tool on the planet. If you use Google Analytics the data you need is here: Audience > Behavior > Frequency & Recency.

Outcomes:

Macro Conversion Rate.

+ Micro Conversion Rate

Pick your favorite benchmark and you'll notice that less than 2% of visitors convert. Focusing on just the Macro Conversion Rate means you don't care if you received any business value from the 98% that did not convert. I refuse to accept that uber-lameness.

Identify your Micro Conversions (/Goals) and obsess about the long and short term business value they deliver. You'll quickly realize the Economic Value they create for you is often far greater than the Revenue your Macro Conversion reports! And optimizing for that will ensure you win HUGE.

Where is it? In Google Analytics it is here: Conversions > Goals. Even if you are a content site the data is there. Details in the Goal URLs report. Setting up goals takes two minutes, setting goal values might take you a week (see measurement strategies here). If you use other tools, please check with your vendor.

+ Per Visit Goal Value

This Key Performance Indicator 1. helps you move beyond the obsession of focusing on the 2% (because it forces you to focus on Every Visit!) and 2. encourages you to create a business that uses the web to deliver multiple outcomes to your visitors.

Every visitor will not convert, but every visitor will, hopefully, deliver some Economic Value. Looking at this metric helps you identify Goals that contribute higher value, and and understanding of simple things like where you should focus on. If Twitter delivers 87 cents of Per Visit Goal Value and Google delivers 97 cents then perhaps I want to keep focusing on my SEO strategies rather than following the advice of the Social Media Guru who's just informed me Search is dead.

Where is it? In pretty much every single report in every single web analytics tool. Click on the Goals tab.

That's it!

For a medium sized business we ended up with nine metrics. Seems about right if you are making more than five million dollars of economic value. They key difference from websites that are in the small business category is that we are going to shoot for multiple conversions, deeper site engagement and better analysis of acquisition efficiency.

Time now to deal with the big boys and girls… large websites!

Best Metrics / KPIs for Large Sized Business Websites

Acquisition:

CPA

Click-through Rate

+ % New Visits

My choice of this metric perhaps betrays my refusal to rest on my laurels. There are clearly a finite number of people in the world relevant for any business. But staying hungry and staying foolish is a popular mantra for me. I use this metric to constantly calibrate my acquisition strategy to understand which inbound marketing efforts are bringing new "impression virgins" to the business.

If you look at your Earned, Owned and Paid media then this metric is especially important for your Paid media efforts. Except for your re-targeting / behavior targeting campaigns, you want your paid search, display, affiliate, and social efforts to bring new visitors to your franchise.

Where is it? It's like air, everywhere! Don't forget to segment for optimal analysis.

Behavior:

Bounce Rate

Checkout Abandonment Rate

Page Depth

Loyalty (Count of Visits)

+ Events / Visit

Every awesome large website delivers complex experiences (videos, demos, dynamic slideshows, configurators + + +) via sophisticated technologies (Flash, AJAX, Gadgets + + +). Almost all of the time we leave measuring their effectiveness on faith (or the HiPPO). I love event tracking because it helps us measure these often astonishingly, expensive initiatives.

Of 110,842 visits to the site, 9,054 interacted with your delightful experiences and each of those visits had 2.24 Events per Visit. Is that good? Bad? Could be better? Are these 2.24 interactions delivering higher economic value to your business?

In the above case the answer was a big NO. In your your case you'll decide based on your strategy and goals. At the end of the analysis you'll make significantly smarter decisions about your content (especially because the Analysis Ninja that you are, you'll triangulate performance of this metric with first, Page Depth and, second, Loyalty).

Where is it? Most web analytics tools do some type of event tracking. Please check with your vendor (it might not be called event tracking in their lingo, just describe my first paragraph above). In Google Analytics the data is here: Content > Events.

Outcomes:

Macro Conversion Rate.

Micro Conversion Rate

Per Visit Goal Value

+ Days to Conversion [or Time Lag for Content sites]

Another pan session metric I adore.

Life, no matter how hot you are, is not a series of one night stands. Yet because of how they analyze the data most companies end up optimizing their web marketing campaigns for one night stands. Come here and convert NOW! If yes: Oh, I love you. If no: Kill the campaign!

That approach is not just short-sighted; it is an insult to your visitors. Convert them at a pace they are most comfortable with. This metric helps you understand how quickly or slowly your visitors convert. You can, at the very minimum, change your campaign messaging and come hither calls to action and adjust your landing pages. If the Days to Conversion are much longer, then create a robust (slow dance) micro conversion strategy.

If you have a non-ecommerce website then there is something delightful for you in the Google Analytics Multi-Channel Funnel reports. Checkout the Time Lag report . It is showing you exactly the same data as the Days to Transaction for Ecommerce sites. The metric you see immediately above is called Conversions. It is essentially your Goals (/micro conversions).

Optimize your "hello, nice to meet you, what would you like, here is what I have to offer, why don't you check with your spouse, come back and check it out again, multiple times, I'm still here, you ready to convert / deliver economic value, here's how… " process.

Where is it? Days to Conversion is in the Ecommerce section of your web analytics reports. It is a standard report. (Don't forget to segment your sources. Deep insights await.) Time Lag may or may not be a standard report in your tool. Please check with your vendor. In Google Analytics it is a standard report here: Conversions > Multi-Channel Funnels > Time Lag.

+ % Assisted Conversions

This is the newest metric I've made standard for all my clients / partners / BFFs. And it is a sweetie.

Assisted Conversions builds on the above mental model. It takes a while for a majority of your visitors to convert (macro and micro conversions), so why does almost all of web analytics focus on single channel analysis and optimizing that single channel in a silo? Just because the Affiliate click was the last one before conversion should it be optimized for that conversion? Especially if the Visitor originally came via Facebook (or Google or whatever)?

How many of your conversions had more than one ad / media / marketing touch prior to converting? Really smart Analysts at really successful companies understand that…

…and then use that data to optimize the portfolio of channels rather than individual channels for the company.

Even if you don't do portfolio optimization (and desperately hope you do) you can easily see how the above data will cause you to execute a different marketing optimization and expectation strategy for Email (1.18 Assist / Last Interaction rate) vs. Organic Search (0.61).

I am being modest when I say that this metric and subsequent analysis will have a fantastic impact on your company.

Where is it? % Assist Conversions may or may not be in your web analytics tool. Please check with your vendor. In Google Analytics you'll find it here: Conversions > Multi-Channel Funnels > Assisted Conversions.

And we are done!

For large businesses we've identified 13 key metrics that would give a robust end-to-end view of business performance. The key difference vs. medium sized businesses is that we are really, really, really focused on pan-session (multiple visits) behavior. Put another way, we really care about people here and not just a single visit.

Here is a summary of the metrics I am recommending in this post…

I hope the picture above will quickly help diagnose where current gaps in your measurement strategy might be.

Additionally if you are a small business you'll know what else to measure when you start to become medium sized and if/when you cross that threshold you'll know the metrics that come with your large business status. :)

You'll notice that I'm not focusing on KPIs like AdSense Ads CTR or Page Load Time or Actions per Social Visit or Search Exits (I love this metric!) or Content Distribution vs. Content Consumption Rate or Conversation Rate (in case of a content site) etc. That's simply because these KPIs tend to be unique to the type of business you are running. My strategy above was to focus on just the KPIs that would be applicable across all types of businesses.

That brings me to a very important point.

While it is my hope that you'll find my recommendations above relevant and yummy… the most optimal way to identify that best key performance indicators for your company will come using the process and structure outlined in the Digital Marketing & Measurement Model.

I'll end with the thought I started this post with… we have more data than God wants anyone to have. But web analytics does not have to be scary or impenetrable. Use the roadmap above, focus on all three elements (acquisition, behavior, outcomes) and I promise you'll soon be on your way to being as happy as God wants everyone to be.

I wish you all the best!

Okay as always it's your turn now.

Does your business use the above recommended metrics / key performance indicators? Do you have an absolute favorite metric that's not mentioned above? Which metric above do you find most useful? Which one most useless? What is your strategy for identifying the most relevant metrics?

Please share your suggestions, critique, and helpful best practices via comments.

Thank you.

PS:
Couple other posts on metrics / KPIs you might find interesting:

• Web Metrics Demystified
• Your Web Metrics: Super Lame or Super Awesome?
• Kill Useless Web Metrics: Apply The "Three Layers Of So What" Test

Best Web Metrics / KPIs for a Small, Medium or Large Sized Business is a post from: Occam's Razor by Avinash Kaushik

In this post about an important Google change, I want you to focus less on the data and focus more on the methodology. And – so important – I want you to help me with your ideas of how we can do this impossible analysis better, in the complete absence of data :). So please share your ideas via comments and let's together make a smarter ecosystem.

On board? Let's go….

In an effort to make search more secure, on Oct. 18th Google announced that users logged into their Google accounts using www.google.com would be redirected to https://www.google.com. The search queries by these users would hence be encrypted and not available to website owners via web analytics tools such as Omniture, WebTrends, Open Stats, Google Analytics etc.

Switching from have all the search queries in the keywords reports was our normal state, not having them feels different. As the change ramped up and more user queries came to be represented, in at least Google Analytics, under the moniker "(not provided)" we all got worried. From our perspective it would be immensely preferable to be able to analyze all the keywords individually. Sadly we don't have that now.

The wonderful thing is that in addition to passionate commentary on Twittersphere / industry blogs / gurus, we also have access to data for our own websites. We can, and should, look beyond simplistic "it is this high or that low" to see if we can understand something (anything!) deeper.

Most analytics vendors, including Google Analytics, reacted immediately to the change in order help us quantify the impact of this change in multiple ways. As you can imagine my reaction was to unleash a flurry of custom reports and apply smart advanced segments and compare data pre and post change and go down a bunch of holes.

From that experience here are five steps I recommend you follow to gain a smarter understanding of this change…

1. Establish macro context.

On Oct 20th on my Google+ page I'd shared a custom report for Google Analytics that makes it extremely simple for you to look at this data. Visits, Unique Visitors, Bounce Rates, Goal Completions for (not provided).

You can download that report into your GA account by clicking on this link after you are logged into GA: Google httpS Change Impact.

Here's what the data for this blog looks like for one month:

Like me first you should compute the high level impact of the change. From Oct. 31 (when the trend started to spike and subsequently stabilized) to Nov 15…

Please note that this number will vary dramatically depending on the type of website you have, audience attributes, geographic location and a number of other factors.

Now you know what the number is for your site, and you can keep the custom report handy to continue to watch what happens over time. Remember to divide the number by total Google traffic. I see people using total search traffic or total site traffic or… other imprecise metrics.

All numbers in aggregate are at best marginally useful, and that rule applies to this one too.

We want to know more. Who are these people? Are they people I should care about? Not care about? And what kind of search queries are these? Brand? Non-brand? What else?

Sadly we can't answer all of those questions, but we can make a small clump of informed judgments based on data we do have. It just needs a pinch of passion, some smarts and a lot of effort.

Let's deep drive into some very cold and choppy waters…

#2: Understand the performance profile of the (not provided) traffic.

One of the things I hate about standard reports in all web analytics tools is that they scatter necessary data across tabs, multiple reports, or outright hide it. #aaarrrrrh

So I always use custom reports . In most web analytics tools it takes as little as 20 seconds to create one. I did one for this particular purpose. It provides me the end-to-end view of search keyword performance in one place.

Here is what it looks like:

You can download it into your Google Analytics account by clicking here: Keyword Performance Analysis Report

Two quick things to note.

So how does (not provided) look? Here's my end to end view:

The numbers in red were added to the report by me. I wanted to know what percentage of the total Visits and Goal Completions (not provided) was. [On that last point, if you have an ecommerce website you can use Orders or an appropriate proxy instead of Goal Completions.]

Bottom-line: 18% of the Visits and 22% of the Conversions.

Big numbers! But with a quick scan of the report, I think I already see that there is something delightful going on here. Stick with me. I think we have a surprise coming.

The custom report has eight metrics (two more than I normally use) simply to try to tease out some nuance of the performance as we look across keywords.

One hypothesis I had was that (not provided) might be mostly returning visitors. The overall search avg % New Visits is 67.96%, for (not provided) it is 65.06%. Very similar to the "average site visitor." But notice that all Brand Terms above (avinash, kaushik, occam's razor) have very low % New Visits. So it is possible that (not provided), contrary to my hypothesis, are mostly new people.

Overall bounce rate is 70.2% (not unusual for a blog/pure content site), and (not provided) is 66%. Again, scanning across the top ten terms you can see higher rates for non-brand searchers (people looking for specific, perhaps quick, answers) when compared to brand terms.

Content consumption, Pages/Visit, seems to be a bit on the higher side compared to the average (1.76). But like the other metrics above, there is a pattern between brand and non-brand (with brand higher on this metric).

I really, really care about Goal 2, hence that conversion rate is in the report. The average is 2.21%, (not provided) is around 2.37%. There's not much conversion going on with the broad non-brand terms (you can't get lower than 0% :).

Goal Completions is very interesting. (not provided) is a huge bucket of goal completions (and it is easy to understand why so many SEOs and Marketers and Lovers are in a tizzy!). The thing to note here are the numbers in red (% of each bucket compared to total Goal Completions, 4,816). See how quickly thing fall off the cliff. Note the difference between brand and non-brand.

Finally, my absolute favorite: Per Visit Goal Value. There is no obvious monetization on this blog, but I have 8 distinct goals and I have goal values assigned to each for the long term impact each adds. (How's that for focusing on customer lifetime value? :)). $1.27 for (not provided), compared to overall of $1.01, and the number does not come close to the other brand terms.

We still don't know what keywords are contained in the (not provided) bucket.

But what we do know is that for this site (not provided) visitors fits this bill: They seem to be new people with behavior that is quite distinct from the "head" brand terms and closer to the non-brand terms.

In the past I've lovingly termed non-brand long tail visitors as "impression virgins." The hint at the end of this step is that I've got myself a lot of impression virgins in (not provided)!

Let's go and see if we can validate that theory.

#3: Deep dive: Match up performance profile to Brand & Non-brand visits.

Based on the clues above, I'm going to try to understand whether the performance profile for (not provided) is indeed closer to brand searchers.

I create this simple segment in GA… should take you five seconds to do it for your own business…

Apply it to my custom report and boom!

[sidebar] A quick thing to note is the ratio of Unique Visitors to Visits. In context of % New Visits that makes sense. But just make a note of it. [/sidebar]

How does this compare, purely from a performance of the key performance indicators perspective, with (not provided) for the same period?

Quite a stark difference as you look across metrics like % New Visits, Bounce Rate, Pages/Visit, Conversion Rate and Per Visit Goal Value.

So how does the performance of (not provided) compare to that of non-branded keywords? Not a difficult question to answer.

Back into GA to create a segment like the one above, expect change "Include" to "Exclude" and I have my non-branded traffic segment.

Here's how those numbers look like in the aforementioned custom report:

When you do this with your data you'll have a similar image and you'll compare it to your (not provided) segment performance, and your brand segment perfromance. In the comparison above it is clear that these three buckets are distinct, but that the performance of (not provided) is not as close to brand as it is to non-brand. Even though the (not provided) segment is small (4.6k) compared to non-brand (21.9k) – thinking about impact on averaging these metrics.

There are two likely scenarios in terms of what you'll find…

In your case (not provided) segment might match overall Google traffic or one of the above segments. In which case you continue business as usual with the assumption of an even distribution.

It is possible that (not provided) segment does not match overall Google traffic, or one of the above segments, in your case. In this chase you understand a bit better how to treat it in your thinking (more keywords connected to your brand or non-brand segments). At the moment you can't take action based on this information (how to you react to visitors whose keyword you don't know at all). But when presenting to your senior executives you can give them a bit more context.

It does not eliminate all the questions, but it does help me go from "I have no idea who all these people/keywords are" to "Okay looks like it might be my non-brand possibly long tail traffic."

Something of value, right?

All of the above is still kind of at an aggregate level. But we all have a lot of keyword level historical data. At some point we should have enough post change data that we can throw it all into a delightful regression model to fine tune our understanding at a keyword level.

At the moment we just know a little bit more than "here's my total (not provided)."

#4: Tentative conclusions. Why this seems so scary, but might not be (at least for now).

Most, but not all, of my branded traffic is my "head" traffic, i.e. traffic that results from a few keywords used by lots of visitors. After all your brand is unique to you and, for any type of website, drives loads of search traffic to you because you rank high in SERPs for those brand queries.

Most of my non-brand traffic is my "tail" traffic, i.e. traffic that results from a lot of keywords used by a few people each. For example you'll notice at the very start of this post that during this time period I had 27k visits. Of this my "tail" traffic comprised of 21,921 visits. These delightful folks used 10,498 distinct non-branded key phrases to find my website.

10,498 distinct search queries drove 21,921 visits!

Remember the two scenarios I'd mentioned above? Let's look at one of them (performance closer to non-brand traffic) and understand what is happening a little more visually. What is happening when (not provided) shows up as your #1 metric in your search keyword reports?

In my case above, closer to scenario #2 for me, the performance of (not provided) as shown by the metrics above looks more like that of the visitors who came via those 10,498 non-branded search key phrases.

Here's what's happening when (not provided) shows up #1 for me (clear in the screen shot in part #2 above), as explained by my head – tail illustration :

Prior to this change by Google, the gray slivers above represent traffic that became (not provided) after the change.

In the past only a small part, if any, of this traffic, for me, would ever show up in the top ten or twenty keywords in the report (head traffic). Because much of it was in the long tail I never noticed it (it is hard to look at all 10,498 key words individually! :).

But after the change by Google, these tiny, in the past invisible, slivers combined look like one scary beast. I've painfully combined every pixel of gray sliver above:

OMG! I've lost a huge chunk of something that was a very important part of my traffic!!

Not really. It just looks scarier than it really is because tiny shavings of your other keywords (now used by logged in users who are opted into https sessions on google.com) appear in one big piece. Individual cells don't look that scary. But combined they look like Darth Vader himself. :)

Let me hasten to add that this does not mean that these "slivers" from user search queries are not important. Or that just because they are mostly non-branded traffic we should ignore them (I argue 100% contrary to that here: Monetize The Long Tail of Search ). Or that you should not worry and that the sun is shining, there is no US debt problem, we have universal health care and Ashton and Demi are still together.

No. Not at all.

But the sky is not falling either.

We can use the actual data we have to keep a very close eye on this traffic and its performance. We can use advanced segmentation and custom reports to understand where this big scary block of traffic used to be. Is it (to repeat the scenarios we outlined at the end of part 3 above) closer to the average performance and hence possibly evenly distributed or closer to non-brand and less evenly distributed.

We sadly still won't know what actual long tail or non-brand keywords or overall keywords they represent or how much of a particular keyword/phrase they used to be. But my POV is that we'll be in a better place.

You can be, if the data in your case justifies this, just a little less worried.

#5: Additional awesomeness: Landing page keyword referral analysis.

One final idea I had was to wonder if the (not provided) traffic enters the website at a disproportionate rate on some landing pages when compared to all other traffic from Google. If that is the case we could do pre post analysis on referring keywords to those landing pages and get additional clues.

It is not very hard to go checkout that theory.

First, create an advanced segment for the (not provided) traffic:

Then go and apply it to your standard Landing Pages report in Google Analytics (or SiteCatalyst or WebTrends or Yahoo! Web Analytics):

The analysis from here on is not very difficult (though in the new version of GA it is harder as the UI designers got rid of the % delta for comparative segments – what a shame). Just use our bff MS Excel.

For example 14% of the (not provided) traffic enters on the home page.

I was able to find a small clump of pages where the (not provided) traffic, at least currently, entered the site at a higher rate than overall Google traffic. I can see the referring keywords to those pages prior to the change and after the https change and attempt to identify which keywords might be contributing traffic to (not provided).

For me this analysis provided a better idea about some long tail non-brand keywords. But it was not as much as I would have liked to learn. Partly that is a function of the fact that those keywords are used by a handful of people and, this makes it worse, they are quite transient – they are not used too many times again.

But since everyone's site and visitor behavior would be different I did want to share this idea with you. It is not a hard bit of analysis to do, and you can let the data tell you something (or not).

That's it.

A simple five step process to go from reacting based on an aggregate number in your keyword reports to a much more nuanced (if imperfect) understanding based on your own data.

Caveats:

Before we go, a few important reminders that are spread throughout the post above but bear repeating….

Anything else I should have here that I've forgotten?

I would love to know how you would go about doing this impossible analysis? What other path would you take in your web analytics tool? What segment, report, metric, walk on water effort would you undertake? Regarding my five step effort above… what flawed assumptions am I making? What would you change in terms of the approach/conclusions in any of the steps?

Was this nuanced understanding of what might be happening better than where you started?

Please share your alternative ideas (please!), critique of the above analysis, ideas for world peace via comments.

Thank you.

P.S: A request. This blog focuses on digital marketing and web analytics, it is not a policy blog. If you are up for it I would love for your comments to focus on the former and not the latter. If for no other reason than that my skills don't extend to the policy part and I would not be able to share anything of value with you.

I appreciate your consideration.

Smarter Data Analysis of Google's https (not provided) change: 5 Steps is a post from: Occam's Razor by Avinash Kaushik

I am going to break the second part of the rule.

I am going to define a way for you to think about measuring social media, and you can't actually easily measure what I am going to recommend.

So why break the rule?

Social media is evolving at an incredible pace. Most of us have no idea how to participate optimally in this unique channel – we are doing TV on Twitter (breaks my heart). The impact on the data side of the ecosystem is that massive amounts of data is being generated and much of what goes for measurement in "social media tools" is profoundly sub optimal (I'm being polite). We have IT-minded people engaging in massive data puking (one report with 30 metrics anyone?) and Marketing-minded people who are using lousy measures of success ("I got 158,632 Fans! Hurray!").

I want to propose a framework you can use to measure success using metrics that matter for one simple reason: They actually measure if you are participating in the channel in an optimal fashion.

Isn't that revolutionary? Use data to incentivise our companies to do the right thing by measuring what matters, what makes this channel so unique.

No more embarrassing your brand on Twitter, Facebook, Google Plus, YouTube. And we build out a loyal cadre of followers / friends / subscribers to boot!

So what actually matters in Social Media?

Not the number of Friends / Followers / Subscribers. Not the number of posts / tweets. Not the ridiculous Followers to Following ratio. Not the… well there are so many horrible ones to choose from.

What matters is everything that happens after you post / tweet / participate!

Did you grab attention? Did you deliver delight? Did you cause people to want to share? Did you initiate a discussion? Did you cause people to take an action? Did your participation deliver economic value?

The "so what? " matters!

Oh, I totally forgot to say this…. the advice in this blog post is only for businesses and brands that participate in social media. Businesses as in Red Bull and T-Mobile and Johnson & Johnson. Brands (all of the aforementioned plus…) as in Mitch Joel and Stephen Colbert and Nancy Pelosi. If you don't fall into those two categories then this social media measurement framework might not apply to you.

I'm proposing four distinct social media metrics we should measure, (and this is so cool) independent of the social channel you participate in.

Excited? Let's go….

1. Conversation Rate.

When I say most brands do TV on social media what I mean is that we do the same uninformed shouting and pimping on social media that we do on TV.

We know little about who is on the other end of the TV set and the medium places limits to what we can do. So to make our marketing more efficient we shout more loudly, more frequently!

We don't have to do that. We can get a very good sense for who is following / friending / subscribing to us. We can measure if what we are saying connects to them (in near real time!). And unlike all others, this channel has the word social in it! Social as in talk and listen and discuss.

So why not measure that?

One beautiful thing… you can measure this on every social channel on the planet. Blog. Twitter. Facebook. Google Plus. YouTube.

What to do with it?

A high conversation rate requires a deeper understanding of who your audience is, what your brand attributes are, what you are good at, what value you can add to your followers and the ecosystem you participate in.

That is why I love this metric. It forces you to do the right thing right away. And it is a lot of work.

So aim for a higher Conversation Rate. Build your own watering hole in the digital universe. Have meaningful conversations with your audience. That's Marketing money just can't buy.

You can always be provocative, say silly things and get a high Conversation Rate. Pick Sarah Palin for your topic. :) But that would not be accretive for your brand equity, would it?

Remember we do not measure to manipulate the metrics, we measure to know if we are adding business value.

How to measure it?

Individually this is not that hard to measure. But across channels there does not seem to be an option.

This is where I need your help. Do you know of a tool that measures conversation Rate easily as defined above across the main social media channels? Please share via comments and I'll add it here. Thanks!

Up next, our second delightful metric…

2. Amplification Rate.

Every channel has inherent limitations, often exhibited by the number of ads you can buy. On Google (paid search), on Facebook (display ads), on Radio (audio ads), and all other channels you can think of.

But social media has a profound advantage you can tap into.

Not only do you have a network, but every node in your network has a network of its own! If you follow my advice and post something "incredible, relevant, of value" to your audience then they can allow you to break free of the limitations of your network and spread your word around to a more massive audience!

Take me as an example. I have, as of today, 57k followers on Twitter and around 12k on Google Plus. That's the limit. Even if every single person who follows me reads every single thing I write, I can at most reach 57k people on Twitter.

But the size of my second level network (the unique people who follow the people who follow me) is 6.3 mil. My real "reach" it turns out is not 57k, it is 6.3 mil!

So measure Amplification, the rate at which your followers take your content and share it through their network.

On Twitter:

On Facebook, Google Plus:

On a blog, YouTube:

(Share clicks as in number of times your social media buttons were used to spread the content.)

What to do with it?

As you post and tweet and you rock and you roll… measure what pieces of content (type) cause amplification (allow your social contributions to spread to your 2nd, or even 3rd, level network). Understand times and geo locations and topics and things.

Then do more of the type that increase amplification. You'll get more sharing and spreading of your content. But this is very, very important: You'll be giving your audience content they consider to be of such incredible value that they want to share it (and hence you'll know what your audience wants / loves).

Oh, oh, oh and…. over time your 2nd level network becomes your 1st level network… because they discover that you rock!

Marketing, relationships and a reach that money, honestly, can't buy.

How to measure it?

I don't quite know how to do it easily across all the channels. Individually you can, see image above, pull out Excel and make magic!

Do you know of a tool that precisely measures Amplification across all channels as defined above? Please let me know via comments, and I'll add it here.

Now on to a metric that had us at "hello"…

3. Applause Rate.

I'm sure you've noticed my secret evil plan to force you to understand your audience (and not just pimp your agenda in Social Media).

One powerful, more immediate way, to understand them is to measure Applause.

One Twitter:

On Facebook:

On Google Plus:

On a Blog, YouTube:

What to do with it?

Simple… you want to know what the audience likes (to use the Facebook terminology) and what they don't. You get a much deeper understanding of what your audience likes so much that it will +1 your content (or contribution) and allow for that to be then shown to others in their social graph.

And consider this…

If you +1 this blog post, you'll not help me understand its relative quality, but when someone in our extended social graph does a search on Google for Social Media Metrics your endorsement of this content will show up in the search results. That's reassuring to your social graph, and it is great for me because your endorsement makes this post stand out over others and I get a relevant visitor/customer.

Sweet, right? Your selfless social media contribution comes back to assist you in driving valuable business outcomes.

That's why you measure Applause. It matters in ways you can't imagine!

How to measure it?

Individually the numbers are available in most tools. Easy to find in Google+ (see example in the end). For Facebook the number is included in Facebook Insights, though it is not available as easily in a simple way (at least not as expansively as outlined above). For Twitter, sadly I could not find it anywhere (inside Twitter or other tools).

So help me. Do you use a tool that will allow us to measure Applause Rate? Please share via comments.

Finally the metric any company leader will adore…

4. Economic Value.

I am smiling. I know that the long time readers of my blog would know that I would never let you get away without measuring hard business bottom-line impact of any digital effort!

It is foolish to believe that just Conversation Rate, Amplification Rate, Applause Rate will get you the eternal love and gratification (and perhaps budget!) of your company's leadership. Yes they care a little bit about this "social media thing." But if you want their adoration (and let me repeat: budget!) you are going to have to quantify the economic value created via social media.

You don't participate in social media to only drive business outcomes. I cannot stress that enough. If that is your primary objective you are going to suck at it (and the above metrics will reflect very efficiently how much you suck).

But.

A small percent of the people in your company / brand's social graph will come to your main digital outpost (usually your company website) and choose to do business with you. Some of them will buy something, others will sign up for your email marketing list, others still will order a catalog or write reviews for products on your site or sign up as an affiliate or create wish lists or marriage registries or phone your call center to order something or… stay with me…. buy your products or services in your supermarket / store / real world thing.

And you know what all of those things are? Macro and Micro Conversions!

And you know what you can do with macro and micro conversions? You can measure Economic Value!

On all social media channels:

Social media participation, done right, adds value to the company's bottom-line. Some of it can't be computed. That is okay. But some of it can be and it is your job, nay duty (!), to quantify that.

It is not very hard to do. Read the two posts immediately above. They share very specific guidance for businesses of different types (B2B, B2C, A2K) about how to identify the macro and micro conversions and then compute economic value.

What to do with it?

Those of you who have been at one of my recent keynotes have seen this slide:

Your job is to identify that blue arrow, and the orange box (what it stands for and what the amount is). It is not very hard, just takes a little patience and imagination.

And here is the incredible, amazing, magical thing. Once you have your highest level segmented view of the acquisition strategy, above, you can in two seconds segment down to individual channels you participate in.

Your view will look something like the one below, from Google Analytics:

I can focus on the Per Visit Goal Value (economic value delivered by visitors from social media channels across my macro and micro conversions – note the 0% in the macro conversions column, ouch!) for each channel. StumbleUpon rocks ($1.43), Twitter takes the next spot (around $0.60) and then comes Facebook ($0.26, clearly not a winner for me).

Now, not only can I tell my CEO what the small amount of direct value added to the business is, I can also report to her/him exactly which channels are contributing how much. You can't be in every social channel that pops up. The above data can give you guidance on where to be.

You do Economic Value and you will never, ever have to beg for investment in Social Media, and your career will get on the fast track. I promise.

And just to repeat one more time. A vast majority of value your business / brand gets from social media will be owning your message, building the watering hole I've mentioned, having a direct relationship with your customers and so much more. But showing some direct economic value will get you permission to do more of that. Without it you are just another "smarty pants" promising "vague outcomes" via "the next hip thing."

How to measure it?

Use Google Analytics, Omniture, WebTrends, CoreIBMInsights, etc.

Takes less than five minutes to set up. Provides a lifetime of joy.

Four Metrics That Rock.

Conversation Rate. Amplification Rate. Applause Rate. Economic Value. Four simple measures that get you to focus on the right thing from a social media participation perspective, help you understand how well you are doing at it, and quantify the business impact.

The challenge is that thus far it is hard to pull them all together in one place. As I had mentioned earlier, Excel is your bff for now. My hope is that vendors will stop creating tools in silos (just do Twitter or Facebook or Google Plus or YouTube or…) and start to think of real world needs of Brands and Businesses and pull together metrics we need into one place (from all social channels).

There are small signs of hope.

Crowdbooster has a very interesting view of twitter:

You can see Retweets (x-axis) and Replies (size of the circle) overall and individual tweet perspective. So both Conversation and Amplification. The other two metrics are missing, but it is a start.

All My + is a early prototype of data from Google+ and provides three of the four metrics recommended in this blog post:

It is missing Economic Value. But you can get that out of Google Analytics or Site Catalyst in five minutes.

If you are a tool vendor… I would love for you to adopt the aforementioned metrics, and definitions, into your tool. All I ask for is a donation of one million US dollars to Doctors Without Borders. Doable?

What About Social Media Advertising?

If you are engaging in brand advertising on social media channels then the metrics you should solve for should be the first three. If you do a Promoted Tweet or Facebook Like campaign or whatever Google+ decides to come up with then you want to measure resulting Conversation, Amplification and Applause (of course only if you did not stink at your campaign).

If you are engaging in direct response advertising on social media channels then the fourth metric, Economic Value delivered, comes into play from a strategic perspective. It covers both the immediate value (revenue via macro conversions) and the longer term value (economic value via micro conversions).

For tactical reporting of your direct response social media campaigns, the metrics you'll use will be the ones I've recommended for all other advertising channels (paid search, display, affiliate, whatever).

Here's that picture, applied to SM DR campaigns:

Value Per Acquisition. Shoot for that.

It will be hard. The enchanting temptresses that are Clicks and Impressions and Avg. CPC will try to lead you astray. Resist their charms. Trust me.

Go for Ninja-hood.

Closing Thoughts.

Social media presents and incredible opportunity to rethink what it means to connect with and influence customers. You need to forget what has worked in the past (and that is why this is so incredibly hard to do. The biggest brands in the world embarrass themselves every day on social media). You'll have to rewire your brain.

In presenting new metrics for you to measure, what I'm really trying to do is provide a very small assistance in helping you think differently.

I hope it works.

Update: Bonus:

Erik Ohlen was inspired by this blog post to create a very simple, and effective, dashboard where you can track the four recommended social media metrics.

As I had stressed above, currently if you want to report these metrics exactly as defined above and from ALL the social channels mentioned then you have to do so manually. Small price to pay for communicating the actual impact of social media to your management right?

Sheet 1 is the dashboard itself, with instructions. Sheet 2 is where you type in the raw data. Could not be simpler.

Download: Social Media Metrics Dashboard. Adapt it to your business. Rock a lot!

As always it is your turn now.

How do you measure the success of your social media efforts today? Got a favorite super lame or super awesome social media metric? Does one of the four (or all four!) metrics above resonate with you? What did I miss about social media? Is there a benefit / outcome / facet that I missed in my measurement framework?

Please share your feedback, critique, suggestions, and cool tools to measure these four metrics, via comments.

Thanks.

PS: A few helpful links for you:

A couple of my older posts with thoughts on social media measurement:

~ Social Media Analytics: Twitter: Quantitative & Qualitative Metrics

~ Viral, Social, Sentiment, Mobile: 4 Delightful Web Analytics Solutions

A post how to segment your social media data in Analytics (includes a downloadable advanced segment):

~ 3 Advanced Web Analytics Visitor Segments: Non-Flirts, Social, Long Tail

A comprehensive post on the most important gift you can give your business, compute economic value of your digital efforts:

~ Excellent Analytics Tips #19: Identify Website Goal [Economic] Values

Best Social Media Metrics: Conversation, Amplification, Applause, Economic Value is a post from: Occam's Razor by Avinash Kaushik

How do you figure out which channels to invest in more and which to kill?

How do you figure out if you are spending more money reaching the exact same current or prospective customers multiple times?

How do you get over the frustration of having done attribution modeling and realizing that it is not even remotely the solution to your challenge of using multiple media channels?

Oh, and the killer question… if you invest in multiple channels, how much incrementality does each channel bring to your bottom-line?

Smart Marketers ask themselves these questions very frequently. Primarily because we don't live in a let's buy prime time television ads on all three channels and reach 98% of the audience world any more.

We have to do Search Engine Optimization. We have to do Email Marketing. We have to do Paid Search. We have to have a robust Affiliate network. We have to do Social Media. We have to do location-based advertising to squarefour people. We can't forget Mobile advertising. We have to… the list is almost endless. Oh, and in case you had not noticed… the real world is still there. TV and radio and print and… Oh my!

The reality is that we can't do all of those things.

Smart Marketers work hard to ensure that their digital marketing and advertising efforts are focused on the most impactful portfolio of channels. Maybe it is Search, Email and Facebook. Maybe it is Affiliate and Paid Search. Maybe TV and Twitter and Newspapers. Maybe it is five other things.

How does one figure it out?

Controlled experiments!

What's that? This: You understand all the environmental variables currently in play, you carefully choose more than one group of "like type" subjects, you expose them to a different mix of media, measure differences in outcomes, prove / disprove your hypothesis (DO FACEBOOK NOW!!!), ask for a raise.

It is that simple.

Okay, it is not simple.

You need people with deep skills in Scientific Method, Design of Experiments, and Statistical Analysis. You need the support of the top and bottom and middle of your organization (and your agency!). You need to understand all the environmental variables in play (a hard thing under any scenario) not just in context of your company but also as they relate to your competitors and ecosystem.

But if you have access to some or all of that (or can hire good external consultants), then your rewards will be very close to entering heaven. Marketing heaven that is.

To make the case for controlled experiments I want to share with you one simple, real world example I was involved with.

My explicit agenda is to spark an understanding of the value of even simple controlled experiments (that might need only some of the horsepower mentioned above).

My secret agenda is to illuminate the power of this delightful methodology via a simple example, and get you to invest in what's needed to move from good to magnificent.

Ready?

The Setup.

This is a multi-channel example. The company truly has a portfolio strategy when it comes to marketing. We are going to simplify the example to make it seem like they only do two things. They mail catalogs and they send emails. The purpose of both is also simple: Get people to convert online (website) or offline (call center).

The question was, should they do both? Should they love one more than the other? Is this digital thing here to stay or is the thing that has worked so well for 150 years – catalogs – the thing that still works ("the internet is a fad!")? What is the incremental value of doing email?

To answer this question the company took their customer lists (catalog and email) and identified like-type customers. Like-type as in customers that share certain common attributes. For your business, that could be people who have been customers for 5 years (or 5 months) or those that order only women's underwear or those that live in states that start with W or those that order more than 10 times a year or only men or people who were born on Jupiter or… (this is where design of experiments comes in handy :).

Then they isolated regions of the country (by city, zip, state, dma pick your fave) into test and control regions.

People in the test regions will participate in our hypothesis testing. For people in the control region, nothing changes.

It is also important to point out that I am keeping the data simple purely to keep communication of the story straightforward. We'll measure Revenue, Profit (the money we make less cost of goods sold), Expense (cost of campaign), Net (bottom-line impact).

What is missing in these numbers is the cost of…. well you. The people. A little army in your company runs the TV campaigns. A larger army is the catalog sending machine. A lone intern is your email campaign people cost. A team of five are your paid search samurais. When you do this, if you can, include that expense as well.

Enough talk, let's play ball!

The Experiment and Results.

Here's the outcomes data for the control version of the experiment. This group of customers was sent both the catalog and the email. Nothing was changed for them – this group was treated exactly as they were in the past.

If the company did both things, revenue was $12.

Because revenue is very often a misleading way to understand impact on the company's bottom-line, most smart people prefer to go for net impact (the result of taking out cost of goods, campaign expenses etc.).

In this case, that amounted to a bottom-line impact of $2.59.

[If you want to learn how a focus on the bottom-line, especially net profit can change your life, and I mean that literally, please see this video: Agile, Outcomes Driven, Digital Advertising. Parts two and three, Rockin' Teen and Adult (Ninja!).]

Here's the data for variation #1 of the experiment… this group of like-type of customers were only sent the catalog – no email. The marketing messaging and timing and all other signals for relevancy and offers used for this group was exactly the same as the control group.

Compared to the control group, revenue went from $12 to $10. Company expense went down a little bit (email campaigns after all are not free).

The net impact went down from $2.59 to $2.00.

17% reduction in revenue, 23% negative net impact to the bottom-line.

Does that help you understand the incrementality delivered by the campaign that is missing in this variation of the experiment (email in this case)? You betcha!

No politics. No VP of Email vs VP of Catalog egos and opinions involved. No you are trying to mess with my budget spit on your face. No but that is not what Guru x at a conference said or but that is not what people on Twitter think. None of that. Just data.

How sweet is that?

Here are the results of variation #2… this group just got the email. The killing of trees, filling of recycle bins, and breaking the backs of postal carriers was paused. :)

Again, and I can't stress this enough, all else was equal.

Compared to our control group there was a whopping 29% reduction in revenue. OMG!

But, a bigger OMG is coming: the net impact on the bottom-line of the company was a measly 2%! OMG!!

So the incremental value delivered by combining a catalog campaign with an email campaign is an increase of 2% on the bottom-line of this company.

Not for every company on the planet. Not even for all campaigns you do. But for this campaign and these types of customers you can confidently say: "Yes there was a drop in revenue and if you care about that, oh beloved HiPPO, then let's send more catalogs. But at least now you know the net incrementalism delivered to our bottom-line from doing that."

If your HiPPO is smart, and in my experience many HiPPOs are smart and well-meaning, shewill ask you this: "Is that 2% ($0.05) sufficient to cover the salaries, pensions, health benefits of everyone we employ to do catalog marketing?"

Controlled experiments also allow us (Analysis Ninjas) to do some subversive work. A question that came to my mind was: What is the incrementality of doing any marketing at all? What would happen if we do nothing, and we retire all our marketing people? Would the company go under?

Now it is rare that questions like those get asked. But it is too tempting not to use this methodology to get a sense for what the answers might be.

So for variation #3, no catalogs or email were sent to the customers in the test group. Here are the results…

It turns out if you completely stop marketing, and you are an established company, the impact is not that your revenue goes to zero! :)

Revenue in this variation went down 58% (pretty big). The impact on net to the bottom-line was a reduction of 42%. Both not great, but not zero.

So now you have some sense of what is the incrementality of all the people in marketing (their salaries, pensions, expenses etc.), and what you have to compute is if it is less than or greater than $1.09 (the loss in net impact).

Talking just a smidgen more seriously, eliminating catalogs and emails (and all marketing) might not make the company bankrupt immediately. But that is simply an outcome within the confines of this experiment. And it is easy to imagine how the impact might just get worse over time. The nice thing is that you can also test that!

Good lord I love this stuff!

The Lessons from this Controlled Experiment.

It is possible to compute incrementality of adding or removing marketing strategies.

It is possible to go back and use this incrementality to make solid, long-term new decisions for the business (and not to keep doing what you have forever until your business goes bankrupt).

It is possible to take politics, bickering, back stabbing and all that ridiculous stuff out of the picture. Okay maybe not all of it, but a lot of it.

It is possible to determine the value of doing Paid Search campaigns for brand terms where you already rank #1 via SEO. It is possible to understand if you should invest in Facebook at all. It is possible to understand how much to support your TV campaigns via Yahoo! display campaigns. It is possible to specifically nail down every incremental dollar added to the bottom-line of adding YouTube to your Search campaigns and then adding radio campaigns and then adding magazine ads and then adding Twitter. And along that chain it is possible to understand exactly when you've reached diminishing margins of return!

Important: The lesson you should not take from this is that catalogs don't work. They may work for you, they may not. All you should take away are the possibilities outlined above.

Closing Thoughts.

Here are some important bits of context, and a few more lessons I've learned from having done this a bunch of times…

If you want to learn more about controlled experiments, and see more examples and a case study, please jump to Chapter 7 and page number 205 in your copy of Web Analytics 2.0.

Bonus: Here's one of my favorite articles… all the way from 2007 but chock full of pithy valuable lessons for all of us regardless of our field: 41 Timeless Ways to Screw Up Direct Marketing

Bonus 2: Google Analytics has a wonderful set of reports called Multi-Channel Funnels. They are very good at showing how many outcomes are delivered via multiple media channels (say search + Facebook + display campaigns vs search only). They are also very good at telling you the order in which these channels were exposed to the person. It is important to know this is happening, and how much. Mutichannel funnel reports won't answer the questions at the top of this report. It might tell you how urgent it is to answer them (see this video, min 21 onwards: Google Analytics Visits Change). Even if you use other dedicated tools in the market that do "attribution modeling" you still won't get the precise answers you need to optimize your channels. Your only path out? Controlled experiments. Go back up and read this post again. :)

Okay it’s your turn now.

Are controlled experiments a part of your marketing and analytics portfolio? If yes, would you share one that perhaps was your favorite? If no, what are the barriers to adopting them in your company? Having read this post what might be the biggest downside to experimentation? What do you find exciting?

Please share your feedback, excitement (or lack there-of), life lessons via comments.

Thanks.

Measuring Incrementality: Controlled Experiments to the Rescue! is a post from: Occam's Razor by Avinash Kaushik