Is that your web analytics existence?

Don't feel too bad, you share that plight with most citizens of the Web Analytics universe.

The problem? The absolutely astonishing ease with which you can get access to data!

Not to mention the near limitless potential of that data to be added, subtracted, multiplied, and divided to satiate every weird need in the world.

You see just because you can do something does not mean you should do it.

And yet we do.

Like good little Reporting Squirrels we collect and stack metrics as if preparing for an imminent ice age. Rather than being a blessing that stack becomes a burden because we live in times of bright lovely spring and nothing succeeds like being agile and nimble about what we collect, what we give up, and what we deliberately choose to ignore.

The key to true glory is making the right choices.

In this case its making right choices about the web metrics we knight and sent to the battle to come back with insights for our beloved corporation to monetize.

A very simple test can allow you to figure out if the metric you are dutifully reporting (or absolutely in love with) is gold or mud.

It is called the Three Layers of So What test. It was a part of my first book, Web Analytics: An Hour A Day.

What's this lovely test?

Simple really (occam's razor!):

Ask every web metric you report the question "so what" three times.

Each question provides an answer that in turn raises another question (a "so what" again). If at the third "so what" you don't get a recommendation for an action you should take, you have the wrong metric. Kill it.

This brutal recommendation is to force you to confront this reality: If you can't take action, some action (any action!), based on your analysis, why are you reporting data?

The purpose of the "so what" test is to undo the clutter in your life and allow you to focus on only the metrics that will help you take action. All other metrics, those that fall into the nice to know or the highly recommended or the I don't know why I am reporting this but it sounds important camp need to be sent to the farm to live our the rest of their lives!

Ready to rock it?

Let's check out how you would conduct the "so what" test with a couple of examples.

Key Performance Indicator: Percent of Repeat Visitors.

You run a report and notice a trend for this metric.

Here is how the "so what" test will work:

At this point you should cue the sound of money walking out the door.

Bottom-line: This might not be the best KPI for you.

Let me hasten to point out that there are no universal truths in the world (though some religions continue to insist!).

Perhaps when you put your % of Repeat Visitors KPI to the "so what" test you have a glorious action you can take that improves profitability. Rock on! More power to you!

Key Performance Indicator: Top Exit Pages on the Website.

[Before we go on please know that top exit pages is a different measurement than top pages that bounce.]

You have been reporting the top exit pages of your website each month, and to glean more insights you show trends for the last six months.

The "so what" test in this case highlights that although this metric seems to be a really good one on paper, in reality it provides no insight that you can use to drive action.

Because of the macro dynamics of this website, the content consumption pattern of visitors does not seem to change over time (this happens when a website does not have a high content turnover – like say a rapidly updating news site), and we should move on to other actionable metrics.

Here the "so what" test not only helps you focus your precious energy on the right metric, it also helps you logically walk through measurement to action.

Key Performance Indicator: Conversion Rate for Top Search Keywords.

In working closely with your search agency, or in-house team, you have produced a spreadsheet that shows the conversion rate for the top search keywords for your website.

Okay.

That's it.

No more "so what?"

With just one question, we have a recommendation for action. This indicates that this is a great KPI and we should continue to use it for tracking.

Notice the characteristics of this good KPI:

#1: Although it uses one of the most standard metrics in the universe, conversion rate, it is applied in a very focused way – just the top search keywords. (You can do the top 10 or top 20 or as many "head keywords" as it makes sense in your case, just be aware this does not scale to the "mid" or "tail".)

#2: It is pretty clear from the first answer to "so what?" that for this KPI the analyst has segmented the data between organic and PPC. This is the other little secret: no KPI works at an aggregated level to by itself give us insights. Segmentation does that.

Key Performance Indicator: Task Completion Rate.

You are using a on-exit website survey tool like 4Q to measure my most beloved metric in whole wide world and the universe: task completion rate. (You'll see in a moment why. :)

Here's the conversation…

Nice right?

Notice in this case you have a inkling to the top super absolutely unknown secret of the web analytics world: If you tie important metrics to revenue that tends get you action and a god like status.

Keep that in mind.

So that's the story of the "so what" test. A simple yet effective way of identifying the metrics that matter.

This strategy is effective with all that we do, but it is particularly effective when it comes to the normal data puke we call the "management dashboard". Apply the "so what" test and you'll make it into a Management Dashboard.

Closing Summary:

Remember, we don't want to have metrics because they are nice to have, and there are tons of those.

We want to have metrics that answer business questions and allow us to take action—do more of something or less of something or at least funnel ideas that we can test and then take action.

The "so what" test is one mechanism for identifying metrics that you should focus on or metrics that you should ditch because although they might work for others, for you they don't pass the "so what" test.

And killing metrics is not such a bad thing. After all this is the process that has been proven to work time and time again:

More here: Web Metrics Demystified.

Ok now it's your turn.

Do you have a test you apply to your web metrics? What are your strategies that have rescued you during times of duress? What do you like about the "so what" test? What don't you like about it? Do you have a metric that magnificently aced the "so what" test?

Please share your comments, feedback and life lessons via comments.

Thanks.

PS:
Couple other related posts you might find interesting:

• Six Web Metrics / KPI's To Die For
• 4 "Useless" KPI Measurement Techniques
• Five Rules for High Impact Web Analytics Dashboards

Kill Useless Web Metrics: Apply The "Three Layers Of So What" Test is a post from: Occam's Razor by Avinash Kaushik

The reason is simple: The ecosystem within which you function on the web contains mind blowing data you can use to become better.

Your traffic grew by 6% last year, what was your competitor's growth rate? 15%. Feel better? : ) When should you start doing paid search advertising for tours to Italy for 2011? In May 2010 (!). What is your "share of search" in the netbook segment compared to your biggest competitor? 9 points higher, now you deserve a bonus! How many visitors to your site go visit your competitor's site right after coming to yours? 39%, good god! Where to do display advertisements to ensure you get in front of men considering proposing to their girlfriends (or boyfriends)? Go beyond targeting men between the age of 28 and 34, use search behavior and be really smart.

I am just scratching the surface of what's possible.

It is simply magnificent what you can do with freely available data on the web about your direct competitors, your industry segment and indeed how people behave on search engines and other websites.

The secret to making optimal use of CI data lies in one single realization: You must ensure you understand how the data you are analyzing is collected.

Not all sources of CI data are created equal. It is key that before you use the data that comScore or Nielsen or Google or HitWise or Compete or your brother-in-law shove into your face that you understand where the data comes from.

Once you understand that you choose: 1. The best source possible that is 2. The right answer for the question you are asking (which implies you have to be flexible!).

Here are the sources of competitive intelligence data.

#1: Toolbar Data.

Toolbars are add-on's that provide additional functionality to web browsers, such as easier access to news, search features, and security protections. They are available from all the major search engines such as Google, MSN, Yahoo! as well as from thousands of other sources.

These toolbars also collect limited information about the browsing behavior of the customers who use them, including the pages visited, the search terms used, perhaps even time spent on each page, and so forth. Typically, data collected is anonymous and not personally identifiable information (PII).

After the toolbars collect the data, your CI tool then scrubs and massages the data before presenting it to you for analysis. For example, with Alexa, you can report on traffic statistics (such as rank and page views), upstream (where your traffic comes from) and downstream (where people go after visiting your site) statistics, and key-words driving traffic to a site.

Millions of people use widely deployed toolbars, mostly from the search engines, which makes these toolbars one of the largest sources of CI data available. That very large sample size makes toolbar data a very effective source of CI data, especially for macro website traffic analysis such as number of visits, average duration, and referrers.

Search engine toolbars are a ton more popular which is the key reason that other toolbars data sources, such as Alexa, are not useful any more (the data is simply not good enough).

Toolbar Data Bottom-line: Toolbar data is typically not available by itself. It is usually a key component in tools that use a mix of sources to provide insights.

#2: Panel Data.

Panel data is another well-established method of collecting data. to gather panel data, a company may recruit participants to be in a panel, and each panel member installs a piece of monitoring software. The software collects all the panel’s browsing behavior and reports it to the company running the panel. Additionally the person is also required to self report demographic, salary, household members, hobbies, education level and other such detailed information.

Varying degrees of data are collected from a panel. At one end of the spectrum, the data collected is simply the websites visited, and at the other end, the monitoring software records the credit cards, names, addresses, and any other personal information typed into the browser.

Panel data is also collected when people unknowingly opt into sending their
data. Common examples are a small utility you install on your computer to get the weather or an add-on for your browser to help you auto complete forms. in the unreadable terms of service you accept, you agree to allow your browsing behavior to be recorded and reported.

Panels can have a few thousand members or several hundred thousand.

You need to be cautious about three areas when you use data or analysis based on panel data:

The panel methodology is based on the traditional television data capture model. In a world that is massively fragmented, panels face a huge challenge in collecting accurate and complete (or even representative) data. A rule of thumb I have developed is if a site gets more than 5 million unique visitors a month, then there is a sufficient signal from panel-based data.

Panel Data Bottom-line: For companies such as comScore and Nielsen panel data has been a primary source for competitive reporting they provide their clients. But because of the methodology's inherent limitations, recently panel data is augmented by other sources of data before it is provided for analysis (including for a subset of data you'll get from comScore and Nielsen – please check & clarify before you use the data).

#3: ISP (Network) Data.

We all get our internet access from Internet Service Providers (ISP's), and as we surf the Web, our requests go through the servers of these ISP's to be stored in server log files.

The data collected by the ISP consists of elements that get passed around in URLs, such as sites, page names, keywords searched, and so on. The ISP servers can also capture information such as browser types and operating systems.

The size of these isps translates into a huge sample size.

For example, Hitwise which chiefly relies on isp data, has a sample size of 10 million people in the United states and 25 million worldwide. Such a large sample size reduces sample bias (surprise!). There are also geographically focused competitive intelligence solutions, like Netsuus in Spain, that provide analysis from excellent locally sourced data.

The other benefit of ISP data is that the sampling bias is also reduced; since you and I don’t have to agree to be monitored, our ISP simply collects this anonymous data and then sells it to third-party sources for analysis.

ISP's typically don’t publicize that they sell the data, and companies that purchase that data don’t share this information either. So, there is a chance of some bias. Ask for the sample size when you choose your ISP-based CI tool, and go for the biggest you can find.

ISP Data Bottom-line: The largest samples of CI data currently available comes from ISP data (in tools like Hitwise and Compete). Though both tools (and other smart ones like them) increasingly use a small sample of panel data and even some small amount of purchased toolbar data.

#4: Search Engine Data.

Our queries to search engines, such as Bing, Google, Yahoo!, and Baidu, are logged by those search engines, along with basic connectivity information such as IP address and browser version. In the past, analysts had to rely on external companies to provide search behavior data, but increasingly search engines are providing tools to directly mine their data.

You can use search engine data with a greater degree of confidence, because it comes directly from the search engine (doh!). Remember, though, that the data is specific to that search engine—and because each search engine has distinct user base, it is not wise to apply lessons from one to another.

With that mild warning here are some amazing tools. . . .

In Google AdWords, you can use Keyword Tool, the Search-based Keyword Tool and Insights for Search.

Similar tools are available from Microsoft: Entity Association, Keyword Group Detection, Keyword Forecast, and Search Funnels (all at Microsoft adCenter Labs).

Search Engine Data Bottom-line:Search engine data tends to be the primary, and typically the best source you can find, for search data analysis. If you are analyzing data for your SEO or PPC campaigns and you find the search engine providing the data then you should instantly embrace it and immediately propose marriage!

#5: Benchmarks from Web Analytics Vendors.

Web analytics vendors have lots of customers, which means they have lots of data. Many vendors now aggregate this real customer data and present it in the form of benchmarks that you can use to index your own performance.

Benchmarking data is currently available from Fireclick, Coremetrics, and Google Analytics. Often, as is the case with Google Analytics, customers have to explicitly opt in their data into this benchmarking service. But this is not always true for all vendors, please check with yours.

Both Fireclick and Coremetrics provide benchmarks related to conversion rates, cart abandonment, time on site, and so forth. Google Analytics provides benchmarks for visits, bounce rates, page views, time on site, and % new visits.

In all three cases, you can compare your performance to specific vertical markets (for example, retail, apparel, software, and so on), which is much more meaningful.

The cool benefit of this method is that websites directly report very accurate data, even if the web analytics vendor makes that data anonymous. The downside is that your competitors might not all use the same tool as you; therefore, you are comparing your actual performance against the actual performance of a subset of your competitors.

With data from vendors, you must be careful about sample size, that is, how
many customers the web analytics vendor has. If your web analytics vendor has just 1,000 customers and it is producing benchmarks in 15 industry categories, it might be a hit or a miss in terms of how valuable / representative the benchmarks are.

WA Vendor Data Bottom-line: Data from web analytics vendors comes from their clients, so it is real data. The client data is anonymous, so you can’t do a direct comparison between you and your arch enemy; rather, you’ll compare yourself to your industry segment (which is perfectly ok).

#6: Self-reported Data.

It is common knowledge that some methods of data collection, such as panel-
based, do not collect data with the necessary degree of accuracy. A site’s own analytics tool may report 10 million visits, and the panel data may report 6 million. To overcome this issue, some vendors, such as Quantcast and Google’s Ad Planner, allow websites to report their own data through their tools.

For sites that rely on advertising, the data used by advertisers must be as
accurate as possible; hence, the sites have an incentive to share data directly. If your competitors publish their own data through vendors such as Google’s Ad planner or Quantcast, then that is probably the cleanest and best source of data for you.

One thing to be cautious about when you work with self-reported data. Check the definitions of various metrics. For example, if you see a metric called Cookies, find out exactly what that metric means before you use the data.

Self-Reported Data Bottom-line: Because of its inherent nature, self-reported data tends to augment other sources of data provided by tools such as Ad Planner or Quantcast. It also tends to be the cleanest source of data available.

#7: Hybrid Data (/All Your Base Are Belong To Us).

Competitive intelligence vendors are observing you from the outside. Any single source, toolbar or panels or isp or tags or spyware etc, will have its own bias / limitation.

Some, smart, vendors now use multiple sources of data to augment the data set they started their life with.

The first method is to append the data. This is what's happening in the case of Quantcast and Google Ad Planner, in both cases they have their own source of data to which your self reported data is added. The resulting reports are "awesomely good".

The second method is to put many different sources (say toolbar, panel, isp) into a blender, churn at high speed, throw in a pinch of math and a dash or correction algorithms, and – boom! – you have one "awesomely good" number. A good example of this is Compete or the DoubleClick Ad Planner.

Google's Trends for Websites is another example of a tool that uses hybrid data for its reporting (see answer #2 here).

The benefit of using hybrid methodology is that the vendor can plug in any gaps
that might exist between different sources.

The challenge is that it is much harder to peel back the onion and understand some of the nuances and biases in the data (sometimes mildly frustrating to analysis ninja's such as myself!).

Hence, the best-practice recommendation is to forget about the absolute numbers and focus on comparing trends; the longer the time period, the better.

Hybrid Data Bottom-line: As the name implies, hybrid data contains data from many different sources and is increasingly the most commonly used methodology. It will probably be the category that will grow the most because frankly in context others look rather sub optimal.

[Update:] #8: External Voice of Customer Data.

This is one often overlooked source of competitive intelligence (/benchmarking) data. There are several ways to use Voice of Customer data.

For starters various companies such as iPerceptions (like CoreMetrics, Google Analytics, Fireclick above for clickstream) publish Customer Satisfaction & Task Completion Rate (my most beloved metric!) numbers for various industries.

If I am in the internet retail game I can use these benchmarks to compare my performance:

Or I can dig deeper and compare my performance by the Primary Purpose segments:

Both of the above are from the iPerceptions Q4 2009 Ecommerce Benchmark report. You'll find other reports in the Resource Center.

With other sources like the ACSI (American Customer Satisfaction Index) you can get a big deeper. Just choose an industry from their site, I choose Internet Travel, and bam!

If I am Travelocity I am wondering what in the name of Jebus did the other guys do last year to have all those gains in Satisfaction where I got a zero.

And really what are those guys at Priceline eating! 5.6 points improvement just last year, 15 points over the last 9! Sure they started with a smaller number but still.

What can I, sad Travelocity, learn from them? From others?

In both cases above the intelligence came from a third party doing the research and giving you data for free.

But you can also commission studies, from the two companies above or one of thousands like them on the web.

Or you can do it yourself.

I just met a Top Web Company the other day and I spent $300 on 20 remote usability participants to go to the website of Top Web Company and their main competitor. I gave the usability participants the exact same tasks to do on both sites.

The scores were most illuminating (and embarrassing for Top Web Company). It allowed me to (without working at either company) collect competitive intelligence about how each were delivering against: 1. Task Completion Rate and 2. Customer Satisfaction.

You could collect your own competitive intel using UserTesting.Com, User Zoom, Loop11, or one of many other tools.

Or for even "cheaper" (and a bit less impactful) insights you can use something delightful like www.fivesecondtest.com. Upload how your pages, upload those of your competitors (or complete strangers not in your industry) and learn from real users which designs they prefer and what works best.

Hybrid Data Bottom-line: I love customers, I love Task Completion Rate as a powerful metric, I love VOC. Above are three simple ways in which you can collect competitive intelligence using Voice of Customer data and drive action perhaps even faster than the first seven methods!

[PS: Nothing, absolutely nothing, works better to win against HiPPOs than using competitors and customers!]

The Optimal Competitive Analysis Process.

A lot of data is available about your industry or your competitors that you can
use to your benefit.

Here is the process I recommend for CI data analysis:

Don’t skip the steps, and glory will surely be yours.

See the additional posts linked to below for types of analysis you can do once you choose the right tool [OR you can also start on page 221 of my new book Web Analytics 2.0!].

Ok now your turn.

Do you use a source of competitive intelligence data not covered in this blog post? Which of the above 7 is your favorite? Was there something surprising you learned in this post? What is one thing you would add to the critical analysis above?

Please share your tips, best practices, critique in comments.

Thanks.

PS:
Couple other related posts you might find interesting:

• Competitive Intelligence Analysis: Metrics, Tips & Best Practices
• Paris Hilton, Kim Kardashian & Telling Stories With Data
• Competitive Intelligence Analysis: Google / DoubleClick Ad Planner
• Competitive Intelligence Analysis: Google Insights for Search
• Competitive Intelligence Analysis: Google Trends for Websites
• Google’s Search Based Keyword Tool

The Definitive Guide To (8) Competitive Intelligence Data Sources! is a post from: Occam's Razor by Avinash Kaushik

There is nothing particularly wrong with the standard 19,000 reports in your web analytics tool. But they do represent the Vendor's best guess about what you should look at. Sometimes they even get it right.

Most of the time though your business is absolutely unique (even as it exists amongst hundreds of competitors) and it is absolutely important that you take your web analytics tool and mold it around you. The power that is given to you even in free tools like Yahoo! Web Analytics and Google Analytics can create a view of data that will help you find faster insights.

This post is inspired by a suggestion from Horia Neagu in reply to my tweet asking for blog post ideas. My thanks to Horia.

Horia's question was: How about a post entitled "10 Google Analytics Custom the Reports You Absolutely Must Set Up"?

I am not going to write about that, simply because the very idea that a report is custom means that there are probably no "ten standard custom reports" to set up.

I am going to share one recommendation and two ideas for making your own custom reports better.

This is a "teach a person to fish" type post. Sorry. :)

No Goals, No Glory.

Here's a cliché: If you don't know where you are going, any road will take you there.

Nowhere is this more applicable than when it comes to trying to find insights from your data you can action.

You report your poor heart away, no one seems to be able to take anything you give and take action.

Often it is the case that you and I have not bothered to sit down with he HiPPO / the boss's boss and tried to understand what in the name of all that is holy and pure is our website trying to do!

What are the goals?

No custom report (or advanced segment, the life giving oxygen) was ever created without an answer to that question.

So ask that question. Get an answer before you go about your customization ways.

If your leaders / clients truly want wisdom from you they will answer the question. But it does happen sometimes that begging or throwing yourself at her/him does not elicit anything of value.

In those rarest of rare cases (after you have already submitted your resume to other companies that will cherish you for the golden child you are) try to figure these one or more of these three things out:

1. Where it the company currently spending money? Email marketing? Affiliate? Paid Search? Online PR?

And what's the biggest bucket?

Now go create your custom reports because if you can help the HiPPO's figure out how to reduce cost of acquisition they will love you more than you can imagine.

2. If possible, without violating HR policies, figure out what your boss's salary bonus is tied to.

Start doing analysis that will help your boss get a raise. A great goal to have, love and promotions likely.

3. Go visit your website, yes yes the one you have not used for a while. : ) Find out the single worst thing about it (should take you less than half hour of clicking around).

Now go look for data that will help you prove that the worst thing is the worst thing. Not a bad goal to have to fix what's completely broken, and people will listen.

Three good proxies if you have no goals to start with. Ideally you'll know what your Macro Conversion is so you'll start your analysis with a bang. Super ideal would be that you know both your macro and micro conversions!

Remember: No goals, no glory. Not for you. Not for your boss. Not for your company.

Custom Reporting Tip #1: Always, Always, Always Focus On The End To End.

One problem with standard web analytics reports is that the data you need is scattered all over the place, making it harder for you to find insights.

For example I am trying to figure out which pages stink and need fixing. In Yahoo! Web Analytics the standard report only shows Page Views and Average Time on Page. How much good will that do?

Or I want to figure out which sources of traffic I should make love to or divorce? The standard Google Analytics report spreads the data I need over four tabs.

Custom reports are good at solving this problem. Drag the dimension you need (traffic sources, landing pages etc) and analyze the data by choosing the metrics that tell the end to end story.

End to end has three pieces: Input. Onsite Activity. Outcome.

Here is my favorite, custom, traffic sources report:

By inputs I mean metrics that help you understand (in line with your goals) how well the "top of the funnel" (usually acquisition) is working.

In my case that is measuring Visits (to know who is sending how much) and % of New Visits (to know who is sending how much that is of value to me – new visitors are very valuable in this case).

At a glance I have the information to start making some preliminary superficial judgments about performance.

By onsite activity I mean choosing metrics that help you understand the behavior of your visitors on your website (thus absolving your Acquisition team of any blame, perhaps!).

In my case that is measuring Bounce Rate (not so fast Acquisition team, don't get me bad traffic! :)) and Average Time on Site (as a proxy of measuring if the landing pages are engaging visitors and as a proxy of how much each traffic bucket engages with the site).

Depending on my goals I would choose different onsite activity metrics for my custom report.

By outcomes I mean, well you don't need to know do you? You read this blog! I am all about outcomes, every day!!

In my case the outcome metrics are Goal 1 (my macro conversion) and Average Value created for my website.

I could also have used $ Index or Per Visit Goal Value metrics if I were analyzing a non-ecommerce / content only website.

Remember Without a crisp articulation of outcomes every battle you fight will be lost, every day and you will live a very very unhappy life.

With these end to end metrics my custom report tells me stories that would otherwise take too long to piece together (or stories I might have missed completely).

One of the stunning realizations was just valuing Twitter traffic for example. (Click on the above report for a higher resolution report).

My twitter (social media) campaigns were doing exceptionally well. Lots of traffic (#3) overall, the second highest conversion rate (0.78%) and a Average Value that was not the best but rather sweet ($136 – which looks ever better when you compare the cost which is negligible).

Yet non focused traffic from twitter is not doing that well. 0.33% conversion and $39 average value. Pathetic.

I can now jump, like a na'vi, from row to row understand performance quickly and efficiently.

The power for a custom report that shows the end to end story.

It is so easy too.

For example here is the exact same custom report created in Yahoo! Web Analytics, just 30 seconds of drag and drop:

[Click on the image for a higher resolution version.]

Always go e2e. If you don't, you better have a good excuse!

Custom Reporting Tip #2: Create "Micro Eco-Systems".

I think I can honestly say that I have get to meet a single decision maker or a department or a company that has yet to tell me: "You know what the problem is Avinash? I don't get enough reports."

:)

We love spewing out data and pretty soon your company has 200 reports and I'll bet you $50 that not a single decision is actually based on data.

So fix it.

Create micro eco-systems.

What I mean are custom reports that do three things:

Let's understand how to do this by looking at a real life example.

My goal is to create a "search ecosystem" report that collects different important pieces of data, for three different stakeholders, all into one place.

I do that by first understanding who all the stake holders are who'll need to use the data (let's hope!) and doing a simple stake holder interview to understand what their business goals are.

Now rather than spamming everyone with a report (that no one will find, I'll have a hard time version controlling, and other such pain), I'll just put it all together in one place (at least in Google Analytics due to a simple yet exceptional feature – tabs!!).

Here is a pictorial view of the process that I'll go through:

[Click on the image for a higher resolution version.]

My first "client" is the Acquisition team, they are responsible for spending the company's money wisely. They are measured on bringing new Visitors (potential customers) to the site.

I create a tab for them that shows Visits, New Visits, Bounce Rate and Average Time on Page (not site). I add the latter two because I want them to see their end to end view and I want them to realize they hold some level of responsibility for people not just coming, but also staying.

We have just one report, each day (God willing) they'll log in and see their own personalized sweet view of the data:

[Click on the image for a higher resolution version.]

But I am not done yet.

Next up is my HiPPO. Let's call him Paul.

Paul only cares about Revenue and all things connected to revenue. He does not care about any other metric. Nothing wrong with that.

Rather than creating another report for Paul I click on *Add Tab* simply do this:

Create a person view for Paul. I throw in Visits (I have to give him some context and some Input metric) and Goal Conversion Rate (so he knows efficiency), Goal Value, Revenue, Shipping (because Paul is having us charge lots for shipping because he thinks of it as a profit center (!!), not great but remember I am personalizing).

Here's the resulting output:

[Click on the image for a higher resolution version.]

You know what the result is?

Paul actually looks at the data every other day (and a bit deeper each Friday) because it does not contain crap. It contains just what he needs to do his job (find people to reward and find people to fire).

That is what you are going for. Taking people from data apathy to data usage.

[Oh yes, yes, I noticed Revenue and Shipping are zero in the above screenshot. I wish I could show you someone's real data! Not today. But you get what the report is trying to do.]

Finally there's Amy. Another key stake holder, but a tougher nut to crack. You see her bonus is tied only to Visits, a low bar if there ever was one.

So what do you do?

You can't over smart Amy, she is too smart for you (and probably a level or two higher).

You are going to lose her if you give her too much data.

You need to entice her to start using data, and restrain your smarts – you know you want to create a impressive 8 column report!

In this case I simply add a tab. It says Amy Chang (so she knows it is her very own personal report). It has Visits and Average Time on Site. I added Time on Site as a Outcome metric, just to keep up with my outcomes obsession.

[Click on the image for a higher resolution version.]

It is simple. It is effective.

It will get her to see just the data she wants (plus one more thing :)).

And here's the sweet part…. since this his an eco-system report perhaps she (and Paul as well) might see other pieces of data in other tabs and might be intrigued enough to ask you to add more metrics.

Then and only then and only at that time and only when you are asked (am I repeating myself?) add those metrics. It is vastly more likely that she (and Paul) will use the data.

There you go… one report that has all the data each stake holder needs personalized and customized.

No one is going to come to you and say: "hey want folder is my search report" or "I don't understand what all this data is saying" – it is personalized. And when you have to make changes, it is all in one place.

Well…

Such simple little things: tabs (or cup cakes :)).

Makes it so much easier for you to create a data democracy. And a bit sad that you can't do this with most paid web analytics tools today – yes you can create a custom report but the above report would be a one huge 13 column report that:

I hope all paid web analytics vendors will incorporate this feature, for the sake for our data democracy!

That's the story. Goals. End to End. Micro self contained eco-systems.

I was hoping to teach you how to fish, rather than just tell you which 10 reports to create. Regardless of the specifics of the reports and metrics above I hope you have learned a bit more as to how to think about approaching the issue and the important things to focus on.

Custom reports are a powerful way to take what looks overwhelming in web analtyics – REPORTS and DATA – and make it didapper. It is also a wonderful way to start the journey of your company, big or small, to start using data.

Ok now your turn.

Do you have custom reporting tips to share with us? What small or big thing you have done that really really worked for you? Have you tried end to end reports? How about micro eco-systems? What strategy completely failed? Got a custom report you think everyone in the world should be using?

Please share your stories / tips / bruises / successes.

I'll send the best one a copy of my new book Web Analytics 2.0.

UPDATE: It was hard to pick just one winner so a copy of the book goes out to SteveK (for advocating common sense!) and to Ali Shah (for emphasizing sharing of context). A bonus prize also goes to MGSeeley (for bringing a smile with his adorable analytics haiku!).

Analysis Ninjas: Leverage Custom Reports For Better Insights! is a post from: Occam's Razor by Avinash Kaushik

I recently did a webinar for the Search Engine Strategies conference (I am doing the opening conference keynote at SES London and SES New York) and my Market Motive co-faculty member Greg Jarboe sent me this KPI via email:

"Your webcast was a big success. Your KPI questions per attendee was off the chart!"

I don't know why I had not thought of this wonderful KPI. So much better than # of attendees.

As always though context is king.

It could be a good thing ("you were great, engaged the audience") or a not such a good thing ("no one understood a thing you were saying, hence so many questions"). Only upon reading the actual questions could I figure out which case it was (mercifully case #1 for me!).

End of a minor web analytics lesson on going beyond obvious metrics and never, ever, never forgetting context.

Back to our story. . . an hour is too short a time to answer all the questions (even in a webinar just focused on attendee questions). So here is a small selection from the 80 questions I could not answer in the wide ranging webinar.

We will cover measuring success of SEO efforts on one web page, how to do search engine optimization for b2b websites, how to rank for highly saturated industries / categories / keywords, and which competitive intelligence tools do I use for search program optimization (and targeting display ads using search data!).

I hope you all find the answers to be of value.

#1. How do you measure SEO performance on a page level? I'd like to know how well my seo efforts for a particular pages have performed.

Every measurement question should start by taking one step back and thinking of goals.

In this case here are some obvious ones:

Now it is not hard to figure out how to measure performance! [Before you do any kind of measurement please consider going through the above exercise. It is simple, effective and works like a charm - not to mention allows to get going faster.]

Before you analyze do one small thing. Log into the Advanced Segmentation tool in your web analytics tool. Create a segment for Organic Search traffic. Sources -> Contain -> Google, Bing, Yahoo! etc. Save. Another way to cheat at this is to simply use Medium Matches Exactly Organic.

If your web analytics tool requires you to call the vendor to set up advanced segments or re-tag your site to get segments then switch. There are too many choices in the market.

Now log into whatever web analytics tool you use and drill down to the specific page you are interested in ("Top Pages Report" / "Content Title Report" etc). Apply the Organic Search segment to that report (in Google Analytics segments are on the top right, in other tools please refer to user manual).

More traffic, not that hard. Stretch the time period to six months (or some large date range – remember SEO takes time). What do you see? Nice and gradual up and to the right trends. Do your happy dance! Something's working. Now look down at the table under the graph that shows traffic sources. If you did your segment correctly you'll see just the search engines and how much each is contributing to your overall traffic. Does the distribution match your goals?

Ready for the next step? Click on Referring Keywords and now you are looking just at the keywords bringing traffic to this page. Do the keywords match the intent of the page? Do they contain keywords you were specifically targeting? No? Why not? On the other hand what are the surprises? Is the customer intent contained in the keywords telling you how to change / improve the page? Do it!

Indexing. . . I am a big fan of Google's Webmaster Tools because of the wealth of data available, if you are not using this free resource (no matter if you are a SEO or not). Bing's Webmaster Tools have also evolved a ton, please claim your account right away and dive in. [I have not had much fun with Yahoo!'s web master resources.] In either tool you are looking for how well your site is indexed (report: Your site on the web -> Top search queries -> Impressions), how well your pages are indexed and, my absolute favorite, which keywords your search results are showing up. You are checking to see if:

1. the pages you are targeting are being indexed frequently and

2. if your site is showing up for the keywords you were targeting.

You want validation that you are showing up for the set of keywords you are optimizing for (above) and that your pages are being recorded as being optimized for the right keywords (above the above :).

Success. . . I humbly believe that the biggest mistake most of us doing SEO make is that we are far too obsessed with ranking and meta this and that and how to work back algorithms etc etc. We should focus more on what was the business impact of our SEO efforts.

So in this context go back to your page report (from step 1 where you applied the organic segment) and look at the $Index [which is: (goal value + e-commerce revenue) / unique views of the page you are analyzing]. That is a crude measure how how efficient your page is being at converting. Of course look at our favorite metric bounce rate by keyword (that tells you if you can get people to give you one solitary click, the most primitive measure of SEO success).

If you truly want to kick it up a notch as a SEO please please please go to the Goal and Ecommerce / Conversions reports and apply your organic segment, stretch the time period, and report (aggressively) how well your SEO efforts are delivering value to the business.

Do it at a overall level, do it by country, do it by search engine, do it by specific keywords you were targeting. . . . and take two minutes to straighten your clothes because a new level of love and praise are about to be dumped on you by your company / client!

[Does the above seem like a lot of work even if it is straight forward? It is. I know we look for short cuts. There is no such thing in real life. But if you are willing to put in a little bit of sweat equity then you'll stand miles apart from your SEO competitors. Not a bad trade off, right?]

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#2. Is there a fundamental difference in SEO strategies for business-to-business sites vs consumer focused ones?

[It is worth pointing out I am not a hard core SEO, that would be Todd Malicoat, I just play one one TV! Think of below as my personal lessons from the front-line of doing this work to the extent my humble skills allow.]

The basic techniques you use to do search engine optimization between b2b and b2c do not change all that much.

Ok All that is the same, no matter if you are a b2b, b2c, b2a (business to aliens, yes they do exist!). Do all that first to make sure you are not coming to play the super bowl naked.

Here are a few things that are different with b2b. . . . .

* Some very effective SEO strategies like allowing users to add reviews and comments and extend the scope of the page do not work as well with b2b as it is a differ net type of engagement and experience with your customers. Well don't give up. You have many many white papers, though leadership papers, webinars, Big B2B Association publications where you contributed and more locked up in pdf or, much worse, behind a forced "give me your login" / "create a account" page. I am going to give you a false email, why not just give me the content, AND let the search engine index it efficiently after all you want people to consume the content.

Did I say already content is king?

* One of the most common issues with b2b websites is that they often have a very specific understanding of their space when it comes to how their potential customers search for information. This results in not speaking the same language (say keywords) as their customers. When I work with b2b websites I spend a lot of time in the AdWords Keywords Tool, Insights for Search, Compete etc analyzing keywords and search behavior in my category. This knowledge goes back into re-doing content, urls etc.

This is of course a good method for b2c as well, but it is significantly more important for b2b.

* Start a conversation. There will likely be a lot fewer individuals talking about you / your industry, a lot fewer tweeting and expressing their love (or hate). I get it. But conversation on your site and away from your site is key (obvious fact). Why not host a user forum on your website for current and future customers to come together and share their thoughts / ideas / complaints / rave about your competitors (scared?)? Why not seek out the few people who do talk about the industry on twitter and engage with them? Why not start a YouTube channel with a series of how-to videos? Why not, : ), start a blog? Not just to highlight your own pomposity and press releases but to really share and lift your industry (not just your company)? Why not become the destination for industry professional?

So few people in the b2b space bother to start conversations, why not use that to your advantage? Even if you can hook 100 people is that not more than worth it?

Three small things that I would prioritize higher when I work with b2b sites.

What do you do differently when it comes to your b2b clients?

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#3. When trying to help your rank in search engines. . . when you are in a saturated industry like health or travel insurance – how does the approach change or differ?

Two words: Long Tail!

When you say saturated most people mean that for the "top" keywords they are interested in there is too much competition. For example: "hotels in las vegas", "cheap health insurance" etc.

When there are a lot of players in the field it can be difficult to show up for the "head terms", especially if there are some strong players in the field. In these cases I have had a very positive experience focusing not on the head terms (terms for which there is a lot of traffic) but rather focusing on the long tail (usually key phrases that individually have little traffic but collectively these key phrases can deliver a ton of traffic).

So, if relevant for your business, try to rank for "california health insurance plans" or "california individual health plans" etc. Key phrases (not just words) that each have much less competition (and will likely deliver more relevant audiences).

You can use various keyword tools out there to identify these key phrases and then adapt your SEO strategy (pages, content, urls, etc) to focus on them. One way I use is to just type in competitor urls into AdWords Keyword Tool and then research what is working for them and adapt my strategy.

Targeting the long tail with SEO can be a bunch of work, hence I have recommended in the past that one effective and cheap way is to use paid search to monetize the long tail. But I can tell you from experience that it works. For example for this blog the top 10 (head) keywords bring in something like 5k visits and the long tail (around 25k keywords) bring close to 34k visits. All organic (I am not rich enough to afford paid search!).

One more bonus tip: Leverage "universal search".

Videos, pictures, downloads, offers, buttons, maps, uploaded menus, coupons, and on and on and on.

When you search for many terms relevant to me you'll see videos pop up, my book (uploaded into Google book search) show up with preview thumbnails, some of my flickr images and my twitter account and so on and so forth. For many of these searches I don't rank #1. But man do those listings (when triggered by the search engine's algorithms) stand out and grab the Searcher's attention. Often for competitor or big paid web analytics tool queries where I have a snowball's chance in a hot place of standing out.

It is ironic that most big companies (with so many assets to leverage) are pretty bad at this. So you win! :)

Also Google (I work there) Local Business Center is really good: http://www.google.com/local/add If you are a small business then this is one more important arrow to have in your quiver!

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#4. Can you look at your competitors sites in the analysis tools you have discussed?

Yes.

But first. . . . it is important to realize that you need to have two skills before you look at competitive intelligence tools:

If you meet the above two requirements. . . . .

I love using competitive intelligence tools because they give me a perspective and context that is simply missing from Omniture or WebTrends or CoreMetrics or the clickstream tools.

In the search context here are some of my favorite tools and what I use them for.

Insights for Search:

I adore I4S because it is perhaps the most comprehensive "database of intentions" thanks to providing us all with access to worldwide Google organic search data.

Use it to understand the latest trends in your category. For example: "How is interest in the computer security category (All Categories -> Computers & Electronics -> Computer Security) and what are the top 100 search terms and the fastest rising brand names / products / searches in that category?"

Use it to identify opportunities. "What states do people search for credit cards the most? What states do people search for Visa credit cards?" Oh look the states with really high credit card searches don't have really high visa card searches, maybe we should do some offline advertising!

Use it to time your campaigns. "When should I have started SEO and PPC campaigns for Italy Tours 2010?" In April 2009!! That's when people first started looking for them. Now go plan for 2011.

Helpful article: How to use Google Insights for Search.

Ad Planner:

This wonderful tool is really built to help you do better display advertising. You log in and you have the delightful ability to do demographic (male, female, age, education, income etc) and psychographic (baby boomers, extreme sports fan, household decision makers, luxury goods consumers, moms etc) segmentation. You can hone in precisely which websites most likely contain your desired audiences. Show them relevant ads and get clicks!

But in the search context there are two things that you use this tool for.

Type in any website you want, expedia.com in my case, and checkout the site and search affinity data:

[If you don't see the image above, turn off your ad blocker.]

"The affinity score estimates how many times more likely you are to reach an audience who visits a specific site or searches for specific keywords versus an audience on the internet overall." Source.

Sweet 'eh?

Second, click on the tab that says Search by Audience and then the Keywords Searched button and now you have an ability to use search behavior to identify audience pools.

To use the examples of my beloved Indianapolis Colts (go Colts!!!). . . . I have an ability to type in a bunch of related keywords (the tool suggests most used ones) and find out which websites are most likely to be visited by people who search for these keywords:

[If you don't see the image above, turn off your ad blocker.]

At the top are keywords I typed. On the bottom are most commonly searched keywords, I can choose these if I want.

I hit ok and then sort by Comp Index, to ensure I sort the data by the highest audience concentration (audience that searches for all things Colts in this case).

I can use this search and web data to identify where audience I am most interested in exists. I can use it to find out the keyword data for those sites. I can use this to identify sizes (visitors, page views etc) of those websites.

Nice right? Actionable too!

Helpful article: How to use Google Ad Planner.

Compete.Com:

Compete is a paid tool (and it only contains US data). I really love using it because of the wealth of search data it can provide, at an affordable prices.

[I have had a complimentary Pro account for the longest time thanks to the nice people from Compete, that might bias my opinion. Other than that I have no other affiliation with Compete.]

In context of Search I use the data for. . .

1. Identifying what are the top referring keywords for any site that I am interested in:

Above data for www.clickequations.com (the paid search analytics company I am on the advisory board of). Of course when you log in with a paid account you would see rest of the data like paid and natural search split for each keyword and time and what not.

Craig will not be happy that he ranks only #12 on the keyword list! :)

I can either use this data to go after keywords that are not currently referring traffic to ClickEquations (more for me!!) or I now know what keywords I need to target to take ClickEquations down in my quest for world domination! Ha!

See how focused you can be with data?

2. Identifying share of search for a keyword:

In this case I would like to own the pear fruit market, though at the moment I only own two trees. So I go into Compete to find who my current competition is (above exact match data for query "pears"). I can get lots of details about volume, paid and organic share, what percent of traffic comes to a site from that keyword, etc etc.

Now that I have a benchmark I can go about my super awesome kick butt SEO efforts and one way I know I am winning is to check this report in a month or two (or three weeks after whenever I think I am done). If I show up here I know I am having a impact.

These are just three of the many tools I use. There are a whole lot out there that sometimes give you similar data to the above three, or often give you a lot more. Just remember that there is a lot you can learn from what is going on in your ecosystem and at your competitors.

Ok now your turn.

Got a couple tips you want to share with us about how best to do SEO for B2B sites? How would you measure success of SEO efforts spent on a page on your website? Would you use any of the four ideas I have suggested? Care to comment on how to do SEO for crowded industries or for keyword categories where one or two players seem to dominate? What is your favorite search competitive intelligence tool?

Please share your tips / best practices / comments / critique.

Thank you.

Dear Avinash: Search / SEO Metrics & Analytics Questions + Answers is a post from: Occam's Razor by Avinash Kaushik

As we spring to action full of passion I wanted to share with you all a short list of things that will expand your little world of online marketing & web analytics.

We all have a tendency of getting caught in a rut, using the same tool to do the same things and spew forth the same data. Change is hard, even if we know that we should be executing a multiplicity strategy to win in the web analytics 2.0 world.

Before all the excitement of the new year wears out, here are five simple things I would love for you to try so that your company will have a glorious truly data driven 2010!

#1: Don't suck.

Seems obvious. And yet in our quest for ever more hard problems to solve we forget that the number one goal of every website is not to suck. Especially at the really simple and basic things.

At a recent conference there were three keynotes.

One was extolling the wonderfulness of their multi channel campaign tracking. When I went to their website it was a 100% flash website with a constrained small size where it took too much looking to click on anything and then too much scrolling to read anything and unclear calls to actions (if any). That's sucking. No amount of great multi channel tracking will save this company, they suck at the basics.

The second was about predictive analytics and how using massive integrations between online and offline databases they had accomplished some really cool reporting of data (and make no doubt the IT work done over 18 months to accomplish this was cool). Their home page is a mess. 24% of the content covers what any visitor might want, rest is the company shouting at you (in many annoying ways). That's sucking.

The third was about how to create data driven cultures and how this person had created a impressively big cross functional team across multiple countries and standardized on Omniture after a lot of work over two and half years. I did a search on some of their products and they did not have page one search listings (on Google or Bing) for what should be their head terms. (That's sucking.) They did have PPC ads, which I click on the ad for specific product they land me on generic nonsense pages. That's sucking.

I share these stories to illustrate vividly how we in the web analytics world get lost in our data and Omniture and Google Analytics and reporting and lose sight of the the basics and the customer experience.

It is important to realize that if you suck nothing else matters. Not your api driven integrated massively multi channel attribution analyzed campaign lifetime databases. That is not going to save you or your company.

Before you attempt the hard make sure that you do all the standard stuff to ensure your company has a fighting chance to win.

Here are some tips to inspire you:

• I LOVE looking at the bounce rates for the top 20 landing / entry pages to the site. Find the losers, fix 'em. These guys are so bad they could not even get one click from the visitors.

• Sit down with the owner of the top ten pages to the site and look at them. I mean really look at them and ask this question: "What the heck are we trying to do with each page?" Make sure there is a clear answer (and a match between Customer Intent and Webpage Purpose).

• Check the load time of your important pages. Use something simple like: www.WebSiteOptimization.com Or whatever complicated tool you have.

• Sign up for your websites campaigns using your personal email address. See how the emails look. Relevant? Personal? Click on the links, what to you see on the landing pages? Fix!

• Create a funnel for your cart / checkout / lead submission process. Find the biggest abandonment page. Fix it.

• Ask your Finance department where most money is being spent on the web. PPC? Affiliate? Display? What? Take a week to segment that data and find out how to save 10% of the cost.

• Count the number of links on your main pages. I mean count them. There are 98 links on a travel site I am looking at right now, on the page for a hotel in Chicago. 98! This is a top site.

  What are the analytics people doing if they are not helping the product page owner figure out how to kill atleast 50% of those links on a product specific page. There should be one link: Search for Hotel or Make Reservation! Do this for your site.

• Fix the 25 things Dr. Pete lists in this delightful checklist: 25-point Website Usability Checklist.

There are so many ideas. I hope that before you go for massive web analytics glory that your use your wonderful powers first to make sure your site and customer acquisition strategy does not suck.

PS: Bonus tip: Make sure you visit your website once a week, atleast.

#2 Learn basic statistics.

The days of tools and reports simply puking data out are rapidly reducing. No longer can tools or "analysts" just puke 15 metrics on a report and hope to survive.

Web Analytics tools are starting to become smart (see: Analytics Becomes Intelligent). Data is starting to truly get numerous.

For all of the above reasons it is becoming ever more important that you are know atleast Statistics 101. You don't have to be armed with the knowledge of how to create various models or be able to jump into SAS and get naked with it. But you are going to have to know what a mean and a median and r squared and standard deviations and Z scores and confidence intervals and all that lovely stuff is.

If you have not been exposed to statistics perhaps you can take a class at a local community college or university. Many employers will pay for ongoing job relevant education.

Alternatively get one of the simpler books on the topic and immerse yourself in self education. Regardless of if you are a novice or an expert I think one of the best books to start with is The Cartoon Guide To Statistics ($13). A cartoon book? Yes. It is quite good.

Once you know statistics 101 you'll find that you'll think of data analysis differently and you'll get better at finding that proverbial needle of insight in the haystack of data. Knowledge of statistics is a key arrow to add to your analytical skills quiver.

Hello statistical significance!

#3 Try one (or two) new usability / VOC tool/'s.

My passion for the customer is, as they say, legendary!

Part of it is the humility I have developed at the powerlessness of clickstream data to answer all the needed questions. Part of it is that there are just so many darn good options out there to listen to our customers.

So this year why not try one of the newer more powerful and yet cheap usability analysis tools?

Here are some tools that are pretty cool and unique:

• Five Second Test. I absolutely love the idea of collecting "first impressions" from current customers, employees or just randomly selected people. Within thirty seconds you can take a screenshot of your lovely home page or landing page, upload it and for free get feedback from real people.

• 4Q / Kampyle / UserVoice. Each of these tools does something completely different, and yet each allows people to type things that you can read and be wow'ed or saddened by. Why not try one of these tools this year and truly get in touch with your customers and a real and meaningful way?

• UserTesting.com. You are not a small enough company, or a big enough one for that matter, to do usability testing. This is usability testing for ultra cheap, $29 per person. Set out the tasks, identify your audience, test happens, you watch the video and read comments, you cry, you fix things, you become rich.

  Also checkout Feedback Army.

• WebSort / OptimalSort. The information architecture on most website is terrible and the reason is that company employees create it for themselves. A great option to hear from the customers was to do card sorting studies. Problem? Expense! Not any more baby. Both these tools are quite affordable, all online and in a fraction of the time it would take to do a offline card sorting study you can get the key data you need. Sweet.

You don't have to do all of the above. But you do have to listen to your customers.

In 2010 Consider trying just two tools listed above that you have not used so far. I promise you that you'll want to give me a big hug the next time you see me.

#4 Try one new competitive intelligence tool.

I practically have a illicit love affair with competitive intelligence. And I am not embarrassed!

If I ever come to see your company, or you see me presenting publicly, then you have seen me present data about your company / industry and then proceed to say nice / not nice things. There is just so much gold out there to be discovered.

Here are some tools for you to try, ideas for analysis you could do:

• Compete.com / Trends for Websites. I love the depth of data now available in both tools for free (even if you use just the free part of Compete). Index your overall performance against your competitors.

  Where do people go after they leave your site? What are the top five referrers for your competitor? What are the top sites that get traffic for the word love? All free from Compete.

  People who visit my site, what other sites do they visit? What are the things they search for? What's the difference between US traffic and India? All free from Trends for Websites.

• Google's Search-based Keyword Tool. If you have never explored the long tail for your website (if you are a medium to large site) using SbKT you might be committing a crime. If you have never taken a list of keywords AND the landing pages recommended by SbKT where you have zero impression share and given it to your SEO team then you should feel bad. There is so much here.

  [Learn how to use SbKT here: Monetize The Long Tail of Search.]

• Google Ad Planner. Some display / banner ads stink because they are just terribly produced and blink and annoy you with sound and do insane things when you move your mouse over them inadvertently. Most display ads stink because they are not relevant / well targeted. Make sure that is not your ads. Use the Ad Planner to hone into the exact sites where you can find your audiences.

  What sites are visited by: Men who are in the market for engagement rings. Women who are interested in the NFL. Young adults who are looking to buy net books. Affluent 100k+ folks or comic book buffs or brides to be.

  Now go buy advertising on those sites (from any ad network) and earn a higher ROI on your campaigns.

  [Learn more about Ad Planner: Competitive Intelligence Analysis: Google Ad Planner]

These four tools should keep you busy for a long time. Don't go at it all at once. Ask your boss's boss what his next 90 day priorities are, find the tool above that might have the insights, go on a honeymoon with it.

#5 Identify two new micro-conversions and goal values for each.

The road to web analytics glory (and a promotion for you) runs through the Micro Conversions path.

I am absolutely convinced that we don't get the love that we deserve from our company leaders because (even if we get beyond data puking) we rarely quantify the impact of all of work that the website is doing.

During Q1 make it your personal quest to identify two new micro conversions for your website (many ideas in the preceding blog post).

Now make sure, and this is absolutely key, you take one more step and quantify the economic value of each micro conversion (instructions and ideas: pages 159 to 162 in my new book Web Analytics 2.0).

That economic value will help you arrive at the number on the right, $83,848. That number will finally help you understand the complete value your website is adding to your business (only $21,454 is from the Macro Conversion). That number will allow you to measure your campaigns with a level of accountability that will be supremely awesome.

If you do nothing else on this list (I hope it does not come to that), please make sure you do this item. It is that important (especially if you are a non-ecommerce b2b government peaceful protest photo sharing website).

For the true Analysis Ninjas let me share one bonus item, one thing that will put even them above the top. . . .

Bonus: #6 Measure one thing that is "intangible".

The hardest thing to do in online analytics is to measure the intangible. How did people feel about the website experience? What was the positive brand lift? Did the unaided brand recall improve 60 days after the campaign (online or offline)? And more such questions.

Each is really hard to answer, one must think differently.

Here is a post with seven different strategies: Brand Measurement: Analytics & Metrics for Branding Campaigns.

As an Analysis Ninja go all out on three of them this year and take your business to the next level of measurement and insights.

Good luck ya'll!

Ok now your turn.

Care to share examples of sucking that you have killed on your websites? Got a creative use of statistics in your web metrics practice? Which is your favorite online customer listening strategy? Have you had success with quantifying goal values for your micro conversions?

What is your company's online, or online analytics, new year resolution?

Please share your thoughts via comments, thanks much!

Five Sweet Web Analytics Resolutions To Kick It Up A Notch is a post from: Occam's Razor by Avinash Kaushik

Web analytics gems lie deep in the data and we spend our lives looking at the top ten rows of data.

It does not matter which report you look at. Affiliates. Products sold. Referring URL's. Pages viewed. Search keywords. Promotions. Geographies. Really pick any report with any dimension you want to look at, we spend our time (and valuable space on our dashboards) looking at the top ten.

We look at the top ten rows of data because:

1. Too much data from our web analytics tools.

2. Lack of clarity from our business leaders about what the site is solving for.

3. Not enough hours in the day to overcome challenge #1 and #2.

But if you just look at the top ten rows of anything here are the two corrosive problems:

1. The top ten of anything rarely changes (with the exception of hourly changing content – news – sites).

2. The top ten only focuses on the head, while the magic is in the long tail of anything. Magic related to finding challenges in your business. Magic related to finding opportunities. Magic that will help identify things you can actually action.

Allow me to make the case for you to look beyond the top ten rows in your reports by sharing three short stories. In each case I request you to look beyond the specific request and tool, rather focus on the analysis and how you could possibly apply it. I hope is to inspire, not to prescribe.

For example take a look at this report. . . .

I am sure when you look at it now it appears all mysterious, full of potential. You can't wait to take it out for a first date and then another and by the third date if you do the same old thing it gets boring. You are done looking at the bounce rates and time on site and conversions of these keywords. In the best case scenario you have even optimized landing pages. Good.

The first week's over, now want? Why keep reporting the top ten keywords on you Executive Management Global KPI Dashboard?

Look at the top of that table. For this website 86,837 visits came from 8,939 keywords!

What's going on with the other 8,929 keywords?

We never bother with them both because it is really hard to look at more than 10 rows of data. Harder still to look at 30 or 50 or 70 rows of data. Not only do we have a hard time interpreting insights from lots of data, we can't actually physically look at that much data and find insights.

Last month this blog received 40,662 Visits from 26,137 key words. The top 12 keywords accounted for 5k visits. The other 26,125 keywords accounted for 35k visits! By analyzing just the top ten see how many visitors I would be ignoring?

Here are three techniques I use to overcome the trap of the top ten rows. . . .

1. Advanced Table Filtering.

In the past we all used the standard reports that our web analytics tools churned out.

I don't do that any more. If you show me a report and it is not a custom report that you have created to better pull relevant kpi's into one place then please know that I will think less of you.

A sign of non-laziness is that you bother to atleast create custom reports. A best practice is to pull atleast some input metrics (Visits) with some attribute metrics (% New Visits), have something that denotes customer behavior (bounce rate) and it is criminal not to have atleast a couple outcome metrics (goal conversion rate, per visit goal value).

That best practice gives me this report for my search keywords. . . .

[Click on the image for a higher resolution version.]

It is a useful report that helps me understand performance much better than the standard reports from Omniture, Google Analytics, WebTrends etc etc.

But remember I have twenty six thousand keywords referring traffic to this blog.

I want to very efficiently look through them to find something useful.

I want to locate my most important brand terms that perform magnificently for me. To accomplish that I click the link called Advanced Filter under that table and do this. . . .

I move beyond the limitation of the top ten rows by creating a simple inline filter.

Find keywords:

containing "avinash"
where the "per visit goal value" is greater than $1.7 (a higher bar since the average is 1.3) and
the Goal Conversion Rate is greater than 10% (again another high bar compared to the site average)

Notice that I can only run a smarter query because I had created a custom report, without it I would have to use the "lame" metrics that I might get in the standard report (or immediately proceed to extracting all the data, all metrics and spending next four hours in excel doing what I can in two seconds in Analytics).

In a second the table transforms into. . . .

[Click on the image for a higher resolution version.]

You know what's in the table?

Keywords we should make love to because regardless of if they bring a lot of traffic or little, they hugely deliver to the bottom line. Making love might be too small a emotion when you realize compared to a site average of $1.3 the per visit goal value is $5.5. And look at that conversion rate!

Also notice up top. . . I quickly went from tens of thousands of keywords to just 193 I should focus on. I need to analyze these keywords, search engines, landing pages, products sold, leads received, and so much more to figure out:

1. what is going on here that is so right that it works like magic and
2. how much can I replicate the lessons learned

Far too often we focus on our losers. Here I start by focusing on winners and see if I can do more of what I know already works.

I could just as well have mined my data to look for

people on non-branded terms
people who come on every variation of the names of my two books
people who come from China
people who use a cluster of terms I consider most competitive or. . .

The limit to the data I can mine (and I use that word loosely here) is the imagination I have (or better put: the intelligence I possess about important business questions).

So do this. Use inline advanced table filters to go from tens of thousands of rows to just a few that you need to focus on.

Yes you can absolutely do this in Excel. But it will take you five times the amount of time and effort required because. . . please pay attention. . . in this case you are querying the entire dataset of your website and in Excel you'll keep going back and forth to get more data or dump it or write more complicated queried or. . . you catch my drift.

Advanced Table Filters can be used in any report in Google Analytics (Yahoo! Web Analytics also has a very similar feature, actually YWA had it before GA! :)).

The one limitation of the approach is that you'll more optimally analyze your known knowns. You'll even get to understanding your known unknowns. But not your unknown unknowns.

2. Use Tag Clouds.

For pulling lots of data from lots of rows all together into one place I do so love tag clouds.

Download all your keywords into a text file (twenty six thousand or so in my case) and upload them into Wordle and bam!

[Click on the image for a higher resolution version.]

O M G!

Did you think that by doing something so simple you could get such a quickly glance-able view of so much data?

I love search keyword tag clouds because they can tell you about the health of the company when it comes to search.

In my case, above, for example I LOVE the fact that above and beyond everything the word Analytics dominates it all, and what makes me happier is that the word Survey is so prominent (you all know I love qualitative data, now here is proof that my blog attracts so much of that traffic).

I worry a smidgen that people will think this blog is about Google Analytics, it is not, so I am happy that the word Google appears atleast as much as the word Web (and variations like website and online etc). I can't drill down in wordle so easily, but I use technique #1 (above) and it turns out 30% of the time the word Google appears in search queries in the spirit of "working for google", and another 30% for queries like "google insights for search", "google ad planner" etc (tools I have blog posts on). My mind is relieved.

See how I can understand about a strategic concern, at least a bit, using a technique as simple as a tag cloud?

Another thing I am rather ecstatic about is the sheer diversity of the keywords in search queries. It is not my brand that dominates (boo hoo! cry cry!) but rather "category" terms (which bring the "impression virgins"). Metrics and Conversion and Data and Questions (look at that!) and Analysis and Customer and Intelligence and Bounce and Best. . . .

That sweet spread validates some my Search Engine Optimization strategy (something I spend a lot of time on) – go for diversity and attract new people to my "franchisee".

Or in your case it may not. It may tell you different things. The main point is it would be hard to understand some of these macro factors in your data by looking just at a table in your web metrics tool of the top ten keywords!

Here is a tag cloud for a small company you might have heard of, Gatorade. The data does not come from them (obviously), it is from Compete. . . .

[Click on the image for a higher resolution version.]

I am not a SEO expert, can't underscore that enough, but everything that could possibly be sub optimal about seo/ppc is wrong with Gatorade.

The one brand term dominates their referring search keywords. This in of itself is not a bad thing, Gatorade is a huge brand. But what it indicates clearly that their site attracts people who already know Gatorade and are "pre converted", when perhaps a greater use of the website would be to attract the impression virgins and blow them away with the greatness of Gatorade so they'll never consider Powerade or any other brand.

Look at the diversity of keywords.

Find any?

People use tens and thousands of different ways to find even a web analytics blog. Look at how much different types of content there is on Gatorade.com and MissionG.com and Gssiweb.com and it is quite clear that Gatorade's tag cloud is telling a sad story.

Finally for all the money that Gatorade is handing out to premier current athletes (and the really expensive content Gatorade has on its website related to those top athletes) only two show up in the tag cloud. One that used to be important (though he is still a big brand) and the other that sadly ran over a fire hydrant a couple weeks back. That shows how exposed the Gatorade brand (atleast online) is should something unfavorable happen to these two guys.

I would humbly dramatically change Gatorade's SEO and PPC strategies tomorrow morning.

It is amazing how when you have so much data in one place, using such a simple technique, that you can find some very intriguing patterns in your data, stories that might validate what you are doing right or expose everything that is wrong with your digital strategy.

Simple but effective. Try it for your site. What do you find?

3. Use Keyword Trees.

This is my latest love. I mean it.

I was so happy when I first saw it because of this constant quest I am on to take lots of data and show it on a page.

Zach and the team at Juice Analytics have created two powerful visualizations: Referrer Flow and Keyword Tree.

I adore that last one.

You simply go to http://analyticsvisualizations.appspot.com click on Keyword Tree and you are on your way!

The visualization uses the free, open and multifaceted Google Analytics API. In a few seconds you'll get something pretty and intelligent (how often have you seen those two together :)). . . .

[Click on the image for a higher resolution version.]

It's a tree. With branches. :)

While in the case of tag clouds it is difficult to understand the relationships between different words that exist in your search queries, that is not the case with keyword trees.

I was looking up the relationships for the word "avinash", image above, click for a higher resolution version. I am looking at hundreds upon hundreds of rows of data visualized all in one page.

I can easily see long tail queries like "top 10 key metrics web analytics avinash" or head ones like "kaushik blog" or even "kaushik web analytics 2.0 pdf" (my book is not available in pdf form but now I know lots of people are looking for it and so maybe we should get it out fast!).

I can simply walk through the various branches of the tree and it helps me understand in a very powerful way the relationships that exist in my data. It always throws up surprises (partly because of my top ten rows table driven existence I have never actually looked at so much data in such a easy to understand way).

The fun though does not stop here. I can actually look at keyword trees using different metrics.

In this view I am looking at the data for the keyword "tracking", the colors shown highlight the bounce rate metric for each relationship. . . .

[Click on the image for a higher resolution version to be truly impressed!]

Now I know the queries that stink like a skunk, the deep reds, and find some sweet ones, "event tracking" is one such word (lots of visits with very little bounce).

But I can switch and say. . . . well our bounce rates stink so we'll not use that as a success metric :), let's use the % of New Visitors as a success metric. Ok no problem, press the button on the control panel on the right and. . . .

[Click on the image for a higher resolution version to be truly impressed!]

Notice the relationships change, the queries you would have paid attention to will change, what you will action will change. Just with the press of a button.

You can also flip the size of the words. I am using Visits in both cases above, but you can just as easily go for quality (in this case) and use New Visits. I would love to see some kind of Outcome metric there, given my passionate and sustained obsession with measuring end success.

You can do lots of true analysis, for free, with your data and get the kind of insights tables from Google Analytics and Yahoo! Web Analytics and WebTrends and CoreMetrics simply can't provide.

Let me share two snapshots to make that point.

I was genuinely shocked at the complexity of the tree and branches associated with the word "google". . . .

[Click on the image for a higher resolution version to absorb the whole thing!]

The darn thing did not even fit my laptop monitor (1440×900), and there was so much going on that it took me a while to absorb all the lessons.

Meanwhile for the "analytics" branch I can see, at a glance, the 70 or so queries that cause the "main flare" and it gives me a peek into the the head of my visitors unlike anything else. Talk about collecting VOC (and actually understanding it!!).

On the other hand I was quite saddened to see the report for the word "metrics". . . .

[Click on the image for a higher resolution version.]

Remember this blog is all about data and metrics. Yet the tree is so "shallow". Or better put it is less a tree and more a bush. Or maybe just a shrub.

For all of the reasons I was less than thrilled with the gatorade data in #2, I am less than thrilled here. From competitive intelligence analysis I know that there is a ton of volume on Google for queries related to "web metrics", and variations, yet I have not done a good job of attracting that traffic.

The above picture does not simply tell me that I need to do a better job of doing SEO for "web metrics", the real lesson is that I need to put in a ton of effort to attract the long tail for "web metrics" because that is where most of the volume is.

You will probably find other lessons from this exercise on your data. Hopefully there is no doubt by now that valuable lessons do await you if you put in the effort to start switching from using tables and excel and shift to using other data analysis / visualization techniques.

Each effort above uses something very simple and while none of them are a panacea, your understanding of web metrics data will not be the same boring self.

Have fun.

[Bonus Item: #4: One strategy to escape the top x rows is listed in the second half of this post, jump to just after the picture of Tiger Woods (!!): Focus On “What’s Changed”.]

Ok… your turn now.

What do you think of these strategies? Have you used them before? Worked for you? Have you used other data visualization techniques that liberate you from the trap of top ten rows? What tools do you use? Got models / approaches / strategies you want to share?

We would all love to learn form you. Please share. Thank you.

PS:
Couple other related posts you might find interesting:

• “Dear Avinash”: Be Awesome At Comparing KPI Trends Over Time
• Consultants, Analysts: Present Impactful Analysis, Insightful Reports
• How Thick is Your Head and How Long is Your Tail?
• Make Web Analytics Actionable: Focus On “What’s Changed”
• Web Data Quality: A 6 Step Process To Evolve Your Mental Model

Analysis Ninjas: Move Beyond The Top Ten. Find Love (/Insights). is a post from: Occam's Razor by Avinash Kaushik