Occam's Razor by Avinash Kaushik » Search Engine Marketing

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

Avinash Kaushik — Mon, 12 Jul 2010 08:56:43 +0000

Stale.

One thing that I never want to be.

We all have a tendency to learn up to a point, we get comfortable and keep chugging along rarely investing in our ongoing education.

I call it the slow but sure path to irrelevancy.

Let me share my prescription for avoiding irrelevancy: Try new things.

Simple right?

At any given time I have six or seven interesting tools running on this website. That's not including others I actively seek out around the web. Most of them are not even related to my current job or problems I know of. And that's on purpose.

I want to constantly be in the know of new and more clever ways of working with data, tools that are often solutions to problems we don't know we have yet or tools that are sometimes seeking problems to solve!!

Irrelevancy is not fun. Stale people are not appealing (just like, as your mom taught you, a week old bread). If there is one thing you take away from it post I hope it is the importance in investing in yourself / your education / your ongoing awesomeness.

In this blog post I want to share four analytics tools that I have been playing with for a while… tools that solve an interesting problem… tools that point to what might be in terms of our near term analytical future… and in almost all cases they don't even know!

I love doing this, I hope you'll have as much fun as I do.

First Some Context.

Remember I am the creator of the 10/90 rule of investment in web analytics.

I had created the rule many years ago, early into my job at Intuit, and quite simply it states:

If you have a budget of $100 to make smarter decisions on the web…. invest $10 in tools + vendor contracts and invest $90 in people (big human brains inside or outside the company to do analysis and the process of producing insights).

When I had created the rule Google Analytics did not even exist!

The rule was borne out from my own experience having inherited a world class tool we were paying $250k a year for and produced crap. Well not crap… lots of data that no one cared about or actioned. I threw out the world class tool, purchased ClickTracks for a fraction of the cost and put money into Analysts and boom!

Ok not boom overnight… but over the course of a few months the org started to be more data driven, because analysts we hired produced analysis. That fed a virtuous cycle. More analysts. More insights. More desire to be data driven.

So as you look at the tools below remember the 10/90 rule.

In the end it does not matter who has the coolest or the biggest tool. Or for that matter how many tools.

People matter.

You matter.

Remember that, at least for the rest of this post. Ok?

Let's go look at some tools…

Measuring "Invisible Virality": Tynt.

Tynt's promise is simple. Add a piece of javascript to your web page (do a View Source on this page to see it), and it will tell you how often your content is being copied.

Copied! Say it ain't so! :)

[Please click on the above image for a higher resolution version, including all the other metrics.]

In the last month data was copied off one of my posts 5,616 times, with most of it being content and some of it images.

But that's not all.

If you look at the higher resolution version (click above) you'll see it also reports other data like Visits Generated etc.

The way it works is that when someone copies a piece of content Tynt adds a little bit of additional text and a trackable code with a hash (#) at the end of the url from where content was copied.

Like so… the text that was copied from my blog is the first two lines… the Read More and link was added automatically by Tynt…

When people click on that link Tynt can report visits generated, page views, where the links were posted (in case there is a referrer) etc.

There is additional data like how many of your copies created links that were posted and then clicked on…

Gold are places were the copied text was pasted with the additional "Read more: http://…" text+link were also posted AND someone clicked on it.

You'll note that Tynt's selling point is connected to SEO. The idea that your copied text creates links back to you which in turn creates visits back to you, and per Tynt, better SEO goodness. You know links and page rank and what not!

I *personally* do not see much value in all that data. Two reasons:

1. Most likely the additional text+link will be posted as is only by someone who is quite careless and perhaps only on the least desirable sites. I mean if someone smart's going to copy they'll be clever enough to get rid of the link+text. :)

2. Search engines are complicated little beings. The days of just inbound links counting towards SEO goodness are long behind us.

So I am less enamored by Tynt data that focuses on all that.

I love the data you saw in the very first screenshot, and I absolutely love this…

[Please click on the above image for a higher resolution version, including all the other metrics.]

The first screenshot shows how often content is being copied and the above indicates the blog post / web page where the content is being copied from.

Why is this cool?

If you are a regular reader you'll notice that at the end of every blog post (before the start of the comments section) is a Topsy widget.

It measures how often a blog post is tweeted/retweeted. Goes viral. Higher the number the better, makes sense?

I also measure the # of Comments Per Post as a measure of how "engaging" / "valuable" people found the content to be. Looking at how often it was tweeted/retweeted is one more layer of information in understanding what subject / ideas in a post / things I write are well received by people and which are not.

But.

Both the above attempts measure two minorities.

1. The rarest of the rare who post a comment.

Context: I write twice a month. This blog has around 70k Visits a month, 39k Feed Subscribers and the average number of comments on each blog post is just 35. Minority perspective right?

2. The rarest of the rarest of the rare who are on social media. Who tweets after all. :)

The cool thing about Tynt is that it allows me to get some sense of "engagement" / "perceived value" / "Like" with the v a s t majority of people who will neither submit a comment nor write a tweet.

People who still use email. People who like something I wrote so much (or hate it so much) that they copy the text and paste it and forward it to others. Or copy the text and post it on their blogs (without attribution of course :)).

I like that a lot.

This entire interaction that was completely invisible to me is now a bit more visible. I can measure the "invisible virality" / "spread" by this big huge non-commenting, non-tweeting audience.

In the time period above I had written 4 posts (5,616 times copies). Check this out… It turns out the post with the fewest comments, just 25, and the fewest tweets, just 100…

…was copied an astonishing 506 times, when all other posts were copied in small double digits.

See what I mean… something I would have perhaps considered to be only a small success turns out was a huge hit with the blog's audience. I just would not have known that so far.

Here's another interesting application. . . Lots of people are measuring "influence" of a blogger (/ piece of content) using data from the "minority activity" (comments, retweets etc) and selling it as the complete truth. But how can you do that without some insight from the majority?

Tynt shares one very interesting piece to the puzzle that perhaps in the future fit some place where we can use it with all other context we have.

Invisible Virality. Cool right?

Applying Smarter Ideas to Measuring "Sentiment": Analyze Words.

Raise you hand if you are in the "If I am any more excited about doing sentiment analysis then I'll pee in my pants".

So many raised hands!

Here's the problem: Most solutions stink. Not just stink… dinosaur's breath after a meal stink.

We are algorithmically trying something that as yet does not lend itself to algorithmic measurement… "emotion". It is darn near impossible to cleanly buckets feelings and nuance into clean Positive, Negative, Neutral buckets.

We, computer programs, are simply not there yet. [Though I am absolutely confident that we will get there at some point.]

For now you are most likely wasting time (and money). Sorry.

Here's the other problem…

Even if it works… I don't think it works. [What!]

Let's say you have a 100% perfect human read and 100% human categorized analysis on hundreds of thousands of rows of text. Clean into the three desired categories. Like in the image above.

Now pause for a second and think… what could you do with this?

You have aggregated data into three pieces and we all know aggregated data stinks at delivering insights!

That does not mean wanting to identify insights from lots and lots of text is not prudent. It is.

I like a much more nuanced approach.

Analyze Words applies one such nuanced approach to text analysis.

It uses the well established and long use LIWC (Linguistic Inquiry and Word Count) methodology to categorize all your delightful text (in this case your tweets).

Why the LIWC? Here's the idea behind the LIWC:

"The ways that individuals talk and write provide windows into their emotional and cognitive worlds."

Cool right?

You go to Analyze Words and you punch in your twitter id and bam (!) your "psychological" profile, or in this case mine…

Nice eh?

No simplified over promise under deliver aggregates!

The three categories and 11 sub categories provide much much much more nuanced understanding of what your text is saying, in this case for your twitter profile.

Why is this cool?

In this case measuring "Personable": Engaged in other people's well-being and at peace with expressing your own uncertainty about the world. High Scores in personable use positive emotion words, ask questions, express their own ambivalence and reference others frequently.

Better than positive, negative, neutral right?

Or "Analytic": "If law school exams were a persona, they would rank real high in this category. Ample large words and phrases that include complex thinking styles (e.g. "if – but not …")."

Love it!

Two magnificent things about this approach (remember it's not the tool, its what you do with it :))…

1. It is very sophisticated in the approach it is applying. Nuance and segmentation rule the day. There is nothing, nothing, more sexy in the world of web analytics.

2. It is immensely actionable. You can quickly see areas where you are scoring well, where you are not and you can start to take action to fix things!

Of course you can do even more.

You know how you are doing… now compare it to your "competition" and find their strengths and weaknesses…

When you do competitive analysis, like above, find contrasts with your own profile, what your brand stands for in the world and their brand stands for.

Highlight differences where you brand strength is strong. Hopefully they'll discover where they stink and for the sake of humanity fix that.

Nice eh?

Analyze Words provides a glimpse of an approach that I hope others follow.

Rather than trying to find short cuts, where none exist, and provide aggregate data, where it just gets crapified, follow a well established methodology while leveraging segmentation and nuance.

We've applied it just for Twitter in the above case but you can easily see how you could apply it to call center data, tech support websites, forums, online survey open text voc answers and so much more.

Applying Simpler Ideas to Measuring "Sentiment": StatsIt.

StatsIt started off as a differentiated web analytics tool, but has morphed into a delightful social media monitoring tool.

It's approach is to index blogs and tweets and delicious and twitter and youtube and on and on and analyze that data to find yummy actionable insights about your social media presence / activity.

Like all tools it gives you pretty charts…

Sweet, now you know how much "activity" is happening. Give it to your boss, she'll be impressed. You on the other hand realize "activity" rarely has insights.

I want to focus on just one part of StatsIt that I adore because of how simple it is in its brilliance when it comes to finding insights from lots of text.

StatsIt has indexed a ton of content from all the social web activity. When you tell it your brand terms (or just your brand name, in my case "avinash kaushik") and it churns through that social web data to provide you with something awesome…. a tag cloud!

[Click on the image for a higher resolution version, along with a peek at other metrics.]

Why is this cool?

Mikko and his team have taken 1,000 words from the English language that are connected to emotion. Good emotion, bad emotion, ugly emotion.

They look at their social web data and in that they look at the words around your brand mention and finally identify the emotional words people are using in context of… you!

The tag cloud above shows the emotional words use around mentions of me for a month's worth of time.

Without having to read all the text I can at a glance now get a really good understanding of the tone and texture of activity around my presence. More importantly it does not take all that long to figure out what emotions should be there but aren't.

A very simple, effective and elegant solution to a complicated problem.

Oh and guess that happens when you click on one of the words in the tag cloud?

You are right… it takes you directly to the text from all the data that StatsIt has collected!

By clicking on the words you are essentially segmenting your data and drilling down to the text (tweets, blog posts) where you can learn more about what the person was saying when they express, say, "great" as an emotion. :)

Effective "sentiment analysis" baby!

Why can't we be this simple in other places?

We are always seeking complexity. Here are two ideas that popped into my head from the StatsIt's approach that might apply in other places.

We collect lots of open text from our online surveys right?

Rather than finding the perfect answer to what's expressed in the text, and of course getting it wrong, why don't the vendors show us a emotional tag cloud?

Can there be a better / easier / faster way to allow us to make sense of all that text, leverage as a segmentation tool and find insights every day?

Vendors! Come on!!

Another idea.

Reviews are important. Most ecommerce sites have them.

But why is it that we only see "quantitative" analysis of the reviews? 5 stars. 3.2 moons. 61% rotten tomatoes. Etc etc.

The richness of the review is only partly in the quantitative analysis of the rating. The real sweet nectar is in the words people write in reviews.

I recently gave a talk at eBay. So let's use that as an example.

You get quick quant rating on eBay that you typically use. But perhaps the real gold is here….

This seller, me, is 100% positively rated.

Now let's say that you want to buy a Sony digital camera that is listed by both me and Emer. We both have 100% positive ratings for our 60 or so prior eBay auctions.

How can you best decide if you should buy from me or Emer? You can't possibly read 120 reviews, or even scan them quickly.

Now would your life be much much easier if eBay choose to provide an "emotional tag cloud" for both Emer and Avinash?

Very quickly you could see that while we both have same quant ratings it turns out that my emotional cloud shows a neutral to positive feelings expressed while Emer's is outrageously positive.

Now is it easier to decide who to buy from?

As our dear friend Sarah Palin would say: You betcha!

So why does eBay not provide this simple emotional tag cloud?

Or for that matter Trip Advisor or Amazon or any site that hosts reviews and ratings?

Simplicity rocks. Especially when it's actionable.

Quick, Efficient, Effective Mobile Analytics: Percent Mobile.

It is always a really good idea in web analytics to understand how data is captured (case in point the delightful blog post on Competitive Intelligence data capture).

No where is this more true than when it comes to mobile analytics.

There are many methods of collecting data depending on the platform you are on, and if Steve Jobs gets upset he can totally shut you down with a mere update of his TOS! :)

I am not going to cover all that here today. For those of you who already have my second book Web Analytics 2.0 please jump to Page 250 to learn all about data collection options, platform limitations, challenges with campaign analysis and finally reports and KPI's you should measure for mobile.

In this blog post I want to share a lightweight wonderful mobile analytics platform called Percent Mobile.

Now most web analytics tools, like Google Analytics and WebTrends and others, will capture and report data for javascript enabled smart phones (like the iPhone, Android and some Nokia phones). Honestly that is all the traffic that is of commercial value, so even if you miss the rest it is not the hugest of deals.

But all these "big boys" have simply "added on" mobile analytics to their tools. The result is that they suffer from both a lack of imagination and, this is important, truly great databases when it comes to devices and carriers and other unique mobile information.

Not Percent Mobile.

They have two incredible benefits:

1. A really expansive and accurate database and detection mechanism when it comes to mobile platforms.

2. A really simple UI and reporting layer, even your mom will understand the data.

They also have four different methods of enabling data collection, I am using their standard javascript tag on this blog (do a View Source).

Here is what the resulting data looks like…

[Please click on the above image for a higher resolution version.]

No hunting and pecking to find the data, like you would in Google Analytics or Site Catalyst or CoreMetrics. A quick at a glance view of how much traffic is mobile, key stats about the devices, the devices themselves (go iPad!!), vendors and operating systems.

If you compare this to your web analytics tool you'll notice almost immediately how much better this data is compared to what the "big boys" are reporting.

Click on the image above and you'll see a bit more clearly other really sweet metrics. % of mobile devices accessing your site via WiFi. Phones with touch screens and full keyboards etc.

[Can you imagine how cool it would be to segment your mobile traffic for full keyboard phone vs none and see which convert better. Or does access via WiFi mean more content consumption than via 3G? Etc. So cool.]

That is not all… if you scroll a bit more you can get a country map view, the networks used to access your site (AT&T still #1 for me!) and countries etc.

Of course it would be hard for me to like any tool that does not allow segmentation. :) You simply drag and drop on to the box on top..

And what would an analytics tool be without the normal search, referrer and all that data we have so come to love (and hate!).

I particularly like the "Activity Types" box at the bottom left, I don't know why web analytics tools don't categorize referrers by default.

I am also surprised at the long tail of referrers. Yes Google is big but there are 91 other referrers for this segment. More mobile SEO!

Why is this cool?

It might seem odd that I would like a tool that would give me similar data that I can get out of WebTrends or Omniture or Xiti or whatever.

The first reason is that, as mentioned above, the data is actually much better because of the databases that power Percent Mobile.

The other thing is that getting this data causes less pain than pulling my two front teeth.

Finally I so do like supporting pretty tools, especially if they have good data!

The one thing Percent Mobile lacks is some way of measuring any outcomes. I can certainly dig to my "conversion pages" but it would be great if they just let me just input them into the tool and then they could measure outcomes for me (even if it is like the Goals process in GA).

But if you want a light weight easy to use free mobile analytics tool just throw Percent Mobile on your site and have fun. Go to www.percentmobile.com , click Sign Up (top right) and use the Invitation Code "Avinash" (no quotes).

Mobile rocks no?

Summary Of Our Lovely "Let's Keep Learning" Cruise.

It is important to point out that I am not affiliated in any way with any of these tools / companies. I am also not recommending overtly or covertly that you buy / use them. That is totally your call.

Of course I would not personally use them or write about them if I did not thing they had value. :)

My sincere hope is that you'll internalize:

1. How important your ongoing education is. DBS: Don't be stale!

2. What it is that each tool does that is so unique, what unique problem each solves.

3. Why it is important that you can separate the wheat from the chaff, notice how I quickly put aside most data from Tynt to focus on just what was important to me.

4. Where are new places in your business you can apply things you learn from analytics, like in my example of emotional tag clouds for Ebay or Amazon.

5. Why simple and effective is better than expensive and complicated (even if "perfect").

I hope you got that, more than names of interesting tools.

I cannot tell you how much fun it is to step outside the world of Omniture and Google Analytics and other traditional web analytics tools. It stretches your mind and sometimes you look at these new techniques and data and you notice you are smiling and feel so happy.

Try it, and have fun.

[In case you were curious at the moment I am playing with these incredibly cool tools: PostRank, Next Stage Sentiment Analysis, SEO Effect, and Colligent. Each in its own way does something magical and quite unlike anyone else.]

Ok your turn now.

What do you think of the work that Tynt, Analyze Words, StatsIt & Percent Mobile do? Have you tried any of 'em? What obvious flaws did I overlook? Are there other tools you are using in the Viral, Social, Sentiment, Mobile space that you really love? If so would you please post them in comments?

Please share your feedback / critique / ideas.

Thanks.

PS:
Couple other related posts you might find interesting:

Viral, Social, Sentiment, Mobile: 4 Delightful Web Analytics Solutions is a post from: Occam's Razor by Avinash Kaushik

Win With Web Metrics: Ensure A Clear Line Of Sight To Net Income!

Avinash Kaushik — Mon, 28 Jun 2010 08:59:27 +0000

We have more web metrics and data than there are stars in the universe (slight exaggeration!).

Yet we stink at informing decisions. Our reports are ignored. Sites & online marketing continue to suck.

A large part of the reason is that a large part of our job seems to consist of glorified data puking, hoping someone will be impressed. After all there is so much data in those reports!! #fail

This blog post encourages you see the forest, the much hyped big picture, and shares a framework that will help you ensure that every single moment of your day is spent on activity that will be:

1. of value to your organization, hence appreciated and acted upon

2. has a clear line of sight to the one thing that matters: profit

If you don't want your professional life to be frittered away then please come along this short journey.

First some context…

If you have seen one of my keynotes recently then you have heard my near evangelical fervor when it comes to trying to convince you to compute Economic Value.

If you have Web Analytics 2.0 then you already know who much attention is paid to this concept in the book (jump to page 159 for how to compute it for your website).

The reason for this emphasis is to help fix our miserable failure at at creating data driven organizations.

To steal your energy away from being just in the report / data production business.

To encourage you to do better than spend a lifetime implementing analytics tools, building data warehouses, chasing the next shiny object.

My recommendation has been:

1. Identify your Macro Conversion (focus on this a lot!).

2. Report revenue. Report like crazy on the 2% conversion rate.

3. Identify your Micro Conversions.

4. Compute the Economic Value (see page 159). Show your bosses and HiPPO's the complete value of your website.

That last one will get any organization to sit up and pay attention.

Why?

Because for the first time in their young and passionate life they'll see the complete value your website is adding to the business. And because my dear it will be a huge number that no one can ignore! You are going to tie your work to the bottom line!

Revenue = Good. Economic Value = God! [Also slight exaggeration :)]

Professor Ken Wong's Magic Potion

Prof. Wong is the award winning Commerce '77 Teaching Fellow in Marketing at Queen's School of Business (and an awesome speaker, you should hire him for your next event!).

He took the stage after my talk and said, I am paraphrasing here, "Avinash did not go far enough in his keynote. Economic value is important but the only thing that matters is Profit!"

That was awesome!

One of Prof. Wong's key points was how the success of our work, as Marketers, is measured based on a lot of things but not often enough based on perhaps the most important metric of them all: Net Income.

Prof. Wong covered a lot of key points (as a MBA with a minor in Marketing I wanted to take off my clothes and jump for joy when he said the 4P's of Marketing are killing Marketing!).

I wanted to share two of his slides that left a lasting impression on me.

They are particularly applicable in the web analytics context. In sharing my interpretation of them my hope is it will change a little bit how you think about your work and success.

The very first slide, "Profit: The Ultimate Client Need", shares the key elements that need to function for the outcome (ROI) that causes companies to remain in business.

My interpretative points.

Net Income is driven by two important variables:

Unit Margins (how much you make on each X you sell or Y service you provide)

Unit Volumes (how many of X or Y you sell)

Margin times Volume gives you the golden metric Net Income!

[Keep this formula in mind, your life should be revolving around it else you are wasting everyone's time.]

Peel the onion back one more.

Unit Margins is in turn driven by two more variables:

Price (how much you charge for X product or Y service)

Cost (how much it costs you to make X or provide Y)

Price minus Cost equals Unit Margins.

Get it?

So if you want to have very high Margins you have two variables you can control. You can charge lots for your product or service (think of a Vertu phone).

You can also make it at the cheapest possible cost (no phone costs $100k, you make it for $300 and sell it for $100k).

You can of course also charge lots and lots and it costs you a lot to produce (think of a Tesla car). But give some thought to how you'll stay in business.

Continuing the onion peeling…

Unit Volumes, our other variable to have high Net Income, is driven by two variables:

Market Share (is your share 90% or 5%?)

Market Size (is that share of a market the size of Maldives or China?)

Both share and size are important.

You'll sell lots of X or Y if you have a high market share and the limit you'll hit is the size of the market (you can then play in the current size or grow the pie).

Line of Sight.

Having a clear line of sight means that you are able to map every metric you report on (or better still torture with segmented analysis to find insights) every single day directly to the strategic objective of the company.

Prof. Wong is suggesting, rightly so, that that strategic objective is Net Income.

And you have only one of four things that you'll move through actions your company takes: Price. Cost. Market Share. Market Size.

Here's my crystallizing question for you. . . .

When you report the metric Page Views Per Visit which of the four are you solving for?

How about with Bounce Rate? Or Time on Site? Or % of New Visits? Or Visitor Loyalty? Or…..

Is there a direct line of sight between what you as a Marketer are being incented on, or you as an Analyst are spending time analyzing?

If not, are you surprised that no one loves you? Sorry… I mean… no one loves your work?

Here is a simple exercise you could go through: Pick out all the metrics you are reporting today (on your dashboards and top reports). Try to put them into one of the four important buckets from Prof. Wong's slide.

The clear line of sight exercise. . . .

Were you able to cleanly bucket all metrics you currently report? Time on Site and Conversion Rate and Task Completion Rate and % Internal Site Search Exits and Cart Abandonment Rate and % of the Page Scrolled and % of Visitors Refreshing Pages and all the other sweet things.

Some of the metrics in the above paragraph are complete crap, you are wasting your time and everyone else's time with them. And you'll now discover that very quickly because you won't have a place where you can bucket them.

Other metrics will make you think harder. Where do you bucket Conversion Rate? Are you impacting Price or Cost?

What about Customer Satisfaction? Or Page Rank!

Not every metric will map cleanly, and that is ok. I had to think really really hard to bucket each of my metric in the above picture. Some of the metrics were controversial. But bucket I did.

If it turns out your web metric has no line of site then it might be time to kill.

If the work you do can't be mapped into Price, Cost, Market Share or Market Size then why are you doing it?

Before you dip your hands into Omniture or WebTrends or Surfaid, :), answer that question.

I know it seems like a lot of work for a "lowly" Analyst to do. It is. But without it there is little hope for your personal success (promotions / bonuses) or your company's success (higher Net Income).

"What Matters Most" Fishbone Analysis

As you look at the picture above it is amply clear that the metrics I have chosen in each of the four buckets are perhaps unique to me/my business.

The reason is simple… they are a reflection of the strategy my company is currently executing, i.e. our "world domination via an effective data driven online marketing plan".

This simple truth, that metrics should reflect current business strategy, is the reason I loved another slide from Prof. Wong's presentation.

It leveraged the same framework, but added "what matters most". . .

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

The focus is still on Net Income driven by, hopefully, improved Margins and Volume which in turn are driven by much beloved 4 levers of Price, Cost, Share and Size.

What is awesome about the "fish bone" above is that it drills down to the 14 specific strategies that most businesses will use to become great (or simply survive).

You Ms. Web Analyst now have a framework you can take to your Marketing Directors and CMO's to discuss which of the 14 strategies they are currently executing to drive the 4 beloved levers.

Ask any Web Analytics "Guru" or "Professional Speaker" or "I am so important you are paying me $5,000 an hour to give you generic advice Consultant" and they will always tell you that all good journeys in web analytics start with asking your bosses this question: What are the goals of the organization?

The advice is sound (and well worth $5k/hr). The problem is that we never get an answer from the customers of our data / our management. You are $5k x 8 hrs short and still none the wiser.

Get off the slow train to nowhere…. You now have a new BFF: Prof. Wong's "What Matters Most" slide!

Don't ask the generic "What are the goals" question. Ask "Of these 14 specific strategies which are we currently executing".

Once they tell you which ones (be patient, it might shock them that you are giving them something tough and specific to think about), you'll be in business.

The 5 strategies they pick from the right-most column will help guide you in terms of picking the right Key Performance Indicators / Web Success Metrics for your business.

And you know why a win now is guaranteed?

Because each metric you identify starts with a specific business strategy which has a direct line of sight to the 4 beloved levers which will have a impact on Net Income!!!

Minorly orgasmic right? [Trust me, you do this and you'll agree. :)]

Summary:

Recommendation #1: The Web Analytics Maturity Mandate!

For far too long we have been like toddlers… bumping into things, having a limited vision, working just what we know (which is little).

What I love about this approach is that it forces us to grow up. It forces us to understand what we are solving for: Net Income. It forces us to have a line of sight between our work and the ultimate goal: Net Income. It forces us to not live in our dungeon but rather take a well defined framework to enable the discussion that will yield wins all around.

No lip service to how important process is. This blog post shares what you specifically must do to succeed!

Recommendation #2: Win With Web Metrics: Steps

Here are the specific steps I recommend you follow for optimal execution of the recommendations.

Step 1: Learn Finance 101 and the terms outlined in the slide titled "Profit The Ultimate Client Need".

Step 2: Don't pick any metrics, don't run reports, resist the charms of Google Analytics, Omniture Discover2 etc.

Step 3: Meet with your Management team (or the senior most Marketing person) and identify which strategies outlined in "What Matter's Most" the company is executing (/wants to execute).

Step 4: For each strategy identified in step 3 identify the Web Metrics / KPI's with a clear line of sight to the 4 beloved levers.

Step 5: Use the Web Analytics Measurement Framework as the foundation of all your reporting.

Step 6: Spend you work day on focused segmented analysis to identify actionable insights you can report using the Web Analytics Measurement Framework that will help drive data driven actions on "What Matters Most" so that your company will improve in the one thing that matters: Net Income.

Step 7: The happiness you'll get from leading a meaningful professional life will make you irresistible to the opposite sex which in turn will lead to happiness in your personal life! Enjoy it.

A simple but effective 7 step process.

Good luck.

Ok now it's your turn.

Do you agree that a focus on Net Income and a focus on "what matters most" is key to success in web analytics? Can Web Analytics tie the work they do, the metrics they report, into Price, Volume, Market Share & Market Size? Or is our work simply not that important? In your job today how do you ensure line of site? Will you change anything based on the recommendations from Prof. Wong?

Please share your feedback / critique / ideas.

Thanks.

[UPDATE]

Zach Olsen, who blogs at By Data Be Driven, has taken the Clear Line of Sight framework outlined in this post and applied it to a medium sized eCommerce website. It is so wonderful, take a look:

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

Zach's effort is awesome for these key reasons:

Really clear line of sight from Business Objective to Net Income.
Clean flow from What Matters Most to 4 beloved levers (Price, Cost, Share, Size).
(This one I love the most…) Identifying of Targets for each metric! You can't be serious about Web Analytics without doing this!

I hope you are as impressed by Zach's effort as I was.

He has also done something sweet for all of us… he has created a excel spreadsheet that you can download and customize for yourself, and hence get a jumpstart! You can download it at this blog, bottom of this post: Web Analytics Framework Example. Please download it!

My thanks to Zach for his effort and for his permission to share it here.

[/UPDATE]

PS:
Couple other related posts you might find interesting:

Win With Web Metrics: Ensure A Clear Line Of Sight To Net Income! is a post from: Occam's Razor by Avinash Kaushik

Identify The Known Unknowns: Leverage Analytics Custom Alerts

Avinash Kaushik — Tue, 15 Jun 2010 09:53:21 +0000

Most of the time spent by Marketers & Analysts tends to be spend looking for "known knowns".

Things we know and expect to see in the data, we look to see if they are there. "Oh look Google is still our Number 1 referrer and we are selling lots of product x as we always do. Yea!"

Some of our time is spent reacting to the "known unknowns". Looking for things we know might be happening but don't know when they happen. "I would like to know when conversion rate dips below q%, let me go see if that happened last week."

None of it is spent looking for the "unknown unknowns"…. mostly because it is a hard problem to solve. But one that is important for Omniture and WebTrends and Coremetrics and other tools to solve. "I did not even know 20% of our customers were from Australia and that 9 days ago they all stopped coming to our site."

[For one approach to solving the unknown unknowns problem, and source of this framework, please see the second video in this blog post: Analytics Becomes Intelligent. Hello Insights!]

I believe that actions taken based on web analytics data dramatically increase when we shift from our obsession with the known knows to the known unknowns.

From: "Oh my God I did not know that metric had crashed for that segment!! If only I had known that I would have taken action sooner."

To: "Thank goodness I had an alert in my inbox about that big drop yesterday, I'm off to fix landing pages for that segment. No I can't talk to you about Desperate Housewives, I have to go take action!"

And you know what? That is easier to accomplish than you might think.

All you have to do is use the built in Custom Alerts feature in your web analytics tool (and every single tool worth its salt now has one, so you have no excuse not to use it!).

How does it work?

You want to know when something of value happened. But you don't want to hunt and peck at data. You want to be poked with a stick that it happened. You need. . . .

Being told when to look at important things you can take action on, sounds magical and revolutionary? It is. :)

In this blog post I want to share some alerts with you with the hope that it'll spark your creativity.

I also want to hear from those of you who have already use this feature. What is your favorite alert in Omniture? What is the one alert that you created in WebTrends that saved your job? What is the first alert you create for a client, and why?

But before we go jump into the alerts pool naked and all excited…

A Prerequisite:

There is one important reason custom alerts are not used more, or when used they provide little value: A lack of focus on the important.

Many of us toiling away in the field on the front line are just tasked with producing "numbers", or fulfilling certain contractual reports production expectation.

So the alerts we end up creating might be on random things, guesses, what we feel might be important or, again, random things. If you triggers alerts based on that you shouldn't be surprised no action gets taken.

Worse to impress our bosses we might spam everyone with alerts and it takes only a few days for people to configure their email filters to send all your alerts directly into spam.

Please do not underestimate how horrible this problem is.

So what's the fix?

You want the known unknowns right? Ask people around you what they want to know that is important to the business, but currently unknown.

You are asking what the business objectives are, you are asking for the goals, you are asking about targets.

In short you need to leverage the Web Analytics Measurement Framework. . .

See how important alerts to identify the known unknows just pop out at you right away?

If you don't put in the effort, as a in-house employee or as a outside Consultant, to go through the process of working out the Web Analytics Measurement Framework you will fail at this.

Spend time with your HiPPO's and Clients. Spend time with the Marketers. Spend time with people who have the power to take action. Ask all these people what's important but they don't know.

That'll give your effort the focus that will guarantee action.

You skip the above process and all you are doing is self foreplay that will yield nothing (except frustration).

A Helpful Tip For Increased Success:

In championing a rethink of how we all approach our segmentation strategy in our web analytics tools I had recommended a Web Analytics Segmentation Selector Framework.

It advocated identifying actionable insights by focusing on three key activities:

1. Acquisition 2. Behavior 3. Outcomes!

Do the same thing with your custom alerts.

Rather than creating all kinds of alerts, they are easy to create, go through the exercise recommended in the segmentation post and focus your energy on the 1. the top priorities and 2. things decision makers might action.

In web analytics it is never ok to not focus on the most important. It is especially criminal behavior if that waste of time and life is cause by you firing off "alerts".

Remember the tale about the boy who cried wolf? Don't be that.

Creating Custom Alerts:

You have your objectives, goals and targets squared away. You are not going to boil the ocean, you are going to focus on identifying the known unknowns in 3 key buckets, for things people care about.

Now, finally (!), it's time to get down to business!

It is not very difficult to create custom alerts. If you use Google Analytics in the left navigation click on Intelligence, then click on the link that says Create new alert. If you are using Site Catalyst or Yahoo! Web Analytics etc please check your user manual.

Let me walk you through a simple one.

You've convinced the HiPPO's that Twitter is where it is. Their response: "Meh!" But you have permission to tweet a storm away, but not during work hours. So you set out to do this as a hobby, but you know you are right, and while you don't want to spend looking at every twitter visit, you want to be alerted when twitter revenue shoots up!

Step one is to choose your primary alert settings. . . .

Give your alert a name. In this case High Twitter Revenue (since you are already adding campaign tracking parameters) to your tweet urls.

With Google Analytics you can apply this to one of your websites or all of 'em or just to a selected few. Quite convenient.

Choose the period for which the data will be analyzed. In this case you want to know the moment glory is achieved. You can also choose Week or Month.

Finally choose (with the check box) if you want to be emailed or for the alert to just be noted in analytics.

So far easy right?

Step two is choosing the sweet settings. . . .

You choose the dimension you are interested in. There are a bunch to choose from. New vs. returning visitors, countries, campaigns, a particular page someone came from or a page someone landed on your site etc. Depending on the tool you use you might have fewer or more options.

I choose Source and the Value I use is twitter.com.

Note the Condition in the middle. Quite important. You can choose Matches exactly or does not contain or ends with or whatever. This one box can be your shining moment or the start of your embarrassment, choose carefully.

Now for the last step. . . .

Choose the metric you want to focus on.

If this is your first alert, or the first few, try as hard as you can to focus on activity #3, Outcomes. That is what people care about the most. Try to resist, for now, the temptation to alert based on visits or time on site or % of new visits. They are nice and all but really…. no. :)

I choose the metric I like as an outcome on my blog (remember a non-ecommerce website!): Per Visit Goal Value.

Now the KEY PART!

For my value I choose 2. There is a lot of thinking behind that.

Not only do I want to prove Twitter brings in revenue, that would be easy. I want to prove that my efforts with Twitter are so magnificent that they will knock your pants off.

So I don't just have a alert set up, it is set up to cross a high bar. My average Per Visit Goal Value is $1.14. My alert is set to be triggered at $2.

You don't win people over by just meeting some averages, you win them by being big and brave. Keep that in mind when you create alerts.

Ok lecture over and as it turns out I am done with my first alert!

Click Save Alert, do a little jiggy, wait for glory.

When it comes, when you've cleared the high bar, it will look like this:

If you did not opt for your email to be sent in then it will look something like this in your web analytics reports:

Now you know when an unknown that you might not specifically be looking for has occurred and you can, as the email says above, partake in "happy analyzing"!

[Note: If you use Google Analytics make sure you use Annotations to add a quick note with your victories directly on the graph. These Annotations can be shared with others and now when they login they'll also say: "Ohhh that Jennifer is so smart, getting us so many wins, we need to promote her!" Video: Analytics Annotations.]

Ideas For Cool Custom Alerts:

The important word in "custom alerts" is the word custom. As in what you will end up creating will be custom to your business, based on what's important to you.

But I want to close this post with some ideas for alerts I have created recently. My hope is simply to spark your creativity as you use this cool feature.

#1: "Head" Keyword by Bounce Rate.

The "head" of your search terms consists of a few keywords that bring in very large amounts of traffic. A very prudent alert is one that keeps an eye on any ups or downs of these ten or so keywords.

I have set the bounce rate around 10% higher than what it actually is because every little increase in this bounce rate is bad for me, and I want to know that.

If you are running very specific search campaigns whose goal is to attract lots of new visits, then set up a alert for that.

If you, God forbid, are trying to get more page views for people who come from Bing, then set up an alert for that. [Note: The god forbid is for the metric not for Bing!]

Focus: Acquisition. Success: Initial goal met or not.

#2: Campaign by "Things of Real Value".

These are my favorite kinds of alerts.

Far too often we are obsessed with conversion rates in an eCommerce context. Why not focus on things that actually matter, things that might indicate real success or failure?

Like Average Order Value. Or Quantity (of items)?

Here's an alert I create, all the time, to set a higher bar of accountability for my campaigns (especially when I have a lot of people / resources dedicated to them):

Tell me when some email campaigns I am running cause an unusual spike in the number of items ordered. I want to know what I am doing right there.

In this case I am focusing on one specific campaign, you could focus on all your email campaigns to allow you to identify the diamond in the rough quickly.

#3: New Visitor by Revenue (Increase).

Making money from our existing customers is important, but getting better at convincing new customers to do business with us is important as well (especially in the context of the fact that we shamefully ignore all our existing customers and focus all the time on getting new ones!).

I like an alert like this one:

Tell me when I have an amazing increase in my daily revenue (not conversion!) from New Visitors when compared to same day in the previous week.

I have set a high enough bar for revenue, a 20% increase, before I am distracted by an email. Note also I have been careful to compare like week days, I don't really want to compare Sundays to Saturdays (for obvious reasons).

As soon as I get the alert I go look at an advanced segment I have already created for New Visitors to dive deeper into the sources (campaigns, direct, search) that might have seen this revenue spurt, the pages or products on my site that are doing well. All to learn what I should do more of.

Of if you apply the condition "% decreases by more than" then things you should stop doing!

#4: Source by Time on Site (Customer Behavior).

I am a movie studio. I have trailers for my movie. I have a blogging strategy. I would like to know when parts of that strategy are causing buzz and word of mouth and viral and …. pick your fav phrase. :)

Here is one small alert:

Thanks to your clever use of event tracking you are able to capture time spent watching the movie trailer optimally. The above alert will show you if there are any sites with the word blog in their name that sent visitors that watched your entire movie trailer (a rare occurrence! :)).

NOTE: Now I know that referral path contains blog will not capture all the blogs (like this one!). Remember this is just to spark your creativity.

#5: Country by Huge Visits.

I don't syndicate the content of my blog. But I did give Sidney permission a little while back to translate some of them into Chinese (like this one). He does a wonderful job.

Almost all of the success of my posts at China Web Analytics will be measured by Sidney, his increased readership or comments or rss subscribers or (sadly) number of times it is copied (pirated?) and posted without his permission on many many other blogs.

But there is a small amount of success for this effort that I can measure.

Do I get any traffic from these posts?

I don't know when it happens (a known unknown!) but I have set up an alert to let me know if there is a big improvement in Visits in context of my current 1,200 averagevisits from China…

When this alert is fired off, perhaps in sync with Sidney's publication of my posts, I'll know syndication was a good idea (on this small measure of success).

You can do the same if you have goals / priorities that are geographically focused.

Flip the coin…. and let's say you are the awesome South American giant Mercado Livre and you depend on the US for a good chunk of business.. you can set up custom alerts to know when traffic from the US or Florida or Miami takes a nose dive.

Consider that alert as insurance that if something broke in your online marketing strategy that you will find it quickly.

In Conclusion:

Custom alerts enhance your ability to find surprises in your data, things you might not be expecting.

If you start by using the Web Analytics Measurement Framework it will help bring a focus on what's important to your execution. If you use the Segmentation Selection Framework you'll find that it brings a discipline to your approach.

I hope the above five examples inspire you to go give the feature a whirl, regardless of the web analytics tool you use because all of 'em have it.

Your Turn!

I have barely scratched the surface of what is possible. How do you use custom alerts? Has an alert you had set up saved your bacon? Does your tool provide a particularly clever option? Do you have a best practice you want to recommend?

Share your ideas for custom alerts (for any type of website, using any tool)!

Thanks.

PS:
Couple other related posts you might find interesting:

Identify The Known Unknowns: Leverage Analytics Custom Alerts is a post from: Occam's Razor by Avinash Kaushik

Online Marketing Still A Faith Based Initiative. Why? What's The Fix?

Avinash Kaushik — Tue, 01 Jun 2010 09:11:55 +0000

The world of the intertubes should be a lot more data driven and awe-sexy than it really is.

Yet for all our collective efforts at writing and tweeting and kvetching online marketing is still based mostly on faith. Not data.

Surprising at so many levels right?

Last week I had the privilege of being invited to deliver the keynote at the annual CMA President's Dinner. John Gustavson, President & CEO of the Canadian Marketing Association, invites a hand selected audience consisting of the crème de la crème of Canadian executives from a vast array of industries. This year they were joined by senior Canadian government officials.

It is difficult to choose something for an address to such a diverse, accomplished and senior audience. My choice was the above thought, faith & data.

My plan was to challenge the status quo, deliver tough love, and inspire transformation.

There were no slides, no notes, just me up on the stage talking. Ok there were around 10 or so bullet items, the talking points. On the flight to Toronto in order to prepare I also wrote down the speech (though I don't read my speeches, so it stayed on the computer).

I wanted to share the speech with you in the hope that it helps you accept the challenging reality we face. I hope it also provides you with a practical set of recommendations to kick your work up a notch or two so we can all win at this web thing.

TV. Internet Marketing. Faith. Data. Problems. Solutions. . . .

__________________________________________________

CMA President's Dinner Keynote.

Good evening.

It is a pleasure to be here tonight and address such a beautiful audience. I want to thank John for inviting me.

My plan tonight is to present some thoughts on how to transform people and companies in the age of the Web, for about 15 minutes, and then address your questions. You are welcome to ask me questions about my talk or anything else connected to the web, companies – marketing – opportunities.

I must admit up front that I am as hard core as any evangelical born again Christian in my passion when it comes to the web. The raw innovation and empowerment that a connected digital world has unleashed is the reason I lovingly refer to it as "God's gift to humanity".

To truly appreciate some of this let us consider the world where marketing is done on faith. Television. Or for that matter magazines or newspapers or radio. All wonderful channels, that are needed and will be around for a long time! But when it comes to measuring success of our marketing efforts all of these channels are largely faith based initiatives.

Consider how we measure success of our TV campaigns.

At a time when there is massive fragmentation of channels and content consumption, where the head is becoming ever smaller with each passing day and the tail becoming really really loooooong, it is amazing that we rely on a measurement system of sampling a handful of viewers who help determine success of tens of millions of dollars of content and millions of dollars of advertising spend. It is outright mind blowing that we use a system whose own legal disclaimers essentially boils down to: "Our data is massively suspect".

Now think of how thin the ice is when it comes to measuring the impact of our precious marketing dollars in magazines and newspapers and other offline channels.

Yet we accept it.

We continue to use faith rather than data to make decisions on $120 Billion (!!) of advertising spend because we don't have much of a choice. We chalk it up to: "It is just the way things have always been." Or: "TV is really hard to measure, those boxes just don't connect or share." [It is rare that we blame the fact that we have not carried out our duty to demand more from both the channel and offline measurement systems.]

All that should explain why I have minor mental orgasms when I think of the online marketing channels and measuring actual business value delivered by our ever more precious marketing dollars.

Just thinking of all the data you can get is enough to put give you a temporary high. With 90+% accuracy you can measure the number of impressions of your ads. You can measure interactions with the ads. You can measure how many people end up on your websites. You can understand how many of them puke and leave! You can measure every facet of success (micro and macro conversions!!). You can measure revenue and economic value! For every dollar you spend! Oh my!!

And to think I have not yet started to talk about how finely you can tune your marketing by leveraging geographic and demographic and psychographic targeting. Leverage powerful metrics like Loyalty, Recency, Brand Perception, Task Completion Rate, Size of Second Level Network, Competitive Share of Voice and more. These are not "loser" metrics like visits and pageviews!

Oh, oh, and you can run experiments! You can fail faster! You can involve your customer in helping you choose the look and feel of your site or the prices you should charge for maximizing profit. You can run controlled experiments to measure incremental online/offline impact and balance the portfolio of media channels you are exposed to, rather than getting distracted by sideshows like "attribution analysis".

So much promise. So exciting. And these are all things you can do today. Don't get me started on the future and what lays ahead, the excitement of it all might cause me to faint.

Yet.

Yet if you look around you on the web you'll see that we swim in a sea of mediocrity. We still see irrelevant blinking banner ads. You'll see astonishingly sucky websites, belonging to come of the best companies in the world. You'll bump into advertising that is remarkable in how irrelevant it is to customer intent. You'll see horrid landing pages. You'll experience missing calls to action, rambling text, and waterboarding through Adobe Flash.

All of it largely driven by faith.

It breaks my heart.

If for no other reason than because your employees are frustrated (they want to be, and can be, so much better) and your customers are being tortured each and every day.

So in a channel that is so full of promise, so full of data, so empowering when it comes to relevance and creativity… why is it that we suck so much?

Based on my humble experience I have boiled it down to three important things:

1. The web has been around forever and yet it is not in the blood of the executives who staff the top echelons of companies.

Make no mistake, they are smart, they are successful and they want to do better. But the web is such a paradigm shift that if it is not in your blood it is very difficult to imagine its power and how to use it for good.

How do you demand innovation & creativity & radical rethink if you can't imagine it?

2. We still believe in and live in the world of "shout marketing", the thing we have practiced on tv and radio and magazines all our lives.

It is not that we don't mean well. But our mental models are jaded.

We still believe in getting lots of impressions. We want to interrupt. We don't despise irrelevance enough. We care about "eyeballs". Because that is all we know. Unfortunately the web (/interactive /digital /social) mandates new mental models, and we are the old dog that won't learn new tricks.

3. Our lousy standards for accountability.

Pause and think of how we measure success today. We measure "reach", we measure "exposure" and other such lame metrics. Partly because that is all we have been trained to expect.

We never say: "Here is a 100,000 for my search campaigns, please come back and report on task completion rates across the top three primary purposes and the economic value added." We never say: "Don't try to fool me with page views generated, did we impact page depth on our content site?" We rarely push hard by saying: "I don't care how frequently our content was updated, what was the impact on visitor loyalty." Or say: "Fine we improved online conversion rate by two percent, but what was the impact on the sales in our retail stores?".

Our bar for accountability is less than low. It is almost non existent.

So…. It turns out the problem is not the web, the problem is not the opportunity, the problem is not measurement.

The problem is you.

The problem is every person in this room.

Our raw understanding, mental models and expectations.

I am sorry. It is kind of a bummer to hear that.

But if you are the problem then the nice thing is that you hold in your hands the power to change your companies and bring about the promised revolution of data driven customer centric online marketing.

Problem identified, how do we fix it?

At the risk of being booed out of this impressive ballroom let me say that the solution is to Embarrass Management!

People who report to you and ask people who report to you to embarrass you.

Why is it awesome?

Turns out no one likes to have their egos bruised. Leverage this powerful force to start to address the three problems I had just outlined.

There are two specific strategies I recommend.

1. Leverage Your Customers.

They want to help. You just have to politely ask.

Not being polite is popping up a 35 question survey on your site. Being polite is inviting them to answer just a couple of questions about their experience when they leave the site. Being polite is uploading your latest "oh my god they are so going to love this (!)" design into fivesecondtest or usertesting and letting your customers share feedback at the cost of a few Tim Hortons coffees. Being polite is running a/b tests on your site so your customers tell you which call to action, piece of content, navigation structure or even product price will yield highest customer satisfaction AND revenue!

Leveraging customers means that when the HiPPO / Boss (perhaps you) opens her mouth to say: "I don't think that will work" or "I like that other way better" or "No one will buy a toothbrush priced $299" or "Twitter is dumb"…. you can say: "Why don't we mock up a quick experiment / online survey / media mix model to validate your hypothesis?"

Allow your customers to help you evolve your mental model. Allow you customers to teach you new and effective marketing strategies. Allow your customers to complement your existing intelligence and savvy.

And if it is hard to get to the above point…. leverage embarrassment!

I recently spoke at a major conference about how one of the top camera companies was disappointing its customers by stinking at the long tail of search. I searched for a digital camera, wireless printer and digital camcorder as a normal undecided customer would. None of my 18 or so searches threw up a single link for this company (not organic, not paid). And yet I was ready to spend $500.

Then I copied exact text from their website for multiple products and searched for them another 20 times. Result? They still would not show up.

Trust me nothing hurts like that raw view of massive failure of your online marketing on the single best acquisition channel on the web today.

Caused embarrassment. Forced a rethink at what is a glaring football field size hole in their marketing strategy.

Who wins? Customers. And the company, they will reduce acquisition cost and make more money.

When there was an argument at a top financial services company about what the home page, the holiest of holy properties per this company, should look like what do you think the company was going to do? Go with the version the President & CEO of the company liked. One smart person interjected to say: "Why don't we take your instinct and convert it into a HiPPOthesis?".

The CEO smiled. They tried three versions. The CEO's performed worst, on goals he had chosen. He still smiled after the test because 1. They made more money. 2. Avoided a big mistake. 3. Created happy customers. 4. He learned something new.

By involving customers companies have figured out that garish zebra print bed sheets are a perfect fit for being sold in their offline stores, identified the perfect song for their tv commercial, designed the best selling dvd covers, discovered pricing / discounts / product bundles that they would never have thought would have worked.

All faster and at a lower cost, with a higher impact on the business. Mental models evolved. Accountability increased.

2. Leverage Competitors.

I have rarely found a strategy that works better at elevating the game of any company than contrasting their efforts with those of their competitors.

It is astonishing that in a medium where your competitor is just a click away, the experience is absolutely frictionless, that we still live as if the burden and hurdles of the offline world exist online.

It is in comparing to competitors, known and unknown, that you can truly get the management to pay attention. Something about the size of the hit to the ego.

Here's an example.

Recently I visited the Sr. Executives of premier technology company and showed two sets of numbers. The ACSI has been measuring customer satisfaction for more than a decade. During that decade Apple's customer satisfaction went from 77 to 84. During that exact time period this tech company's numbers went from 78 (one point higher than Apple!) to 74.

Ouch. That hurts. Especially because they have poured many millions into "improving" the site (and a few million on analytics!).

Sure they don't have the "fanboyism" of Apple, yet Apple had that 10 years ago too. It is painful to realize that Apple started behind them and moved so far ahead, during a time where they not only did not defend their lead…. they actually regressed.

What do you think the management is doing now? Yep, questioning key things like who makes decisions, what the org structure looks like, how can they replace current hyper matrixed accountable structure with something that forces the right behavior at all levels.

Here's another example.

Rather than showing a CPG company how one of their sites was doing I took the liberty of comparing their tea website with their detergent website with their shampoo (personal grooming) website. It was astonishing how each was doing. For example the much smaller tea business was doing better than their key personal grooming business.

But I did not stop there. I compared them to an external benchmark.

What do you think I used? Their direct competition? No. I compared them to my blog's traffic.

It turns out I get two times the traffic when compared to all three of them combined!

Now my blog has nothing to do with a large multichannel CPG company. Yet I write a blog on an esoteric topic (I know that no one really cares about web analytics) and I write twice a month.

Yet I can get more traffic! Part time. With no marketing.

And they spent a couple of million dollars building their websites. To deliver what outcome?

Can you guess the result of this effort?

If you guessed a massive evaluation of their online strategy, ordered from the very top, then you would have guessed right.

Competitors provide a great contrast to your lameness or awesomeness. Be it leveraging the full power of online marketing channels. Be it creating optimal customer experiences. Be it bringing a new layer of imagination and accountability to your existence.

Embarrassment works.

Of course you have to do it right and be absolutely transparent that comes from a place of deep love and from a desire to to be better.

Because you see the goal is not to embarrass. The goal is not to be rude.

The goal is simply to provide context, fast. The goal is to get you, and your companies, to move beyond faith. The goal is to see the obvious potential in front of us. The goal is to throw away the shackles that have for far too long weighed us down.

That is what I mean by, now in quotes, "embarrass".

I hope you take away the passion I feel for making sure that advertising on the internet has to be magnificent and accountable. I hope you'll go empower your organization to "embarrass" you and that you'll do the same to them. I hope tomorrow will be the first day of a revolutionary transformation for your business.

Good luck!

__________________________________________________

The speech was received better then I expected (never easy to tell your audience they are the problem, or lay out tough to swallow solutions). I was profoundly grateful for that. The Q&A session following the speech was a of fun as well (always nice to get a chance to give my "It's not a OR world we live in, that's for super lame folks, it's a AND world!" mini sermon).

It's your turn now.

I would love to get feedback. What are your thoughts on the promise, the three problems and the two possible solutions to jump start a magical revolution?

Online Marketing Still A Faith Based Initiative. Why? What's The Fix? is a post from: Occam's Razor by Avinash Kaushik

Web Analytics Segmentation: Do Or Die, There Is No Try!

Avinash Kaushik — Tue, 18 May 2010 08:24:16 +0000

My love for segmentation as the primary (only?) way of identify actionable insights is on display in pretty much every single blog post I write.

I have said: All data in aggregate is "crap".

Because it is.

One of my earliest blog posts extolled the glorious virtues of segmentation:
Excellent Analytics Tip#2: Segment Absolutely Everything.

Many paid web analytics clickstream analytics tools, even today (!), don't allow you to do on the fly segmentation of all your data (not without asking you to change javascript script tags every time you need to segment something, or not without paying extra or paying for additional "data warehouse" solutions).

So it was with absolute delight that I wrote a detailed post about the release of Advanced Segmentation feature in Google Analytics in Oct 2008:
Google Analytics Releases Advanced Segmentation: Now Be A Ninja!

Of course Yahoo! Web Analytics, the other wonderful free WA tool, had advanced segmentation from day one.

And as recently as two weeks ago I stressed the importance of effective segmentation as the cornerstone of the Web Analytics Measurement Framework.

The Problem.

You can imagine then how absolutely heartbreaking it is for me to note that nearly all reporting that I see is data in aggregate.

All visits. Total revenue. Avg page views per visitors. Time on site. Overall customer satisfaction. And more. Tons of data "puking", all just aggregates.

The achingly tiny percent of time that the Analyst does segmentation it seems to stop at New vs. Returning Visitors! I have to admit I see that and I feel like throwing a tomato against the wall.

Yes new visitors and returning visitors are segments. But they are so lame that I dare you to find any insight worth, well, a tomato based on those two. You can't. Because new and returning are still two big indefinable globs!

Even if your business actually is tied to understanding the first and then subsequent visits by a person then you are far better off segmenting using Visitor Loyalty (in GA count of visits).

But I am getting off track (this whole non-segmentation business drives me bananas!).

Deep breath.

The Unbearable Lightness of Being.

Segmenting your data is key to your success and that of your company.

It is not very difficult to segment your data. Many tools include some default segments you can apply to any report you are looking at.

For example when you look at your revenue or goal performance it takes a trivial amount of effort to look at All Visits but add to that report the Paid Search Traffic and Non-Paid Search Traffic and get deeper insights.

You can tell your boss: We made 900k, and while you are obsessed with Paid Search please note that 850k of the revenue came from Organic and only $25k from Paid.

PS: Our business is in trouble because we are over-reliant on Search!

See what I mean, a bit better insights.

Among things in the above image I love analyzing Direct (to understand value of the free traffic), Visits with Conversions (to understand my BFF sources and pages and behavior), and Non-bounce Visits (to understand people who give me a chance to do business with them).

But true glory will only come from going beyond the default segments.

Because default segments are created to appeal to everyone / the lowest common denominator, and we all know that there is no such thing as "everyone".

You are unique. The top three things your business is working on are unique. The multi-channel strategy you are executing is unique. Your investment in tools vs people in your company is unique (you are 90/10 instead of 10/90!). You are struggling with your own unique challenges.

You have to have a segmentation strategy that is unique to you. And if you don't then your employment with the company needs to be re-evaluated. (Sorry.)

So how do you go about identifying unique segments for your business or non-profit?

Ask a lot of questions. Tap into the tribal knowledge. Force your leaders (ok HiPPO's) to help you define Business Objectives, Goals and Targets. [Key elements of the Web Analytics Measurement Framework.]

Let me tell you that without the above there is no hope. The first two will tell you what is important and currently prioritized. The third will tell you where to focus you analytical horsepower (based on actuals vs targets).

If you have O, G & T then it is time to select the segments to focus on, the micro-groups of data you'll focus on.

The Segmentation Selector Framework.

My humble recommendation is that as a best practice you should pick at least a couple of segments in each of these three categories:

1. Acquisition. 2. Behavior. 3. Outcomes.

You'll choose to focus on the micro group that is of value to you, and just to you, in each category. You'll apply those segments to web analytics reports where you hope to find insights (and if you choose the right segments you will!).

Let us look at each category I am recommending.

Segment Category #1: Acquisition.

Acquisition refers to the activity you undertake to attract people (or robots!) to your website.

This would include campaigns you run, like pay per click marketing (PPC), email, affiliate deals, display / banner ads, facebook marketing campaigns.

Acquisition also includes search engine optimization (SEO), because it is an activity on which you spend time and money.

Ask yourself this question: "Where is my company currently spending most amount of time and money acquiring traffic?"

Bam! There's the most important segment you will focus on.

Why? If you do your analysis right you can lower cost (by identifying and eliminating the losers!) and you can increase revenue (by identifying and investing where things are going well).

See the process I followed there?

Ask the question to identify what's important / high priority for the business.
Create a segment (and then micro segments) for that one thing.
Apply on the relevant reports to measure performance using key performance indicators.
Take action. It will have an impact!

Don't just log into Site Catalyst or WebTrends and go on a fishing expedition, or treat every single thing with equal importance.

Paid search. A specific group of keywords. Television campaigns. Email campaigns to prospective customers in Florida, New Mexico, Arizona and Utah. Coupon affiliates. "Social media campaigns" (context). Billboard ads on side on highways. Business cards handed out at trade shows.

All of the above are examples of acquisition strategies.

When you look at your web analytics data look at All Visits AND at least one of the above.

Two acquisition segments is normal.

If you make it three then choose one acquisition strategy that your company is experimenting with.

Say you have 1/10th of one person doing some tweeting or facebooking, :), then add that one segment to your top two. This will allow your management to look at what they are focused on and also one thing that sounds cool but they have no idea if it is actually worth it.

(Short term focus) Win – Win (Long term focus)

How To Apply Segments / Analyze Data.

The reports you'll apply your acquisition segment to will depend on the Key Performance Indicators you have chosen. But a typical set of metrics you'll evaluate will hopefully represent a spectrum of success, like for example. . .

The effort will be to try and understand if for our acquisition segment (say all my brand keywords or for email campaigns to increase sales of the most expensive products). . . .

How many visits did we get (to get context)
Of those how many were new visits (if that is a focus)
How many could we get to give us one pathetic click (bounce rate!)
What was the cost of acquisition (if you can get total cost give yourself a gold star)
What value could we extract at a per visit level
How many people could we get to convert (replace total goal completions with conversion rate if you want)
What was the total value added to our business or non-profit

As you look at your acquisition segments in context of all visits you can quickly see how you can start to find insights faster. Don't focus specifically on the metrics I have used above but rather the thought process behind their selection.

This is not the end of your journey but it is a darn good start!

[If you have Web Analytics 2.0 pop the CD at the back into your computer. In dashboard examples look for Stratigent_Sample_Dashboard.xls, via my friend Bill Bruno at Stratigent. It has an excellent example of segmented acquisition display, you can immediately steal it for your company!]

Segment Category #2: Behavior.

Behavior refers to the activity people are undertaking on your website.

When people show up, what is it that they are doing? Is there anything discernable / important in their behavior that is adding value to your online existence? Or, the flip side, what do we want people do to on our site, and is anyone exhibiting that behavior?

Even people who sometimes have segment their web analytics data often forget to segment by online behavior.

Many, but not all, behavior segments fall into these two buckets: People who see x pages. People who do y things.

Here are some specific examples (all of which you can create in Yahoo! Web Analytics or Google Analytics in a few seconds without having to pay anything extra for vars and slots or having to update your javascript tag or having to buy an add-on, you can also apply them to all your data including all your historical data).

Visits with more than three page views. . .

This can be so valuable on content only websites (more page views more impressions of irrelevant display ads!) or even on ecommerce websites (more pages views the deeper you sink your hook into the visitor, engagement baby!).

Where do these people come from? Do they buy a lot? A little? Do they write reviews? Did we acquire them or did they just show up? If they see so many pages what type of content are they interested in (politics? naked pictures? sports?)?

So on and so forth. Segmenting one behavior, understanding its value.

Similarly another could be focusing on people how add to cart and then abandon the site.

Or people who enter the site on the home page and their behavior. . .

Or all those who did not enter the site via the home page!

Or people who use the site's product comparison chart or car configurator or, my fav, internal site search. Vs. those that don't.

Or people whose Days to Purchase (/Transaction) are 5 vs for those for whom the Days to Purchase is 1. . .

Or, cuter, those whose last visit to our website was 100, or whatever, days ago. Why? And what do they want?

Or people who visited the site more than 9 times (!) during the current time period. . .

Where are these sweet delicious people coming from? (Note: To a blog updated only twice a month!) What do they read? What do they buy? What can we learn from them and do more of?

Those are the types of questions you'll answer from your behavioral segments.

The more you understand what people are doing on your site, the more likely it is that you'll stop the silliness on your site (kill content, redo navigation, make cross sells better, eliminate 80% of the ads, learn to live with 19 days to conversion, don't sell too hard, and so much more).

It is also likely (I want to say guaranteed) that you'll find the delta between what you want to have happen and what your customers want. You'll choose to make happier customers, who in turn, in the naughtiest way possible, will make you happy.

And it all stars with being able to identify and focus on the right behavior segments.

Pick at least two.

But I have to admit in this segment category I truly "play" with the data a lot because it is so hard to know what the right segments are, because visitor behavior is such a complicated thing (they are constantly trying to mess with us Analysts!).

It is only after experimentation (a lot) that I end up with something sweet.

Segment Category #3: Outcomes.

Outcomes are site activities that add value to you (business/non-profit).

I find that here the problem is less that the Analysis Ninjas don't segment, rather it is that they are incredibly unimaginative.

But first what is it?

Segments with outcomes are people or visits where you get a order (at an ecommerce website) or you get a lead (at Organizing for America).

Those two are obvious right?

Segment out people who delivered those two outcomes. Give them a warm hug and a kiss. Now go figure out what makes them unique when compared to everyone else who showed up at your website, all those other people who you worked so hard to impress but failed to.

Take the insights and do more of what works for this group.

Or segment out everyone whose order size is 50% more than the average order size. . .

These are your "whales", people who spend a lot of money with you. Don't you want to get to know them a lot better? : )

But there is more.

Remember macro AND micro conversions!

No one is going to sleep with you on the first date. (Ok maybe a few will!)

So focus on micro conversions that lead up to a macro conversion… like people playing a product video (or on content site watching five videos!). . .

Or adding a product to their Wish List.

Or signing up to show up for a protest for your ultra liberal policies!

Or apply for a trial, or download a trial product.

You can also focus on micro conversions that all by themselves are of value to you, even if not as much as the macro conversion.

For example submitting a job application.

Or signing up for a RSS feed.

Or clicking on a link to go to a different site you want them to go to (like clicking on the amazon link to go buy my book – great outcome :)).

Of course if you are really really good you'll also segment my absolute favorite metric in the whole wide world: Task Completion Rate. It is the ultimate measure of outcome (from your customer's perspective).

[If you use 4Q then now you can do some very very cool segmentation directly in Google Analytics! Watch this video to learn how to merge your quantitative GA data with your qualitative 4Q data. Pretty sweet.]

Net, net. . . it is absolutely critical that you segment your data by the key outcomes important to your business. Not just because your site exists to add economic value, but also because I cannot think of another way you can earn the love of your boss or get promoted.

By understanding what it is about people who deliver outcomes you can understand what to do with all those that don't convert.

Outcomes. Outcomes. Outcomes!

Pick at least two.

If you pick three or four that is ok.

If you pick nine it might be a signal you don't know what you are doing (and you want to corner your boss in a non-HR-violation manner and ask her to help you focus on the most important).

In Summary.

Segment or die.

It is as simple as that.

The next time you start to do true analysis of your data I hope you have your minimum six segments in hand (two for each category). If you do you'll find that web analytics, this world full of web metrics and what not, suddenly becomes a lot more interesting (and you no longer feel like jumping out of your office window in frustration!).

Love, money and glory await you.

Not to mention how proud I'll be of you when I see your analysis. ; )

Ok now your turn.

Are you a segmentation God? What are some of your favorite segments? Have you used this three category framework in the past to find segments? Do you think they'll work in real life? In the context of segments what do you think is missing from this blog post? What did I overlook / not stress enough?

What's your excuse for not leveraging segmentation? (Best answer to this question win's a copy of Web Analytics 2.0!)

Please share your thoughts / wisdom / critique / guidance.

Thanks.

PS:
Couple other related posts you might find interesting:

Web Analytics Segmentation: Do Or Die, There Is No Try! is a post from: Occam's Razor by Avinash Kaushik

Excellent Analytics Tip #17: Calculate Customer Lifetime Value

Avinash Kaushik — Mon, 05 Apr 2010 08:58:34 +0000

Some Marketers / Analysts use Click-thru Rate (CTR) to measure success of their acquisition campaigns. Nothing much to write home about, but certainly better than executing faith based initiatives.

A smaller percent of those Marketers / Web Analysts will move beyond clicks and measure Visits / Visitors and Bounce Rates to measure success. Lovely, warm hugs and smiles for them.

A fraction of those Marketers / Directors will calculate Conversion Rates for those marketing campaigns. They deserve our love. [And if they measure Micro Conversions they deserve our love AND respect for exhibiting savviness by using economic value.]

But all of the above is still focusing on short term success. Even measuring Visitor conversion rates (Visit based conversion rates promote bad marketing behavior) is akin to declaring success after a one night stand.

I reserve the best hugs, kisses, smiles, love, respect and my deepest admiration for Marketers and Analysts who use Lifetime Value computations!

That is focusing on real success, not simply the first conversion (the one night stand!).

That is focusing finding the customers that create value for the company, long term.

That is truly doing the kind of Analysis Ninja work that solves tomorrow's problems today!

For the above reasons I have been meaning to write a post on computing Lifetime Value for a very long time. But perhaps a better idea is to get an expert to do it, the result will clearly be far better than anything I would write. So I emailed my friend David. : )

David Hughes is the Co-Founder of the email marketing consultancy called The Email Academy and the author of one of my most beloved phrases: Non-line Marketing! His blog, Non-line Blogging, is a favourite of mine.

There are a handful of people in the world I could spend the whole day talking work and still have things left over to discuss, to learn. David is one of those super-smart, funny, and nice people. I have consistently found his ideas to be practical, grounded in common sense and instantly useful.

I could not be more thrilled that he agreed to cover this tough, yet rewarding, topic.

In this post David covers:

Why Life Time Value is important (especially in context of Acquisition)
How to optimally leverage value based segmentation & Lifetime Value
Share a sample analysis and, this is so sweeeet, a spreadsheet with a sample model that you can use to jump start your own LTV journey!

Buckle up, this is going to be fun and it just might change your life! :)

Here's David. . .

__________________________________________________

Solve tomorrow's problems today – introducing Life Time Value.

Acquiring new customers isn't getting any easier: We've picked off the low-hanging SEO fruit, we're paying more for quality clicks in AdWords and the going rate for affiliate deals just keeps getting higher.

We are also haunted by the specter of "marginal cost": The more customers you need, the more impressions and clicks you need. But as we drill deeper into worse performing media, or pay out for lower-volume-lower-relevance search terms, our cost per sale gradually rises.

There is a better way to analyze your acquisition strategy than simply using Conversion Rates or Cost Per Acquisition (CPA). Using Life Time Value might be a much better idea.

Life Time Value (LTV) will help us answer 3 fundamental questions:

1. Did you pay enough to acquire customers from each marketing channel?

2. Did you acquire the best kind of customers?

3. How much could you spend on keeping them sweet with email and social media?

I'm going to suggest that maybe you should be paying significantly more money for the right customers.

Let's start at the very beginning…

…that's a very good place to start. Take a snapshot of your customer database for the past 2 years and it may look like this:

That is an average.

The trouble with averages is they conceal all the really interesting stuff that's going on beneath the surface.

If you look beyond the averages you'll find that some of your clients are "better than average" and some are "worse than average".

Try and segment the customer base by total purchases over a longer time period, say a year, or total spend and you may come to a conclusion that says something like:

My most valuable customers last year bought 4 times compared to an average of 2. They tended to spend 40% more than average per order. However, they might cost significantly more to acquire.

Much better than the average right?

So, where did you get the valuable customers from?

Simply knowing that you are getting lots of conversions is not enough, you might just be getting new low value customers.

This is where Lifetime Value becomes interesting: Some companies are getting really worried about the lasting impact of "buying cheap customers".

For example, in many markets the price comparison intermediary (/engines) is an easy option – you pay your money (affiliate fees) and you take your customer.

But how likely are these customers to buy another product? Or hang around for a few years? With no brand affinity there's no desire to cross-buy and maybe we're filling up our databases with low value, promiscuous customers.

A simple segmentation by channel can easily help us answer these key questions. The output may tell the following story:

But, I hear you cry, Search Marketing is labour-intensive, risky and costly compared to buying customers at a fixed price from an intermediary.

OK, so let's look at how much MORE we should be paying for Mr Right, rather than Mr Average.

Let's change the headings of the table above to be clear what we're talking about…

Best and Average customers will have different Year 1 buying patterns:

Once we have done this basic segmentation we can then factor in the cost of acquisition per segment to determine the Net Profit per customer per segment.

You'll work with your acquisition team or your finance team to get the cost data. For some of your campaigns this data might not be easily available in your web analytics tool (it is also quite likely you are doing all of this analysis in Excel).

The table you'll end up with might look like this:

It should be pretty obvious at this point that simply taking the short-term view with metrics like Cost Per Acquisition (CPA) might not be prudent since you are rewarding the source sending you Mr. Right and Mr. Average just the same. Yet they are not of the same value to your business (Net Profit!).

It is important to move away from a cost-based acquisition model to one that recognises the cross and up-sell rewards of acquiring the right customers over the duration they'll be our customers.

Spend an extra $8.00 per customer, if you have to, and you're still twice as well off than buying rubbish ones!

But we can do so much more… let's take a longer term view.

Value-based Segmentation & Life Time Value.

By now we have established this: Some of your customers are going to be spending more with you, for longer.

Let's say I am a car insurance company, or a subscription publisher, with a desire to sort out some of tomorrow's problems today.

I know that the initial cost of acquiring customers (or policies/subscriptions) will only go up as more of my competitors sail for the calm waters of "cost per acquisition" pricing.

So, if I need to sell 10,000 policies every year I have 2 options.

Buy cheap customers and hope that a few may buy again

Buy the right customers that stay with me for 2 or even 3 years

Without doing the value-based segmentation we'll never understand which channels bring in the best customers and that would be a terrible shame.

The ground truth is that I can re-new a policy or subscription for considerably less than buying a new one. How?

One strategy might be to spend an extravagant $1.00 of marketing costs to show my love an appreciation to our customers throughout the year via email or social media, increasing the chances they'll buy again.

That means I won't have to spend $20.00 buying a new one… a saving of $19.00 per renewal.

So if I can grow my repeat purchase rate from 20% to 40% that means I will generate 2,000 policies at $1.00, not $20.00.

That's a $19.00 savings on each of the 2,000 policies. BAM!!

Moving to a Life Time Value acquisition strategy will save my company $38,000. Not bad for a couple of days work.

Let's finish off the concepts of value based segmentation and lifetime value by going back to the original example we were working through.

If we can identify channels, campaigns, media or propositions that deliver "better than average" customers we can begin to see how much more profitable they are and decide how much more we should be spending on them.

Here's the (sample) analysis I (or you!) would do:

Ladies and Gentlemen – select your lifetime!

In the above example I've modelled a 3 year lifetime – that would be sensible for a typical consumer e-commerce player.

Publishers and financial services companies may take a longer term view… certainly off-line we have been building 5 year plans in publishing for decades.

If you're more comfortable with 6 months or 18 months, then go for it!

If you do you'll need to be looking backwards and forwards at the same time.

You may only have 6 months of on-going data for some segments, but use that as a starting point and build some simple scenarios from there:

What if 50% of them spent 10% more in the next 12 months?

What if 30% of them spent 40% more in the next 6 months?

Over time as you replace modelled data with real data you should be able to re-weight your acquisition spend, replacing one affiliate with another as the cross and up-sell orders begin to roll in (i.e. the customers you acquired begin to make additional purchases from you).

By rewarding the better partners / media / acquisition channels with higher CPA's you'll be building a defensive position that prevents competitors buying their way into the good sources ("How can they afford to pay THAT MUCH?!" they'll all be wondering). It will be our little secret.

Life Time Value is for Life, not just for Christmas.

We've really only just scratched the surface of LTV in this blog post.

Many people have devoted their whole careers to unlocking its mysteries so apologies to all of them for the "top level" content here.

However, it is a concept that deserves the attention of a new generation of digital marketer and it will alter the way many companies approach acquiring and retaining customers.

__________________________________________________

Amazed?

Don't cha feel a little bad that you were making decisions about where to invest your precious marketing dollars based on either Conversion Rate or based on Cost Per Acquisition?

What's scary is that you could currently be using Conversion / Average Order Size / Cost Per Acquisition to invest more in one particular channel, all the while, unbeknownst to you, shoveling "poor quality" customers. Or "high CPA's" might have caused you to not spend enough on a channel where you can get lots and lots of high value customers.

Scary! Yet exciting that finally you can be so much smarter!!

Bonus: As a very special treat David's created an Excel spreadsheet to help jumpstart your Lifetime Value journey.

The spreadsheet has two tabs.

Comparison LTV lets you model two segments of customers by helping you walk through clearly articulated questions.

Detailed LTV kicks things up a few notches by allowing you to make better decisions by modeling out the long term performance for a given customer segment. [Create more copies of this tab to model out multiple customer segments and then compare / contrast to make wiser decisions.]

Download: Comparison + Detailed Lifetime Value Model.

[Please do not click on the link above, rather right mouse click and choose Save Link As or equivalent in your browser. Thanks.]

Closing Operational Thoughts:

I wanted to add a few thoughts about the operational things you need to worry about / keep in mind, as you revolutionize your company by using LTV:

1. You'll notice instantly that almost none of the data above is available in your web analytics tool. Not Omniture's Site Catalyst, WebTrends Analytics, Coremetrics, Google Analytics or Unica or whatever. This type of PII and financial data does not exit in these tools (often for a very very good reason).

Even the web analytics tools that say they create Lifetime Individual Visitor Experience (LIVE) profiles to compute Customer Lifetime Value (CLV) won't have the key Margin or multi-channel data, and hence not truly allow you to do the above, contrary to what might have been implied.

Web Analytics tools, even ones with lifetime visitor profiles, usually can't even stich together one person's clickstream behavior over the long term because of cookies and other data erosion issues. So plan on looking outside.

2. [Because of reasons immediately above and more...] Remember to focus not on the "Individual Customer", rather focus on the acquisition channel by analyzing segments of customers.

Individual anything ("you can track every single customer and understand every single customer and react to them in real time!!!") is over-rated.

Optimizing acquisition channels with LTV. Yea! Optimizing for Jim Sterne with LTV. Nah!

3. You'll do most of this type of analysis via your ERP / customer data storage system / financial data warehouse.

Your BFF will be the Finance team, both to initially teach you some of the financial intricacies and give you access to data you need. Look 'em up. Take 'em out for dinner. Trust me when I say that the LTV work will be a tremendous asset to your career and expose you to the highest levels of your organization. A really really good thing.

4. You are going to have to darn near sleep with your IT team/person to ensure the key meta-data required to do this analysis passes from your website to the sources mentioned in #3 above.

For example in my first job I had to request (ok beg) the corporate IT team (ok one person) to enhance the corporate system with two columns so each web order order could be distinctly identified and contain "campaign id" and "acquisition cost".

The lack of this meta-data is where most LTV efforts fail.

Even if you are a 100% web business you'll have to ensure the "backend system" that contains this key web analytics meta-data else you are doomed. Sorry.

5. If you are multi-channel company (web, call center, stores, catalogs) you'll want to ensure an equivalency exists in your backend system to [A] track the same customer's multi-channel orders correctly [B] contain cost data from all multi-channel campaigns.

This is really really hard to do. Don't try to climb mount Everest on day one. Start small and build over time. Remember David's tips on making do with just what you have.

I want you to be aware of these few valuable lessons I have learned in my own journey. I had to learn them the hard way. : )

If LTV sounds like it needs effort and love then you have understood it correctly. Everything worth it is hard in life, but if you put in the effort you'll create an enviable advantage for yourself and your company.

In closing:

1. Focus on long term success, acquiring truly valuable customers…

2. by embracing Net Profit and Lifetime Value…

3. and becoming BFF's with the Finance Team, good things will come of it!

Good luck!

Ok now your turn.

Have you used lifetime value or other such metrics to enhance your acquisition strategies? What was your experience like? If you have not used LTV, do you plan to use it now? What did you find to be of most value in this post? What would you disagree with? Did you want to run to England and give David a hug? :)

Please share your feedback via comments.

Excellent Analytics Tip #17: Calculate Customer Lifetime Value is a post from: Occam's Razor by Avinash Kaushik