December 2007


11 Dec 2007 01:13 am

metisseConfused about Web Analytics?

How about Web Metrics?

Have you been successfully scared?

Rhetorical questions. Don't answer. :)

Let's do this one step at a time, first let's demystify web metrics. We'll do web analytics another time.

The hardest thing you'll do in your life as a Web Gal / Guy / Marketer / Analyst / Researcher / Jack is identify what constitutes success for you when it comes to measuring Outcomes for your website.

Step two will be to identify the Critical Few metrics to measure those successful company, and hopefully customer, outcomes.

So what makes a great Web Metric? And what are the factors you need to keep in mind to ensure that your valiant efforts to measure business success in this first life will be successful? :)

This post is inspired from my segment of the WAA's well received webinar on the newly defined Web Metrics Standards last month.

The intelligent Ms. Angie Brown and the fabulous Mr. Jason Burby spoke about the tough work that went into creating the new standards. I spoke about Web Metrics Demystified .

In this post you'll learn how to find diamonds in the rough, how to know that a metric you have identified for your Management Dashboard is actually a good one, and you'll learn the process you can, and should use, to keep your web analytics metrics relevant.

Enjoy…..

Four Attributes of Great Metrics:

Metrics are a dime a dozen. Especially on the web. There are books and blogs full of 'em.

How do you know which one is your must have darling?

In my humble experience here are four attributes that all great, nay magnificent, metrics possess…

1. Uncomplex

Great metrics almost always are uncomplex.

Because we did not make much headway with recommended metrics foisted on us, our response has been to create complex metrics. Six things each with its own unique multiplier / variable predicting the position of the sun when visitors click on your site.

Here is the thing to think about: Decisions in companies are not made by one person. If you want action then the democracy needs to understand performance, the democracy need to make decisions.

Not you. Certainly not your consultant. Or best friend.

uncomplexify (http://www.abchiharmony.com/images/ComplicatedFS.gif)

If you are the only person who understands the metric, the Key Performance Indicator, then you have just guaranteed that your company, big or small, will not take action. Because you know the metric, but not the business.

Don't sexify, uncomplexify. Solve for the masses making decisions. It is not as easy as you think, try.

2. Relevant

Is the metric you have chosen relevant to your business?

Since we have so many metrics we pick our favorites and then stick with them. The problem is that each business is unique, even businesses that seem like they might be in the same business.

In Web Analytics: An hour A Day I use the example of Best Buy and Circuit City. You might think that they should / would / could measure their website with similar Web Metrics. Nothing could be farther from the truth.

relevant to youThe only thing they have in common is the fact that they sell large screen TV's on their website. Everything else is different. Their business models, their priorities, how each tends to use the web in its multi-channel portfolio.

The metrics you would use for each company to measure success would be different.

It is ok to seek inspiration from your friends and competitors. In the end truly stress test that the metrics you identify are relevant when it comes to measuring the success objectives that are unique to you and your website.

Remember what works for Jason might not work for Shane. And those two are close! :)

3. Timely

A few years back I was interviewing at one of the biggest companies on the web. They had just closed their quarter, it had been tremendously profitable. I asked them what the reasons were for that great success. The rest of this is absolutely positively 100% true.

Them: "We have just kicked off the query against our data warehouse, it typically returns the results in three months."

Me: Stunned silence.

Granted they were a big business. But still.

I learned a very important lesson on that day. Be on time or die.

That big company's stock price is a fraction of its price at that time. While not all of it is related to their ability to measure, you can imagine how hard it is to be successful in your business (on the web for Pete's sake!) if it takes you three months to know what worked three months ago.

Great metrics can be provided in a timely fashion so that your business decision makers can….. make timely decisions.

timely

I am not a big fan of real-time (see this post: Is Real-Time Really Relevant? ). But between real time and three months there is a sweet spot. Find out what your sweet spot is and then ensure your data can be collected, analyzed, and metrics provided with insights in that sweet spot.

Even the greatest metric in the world is useless if takes nine days to get (with insights!) when your world changes every three days (key word bids, affiliate bonuses, email promotions, web page updates, whatever).

Be timely.

Sacrifice complexity and perfection for timeliness.

4. "Instantly Useful"

I absolutely love this one. Smooch, smooch, kiss, kiss.

I credit my early experience with ClickTracks for that love. Dr. Stephen Turner and John Marshall had eliminated all the non value added stuff from the application so that no matter where I went, what report I opened, it was instantly useful.

It was a combination of the fact that there were fewer metrics but also the fact that they were presented in a way that made it easy to understand performance and get the first blush of insights.

Instantly useful is when you understand quickly what the metric is, and you can find the first blush of insights as soon as you look at it.

Here is a great example, the What's Changed report in ClickTracks:

instantly useful

Anyone can tell you what your keywords were this month, or last month. The ClickTracks reports shows you "what you should care about", keywords that rose in their importance this month and which ones reduced in importance.

All the complexity is "hidden", there is no crap, just stuff you should care about. In front of you.

Now does that not simply kick butt? [Click on the image above for a higher resolution version.]

It will take some nice analysis and time to understand all the nuances and unlock the mysteries and deep stuff (just like say for example with your wife / girl friend, less so with your husband / boy friend!).

But the first blush is there. As soon as you look at it.

[I think Google Analytics V2 also does this well through use of layout and color and summaries or things like Compare to Site Average, Compare to Past etc etc. But I admit I am greedy. Every time I look at a report, current or new, I ask for more instant usefulness! Phil and the team humors me by making stuff even better.]

In a data democracy metrics have to meet the bar of being instantly useful. And not just that, think of your boss, her boss, his boss. How little they know. If send them a metric and it is not instantly useful then it will be instantly ignored.

You want instantly useful, no explanations required, because that will give you the opening you need to show your "deep stuff", explain the nuance, highlight your analysis!

Smooch, smooch? :)

Example of a "Great Web Metric":

Let me give you a very simple example that I think will crystallize the methodology above.

I think Bounce Rate is a "great metric". Here is how it passes the required four attributes test:

Uncomplex? Single Page View Visits. Easy to understand, explain and propagate. Enough said. :)

cheerleaderRelevant? It identifies where you are wasting marketing/sales dollars and which pages stink when it comes to delivering on the "scent". Those two things apply to most web businesses. Bam!

Timely? Bounce rate is now standard in pretty much every web analytics tool, and available in every report. Every day. Nice!

Instantly Useful? You can just look at it and know what needs attention, what needs to stop. You see 25 – 30% for your site and instantly you know things are fine. You look at a page with 50% bounce rate and you know it needs attention. You see a campaign / keyword with 70% bounce rate and you know there is a fire.

Set aside half hour today or tomorrow or at the end of the week and apply the four attributes test to your own important web metrics. What do you see?

Three Important Final Lessons:

Here are three lessons that are directly from the front lines (sourced from painful battle scars!)…..

1. Perfection is…. the enemy of good enough.

Data quality on the web is not perfect, things change too fast, everyone wants a piece of data yesterday, your competitors are strong. Don't spend time getting things perfect when it comes to your metrics.result of the prefection quest

If you have 90% confidence in the data (how it is collected, processed, and presented) then make a decision. Don't wait for perfection.

Too many times we spend too much time being distracted by missing tags and the hoopla around deleted cookies and more. Follow best practices, then move on. Go for precision and not accuracy.

As Mr. Stuart Gold says: An educated mistake is better than no action at all.

2. Critical few baby, critical few!

I owe Steve Bennett the CEO of Intuit all the credit for this important lesson.

Steve is fond of pushing everyone to identify their "critical few". Priorities. Goals. Metrics.

My interpretation of Critical Few: When the proverbial crap hits the fan what is most important.

That statement has a phenomenal clarifying power.

critical few

If your business was on the line how would you know things are going well or badly? Cutting through all the clutter of data, what are the metrics that are your Critical Few?

Almost all of us have too many things we measure, too many things that distract us, take away our precious time / attention.

You probably have at most three Critical Few metrics that define your existence. Do you know what they are?

If you have 12 then you have too many.

3. Metrics life cycle process is your friend!

Metrics no matter how great have to stand the test of time. And business changes. Repeatedly.

I recommend this simple Metrics Lifecycle Process…..

web analytics metrics lifecycle process

The idea is quite simple really: Use the four attributes test to identify your critical few metrics, go measure them, then analyze the data you collect, take action. Here's the fork on the road. If you can't action anything then perhaps it is the wrong metric for your business. Eliminate it. If you can take action figure out how you can improve it further.

Execute the Metrics Life cycle Process in a timely manner, I recommend atleast once a quarter.

Some metrics will stay, those are your best friends, others will outlast their value, give them a warm hug and say bye bye.

There. Web Metrics Demystified!

Not that hard, right? Just a dash of thought, a drop of common sense and a pinch of passion.

Ok now its your turn.

Please share your perspectives, critique, bouquets and brickbats via comments. Thank you.

[Like this post? For more posts like this please click here, if it might be of interest please check out my book: Web Analytics: An Hour A Day.]

04 Dec 2007 12:58 am

yum yum yumThere is always something delightful to report back from each eMetrics summit, even if it late in getting to you!

Typically though it tends to be stuff from new folks who present and bring new perspectives.

This time it was different. There were a ton of presenters and many new faces and voices. But both presentations that I found delightful, with real solid actionable nuggets, were from old people.

Ok before Jim and Neil crucify me let me hasten to add that by old people I simply mean my colleagues who have presented at many a eMetrics summit in the past (this was my seventh consecutive presentation at eMetrics, so I am "old" as well!!).

Both veterans presented something new and interesting that, IMHO, overshadowed other insights, for me. Three cheers for non-recycled content!!

For people who speak at many conferences, this is a gift. It takes an extra effort to come up with good new content, but it is appreciated as a gift (from the knowledge Gods! :)).

It was nice to see friends, blog / book readers, vendors, analysts and everyone else at the summit. Thanks to everyone for making the time. Let's get on with my favorite insights……

Who: Jim Novo, The Drilling Down Project
What: Web Analytics Meets Business Intelligence
Why: Accuracy, Precision and the Actionable Data Pyramid

Others have talked about this but I have never seen someone explain it so clearly, the difference between accuracy and precision……

accuracy vs precision

Get it?

Both of the above in a perfect world are not desirable. But each brings a interesting set of challenges, and there is one of the above that is preferable.

Which one is it?

Precision.

Jim's recommend precision because it is predictable and insights that can be gained can be actioned with significantly more confidence. Think about it….

If you don't know where the shot will land every time you fire, what can you predict about the next shot you fire?

But if you know where the shot will land every time you fire, even if you don't score a bulls eye, can you predict what will happen with the next shot you fire?

Of course the choice now is stark.

Most people (Marketers, Analysts, Decision Makers, Report Writers) focus on Accuracy.

I think it is driven by "business world 1.0" where things were far less complex, the world moved at a glacial pace, the price for perfection was bearable because there were three variables on which decisions were made and even if it took five months to get the last 4% accuracy then it was worth it.

spur gear

Because decisions were big, change was slow, mistakes were expensive, tolerance for risk was low.

Unfortunately "business world 1.0" is dead. Atleast Online. Has been for some time, it will take the Fortune 500 a little while to realize that. Decisions are made on a lot more than just three variables (to get a sense for it just see Web Analytics 2.0). They need to made much faster (if you don't then your agile competitors will). Risk can be managed (even with your most outrageous ideas, say a test, you can control for risk – just split: control 95% and test 5%).

Change is all around you and happening faster every single day. For all us that don't want to get run over, let's determine to go for precision and not accuracy. Please.

Do the best you can with Tags, Cookies, Instrumentation, then jump into the arms of the sexy Ms. Precision.
[I don't know why but Accuracy seems so much more a male thing! Yes I get the irony.]

End of what you all surely agree is a rant.

There was one more delightful slide from Mr. Novo. This was particularly powerful for me.

What data yields insights that can be actioned the most? Here's Jim's answer…..

actionable data pyramid

Did I already say I adored this slide? It is adorable.

Jim's points are extremely obvious (actionability, relevance of insights that can be actioned decreased as you go down the slide). Let me share my learnings.

There is this myth that if only I know who you are that I'll be able to find earth shattering insights that are relevant and actionable. You age, your income, your marital status, your education level. That is worth a lot less than people realize.

I think partly people don't trust web analytics data because it is anonymous and cookie based. Demographic data seems to be the magic answer. While it is useful in some cases, increasingly for many businesses it is of less relevance and scores lower on the actionability index.

demographic 1Jim has worked in the online, offline and nonline worlds. His experience is that if you have actual behavior of your customers then that is most insightful in finding insights that driving action (what they do on your site, what have they done in the past, what made them fork over money to you, what creative / messaging got them to submit the lead…).

Then comes inferences based on implied behavior. You are doing this so far and everyone else who did that ultimately ended up sending us a truck full of money. People who have compared cars on Yahoo Auto and are on our site probably want to do this/that. This takes an even balance of art and science.

Then come Psychographics and finally demographic data.

I have a lot less experience than Jim but my humble experience, especially online, has reflected Jim's recommendation above.

Don't get red herrings lead you down paths where the output of your effort leads to a red face.

Jim's blog is: Marketing Productivity.

__________________________________________________

Who: Neil Mason, Applied Insights Foviance
What: Cutting through the NOISE!!
Why: Application of Predictive Analytics

I have had the distinct pleasure of hearing Neil Mason speak atleast three times and each time I am impressed with his insights and passion.

In our space Neil is the most "I have it all together and you will listen to me and you will be wow'ed" speaker. If you get a chance don't miss his talk.

Neil's presentation had this wonderful slide that I was quite smitten with.

It outlines something simple (yet non obvious): all of the variables that will determine the size of Neil's audience at a conference……

application of predictive analytics

Notice how incredibly well thought out it is! Neil's thought of all the elements, and now he has a magic formula that spits out a number. 250. Packed into a room that holds 150! :)

Neil's slide, for some odd reason, made me think of how hard it is to understand all the reasons why there is a outcome on your website.

Just look at the variables for a "simple" problem that Neil tries to solve above.

Now imagine trying to understand why your website is doing better than last month or worse. I think people desperately underestimate the complexity of mastering this talk.

improvementTake for example conversion rate.

Your boss comes into your office and says improve conversion rate by 10%. Not to ten points, that would be huge! By ten percent.

What do you do?

How easy or hard is your task?

Should you run out and spend a ton of money on Affiliates / Email Campaigns / Paid Search Ads? Should you run to identify the demographic profiles of people who visit your website? [That was a trick question, the answer is no! :]

Instead I recommend that you do the "Neil Mason Exercise".

Here is what my humble attempt looks like…….

application of predictive analytics - conversion rate

Before I figure out how to improve conversion rate I am going to sit down and identify all my "levers". That's what you see above.

Conversion rate depends on my acquisition strategy (where am I spending money to acquire traffic), my organic ranking of the "head" keywords, how crappy my checkout process is, distribution of why people come to my site (Primary Purpose), my website "scent" (Tip of the hat to the Eisenbergs) and so on and so forth.

In fact as I was writing these I ended up with way more variables than the seven slots available from Neil's slide. They are all the other green arrows you see above. :)

Lesson #1: This exercise is of tremendous value.

Lesson #2: This is hard.

Lesson #3: You can't improve what you don't understand.

Next time you get a challenge to improve a metric, any metric, go throug the exercise above. Then……

Go get the data for each of the variables you have identified and try to identify where the true opportunities are for improvement (classic: here are three areas out of 15 we stink at and now let's do a cost benefit analysis of where we can get the maximum bang for our bucks).

If you have done a good job of identifying all the variables then I promise at the end of this exercise you'll be surprised at what you need to improve to win. It won't be the obvious areas.

Neil's Blog is: Applied Insights. [Neil: More content please!!! :)]

__________________________________________________

Ok I am done! One summit, three excellent ideas, what more could anyone ask for!

Its your turn now…..

Please share your perspectives, critique, additions, subtractions, bouquets and brickbats via comments. Thank you.

[Like this post? For more posts like this please click here, if it might be of interest please check out my book: Web Analytics: An Hour A Day.]

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