Click here to start the wizard

• Does the wizard neglect to recommend a useful next step in a particular situation? You can now add your own thoughts to each step in the wizard.
• And over time you will be able to see what others have been recommending.

The flow-chart for a bird’s eye overview is now interactive.

• From anywhere in the wizard you can jump to the flow-chart to retrace your steps
• In the flow-chart you can click on any step in the wizard to jump to that step.

Our web analytics tools can answer almost any question. But practitioners had been left to their own devices when it came to figuring out what series of questions to ask.

Click here to start the wizard Click here for a bird’s eye view summary flow chart

So, each practitioner has had to reinvent “analysis” on their own.

Lots of books and helpful consultants are available to educate practitioners on how to do that. But that doesn’t make it less silly that thousands and thousands of analysts have had to reinvent the wheel every time.

So, it is with great excitement that I get to publish the (apparently) first “Web Analytics Question Support System” (QSS) today.

What is covered in this QSS today?

This first release is only very limited in scope.

It only addresses the situation where there has been a drop in the number of conversions on the site. You, as the web analyst, have been tasked with identifying the cause of the drop in order to remedy the situation.

The multi-step wizard will guide you through investigating whether the problem is in various details of your acquisition tactics (PPC, direct traffic, etc.). If the problem isn’t acquisition related the wizard will also guide you to investigate your conversion process and check on external effects such as competitors or seasonality.

What is not covered today?

If your web site is doing the same as it was during the last period and your question therefore is what you can do to improve things further, then you won’t find guidance in this wizard today. That will be my next project.

How does the QSS work?

The wizard walks you through a series of questions in logical order. Based on your answer to each question, you branch to a series of next questions and eventually to suggested next steps.

In order to determine your answer to each question you will be querying your web analytics solution, whichever you may be using. Down the road, I would like for such a QSS to be directly integrated into Unica’s web analytics and interactive marketing solutions. Some of the answers could then be automatically retrieved by the solution to save time.

But much more important than automating the wizard today is to validate and improve the content with your feedback. Therefore, please treat this as an RFC release, i.e with kind request for your comments and feedback.

What else will you need besides web analytics?

It is common knowledge among web analysts that they have to juggle a series of analytics tools in order to do their jobs. Besides web analytics, these include competitive intelligence or audience measurement, performance management, voice of customer, etc., etc.

But while crafting this wizard I was flabbergasted just how absolutely essential it is for analysts to use these tools in conjunction with their web analytics product. A logical analysis of the situation very quickly reaches points where the data coming from web analytics / page tags is simply insufficient for making informed decisions.

For example, I’d like to take my hat off to Bill Gassman from Gartner who has been pointing out for years the importance of integrating your site’s response performance data into your analysis.

Copy and improve this content!

Since I work at Unica, the company holds copyrights to the content that is published in this wizard. But my colleagues and I at Unica encourage you to copy, improve and reuse the content to your heart’s desire as long as you clearly refer to the original source, i.e. this blog and Unica. All of us in the industry stand to gain. Thank you.

Credits and additional comments

• Great minds think alike, they say. I am indebted to James Dutton at insight for the chance to discuss various options for shaping a QSS. Tradeoffs that we discussed ranged from the kind of strict wizard that I created to a searchable database of Q&As that James thought of. Both approaches have their merits.
• The good folks of Wripple had replied to my original blog post indicating that they are working on a very similar idea. But they are taking it one step further and making integrations with web analytics possible  Can’t wait to check them out as they go live!
• I am also indebted to Dylan Lewis for a quick review over the weekend and constructive recommendations for improving usability.
• As I said before, this QSS won’t eliminate the need for having well trained, well read, and well supported web analysts. Just like a clinical DSS doesn’t replace the need for doctors. Besides, analysis is just one of many things that a web analyst does.

What did it for me?

It was watching the tweets come across the ticker in real time on Tuesday while Google were announcing their new features at the emetrics conference in D.C., some 2,500 miles away from me.

It was like being there in person. Thanks to tweets, e.g. by @June_Li. What a great use of Twitter.

But Twitter has a problem:

It hasn’t found a business model.

And, famously, Twitter users also have a problem:

The vast majority of tweets are boring and a nuisance. And some tweeters tweet more often than they have interesting things to share.  It’s a new form of spam! There should really be a frequency crap. [Note on Oct 26th: oh oh, freudian slip, as Mike Keyes caught. That was meant to read "cap"]

Twitter could do everybody and themselves a big favor and solve both problems with a single strike.

I’d propose they should charge an increasing price for each tweet per person per day, e.g. as follows:

• Your first tweet per day is free
• 2nd tweet per day, you pay 50 cents
• 3d, you pay $1
• 4th, you pay $2
• 5th, you pay $4
• 6th, you pay $8

Surely, if something is worth saying to your followers you will spend a buck to do so. And if it isn’t worth a buck even to you, then, by all means, shut up.

Meanwhile, Twitter would leave it completely free to follow as many tweets as you like.

Twitter could forecast how much revenue they can expect from a move like this. Since they aren’t doing this, I presume they will have thought it through and probably concluded that there is a problem with this idea. The numbers might not add up to justify their current $1B valuation maybe.

This content comes at a very interesting time when many are wondering what the future holds for this little industry of ours:

• Adobe acquired Omniture suggesting one direction into which things might evolve
• Eric Peterson just authored a very interesting whitepaper with one of Unica’s competitors, SAS, on first, second, and third generation of web analytics. (Not sure if it is online but a preview was distributed at the Xchange conference.)
• Unica has voiced a clear vision of how web analytics should evolve beyond just the traditional use.
• And a whitepaper is available to webcast attendees with our view as to next-generation capabilities that everyone should expect from their web analytics solution today.

Without going into the above explicitly, John is going to share his research, experience and views on the past, current, and future of web analytics.

———-

Note: Link to recorded version is coming soon.

Ben’s leadership aligned us behind a common hash tag (#unicamis) for the conference. A big screen station running TweetDeck was set up in the coffee break area. And, thanks for these, the conference “was tweeted”.

Now, I had admitted my own difficulty with saying anything useful in 140 characters earlier. And, I don’t know how much the marketing professionals in attendance gained from the tweets.

But the following small anecdote opened my eyes a bit.

A little Twitter success story

The closing keynote was by Forrester’s Christine Overby. She had many great comments during her presentation including the following that was irresistible to tweet:

“customer intelligence to become the molten core of marketing“.

So, this became my one “good tweed” done for the conference.

Next day, I am on the phone with Forrester’s John Lovett in far away New England to learn more about his upcoming webcast in regards to next generation web analytics.

And to my surprise …

He had already picked up his colleague’s quote from Twitter and found it to be a good fit to underline one of his points in his slides. Meanwhile, other industry observers from Boston to Singapore re-tweeted the quote as well.

From one person’s mouth to the twitterverse and back into the real world.

The moral

Of interest was not only the viral effect here.

But being that the re-tweeters were often industry influencers (e.g. analysts) themselves, this was just a small reminder that social media are no longer really a choice but a necessity.

In this case, tweets have become a metric for engagement.

Like all engagement metrics, volume and content of tweets are not a perfect measure.

But if there hadn’t been any tweets, worldwide industry observers would be excused to wonder whether the conference was not worth a Tweet, or attendees weren’t up to the Twitter.

When in fact, attendance was up 50% over last year, and many of the cutting edge customer presentations on online and offline integration had me sitting on the edge of my seat.

So, tweet it, just tweet it.

Thank you Ben!

Is it the tool or the analyst or both?

Meanwhile, I am counting the days until the upcoming eMetrics Marketing Optimization summit in Washington D.C. on Oct 19.

To that effect, Jared Waxman was kind enough to leave another thorough comment as an ex-Amazon’ian. (or do they call themselves Amazones?) Thought, I’d point you to it so it doesn’t go under in its location within a past post.

Thanks much to Jared and Ned and others who commented.

In that post I referred to medical expert systems as an analogy to convey that this is a realistic idea even if it may seem at first that the web is too complicated. But I was struggling to find a good link to such medical expert systems even after torturing my favored search engine.

Well, turns out this was because they aren’t called expert systems anymore, but Clinical Decision Support Systems.

Below is a relevant exert from the related Wikipedia article.

—————–

Purpose/Goal

The main purpose of modern CDSS [clinical decision support system] is to assist clinicians at the point of care. This means that a clinician would interact with a CDSS to help determine diagnosis, analysis, etc. of patient data.

Previous theories of CDSS were to use the CDSS to literally make decisions for the clinician. The clinician would input the information and wait for the CDSS to output the “right” choice and the clinician would simply act on that output. The new methodology of using CDSS to assist forces the clinician to interact with the CDSS utilizing both the clinician’s knowledge and the CDSS to make a better analysis of the patients data than either human or CDSS could make on their own.

—————–

In the case of our analytics world, it wouldn’t just be analyst vs. this “WDSS” (web analytics DSS) but it would be a matter of combining:

• analyst
• WDSS
• Web analytics solution to supply information on “the patient”, a.k.a “the web site”
• CompIntel benchmarking / audience mesaurement
• VOC
• Customer experience mgmt.
• etc.

But I think the WDSS will be a great addition to help the analyst work with these other “talkative” but very deep systems.

Can’t wait to provide some examples.

A: Very exciting news for all of us. This proves that web analytics are worth billions of dollars. Everyone that knows something about analytics should get a big raise this week.

Q: My wife says reading about web analytics topics can cure insomnia. Why is such a geeky, nerdy number juggling sport worth billions?

A: Because the WWW is becoming the most central channel not just for advertising (as seems to be Adobe’s focus) but for interactions and transactions. Without web analytics at the heart, it would be like flying a Boeing 777 without instruments and only a kite string for control.

Q: So, are you jealous?

A: What me? Jealous of 30 somethings selling their company for billions of dollars? … On top of that, Josh James also has more hair than I do! That is just not fair.

Q: And how does this make sense for Adobe?

A: The funniest quote that was sent around on that is this one: “hey, why didn’t they buy Wendy’s” . Joking aside, there are a lot of puzzling questions open and still to be determined.

Q: And how about Omniture customers?

A: Phil Kemelor’s post today is worth a read on that one, especially when it comes to Genesis.

Q: How about other web analytics competitors of Unica’s?

A: Well, this big “For Sale” sign at Webtrends reminds me of a time when Visual Sciences’s new/old CEO had made a similar unmistakable public statement that the combined VS/WSSI were for sale. It didn’t take long from there until Omniture had announced its acquisition of the combo. So … shall we conclude and bet that Webtrends may change owners before Dec. 31st?

Q: Last words?

A: Personally, I look forward to competing with Adobe. But I will miss using PDF and Flash now that I have to uninstall those from my computer.

But the common man’s approach to doing web analysis still seems a bit more like a teenager dabbling around in the dark vs. an engineer that systematically constructs or troubleshoots an issue. That is to say web analysis still seems very ad-hoc instead of being methodical.

No, the best practice of “set KPIs and implement a continuous cycle of improvement” is NOT enough.

Everyone who is in the space has heard of the best practice. It is a well taken recommendation. But it is only the beginning of a methodical approach.

As soon as one of your KPIs is down the “methodical” part ends and instead you are advised to check your funnels and your paths and segment and drill and compare and trend and experiment and yada, yada.

Where is the methodical best practice for that part, heh?

Car mechanics receive more complete training than web analysts

Imagine you towed your kaput car to the mechanic. The KPI of “starter” is clearly down, i.e. the car doesn’t start. But now the mechanic takes a screwdriver and randomly checks each of the gazillion screws on your car.

That would be ridiculous!

Clearly, the mechanic will be trained to apply their knowledge of what should be happening vs. where in the process the breakdown is occurring to narrow down the cause of the issue.

You might say that is exactly what we would do with funnel reporting in analytics. But not so fast!

Take an example.

Say, we are an eCommerce website and our KPI “revenue” is down this week

There ought to be an expert system that advises the web analyst in which order to investigate following interrelated questions:

• Are conversion rates down?
• Are average order values down?
• Is traffic down?
• Are new or repeat visitors down?
• Are direct or campaign traffic sources down?
• Which campaign channels are down?
• Are click throughs on your search ads down?
• Is search inventory down?
• Is your paid search ad rank lower?
• Are you running out of paid search budget during the day?
• Are the direct competitor’s traffic and/or conversions up?
• Are site errors up?

See what I mean?

There are too many questions for you to always have to derive from scratch in which order you should ask them.

Why should we need to reinvent the wheel every time instead of having an expert system walking the analyst through?

Similar to the car mechanic’s job, there is a logical order in which to investigate web site issues

For example:

Is Traffic down?

• If Yes, then go on to troubleshoot traffic sources
• If No, then go on to troubleshoot conversion rates

But this is not as simple as a “decision tree”. It will be more like a network of questions.

For example:

• Traffic could be down because people may have shifted to clicking more on competitors’ search listings.
• Conversion rate could be down because visitors may have shifted to dropping off and buying more from competitors

So, in both the Yes and No branches of the above question/answer case the logical path can reach a point where you ought to switch from your web analytics tool to your compIntel tool to answer the next logical question.

My point is though — did I miss something or

• Where is there a white paper by our consulting gurus that has troubleshooting flow charts for each of the 5 site types and the most common 3 KPIs for each site type?
• I haven’t gone through the UBC/WAA course ware so if it is in there, someone let me know please.
• I have read most but not all web analytics books, so educate me if one of these has flow charts of questions in it?

Am I on crack?

I am sure you are yelling out loud by now: “Darn it, analytics are too complicated to turn into a static network of questions and web businesses are too different from each other even if they fall into just 5 common site types. “

• eCommerce
• lead gen
• content / publishing
• customer service
• brand marketing / educational

But dude, medical Expert Systems could not eliminate medical doctors either — They assist doctors in doing their work more efficiently and more reliably!

And if the expert system runs out of ideas and can’t find the issue … you can always go back to applying your own brain.

That is all I am saying.

The expert system could never eliminate the need for having educated web analysts and consultancies. But it would make everyone more efficient and effective.

Road map

• Phase 1: write down the trouble shooting algorithms on paper and try them out until they are ripened
• Phase 2: turn them into an expert system for easier use
• Phase 3: automate the connection to web analytics tools so that the expert system can check some of the answers itself and spit out a check list

An opportunity for the WAA, maybe?

Couldn’t this be a cool new online business for the Web Analytics Association?

• The system would be open for members to upload their own expert rules
• Members could select “trouble shooters” by site type and KPI
• Members could rate other people’s trouble shooters so that the best ones will bubble to the top
• An API would allow hooking up with the coolest web analytics tools, say Unica’s.

I suspect it would take too much work for volunteers though who may not have a real incentive for bottling up their expertise. So, I will be sure to talk to my colleagues at Unica and our consulting partners about this one.