As I said in an earlier comment, I didn’t get to see many of the sessions at eMetrics DC due to a raft of WAA stuff and great interactions with the people at the show outside the sessions.  But I have seen a lot of commentary, notably from Gary, Judah, and Eric, and related, from Christopher, on the overall message.

I have to say I agree (or is it have agreed?) – web analytics is headed for the BI shop.  In what form, we can only speculate.  But I have a few ideas, and a great resource that could be quite helpful depending on where you want to go with your analytical career.

The Google Analytics API, for one thing, is going to be huge from a BI perspective.  Just exactly what you have access to and in what format will be an issue for some BI folks, who tend to want “all of it”.

If BI really wants all the data, WebTrends was talking about cleaving the reporting from the processing – just like a traditional BI scenario, where the analytics app sits on top of any warehouse.  But I think in general most BI folks are over-thinking this issue and in time, they are going to be more satisfied with the “right” data, as opposed to “all”.

Here is what I mean.  I think you are going to see this split, where the higher level web analysts are going to head into BI, because they already know what they know, and what data is important.  BI will suck the “right” data out of the web anlaytics area and leave the rest of it.  Meanwhile, there will still be web analysts that will use “all the data”, but that will be pretty much relegated to what a lot of folks do now – straight traffic reporting, basic analysis, optimizing the web site at the campaign and page level, all that good stuff.  Important work, but for many business models, not mission critical.

Said another way, we’re going to get a split along Visitor versus Customer.  Web analytics will still be dealing with the transactional, backword-looking web stuff at the Tactical / Visitor level, and BI will handle data integration and all the forward looking stuff – Predictive analysis.  This means BI will be dealing with the C-Level and Strategic issues for the web.

Now, it certainly doesn’t have to turn out like this, and many shops using the advanced or Enterprise level web analytics platforms that run on a real data warehouse no doubt are already there – BI has come to the web analytics shop.  I suspect a lot of the pure online commerce folks are in this bucket.

I’m sure many BI folks think of web analytics apps as “bridge technologies” that will have limited use once BI gets their hands on the raw web data.  I doubt this is really true in most cases; there will still be a need for “reporting” at the site level for optmization, and the BI folks I think dramtically underestimate the overhead of dealing with this kind of reporting in a data warehouse. 

So, there is going to be a split, with commodity Visitor Reporting down the web analytics path and high value Customer Analysis / Insight moving into BI.  This means a potential player split as well.

Some players, on both the Tech and Marketing side, will stay with the commodity Visitor reporting side of the business.  Others on both sides will choose to move up into the BI world.

On the Tech side, a move up into BI means data warehousing, ETL, and that whole area, where a web analyst would be extremely valuable in terms of understanding and configuring the combined solution.  Pure analysts will start to grapple with (aggregated or event) web data in SPSS / SAS or similar apps.

On the Marketing side, it’s a move away from the Tactics of Advertising to the Strategy of Marketing, where you’re not just looking at the media but also customer service, product configuration / packaging, pricing, fulfillment – all the customer touchpoints.  This movement is well underway at companies that were born customer centric: catalogs, TV shopping, other Relationship Marketers.

To me, one of the great paradoxes of online is everybody talks about customer centricity but few actually measure anything at the customer level;  the non-stop blah blah blah is all about Visitors and Campaigns instead of Customers.

I think this paradox will start resolving itself during this next business cycle, since there is never more focus on customer analysis than there is in an economic downturn.  As I said in my presentation at eMetrics, it’s fairly easy to get into the prediction game with some simple analysis that is really Strategic in nature. 

Imagine the power of predicting your business will be doing better or worse 3 months from now.  What are we doing right or wrong today that will help or hurt us in 3 months? 

That’s what the BI / Customer angle brings to the party, for alas, web analytics / marketing has for the most part stubbornly refused to get into the Customer measurement game.  The general model and approach I presented at eMetrics, which I referred to as the Past / Last model (Frequency / Recency) for that audience – is on this blog, for Campaigns, Visitors, and Customers -  if you are interested.

So, what to do about all this if you are a web analyst?

If you see yourself going the tech / warehouse route, and especially if you already have the WAA / UBC Award of Achievement in Web Analytics, I would consider going for the Certificate in Web Intelligence from UCI.  I heard a fabulous story at eMetrics from Shaina Boone at Critical Mass about some very intense warehouse stuff they are doing, and it’s working out quite well for the clients.  She’s in or completing the UCI Certificate program right now, and said this UCI material was a tremendous help with that task.

On the Marketing / Business side, are you one of those folks who can consistently pick the winners before the A/B testing even starts?  Or have you provided a solution that outperformed all of the machine testing just by looking at the page? 

If so, you have developed deep insight and empathy for the customer, are a truly customer-centric thinker.  This kind of person can excel in execution on the BI side, Turning the Data into Profits.  Not by creating Campaigns, but designing entire Marketing Programs that may involve other areas like Customer Service. 

If you’re looking for education in this area, check out some of the courses offered by the Direct Marketing Association or read one of the great books out there on this topic.  The WAA is planning on expanding the Certificate program to cover these areas as well.

In the end, the difference between Visitor and Customer analysis is a matter of perspective.  Clearly a Visitor and a Customer can be the same entity; the difference is how you look at the data.

Visitor analysis tends to be very “one-off” transactional and is backward looking; Customer analysis tends to be about behavior over time and is forward looking / Predictive. 

For this reason, Visitor analysis tends to optimize towards performance “now” while Customer analysis optimizes for the future and is willing to take a hit in the present for higher ROI down the road. 

Finally, Visitor analysis is very Marketing-centric while Customer analysis is often cross-functional, often dealing  with Content, Customer Service and Product issues as well as Marketing.

So, where are you headed?  Any thoughts on the above?