It is often said that building (or proving) the business case for (site-side) behavioral targeting has been a lot harder than justifying an investment in more straight forward site optimization techniques such as A/B testing.
It is often said that building (or proving) the business case for (site-side) behavioral targeting has been a lot harder than justifying an investment in more straight forward site optimization techniques such as A/B testing.
As a result, you can read independent industry analyst reports observing that some applications that can do testing and targeting (hint, hint) are a lot more frequently used for just testing rather than targeting today.
You can even hear from some of the best known and experienced consultants in the online optimization industry that they don’t feel convinced by the business case for (site-side) behavioral targeting because they feel it is less clear cut vs. testing.
This doesn’t need to stay this way.
The problem is that we have been asking the wrong question.
The question should not be “proving the business case for behavioral targeting”. But we need to make the question specific to the use case for targeting that the marketer wishes to pursue / prioritize.
That is to say, we need to seek the business case for using behavioral targeting technology to do one or multiple of the following things:
- Improve conversion rates for acquiring new clients
- Improve on-boarding of customers
- Improve cross- / up-sell
- Improve customer service case resolution times
- Improve customer retention
- Improve win-back of former customers
- Improve satisfaction with the site’s usability, i.e. ease of finding what visitors are looking for.
When restated in this fashion the business case becomes much clearer. For example, if behavioral targeting allows you to improve customer retention by 1%, then you can calculate what that is worth to your business.
How do you prove it then?
How do you prove that behavioral targeting has been able to help you improve XYZ by some percentage though?
Simple
You do it through hold-out testing. You simply compare what happens to the hold-out group vs. the test group who are exposed to behaviorally targeted recommendations for the use case.
If you think that hold-out testing is complicated … then you have no business even thinking about behavioral targeting. Your organization needs to first learn how to do A/B testing.
Why has this been so hard for online marketing optimizers then?
My personal guess is because:
- Despite the wonderful, 2001 emetrics paper by Jim Sterne and Matt Cutler, web analysts are – still – not thinking about the customer life cycle enough (i.e. acquire, convert, on-board, grow lifetime value, retain, etc.). Instead, analysts may be too busy optimizing ads and pages. We aren’t measuring customers but ads, pages, transactions. And frankly, web analytics tools were originally created for the latter and most do a horrible job when it comes to measuring customers.
- We seem to have a blind spot for hold-out groups somehow. As a symptom, Jim Novo and Kevin Hillstrom have been frequently reminding their readers of this neglect. Strange though. After all, hold-out testing is just another name for A/B testing, which we supposedly master so well online.
Go figure
