This is not just an ‘interesting idea’. This is a battle tested solution used by broad spectrum of companies over period of more than 2 years.

During that time the method has consistently delivered speedy results, it has eliminated testing risk, and it was very easy to use.

The algorithm is designed to take into account a time varying nature of website visitors. It collects combinations statistics over different day parts or days in the week. It’s decisions are driven by relational statistical model a not how an individual combination performs. As result it can effectively adopt to changes in visitor behavior.

Now, lets talk about your hypothetical ‘February 14th chocolate or flower sales’ example that in your mind kills the adaptive methodology.

Assuming that you are right about visitors behaving completely differently on February 14 then any other day, your options are:

* Option 1 – Adaptive optimization: A system will adopt itself to a new situation, but because of a short burst nature of the change the adaptive response will be sub-optimal. Useful but not a perfect one.
* Option 2 -Traditional multivariate testing solution: These methods will not react to change at all.
* Option 3 – Let the human take control of the ‘stick’: This is a guessing game that can not guarantee consistent results.

Today, to better manage their website, the most companies are applying the best practices and ‘gut feel’ measures. The end result is that we have 98% of general web traffic wasted.

That is why we recommend use of a solution like http://www.hiconversion.com to merge the optimization science with a good marketing insight. There is not denying, an optimization test is only as good as input provided by a marketing person. Our tool gives you an ability to easily test many promotional ideas while helping you to consistently produce measurable increases in the online marketing ROI.

Cheers,

Zee
President & CEO
Hiconversion, Inc.

For example, if the algorithm automatically adjusts what percent of each version is shown after only looking at Monday’s traffic, then the decision it makes is based solely on user preferences for Mondays, not for other days of the week.

Similarly, suppose you are a flower or chocolates website … if the algorithm looks at traffic from Feb 1 to 13th, adjusting several times in that timeframe, it probably zeros in on what it thinks is the “best” version. But, come Feb 14th (Valentine’s day), everything changes because the big “event” has come and gone, and now the shopper’s dynamics are totally different. Where are you then? You basically need to start over.

These are some of the fundamental issue with self-optimizing “auto pilot” systems. Even when we fly airplanes, we don’t let the auto pilot take us the whole way … there are many times that the human needs to take control of the stick.

DM

Just wondered if you used their product, and if so how you found it?

You dont seem to have subscribe to comments, so perhaps you could reply to my mail? If so many thanks in advance.

Best rgds
Richard