FetchBack announced yesterday that it has launched a recommendation engine as part of its retargeting solution for advertisers. Read the release.
FetchBack CEO Chad Little discussed the new product and recent developments in retargeting.
AdExchanger.com: Please provide a “use case” on how FetchBack’s machine-learning technology works.
The only use case we can provide now is just to describe more about how it works since advertisers are just getting going.
The recommendation technology (like most) looks at the data on browsing behavior, shopping cart abandonment behavior and purchase behavior of each individual. It then looks a like-minded individuals and what their behaviors are. We’re analyzing data patterns on each individual advertiser site and as time goes by the recommendations get better as the data gets more rich. The most important individual to be targeting here is the person who has made a purchase as we’re able to make recommendations based on what other like-minded individuals have also purchased. So the tech works at an individual level as well as looks at overall site patterns so if we have very little information about a user because they haven’t browsed deep into the site we’re still able to make a recommendation that should be on target.
Given the technology’s ability to provide branding as stated in the release, how will the pricing model work? Any thoughts about pricing according to engagement metrics, for example?
We work on CPC, CPA and CPM pricing models. Our product can provide more conversions that any other offer out there – but the key to your question here is detail that can be found in our analytics – we do provide information such as engagement with the ad (and this is going to become more rich as we can now serve up to 10 recommended products in a single ad) – this engagement data along with engagement mapping and a/b testing provide substantial data as to how the ad is driving a conversion.
Now that Google’s AdWords has announced self-service retargeting, does this impact FetchBack’s opportunity? Why or why not?
Overall it’s a positive – Google’s strong entry validates the opportunity in the market. At the heart of it – Google can not drive the level of conversions that FetchBack can. While we can continue to expect Google to provide innovative product offerings (possibly even recommendation technology like what we’re talking about here) – but Google will most likely always distribute to it’s network – which, while it’s a large one can’t compare to the reach FetchBack can provide – FetchBack is network agnostic and works with many players who can provide high-quality traffic – this enables us to reach 70-80% of a clients lost prospects. When you’re working to integrate an offering like retargeting and manage multiple providers like fetchback and google it can become cumbersome – there are a lot of benefits to working with just one.
By John Ebbert
