I finally caught up with Optimove for a briefing on the Optibot technology they introduced last September. For a bit of background, Optimove is a Journey Orchestration Engine that focuses on customer retention. It assigns customers to states (which it calls microsegments) and sends different marketing campaigns to people in each state. See my original Optimove review from three years ago (!) for a more detailed explanation.
What’s new about Optibot is that defining microsegments and picking the best campaign actions per segment have now been automated. Optimove previously analyzed performance of microsegments to find clusters within the microsegment with above or below average results. When it found one, it gave users a recommendation to treat these clusters as separate microsegments and potentially stop promoting to the poorly performing group. Optibit takes the human out of this loop, automatically splitting the microsegments into smaller microsegments when it can.
Optibot also automatically tests different actions against people within each microsegment. If it finds that different actions work better for different clusters, it will assign the best action to each group. (In practice, it slowly shifts the mix in favor of the better actions, to be more certain it is making a sound choice while minimizing the opportunity cost of poorly-performing actions.) The system gives reports that compare actual performance with what performance would have been without the additional segmentation and optimization. That’s a helpful reassurance to the user that Optibot is making good choices, and of course a nice little demonstration of Optimove’s value.
Finally, Optibot provides users with recommendations for things they can do, such as create new actions for microsegments that are not responding well to existing actions. I’ll assume that Optibot does this because it really can’t create new actions by itself, and not just so marketers have something to do other than watch cat videos all day.
I’m probably making Optibot sound simpler than it really is. There’s a lot of clever (and fully automated) analysis needed to find the right clusters, given that there are so many different ways the clusters could be defined. Optibot also needs a goal to pursue so it knows which actions and clusters are giving more desirable results. Defining those goals is also still a job for human marketers. Fortunately, it only has to be done when a program is being set up, so it won’t cut too deeply into precious cat video viewing time.
Sarcasm aside, the real value of Optibot isn’t that it automates what marketers could otherwise do manually. It’s that it manages many more segments than humanly possible, allowing companies to fine-tune treatments for each group and to uncover pockets of opportunity that would otherwise be overlooked. Marketers will indeed need to create more content, and will no doubt find other productive uses for their time. And, frankly, if Optibot meant fewer 60 hour work weeks, that would be okay too.