As 2013 begins, I have reached out to top technologists working on personalization solutions and technologies. I want to hear where they think the industry is headed, and how 2012 has advanced the art and science of personalization.
Kimen Field is a Senior Product Manager at Adobe Systems Incorporated focused on Adobe Target. She has been a product manager for Test&Target for six years since it was a startup called Offermatica. Adobe Marketing Cloud puts everything digital marketers need in one spot, including analytics, social, advertising, targeting and web experience management solutions and a real-time dashboard. Adobe’s personalization solutions include Adobe Recommendations, which clients optimize using Adobe Test&Target.
Question: How has the recommender systems market changed in 2012?
The biggest change is a move toward including recommendations in a broader optimization and personalization strategy, rather than just offering (and implementing) Recommendations on its own. Themarket has realized that product/service/contentrecommendations need to be very relevant to the user at a given moment, as well as well integrated with the whole consumer experience; it’s easier and simpler to do it all with the same solution and experts involved.
Question: What are your proudest accomplishments for 2012?
We combined Test&Target, Test&Target 1:1, Recommendations, and our Search&Promote teams and began broad efforts to collapse the products into one solution, called Adobe Target, part of the Adobe Marketing Cloud. Starting January 2nd, we are offering thissingle solution for our customers to perform all of their personalization and optimizationtasks without having to think about each individual product. Instead, it’s a complete set of capabilities that can be used freely or combined to cater to specific business scenario needs. We’re following this up later in 2013 with the release of a simplified combined product that will be a single interface for onsite optimization.
We engaged heavily with the Adobe Advanced Technology Labs, a team of 20+ PhD data modelers and statisticians within Adobe (same team is responsible for the magic that is “content-aware fill” in Photoshop) to work on more advanced algorithms within the Recommendations engine. We can now usemore data and deliver better results than ever before. We’ve also implemented a “model evaluation framework” to easily and continually test new ideas and algorithms with production data to quickly deliver improvements to our customers.
Question: What part will recommender systems play in enabling an increasingly personalized customer experience?
Recommender systems will continue to be a huge, if not required, component to a company’s personalized customer experience. In fact, we find it is a great starter point for personalization. Consumers have come to expect this crowd-sourced data to help them in purchase (and entertainment) decisions; time and again we’ve found that delivering this relevant content to users at the right time greatly increases engagement, conversion, and con-sumer loyalty. Perhaps more importantly, it’s a type of deep personalization that doesn’t scare consumers at all—they are eager to allow the business to suggest relevant products and articles to them; helping them find items of interest much faster than on their own.
Question: What does the future hold for recommender systems and personalization?
In a lot of ways, we’re already at the peak of what we can do with the anonymous online data available to us. There are only so many ways to massage the same data to get better results. We need to continue working on ways to get more data: from POS systems, from call center information, etc. We also need to work with businesses to implement recommendations in more of their mobile experiences: the limited real estate on these devices makes recommendations unbelievably important; it’s much harder for consumers to scroll through tons of irrelevant products or article to hopefully reach something that engages them. The technology is here for mobile implementation; but we need to make it easier to do so more online businesses take advantage of the huge opportunity.