Interview with Dan Darnell of Baynote: Predictions for 2013
As 2012 comes to a close, 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.
Dan Darnell is VP of Marketing and Product for Baynote. He blogs here. Prior to Baynote, Dan has spent the 21st century working on marketing automation and analytics systems at Siebel, Oracle, Optimost, and Adchemy. Baynote is a supplier of personalization and recommendation solutions for multi-channel retailers.
How has the recommender systems market changed in 2012?
Personalization is becoming mainstream. Our conversations in the recent past had been mostly with technologists, now we are having more discussions with business people. And it’s not just product recommendations, the question are more about how I guide customers to their goals within a session, across sessions and across touch points, i.e., Omni-channel. When we talk to business users, however, we have to do a lot of education on personalization. There are a lot of people out there who think that personalization is about a unique experience for every user when in reality it’s about relevance and helping customers meeting their needs. From a practical standpoint, if a group of customers have same needs, the business can meet them the same way and the users feel like they had a personalized experience. We did a great paper on this topic this year which is available on our site – here.
We have also seen some interesting transitions from the vendor side. Some of the traditional players, from the recommendations market, like RichRelevance, are focusing on the advertising. We also saw some old players come back into the market. For example, we saw Infor Epiphany this year for the first time. I was a product manager on Siebel’s Marketing Automation and Analytics products when Epiphany was hot in the market. Back then few marketers wanted a black box; they wanted workflow and rules, and the company faded. A decade later, marketers now want automation, algorithms, and machine learning and Infor has seen the opportunity to revive the product. IGoDigital was another interesting addition. They reentered the market with a recommendations and personalization platform and was then acquired by ExactTarget before they could get much traction. Given the number of established vendors in the space, this seemed like a little too little a little too late.
Our focus remains on the digital experience onsite and across devices. The new wrinkle for us is the emergence of mobile devices including smartphones and tablets. Customers are trying to figure it out. Mobile means yet another data source, new data types, and the small screens demand a different approach. Our research shows that tablets and smartphones are used differently, and need different approaches. The smartphone is a shopping helper used to locate and price goods. The tablet is for couch surfing: people are not taking tablets to stores…yet.
What are your proudest accomplishments for 2012?
I’m most proud of our progress as a company. We’ve turned a corner in understanding the people, process and technology steps we’ll take to build a great company. A start-up needs to be flexible, but there comes a time when you need repeatable process. For example, we’ve got a strategy and process for knowledge management and have a strong PMO function that has a big impact on our effectiveness. With our renewed focus, we are retaining customers at a good rate, while increasing our momentum in acquiring brand name retail and travel clients. We’ve also made great strides in modernizing our platform on Hadoop and in conceiving and implementing new personalization solutions. You’ll see announcements on this in 2013.
What part will recommender systems play in enabling an increasingly personalized customer experience?
The fundamental technology supporting recommender systems, such as machine learning, will support the next generation of customer experience solutions. There are different use cases, from different companies, deploying the technology today. For example, Bloomreach’s relevance engine addresses SEO and landing pages, Baynote’s solution addresses landing pages, onsite search and recommendations, RichRelevance is working on targeted advertising. In future, I see a convergence across these use cases. Baynote is a big data personalization platform; the recommendation engine is part of the solution. The big data platforms or so called big data applications will take off, to solve more types of problems across industries. This is going to be big!
What does the future hold for recommender systems and personalization?
I believe the market is heading toward much more automated marketing vs. marketing automation. There is a lot of investment in using big data and machine learning to automate lot of things like SEO, landing pages, onsite search, product and content recommendations, retargeting and just plain ad targeting. Algorithms are now much easier to deploy and leverage than when Baynote started. With the advent of technologies like Hadoop and our new modeling engine, a new algorithm on our platform requires an order of magnitude less code and is much faster. This is the kind of revolution that will make the these next generation big data vendors deliver the order of magnitude change in results that marketers have been waiting for.