Sramana Mitra: Can you walk us through some use cases? You talked about Claritin and the allergy season as one set of identifiers around which you are personalizing. What are some other examples?
Diaz Nesamoney: The hotels, for example, are looking at multiple such data points. The loyalty program says a lot about you. They know how frequently you stay and what type of properties you stay in. Do you travel for business or for pleasure? They start to understand what your travel patterns are. If a hotel analyzed me, they would realize I go to New York every other week, I go to London once a month, and go to India every quarter. It’s fairly predictable.
Then they can do a more precise personalization. There are also some interesting surprises. With one of the CPG companies, the Brand Manager was very convinced that personalization should be based on demographics. Because we are big believers in using as much data as possible, we persuaded them to also have time-of-day messaging. Most people would say, “Are people paying that much attention to an ad to see if a different message comes on in the morning versus in the evening?” Everybody was surprised to find out.
Our optimizer flagged it and said, “Messaging based on the time-of-day is actually generating better engagement than even who the person is.” It was a simple case of showing a breakfast food item in the morning, a lunch item in the afternoon, and then a dinner item in the evening. There are some interesting things that you discover. It’s also specific to the industry.
We’ve developed a lot of best practices around these industries where we’re able to advise clients, “If you’re in the travel industry, these are the things that we think matter.” It’s quite eye-opening for them to also see it because we’ve accumulated enough data to show that these kinds of triggers do actually influence engagement and purchase.
Sramana Mitra: What are some other examples from a couple of other industries?
Diaz Nesamoney: Auto is another one. You’d be surprised to hear this, but color of the car matters.
Sramana Mitra: Of course it does.
Diaz Nesamoney: Why then do auto advertisers advertise one color to everybody? We’re doing that now. It’s not just about the fact that they went to an auto brand site but what they actually see there. There’s a lot of data there. It gets very granular. In the past, even if you had all the data, it’s very hard to use that data meaningfully and intelligently and to generate so many different variations. That’s essentially what our software is doing.
It’s making it possible to look at so many different points. For an auto user, you could say, “This person cares for the financing of the car.” Financial services is starting to engage more now. A lot of them are a little bit more B2B. They are starting to look at even how the markets are doing on a particular day and saying, “People tend to be optimistic in certain days.”
Sramana Mitra: If you look at your business, what is your top segment where you have huge adoption of this kind of technology?
Diaz Nesamoney: Consumer-facing segments. Retail, travel, hospitality are the most advanced users, particularly retail with e-commerce because they do have a lot of data. They are very metrics-driven.
Sramana Mitra: It’s also easy because the entire transaction happens on the site. It’s very easy to track.
Diaz Nesamoney: Exactly. They’re very data-rich. The CPG brands are starting to come in. We have several large ones. They don’t have much data because people buy from retailers although weather and location are available to them. They are able to leverage some of that. It’s quite across the board. We have enterprise software companies as clients. The idea of relevance is true in any form of marketing whether you’re B2B or B2C. Even if you have four products as opposed to 40,000, there’s a notion of relevance.