Aziz discusses the infrastructure necessary for brands to do sophisticated mobile advertising.
Sramana Mitra: Let’s start by introducing our audience to yourself as well as to Sabio Mobile.
Aziz Rahim: I’m the CEO of Sabio Mobile.
Sramana Mitra: What do you do?
Aziz Rahim: Sabio Mobile has something called App Science. Our view is that App Science is a gateway into understanding a consumer’s behavior both from purchases as well as general behavior on mobile devices.
Sramana Mitra: What, in the domain of artificial intelligence, is relevant?
Aziz Rahim: Most of the folks in our industry have always looked at apps as current snapshots. For example, a person app profile is a current snapshot of where they’re at. We’re using artificial intelligence to do a little bit more projections of how of how they got to that point in terms of why they loaded those apps. This is almost behavioral targeting based on those profiles and some deeper analysis of existing correlations. We believe there is a causal relationship, in many cases, to why people load apps.
Sramana Mitra: How do you fit into the food chain?
Aziz Rahim: Our customers are primarily brands that we work with through large ad agencies. What we’re trying to do is provide them a deeper understanding of a mobile consumer beyond just the view of a duopoly perspective. We’re trying to give that consumer a deeper understanding of what it is, who their audience is, and how do they identify more precisely. We’re very focused on working with large brands.
Sramana Mitra: Can you explain to me, architecturally, where you’re sitting? Who’s installing what for this data to be available to you?
Aziz Rahim: We’re one of the very few companies of our size that have built the full infrastructure. We have our own ad server. We have our own DMP. We have the benefit of multiple datasets coming into that infrastructure both from our advertising ad-serving capabilities along with third-party data relationships that we have. We’re really bringing a lot of these datasets together in one consistent way, cleaning them up in some cases, and then doing the deeper analysis that helps us understand.
Sramana Mitra: Can you talk about some examples of the types of insights you have provided for your customers? You can take maybe two or three customers and walk us through a more visceral understanding of what kind of insights you provide.
Aziz Rahim: Just to clarify, we’re not primarily an insights data company. We are a company that provides a full-service mobile solution for clients on the advertising side. An example of what we would do is for banking customers, we would be able to identify consumers who are likely to have their banking app as well as that of competing banking apps to facilitate the execution of a campaign for something along the lines of people who are interested in potential mortgages in the next 60 to 90 days, or people who potentially are interested in opening up checking accounts. These are the kinds of insights that we are identifying with our App Science capabilities. That’s one category.
In automotive, we’re able to identify consumers who are likely to be in market and project that out for a few months before they’re actually in market. We also help identify consumers in terms of multi-cultural consumers, specifically Hispanic. The prevailing view has always been to identify Hispanic consumers based on the content they consume. Those lines have been blurred a little bit. As recent stats have shown, consumers of Hispanic origin aren’t natural consumers of content in Spanish anymore. We also use this idea of App Science in identifying consumers via their app profiles to identify them from a multi-cultural perspective.
This segment is part 1 in the series : Thought Leaders in Artificial Intelligence: Sabio Mobile CEO Aziz Rahim