Thought Leaders in Big Data: Interview with Ron Bodkin, CEO of Think Big Analytics (Part 4)

Sramana Mitra: There are plenty of big data application layer companies that specialize in specific verticals. Yieldex, for example, is delivering very specific value in getting more out of the online inventory. DataXu is working on the advertising optimization space. There is Evolven in the IT operations area. There are a bunch of them working in the financial services space. 1010data, for example, is an interesting company in this space. There is Oversight Systems in fraud control. I can mention another 15 to 20 companies that are generating serious revenues in each of these categories.

Ron Bodkin: I wouldn’t claim that there aren’t companies that have products. I believe there is a difference in the nature of what these different products offer.

SM: There is a platform player category and a vertical application solution layer category. There are platform companies like GoodData and others, and then there is a domain knowledge layer, which is where people understand a specific domain really well and know how to extract value out of big data analytics. I cannot imagine how services companies can even think about competing in that space because the richness of the heuristics is so high when a company goes at solving particular domain problems. AgilOne, for example, has more than $20 million  in revenue, and is a retail recommendation systems company. They have been in business for quite a while and have deep domain knowledge in retail. The real question I would ask is, where are the gaps where there are no vertical solutions? I know compelling vertical solutions where it is still all custom development.

Anna Yen: This is Anna, [VP of marketing]. If you take the last company you mentioned, would you feel as though they are completely open to integrating? Does their product have the ability to integrate any type of data set that a customer might want to wrap in?

SM: This is not new. It is how enterprise software has always been built and sold. Usually it is 70% to 80% product and 20% to 30% service kind of business. If you are working with large enterprises, especially with Fortune 500 scenarios, typically what happens is that there is going to be a 70% to 80% overlap in functionality, and the rest of it is done in services.

AY: That is exactly what we are talking about. It is not that we don’t acknowledge or appreciate the products that are out as a package solution, but every product like that requires some amount of customization. That is actually the business we pursue.

This segment is part 4 in the series : Thought Leaders in Big Data: Interview with Ron Bodkin, CEO of Think Big Analytics
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