Thought Leaders in Big Data: Interview with Bob Tennant, CEO of Recommind (Part 4)

Sramana Mitra: That is interesting. Are there any other major use cases, or are those more or less representative of how you gain accounts?

Bob Tennant: There are others on the license side of our business, also in customer experience optimization. There you basically pull together information from a wide variety of repositories, because often you can get a much more holistic view of the current state of a customer when you draw from the CRM system, the email system, and the marketing management system. Then you can start to build a model of what the customer looks like and recommend how to improve the customer experience or better target sales. This we do relatively frequently.

SM: Are you a relatively horizontal company? Are you selling to all different verticals, or is there any kind of vertical nuance to your work?

BT: The technology itself is entirely horizontal and always has been. But we have taken a relatively calm “bowling pin” approach to building the business. We have a different financial profile from a lot of Silicon Valley companies these days. We have grown the business from cash flow from day one. If you do that, you have to be relatively careful about how you do it because the needs of users in one vertical are usually quite different from the needs of somebody in a different vertical. But there are always nuances. We started off in one market, which was the legal field, and then we branched off into the others – the financial market, the government market, the healthcare market, etc.

SM: When you say that you are different from a typical Silicon Valley company, does that mean you have not raised venture capital? Have you done it on a bootstrapped basis?

BT: We have raised a very small amount of venture capital, but largely the company has been bootstrapped.

SM: Would you talk a bit about the genesis of the company? We are very supportive of and interested in bootstrapped businesses.

BT: The company was founded by a couple of post-doctoral researchers from Berkeley. I seed funded the company. From the origin, I took the concept behind the company, which was basically a set of machine learning algorithms – one in particular that helps you understand constant text – and thought about where that might be applied. When the research was being done in the late 1990s – as you can imagine back then it seemed like recommendations for e-commerce systems were going to be a really big market (hence the name “Recommind”) – it seemed like a lot less of a good idea to pursue that market.

What we did was drop a few different fishing poles into a few different ponds. These were all kinds of markets – anybody with a lot of text – you would expect might have a need for this kind of technology. In that area we saw who was most interested. The legal market was most interested at that time. This was in 2002. If you recall, Enron was collapsing, WorldCom was collapsing, etc. You could see that as data volumes were going to continue to rise, it was going to become more and more difficult to manage and analyze unstructured information because it was accumulating in an ad hoc fashion.

A lot of the strikes that were caused by the Enron and WorldCom knockdowns were a result of understanding what was inside of that unstructured information. There were big legal and regulatory implications to that, so we felt that the legal market was small and specialized enough that it could provide a place for us to grow without butting our heads against Microsoft every time we turned a corner. It was also big enough to provide decent growth for a small company. It was also not a dead end, though. It was a stepping stone toward a general corporate sphere as well, and we would provide an avenue into those corporations by addressing their legal and regulatory needs.

This segment is part 4 in the series : Thought Leaders in Big Data: Interview with Bob Tennant, CEO of Recommind
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