Omer Artun is the founder of AgilOne, a company which provides cloud-based predictive customer analytics. He studied at Brown University and holds a PhD in computational neuroscience/machine learning and physics. He previously worked for McKinsey & Company and for the marketing division of Best Buy. Seven years ago he decided to found his own company to apply his expertise to medium-sized businesses.
Sramana Mitra: Omer, let’s start with some context. Tell us a little bit about your company. How long has it been in business? I know you are moving from stealth mode to a more public launch, so please give us some context.
Omer Artun: I started the company about seven years ago. I bootstrapped it from no revenue to having about 40 employees when I received the first funding. I started the company out of firsthand frustration that I had as a marketer. I used to run marketing for a division of Best Buy – Best Buy for Business – and before that I was VP of marketing at Microwarehouse, which was a direct marketer of computers and related products. Before that I did strategic consultant for McKinsey, and I have a PhD in machine learning. When I was running these marketing departments, which had millions of customers, millions of transactions, and billions of clicks, there was so much information in this data which could be utilized [to make] better marketing decisions. From a span perspective, that means building a better relationship with a customer over time. You need both the data management skills, and you need the strategic skills to know what questions to ask in regard to the data. Then you also need the math skills to filter the noise out of the data. This is why I started the company seven years ago. At that time, there was no big talk about data, which is what I tried to do. Then demand for the company suddenly increased, so I moved the company to Silicon Valley to get it to a higher gross mode as well as to focus on software – to take all the services we had done with the domain expertise and IP, with all the algorithms and the machine learning we had, and turn it into software. We have mainly been focusing on that for approximately the past three years. This past year has been [one of] explosive growth in terms of both how we were getting into the market and how we are investing in the technology.
SM: Where were you located before? Was it in Minneapolis?
OA: No, we were located in Norwalk, Connecticut.
SM: You were obviously working on a big data solution. What is the primary source of the data? Are the clicks and the views on a website the primary source of the data you are manipulating?
OA: They are not. We get data across all of the touch points that the customer would make with the company. This involves all of the orders, returns, product information, customer information, clicks, and emails and catalogs the customer received, etc. What we capture and [put] into our system are all of the touch points which are centered on the customer. Clicks are a portion of it, but they don’t tell the whole story. We are getting offline transactions as well, we are getting emails, and we are getting direct mail catalogs which the customer receives. That is a small piece of the data.
On top of that, we also have our own internal sources that we can attend to in order to make it more useful for the marketer and the sales team. You might have a million customers in California. But then the question might be: “How many customers do we have in California with income of over $50,000 ?” Let’s say there are 10 million people like that. Then I know that your penetration in California is 10%. We have other information which the customer doesn’t see, so we bring it in to make it more actionable. Therefore our clients can start focusing on matters like customer penetration, which they weren’t able to do before.