On the Internet today, there is a massive amount of information available on what consumers think and believe, from blogs, discussion forums, product review sites, and more. Santa Monica-based WiseWindow (www.wisewindow.com), a startup which has developed technology to track consumer opinions on the Internet, is looking to provide companies with a better understanding of those opinions. We spoke with serial entrepreneur and founder of WiseWindow, Rajiv Dulepet, about the company and its recent seed funding. Ben Kuo conducted the interview.
Tell me about what your company and technology is all about?
Rajiv Dulepet: WiseWindow is as our tagline says -- emerging wisdom on the fly. What that really means, is we crawl the internet for consumer opinions--product reviews, brand reviews, forums, messages, and blogs. We offer a consolidated feed of these opinions. At the same time, we believe these opinions are very subjective. The best way of explaining how this works is a scenario. Say, someone earning $1000 a month goes into Whole Foods -- their review of the store might say that this is an expensive, terrible place, because Safeway is ten times cheaper. On the other hand, you might have someone earning $100,000, they might think it's a great place, because it's got lots of organic food. One would give it five stars, the other one star. So if you just stick to one item, the star rating, it has no meaning. We think it's more important to look at what it is good for, and bad for. It's like a restaurant -- you may like one dish in a place, but maybe not like every dish in that restaurant. So we search for those opinions, and discover new facts about them and analyze scenarios. There are many applications of this, including in the consumer market, but our initial focus is on companies. We're looking at the corporate market, purely to make sure we have solid revenues and generate revenues rather than just looking for eyeballs. Companies can use this to slice and dice information to discover new facts, such as what someone thinks of a new product or brand. That brand can be a product, or it can even be a person. It can be Nike, or it can have anything that has a name to it. The difference between our solution and others, is that traditionally, these solutions just generate a report. We believe with ours that you can wake up in the middle of the night with a hypothesis, and can use this to dig through millions of things and get visualization of those opinions.
How did the company start, and what's your background?
Rajiv Dulepet: I cofounded and sold a Kleiner Perkins backed startup in 1999, in Silicon Valley. That company, Objectmart, was sold to ONI Systems in 1999. I had this vision, when I came here from India, was that I'd join a startup and retire by 30. Well, by 29 I was done with the startup, which I hadn't planned for. Prior to that, I had worked at Microsoft and Bell Labs. So I went through that, and was fascinated by the 2000 elections and was looking into polling, and wanted to get into research and applications in information retrieval and text mining. I ended up becoming a visiting scholar at Stanford, and was there for three years. During that time, one of the most interesting things I worked on was Stanford Predicts, a software application which created election predictions on behalf of Sanford. It predicted that President Bush would beat John Kerry, using 270 sources on the net gathering quantitative information, and gave the opinion that Bush was going to win, and got lots of hits. We had put that together really fast, with just a few hours of programming, and it's still up at Stanford. Then I started looking at applications like financial data mining, using databases to figure out who are the movers and shakers, and rather than looking purely at quarterly reports looking at discussion forums. I also read a book on the wisdom of crowds, where they talk about how crowds get things right something like 99 percent of the time, and experts only get it right about 65 percent of the time--and I thought there was some value to this opinion thing. The question was, how do I quantify qualitative information. We were initially looking at the consumer side, but we talked with Sid Mohasseb at Venture Farm who helped us bring direction and focus, and genesis of the current business.
How far along is your product, and how soon will people be able to use it?
Rajiv Dulepet: The product is pretty much ready right now. We received a seed investment from Venture Farm, though actually I did not actively pursue venture capital. You can visit wisewindow.com, and people can sign up for it and start using it as a beta user. We discover all kinds of information -- we're agnostic to domain--whether it's entertainment, or it's consumer products like the iPod, to hotels, to beauty products. The technology is pretty flexible, from that viewpoint. It's pretty ready, but you know how products are, they are never fully ready. The day you think they are done, it's the end of the road for you. But, it's done from the point of view that it's usable for a company.
Who specifically are your customers, and what kinds of companies are you starting to approach?
Rajiv Dulepet: Even during development, we talked to many big companies in the consumer products industry. We have a bunch of people we could actively partner with, this could be a great partnership with companies like Cognos and Business Objects, who have done quantitative data mining. This is qualitative, and augments what they do. Our approach has been to change the dynamics of the industry -- similar to how Microsoft, and Google have changed dynamics -- with our product pricing. We really believe in volume, and corporate-wide marketing. We're not interested specifically in the enterprise, we believe this can be used corporate wide. Technology is one industry we're going after, but we also believe design firms could use this to innovate. To give you an example, a beauty care company could look at something like menopause, and figure out a link between shampoo and menopause, and discovery a new market by doing crossover analysis. There are lots of interesting applications.
We've run into a number of firms in this field who have started doing similar things, how are you different?
Rajiv Dulepet: Generally, everyone has their own angle, and we have a lot of respect for our competition, in general. The paradigm shift is the way we're thinking of stuff. The big difference from lots of these companies, is they are very, very aligned with facts and creating excellent reports, and are always a combination of technology and consulting. They do a great job at what they do. But our model is simple, we believe that the technology we have is not offering you an opinion, but allows you to make the decision. All I know is that I'm enabling you to cut through information very easily, and allow you to make decisions.
What's next for the company?
Rajiv Dulepet: There are a couple of things. Until now, we haven't approached the next round of funding. We intend to go for a Series A funding. We're also looking for relationships with customers. With development, it's always constant, but the product is very firm. So we're very active with sales and active on our next round. We're also looking for a CEO with a consumer marketing background.