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Rising investor Brian Ascher is gunning for startups in social search and data analysis.
Entrepreneurs in the social and real-time data sectors would do well to study up on Venrock’s Brian Ascher. At the spritely age of 43 with several big tech exits under his belt (Adify, DatAllegro, Unicru), the investor is bound to be a force in the global Silicon Valley for a while to come.
He’s interested in startups that follow what he calls the "data-as-a-service" model: gather tons of data by offering some service or tapping into a data pipeline, create an algorithm that you refine over time, and sell intelligence to clients on an ongoing basis. He sees big opportunities in social search and services that help consumers make fuzzy, subjective kinds of decisions--what movies to watch and where to go on vacation--areas where social graphs are particularly valuable.
Ascher’s driven to boost personal empowerment, wring out inefficiencies and help smaller independents entities take back Main Street from the Big Boys. Below is Part 2 of our interview with him. Click here for Part 1, in which he gives advice for entrepreneurs and investors navigating the tech markets in 2010.
The Data-as-a-Service Model
MB: You mentioned that there are big opportunities in collecting hoards of data and turning that into marketable value.
BA: This notion of data-as-a-service, collecting data as part of some other workflow and applying intelligent algorithms and selling access to that insight is a great business model. In fact, it’s kind of what underlies Google’s success. They’ve seen so many more searches than others that their algorithms can be better tuned to provide better search results, but also on the AdWords side, they see what advertising gets response rates, so they’re just going to perform better. When you can do that based on free data, it’s tremendously powerful, and the thing is, the next guy can’t catch you. Someone can always write the same lines of code, but if they haven’t had the experience of processing terabytes and terabytes of data, they’re just not as smart as you.
A couple of examples from our portfolio: one is Inrix, which is a leading independent provider of automotive traffic data, taking GPS coordinates from fleets and cell phones and converting that into real-time traffic data to show you how traffic is flowing not just on the major highways and major incidents—a tractor-trailer jackknifing—but on secondary and tertiary roads in smaller cities and towns. That’s the kind of business where more data is always better, and as long as you have more data than the next guy, they can’t possibly catch you.
MB: How does Inrix get its data? Do users sign up for it?
BA: No, Inrix sells on an OEM basis to car companies, to mobile operators to handset guys, to personal navigation device folk, to departments of transportation, etc.
MB: Are there other companies with this kind of model?
BA: I’m on the board of a company, Retail Solutions which gets point-of-sale data from the retailers, analyze it, apply intelligent algorithms to it, and sell that to the consumer products companies and all the vendors who supply the retailers with a product, and this data, when analyzed by Retail Solutions is extremely valuable for things like on-shelf availability. One of the worst things for a retailer and their vendors is when a consumer goes to a store because he saw a promotion and the item is out of stock.
A lot of times, these problems are pernicious in that a system in the retailer says there are two units on the shelf but the shelf is bare, and it won’t reorder for weeks sometimes because the old systems say don’t re-order if there are units on the shelf. But it’s phantom inventory and sometimes even the managers know that but they’re reluctant to report it because the get dinged for shrinkage. Retail Solutions has algorithms that can very intelligently say, “You are out of stock,” or “You’re about to be out of stock, you need to re-order.”
So they get reams and reams of data in real-time on individual products in individual stores and they can make all sorts of intelligent alerts and decisions.
Another thing they do is design for promotions. Promotional effectiveness is a big deal when a vendor goes through the bother and expense to create all this in-store signage and end caps, etc, and the problem is a lot of stores don’t do it right; they don’t display it on the end cap, or they take the product and they stuff it in the shelf instead of in the promotional vehicle, etc.
Retail Solutions’ goal is to take the best practices of the best-performing stores and replicate that everywhere, so headquarters has visibility into how all the stores are actually doing versus just what they think is going on in the field.
MB: So we’ve got traffic, retail sales… are there other applications where you’d be interested if an entrepreneur came to you and said, “I want to be the brains behind THIS kind of data”?
BA: Absolutely. There’s stuff in financial services (you mentioned Mint earlier), anything that has dynamic pricing—travel is an area.
The beauty about this is if you’re a SaaS company and you have a lot of great features, eventually someone can match your features, but if you have a head-start and you process more data, it’s so hard for someone to catch you.
Making Social Make Sense
MB: You also mentioned you're interested in real-time and social technologies…
BA: One of the most interesting opportunities is Social Search—the notion that when I have any need for information and I conduct a query, I’m going to get results filtered based on my social network or graph. It could be a tweet that you posted last week or a review you made on Amazon, or a rating you gave a film on Netflix. If I’m doing a search for hotels in Maui, your Flickr photo from your vacation to Maui a year ago is relevant to me. The hard part is how to match all that content that all my friends have created out their with their individual persona (because we have different log-in names with all of our different accounts that are semi-anonymous or completely anonymous) and how do you know what that graph is so that I, when I go to this mythical search engine, don’t have to tell it who all my friends are. It will just know because all those relationships are out there on the web.
So that’s a tremendously powerful opportunity. I think Facebook’s actually in the best position to capitalize on it, especially with Facebook connect, but I think there are opportunities for independent companies to chip away at the problem.
MB: This seems like a dangerous play because a Google or Microsoft, have already done deals with Facebook and Twitter to begin to solve this problem. So what are some of those areas where other companies can chip away?
BA: I’ve always been interested in things that we research that have some subjectivity to them. Let’s contrast making a decision on a new digital camera versus a restaurant or place to go on holiday. I think Amazon does a pretty darn good job giving you a sense of features of best-selling digital cameras. It’s fairly quantitative and metrics-driven, but choosing a hotel is very subjective, and that’s where you really have an advantage knowing friends whose tastes and opinions you’ve calibrated somewhat and getting their advice. They know you and they can kind of guide you.
An area like travel, restaurants, even choosing a college these are subjective decisions that I think could benefit from a social layer on top. How you grab and federate all the information that’s already been produced by your graph is the hard part.
MB: One last question: as an investor, most of your decisions, I imagine, are maximizing value, but you’re also making decision that are shaping how society interacts, their health, how people do business in the future. What are some of the values that drive your decisions? What kind of a future would you like to lead us into?
BA: I think a lot of this comes down to personal empowerment. Giving people the information to make decisions and take actions that puts them more in control. That’s kind of a unifying theme of a lot of what is powerful about the Web and other forms of technology—the democratization of decision-making and leveling the playing field.
Also, being the Type-A person that I am, wringing out inefficiencies from systems so that things run smoothly, and what you expect to happen happens.
MB: Personal empowerment—that certainly resonates with our national heritage championing the individual. But we’re also interdependent. Is there a danger of holding up a vision of man that is TOO independent—too much ‘superman’?
BA: Well, I don’t mean “personal isolationist.” Let me give you an example. I bemoan the homogenization of society—a Starbucks on every street corner is a shame to me. I find services like Twitter and Yelp sort of give back to the individual proprietor and individual consumer to reward excellence, so if that independent coffee shop, that owner gets to know their clientele and produces great coffee, they can beat Starbucks, and they will be rewarded, because they will get better reviews on Yelp, and they’re following can spread through all the great social media tools. That’s the kind of personal empowerment that maybe wasn’t there ten years ago when the Big Box concept started to push all the independents off Main Street.
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