Startup Spotlight: InfoSpace co-founders lead marketing analytics startup Versium
Two decades in the big data and analytics space revealed a problem that Versium co-founders Chris Matty and Kevin Marcus believed they could solve. They observed the huge volume of data generated by businesses and watched them struggle to make actionable sense of it.
In 2012, they decided to build a solution. They created a suite of tools to help marketers make sense of data — both internal and external.
“The amount of data generated by businesses, as well as consumers, is just incredible – especially when you consider the rise of mobile, social, interactive websites, government third-party data and other sources,” said Marcus. “Companies are just sitting on these enormous piles of data, but they’re unsure how to derive actionable intelligence from it in a timely manner. This presents a need for solutions like Versium’s that provide actionable data intelligence (in the form of a predictive score) faster, more accurately, and at a fraction of the cost of traditional predictive analytic solutions.”
The startup raised $ 1.7 million in funding earlier this year on top of a $ 2.5 million round in 2013.
Before launching Redmond-based Versium, Marcus and Matty helped found several startups, including InfoSpace. We caught up with Marcus, who serves as Versium CTO, for this Startup Spotlight. Continue reading for his answers to our questionnaire.
Explain what you do so our parents can understand it: “Versium delivers a suite of automated predictive marketing solutions to help marketers identify the best prospects and customers.”
Inspiration hit us when: “The field of statistics and modeling has been around for decades, but in recent years new technological advances have made it possible to leverage data and apply it to new sets of problems. However, as the big data wave hit we realized that there aren’t enough available data scientists to meet the demands of businesses seeking data analytics services. We knew there must be a better solution – so we came up with the idea to produce predictive scores, in an easy, automated and intuitive platform that anyone can use. We wrapped up all the data science, technology and components and into an easy-to-understand score that helps marketers quickly understand their prospects.”
VC, Angel or Bootstrap: “We were fortunate enough to self-fund for the first 18 months. At that point, we realized that there were some big opportunities that we risked missing out on if didn’t accelerate with outside capital so we began exploring our options. We raised $ 2.5 million pseudo-series A with a small group of angel investors in September 2013, and we recently raised another $ 1.7 million in 2016.”
Our ‘secret sauce’ is: “We have three secret sauces: First, our LifeData data warehouse contains over 1 trillion attributes on consumers, businesses, locations and assets that are not generally available in the marketplace. We consistently update the warehouse with fresh data so it’s comprehensive and accurate. Second, we developed an automated matching solution based on machine learning technology that enables us to determine — in real time — how individuals, businesses, assets, and locations are related. Our data warehouse and matching service work in tandem to deliver the third sauce: predictive scores. Our scores function like a credit score to help marketers quickly understand which prospects are most likely to convert.”
The smartest move we’ve made so far: “Our smartest move so far has been focusing on our REST-based API. A simple request/response API is the most effective way to integrate into a business workflow. Wrapping up our unique data, matching solution, and scoring system into a single call has proven to be a powerful and flexible way to enable businesses to integrate our services. We also power some of our own applications with the same API that our customers use.”
The biggest mistake we’ve made so far: “Early on, we brought someone onto the team because ‘the price was right.’ Unfortunately, it didn’t work out and ended up costing a lot more to fix the problems that were created.”
Would you rather have Gates, Zuckerberg or Bezos in your corner: “Bezos for sure. He doesn’t seek publicity for himself, and he carefully calculates his moves so when he makes them he knows he’s going to win. Also, he likes outer space (as evidenced by Blue Origin), so we’d get along outside the office too.”
Our favorite team-building activity is: “Company-wide pizza Fridays.”
The biggest thing we look for when hiring is: “We look for people who would fit in with our team dynamic while bringing new skills to the table. Our ideal candidate is a creative problem solver who looks at situations from a fresh perspective. We also value candidates who can take a complicated subject like data analytics and make it easily understandable for someone who isn’t familiar with the topic.”
What’s the one piece of advice you’d give to other entrepreneurs just starting out: “Find people and partners with skills that complement your own to make sure you’re laying a robust foundation. Every deal should improve your platform a little bit.”
