The science of predictive analysis is a burgeoning one as companies take on more and more data daily. Versium takes billions of data points from businesses and consumers and makes sense of them to monitor purchase interest, social behavior and financial information–to name a few. We caught up with Chris Matty, CEO of Versium, to get the details. insideBIGDATA: I understand that Versium is a data analytics company. What services do you offer?

1. Versium: Predictive Analysis for Actionable
Consumer Intelligence
The science of predictive analysis is a burgeoning one as companies take on more and
more data daily. Versium[1] takes billions of data points from businesses and consumers
and makes sense of them to monitor purchase interest, social behavior and financial
information–to name a few. We caught up with Chris Matty, CEO of Versium, to get the
details.
insideBIGDATA: I understand that Versium is a data analytics company. What services do
you offer?
Chris Matty: Versium is a data technology company that operates a LifeData™
predictive analytics scoring solution that produces predictive scores. These
technologies enable organizations to be more data-driven by powering solutions that
help optimize consumer engagement, im
[2]prove marketing
efficiencies and better understand, retain and find new customers. Versium brings
together disparate sets of observational data, comprised of over 300 billion real-life
behavioral attributes. These insights are combined with an organization’s existing
enterprise data to provide more actionable consumer intelligence and delivery of
predictive scores that address ROI driven specific business cases.
insideBIGDATA: And at whom is this technology aimed?
Chris Matty: Examples of organizations that can leverage real-life analytics to better

2. understand their customers and predict behavior include:
Corporate marketing departments that wish to enhance their insights on existing
consumers and prospects
Online publishers or ad networks looking to improve their targeting algorithms to
generate higher CPMs.
Outbound marketing organizations who either sell contact lists or provide
outbound contact services can garner finely targeted lists, and generate higher ROI
for its customers.
Finally, consumer research companies who are looking to augment the surveydriven insights they provide to their clients.
insideBIGDATA: How do you use behavioral data along with an enterprise’s existing data
to predict fraud?
Chris Matty: The proprietary LifeData platform is a compilation of information created
by individuals as they interact in the real world, which companies typically have been
unable to capture until now. Versium’s analytics platform combines a company’s
proprietary enterprise data with LifeData to provide richer insights into behavior, and
enable more accurate statistical and predictive models. The system outputs various
predictive scores (similar to a credit score, but for marketing purposes) based on a
desired business case and underlying ROI objective. LifeData insights and predictive
scores can be accesses via real-time API query, or batch process, so that these insights
can be built into existing enterprise applications (i.e. CRM solutions and marketing
automation tools) to enable rapid access and use without the need for platform
deployment and support.
insideBIGDATA: How does this technology help an organization optimize consumer
engagement?
Chris Matty: Our customers love the concept of predictive scores – they are accurate,
easy to access and you don’t have to be a data scientist to interpret them. Enterprises
don’t want another complex platform that requires support and training – they just
want the answers to the questions that deliver ROI benefit and that’s exactly what a
predictive score does. When it comes down to it, the numbers don’t lie. Being armed
with this level of actionable intelligence provides companies with specific data to
better maximize profits, mitigate risks and optimize consumer targeting, a significant
competitive advantage.

3. insideBIGDATA: Can you see more uses for the underlying technology here–outside of
fraud detection?
Chris Matty: Yes, we have a whole suite of predictive scores including:
Churn Score: Identify which customers are most likely to cancel memberships.
Shopper Score: Identify full price buyers versus discount shoppers, and gain insights
into which customers or prospects will respond to specific offers.
Social Influencer Score: Optimize social campaigns and recognize which customers
or prospects are the most socially influential.
Fan Score: Understand which customers are of the greatest value to an organization.
Other scores in development include: Wealth Score, Donor Score and Green Score.
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1. http://versium.com/
2. http://i-com.typepad.com/.a/6a00e54fc0548f8834019aff6d4cd2970d-pi