As CEO of Cortera, Jim Swift’s, mission is to change the B2B information universe with long overdue insights into businesses to help organizations improve sales performance and risk management. Prior to Cortera, Jim was the COO of LexisNexis Risk Management and Executive Vice President at Seisint, which was acquired by LexisNexis.
Cortera is the go-to-source for Business Behavior Data and Insights designed to increase revenue, improve sales and marketing effectiveness, and reduce risk for business-to-business companies. In addition to monitoring investment activity, hiring, firing, news, blogs, social, public record data, Cortera tracks $1.6 trillion in business-to-business purchases across 45 spend categories to deliver insights on 20 million U.S. business locations.
MO: Can you elaborate on how you’ve managed to parlay your boyhood fascination with sports statistics into a successful career as a data geek?
Jim: Whether it was snowball fights, super pinky tournies, or games we invented using data on the back of baseball cards, I kept track of the stats: who had the most direct hits with snowballs, or who should be named super pinky MVP – and how many times he earned that title. So it’s not surprising that I earned the reputation as a stats freak. Soon all of the gifts under the Christmas tree were reflective of my obsession with stats, such as the Official Associated Press Sports Almanac, Golf Digest and, of course, more baseball cards. As a result, I developed a knack for identifying patterns in data. But instead of pursuing a degree in something theoretical, like economics, stats or computational mathematics, I opted for engineering because I wanted to build stuff – but with data, not steel. So early in my career, I helped many organizations re-structure their systems processing based on data flows. After all, the only reason why we have computers and information technology is to manage the flow of data – it’s the basis of all that we do. This eventually led me to database marketing in the consumer credit world where I became fascinated with what’s now known as “Big Data” – particularly behavioral data that is far more predictive than demographic data alone when it comes to marketing.
MO: Can you break down how Cortera helps companies leverage “Big Data” to understand business behavior to dramatically improve intimacy with their customers?
Jim: Business behavior insights help business-to-business companies not only foster stronger relationships with existing customers, but also help pinpoint sales prospects based on a behavioral profile of those existing customers.
Consider how the B2C world leverages behavior data: it helped Target learn that a teen was pregnant before her father did. Through market basket analysis, Target discovered the purchase of certain items together, such as extra large bags of cotton balls and scent-free soap, by women in a particular demographic were surefire indicators of pregnancy. In fact, based on what items are purchased, Target could estimate the delivery date. This teen’s purchase behavior and demographic profile triggered targeted marketing. As the story goes, when ads for baby-related items appeared in the family mailbox, the outraged father visited the local store to complain that this promoted early teen pregnancy. Wasn’t he shocked later to learn his daughter actually was pregnant!
Why don’t business-to-business companies have that kind of insight into their customers and prospects? Businesses, after all, like consumers, aren’t one-dimensional or static. They are constantly changing, evolving, dynamic – as reflected in their behavior and captured in the data. This is a founding principle for Cortera. As a result, our mission has been to collect richer data on companies than any other business information provider in the market. We track $1.7 trillion in spending by U.S. companies across 45 categories on an annual basis – this is purchase behavior, something that has never before been tracked on a granular level. We also bring in other behavioral data elements, including hiring, news events, investments, social sentiment and as well as the traditional demographic data, public record information, and others. Once a company sends us a file of their customer portfolio, we analyze their data as well as our database and use modeling techniques to define what equations, clusters and relationships best describe their customers. From this, we consistently monitor their behavior and deliver daily alerts of changes across multiple categories to help companies reduce risk, identify upsell opportunities and find new prospects. The latter is our most recent feature, called Lookalikes, an auto-generated list of prospect companies that look and act like a company’s existing customers.
MO: What are some ways that you can help enable finance and credit teams to minimize risk when it comes to examining a company’s financial health?
Jim: Payment behavior, the traditional basis for evaluating company financial health, is a lagging indicator of a company’s financial health. Credit and risk professionals have long relied on this information because it was the only data available.
Business behavior data provides much better insight into a company’s financial health and serves as a leading indicator. Thus, they can now accurately predict a company’s credit-worthiness and overall health. The decline of Mayville Products Corporation is a tale of two companies that aptly illustrates the difference between lagging indicators and leading indicators.
On January 20th of 2012, the Mayville Products Corporation of Mayville, Wisconsin, announced that it would close its factory doors at the end of March and lay off all 130 of its employees. For a year and a half prior to this announcement, two different sets of financial information revealed two dramatically different pictures of the company’s fortunes.
The company’s credit ratings had consistently portrayed solid credit-worthy performance for years. And nothing in the company’s public-facing information revealed anything alarming, which likely gave unsuspecting suppliers a false sense of confidence and led them to extend credit to Mayville.
However, there were several red flags that painted a different picture of the company’s rapid decline. First, a decline in materials spend: a sizable drop in materials purchases signaled a drop in manufacturing volume, due to declining orders and weak sales forecasts. Next, a decline in shipping spend logically follows a reduction in manufacturing output, weak sales – or both. Finally, a decline in operations spend – from paper clips to printer ink to computer maintenance – signals a slowing of business operations and an effort to conserve cash.
These leading indicators help credit and risk professionals better assess credit risk – but can also help sales and marketing professionals identify upsell opportunities within their own customer base.
MO: What are some trends in “Big Data” that you’re excited about?
Jim: As an engineer, I am most interested in practical applications of Big Data – or how the data can be harnessed to solve real problems. My top three:
1. New Ways to Predict and Measure Product Performance: Social media can track quality issues and satisfaction in real-time for the automobile industry – thus enhancing not only performance and the bottom line, but also road safety.
2. Supply Chain Management: Data can be used to significantly improve forecasting – which will then optimize the entire supply chain – from raw materials, supplier management to inventory optimization and on-time delivery of finished product. We may see a renaissance in American Manufacturing yet.
3. Anticipating Customer Needs: This is the promise of behavior-based data and customer marketing. B2C organizations can predict a customer’s wants and needs based on his or her behavior – think back to the Target example – and even more interesting is in the mobile app world and real-time location-based offers.
MO: What inspired the recent launch of Cortera Lookalikes? What kind of results have you seen so far?
Jim: B2C organizations have long leveraged behavioral data to market to an individual’s life events –leading to better qualifying of sales targets, enhanced customer intimacy as offers and messaging are extremely relevant, and significantly higher sales revenue. When a person buys a mini-van, it follows that the individual is probably in the market for a crib and diapers. Retailers now know who to target for which product and when to launch an offer – as illustrated in the Target example.
This is the basis of Lookalikes. Business-to-business companies have long used demographic data alone to find sales prospects. This may tell a marketer or sales person what a company is, but it does not reveal how a company behaves. If you’re in logistics and you could identify companies that were increasing their transportation spend, you’d have a highly qualified prospect – one that has a propensity to buy your services. Lookalikes first builds a behavior-based profile of your existing customers and uses that profile to identify targets – in our database of more than 20 million companies – that look and act like your current customers.
One client said that he was initially shocked by the list of Lookalikes that he received because it didn’t fit his prospect profile. But after looking into each prospect, he realized that he had been wrong in his original assessment; the lookalikes generated by Cortera were much better targets because they were based on an analysis of the behavior of his existing customers – something he’d been unable to do. His sales reps are now 6 times more efficient – and he’s closing new business much more quickly.
A leading 3PL reported 10% top line growth, a 100-to-1 return on investment and Lookalikes are now viewed as its “secret weapon” for unprecedented growth.
For a guy that wanted to build something out of data, this is very exciting: we’re building the ultimate business-to-business database in order to become the go-to-source for business behavior insights.