Recently, the financial salespeople at Lord Abbett Investments were struggling to make sense of the fire hose of customer and market information coming at them. The result was that when the investment firm’s salesforce reached out to financial advisors in independent firms, insurance companies and banks, they had no consistent way of identifying the best product to pitch — or, even more important, predicting which would sell. The result was a sales process that was to some degree a hit-or-miss proposition.
“There’s no human being who could keep up with all that information by themselves,” says Mario Barbato, Abbett’s Director of Client Information Services.
But then Barbato found a kindred spirit in Vibhu Walia, a Director at the Dynamic Science Labs of business software maker Infor. Walia, who has a master’s in computer science and runs a data analytics team, shared Barbato’s interest with understanding how customers make decisions. “We wanted to know not only what happened,” said Vibhu, “but why it happened, what’s going to happen and what you should do about it”
With Infor’s DSL and Walia, Barbato found a unique approach that applies data science to practical customer concerns. The outcome is predictive software that helps companies to make better decisions that improve their performance. In the sharp-elbowed world of business software, the capability is also a competitive weapon for the New York-based company.
For Lord Abbett, the specific solution is a custom software dashboard developed together with the lab. It presents a wealth of customer data in an easily readable format — displaying contact information, past purchases and the like. But unlike similar systems it is also a prediction engine.
Based on an analysis of Lord Abbett’s own customer data — plus an aggregation of industry information, outside trends and market changes — the system gives Lord Abbett’s salespeople an edge. It tells them what similar customers are buying now, much like Amazon.com does with consumer products at the bottom of its web pages. And it looks at patterns — where one investment typically leads to others. The outcome is that salespeople now have a better idea of what a client is likely to buy next.
Today, Lord Abbett’s salespeople needn’t fish for hints, walk through general questions or make pleasant conversation. They know — before they start talking –what customers are likely to be looking for and how to turn the call into a vehicle for building relationships. Equally important, since only 20% of a salesperson’s daily calls are answered right away, the system helps them frame effective follow-up emails and voice messages — generating more call-backs.
Barbato was also attracted to Infor because Walia shared a genuine desire to collaborate. Other venders started with their solutions first and seemed to put Lord Abbett’s needs second.
“They wanted to sell us software, they didn’t want to talk about the data,” said Barbato. “Infor actually wanted to hear our story — and when I got up off the floor — they came down to our office and listened for hours,” he added. “They worked with us before we ever had a conversation about contracts and pricing.”
Lord Abbett’s software dashboard identifies buying patterns and tells its salespeople what similar customers are buying now, much like Amazon.com does with consumer products at the bottom of its web pages.
While it’s still too early to share quantifiable results, Barbato is satisfied with the progress to date. What’s more, his salespeople are convinced the model is a substantial improvement.
What started as a pilot has evolved into a growing relationship. Now Lord Abbett is ready to move forward with Infor and is looking to turn their proof of concept into a working product.
“The pilot proved to us what we needed to know,” he says. “Now our people know there’s a science behind it.”
