News Byte: New Lattice App Brings PA to Lead Scoring

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Lattice: PA leads to solid leads.
Lattice: PA leads to solid leads.

Lattice Engines today introduced Lattice Predictive Lead Scoring, an application it says uses predictive analytics to answer B2B marketers' most overwhelming question: What's the definition of a good lead?

By combining data already tracked in marketing automation and CRM systems with input from the Web and social channels, says the company, Lattice Predictive Lead Scoring pinpoints the purchase-enhancing qualities of a lead. These are consolidated and run through a predictive analytics program that passes the most sales-ready leads to CRM.

“Approximately 75 percent of lead models are not data-driven. Instead, they are based on the feelings and beliefs of marketing and sales about lead quality," said Lattice client Jay Famico of SiriusDecisions in a statement announcing the new application. “The use of statistical techniques increases precision and decreases the number of leads that are false-positive or false-negative. This increases sales-accepted lead rates, improves sales effectiveness, and better aligns sales and marketing."

In assessing the need for PA in lead scoring, Lattice quoted a study from Decision Tree Labs that said marketers gave an average score of only 5 out of 10 to current lead scoring programs. The top two deficiencies named: little confidence in the accuracy of data and lack of insight into what constitutes actual buying behavior.

“Lead scoring is the next frontier for predictive analytics in marketing,” says Lattice CEO Shashi Upadhyay. “Now companies can benefit from applying science to the universe of prospect and customer knowledge to predict and close their best leads."

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