Lattice Engines has announced the introduction of Lattice Predictive Lead Scoring, designed to bring together first-party data about the customer from a company's CRM system and information about a lead from the Lattice Data Cloud to allow marketers to grade leads. The announcement was made at Oracle's Eloqua Experience in California today.
With Lattice Predictive Lead Scoring, marketers will be able to pass on leads to sales teams, identify leads that may need further nurturing, and know which leads are the least valuable. The Predictive Lead Scoring tool will show the top factors contributing to scoring, making the process more transparent for marketers.
Lattice Engines wanted to "answer the questions sales and marketing executive obsess over, [like] who is most likely to be going to be a customer tomorrow, who has a need today, or who is most likely to leave," explains Shashi Upadhyay, CEO of Lattice Engines. Customers have already implemented the beta version of Predictive Lead Scoring; it will be available widely this quarter.
Predictive Lead Scoring makes heavy use of the Lattice Data Cloud, which uses third-party information that can predict a customer's propensity to buy, including everything from job postings to a company opening a new regional office. While the leading predictors vary across sectors, Upadhyay says, citing a less intuitive example, "we found that companies that provide 401(k) coverage to employees tend to spend more on technology than others. Very often for technology companies, it ends up being a good predictor of purchase." If a company deploys one cloud technology, it is more likely to follow with additional software as a service products in the near future.
Lattice uses the service itself to identify potential new customers. It knows to target companies with mature CRM and marketing automation systems, and look for transitions in chief sales officers.
Lead scoring is still not widely used among businesses, with many products judged to be ineffective by marketers. According to a survey of 250 marketers by Decision Tree Labs, just 44 percent currently use lead scoring, with another 16 percent planning to implement a lead scoring tool in the next year. Among marketers that currently use lead scoring, many expressed skepticism and dissatisfaction with their current product. They graded their programs an average of five out of ten for effectiveness. The leading issues were inconsistent or incomplete data on their prospects (59 percent) and an inability to find correlations between prospect attributes and buying behavior (43 percent). Despite these issues, the projections of fast growth indicate many realize the value in high-quality lead scoring.
"Marketers are moving from being gut feeling-based to data scientist-based," Upadhyay says, positioning Lattice Predictive Lead Scoring as a way to qualify leads not through a salesperson's small existing window of knowledge but by utilizing a larger cloud that can identify important changes. Predictive Lead Scoring will help limit the number of leads marketers pass on to salespeople, and improve their quality. It also speaks to "the convergence of sales and marketing, as their goals align," Upadhyay concludes.