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Lattice Engines Applies Predictive Technology to Upsells and Retention
Users can deploy predictive technology across the customer life cycle.
Posted May 23, 2014
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Lattice Engines has extended its technology to customer retention and upsells. The company pulls more than 1,000 different attributes of public and private data together, then finds out which attributes are "trigger events" for each company that might indicate an opportunity for an upsell or cross-sell, such as a move, hiring, acquisition, or change in their credit rating.

Lattice Engines has long applied this technology to finding and acquiring customers, but it hadn't yet upgraded its product to analyze information of existing customers for retention information and upsells.

"People are not spending enough in marketing and sales on customer retention and selling to their customers," explains Brian Kardon, chief marketing officer at Lattice Engines. He cites a recent global survey by McKinsey, which found that companies spend just 12 percent on retention. While existing customers can be a great source of additional revenue, "companies never had a tool to hang on to existing customers," he says. "We think this is an area that has been overlooked."

With these extensions of Lattice playMAKER, companies can also move from predictive to prescriptive analytics. Kardon offers the example of Staples, which has 1,000 inside salespeople who call small businesses asking if they need anything. With Lattice, they can recommend a paper order if it's been 180 days since the last order instead of 120, or suggest new office chairs and desks if Lattice has observed that the company has been posting jobs and it will likely have new hires. It can also figure out what kind of products would be appropriate for a specific type of small businesses, such as a delicatessen.

Kardon estimates that market penetration of predictive technologies like Lattice's are currently at just 5 percent. Marketing automation, in contrast, has about 60 percent market penetration. Lattice Engines' algorithms include information from CRM and marketing automation systems, which it marries with other sources of data.

Lattice Engines' current client roster is heavy with tech companies, including Dropbox, Concur, McAfee, EMC, HP, DocuSign, and Juniper Networks, though Kardon notes there are nontech companies as well, such as Bank of America and Staples. "Tech companies are the early adopters. They were the early adopters of Google AdWords, of social, of mobile," he observes. "Marketing was in the arts and crafts department twenty years ago, and now it's moved to left-brain analytics. What's going on is emblematic of that change."

Lattice Engines has 100 customers and 50,000 users globally. It started out as a consulting firm, but four years ago switched to creating the software-as-a-service, cloud-based product it has today when it saw the need among smaller clients who couldn't afford to have a data scientist in house. Lattice Engines is a "data scientist in a box," Kardon quips. "What Lattice is doing is democratizing predictive analytics, and making it available for everyone."


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