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Using Predictive Modeling To Boost Conversions

MarketoSummit 2014CA Technologies’ marketing department was generating a steady flow of leads through a variety campaigns, so volume wasn’t a top concern. However, the management software and solutions firm wanted to get better at identifying which of those leads would most likely convert to sales.

To accomplish that goal, Beki Scarbrough, Senior Director of Demand Generation, told an audience at the recent 2014 Marketing Nation Summit that her team decided to look beyond the standard sales funnel. “It is important to recognize that there are leads, names and contacts completely outside of the funnel. That’s where you need to go.”

For the past year, CA has been using a combination of technology to do just that, including Marketo, Salesforce and Lattice Engines. The result so far has been a 400% lift in MQL to SRL conversion rate.

According to SiriusDecisions, 94% of MQLs will never close and more than half of sales reps are failing to meet quota, according to CSO Insights, noted Brian Kardon, CMO of  Lattice. “As marketers, our job is to improve lead flow and drive demand to grow revenue. We have all been part of a transition from the arts and crafts marketing to modern marketing and beyond.”

The mindset has to change from looking leads that meet a certain criteria to looking for prospects that match the profile of your most successful customer engagements, Scarbrough said.  An ideal lead may have downloaded a whitepaper or a trial but an ideal customer recently hired a new CIO and is growing. “Get sales to describe the perfect customer to you. Trust the guys who do this every day.”

Using Lattice’s predicting lead scoring, CA is now funneling leads to sales that have a 30% to 40% chance of closing.

Continuous feedback helps to improve the predictive lead scoring model, Scarbrough said. “It’s predictive lead scoring, not psychic lead scoring. Keep the feedback loop going and you’ll continue to get closer to the perfect lead.”

Predictive lead scoring continues to improve as companies make better use of the data they have about their customers and prospects, said Kardon. He explained that most companies have access to a small percentage of the available data about their customers and prospects. “Your purchasing history is just 1% of what Amazon knows about you.”