Ben Lewinsky, Director of Sales Operations at Culture Amp, is no stranger to using data in creative ways to solve a problem. In his previous role at Falcon.io, he created a sales engine by using third-party intent data to gather information on prospective buyers. “We were pounding the Facebook API, because our TAM (total accessible market) was anybody who needed a social media marketing tool, and the Facebook API gave us information about how they were using a tool, and when they were posting,” says Ben. “That was a pretty clear aid that we could qualify that they needed a tool.”

He used the BANT (budget, authority, timing, and need) model for sales qualification. “We knew that they had budget for the tool, because they were using it; we knew that they had the need, and we knew about the timing,” Ben explains. “The only job left was to find the person with the authority and send them a pretty compelling message…and the message could be really personalized because we knew what tool they were using.

“I think the underlying story is, find a unique data point that will help you sell and market to these people better,” says Ben.

Lead scoring in a multi-product world

Since joining Culture Amp, Ben has faced the challenge of measuring buyer intent across a multi-product offering. “We started off as an employee engagement software,” says Ben, and back then, they had a standard lead scoring process. “It didn’t need to be multifaceted,” Ben recalls. “It didn’t need to think about multiple personas or multiple problems.

“As we've gotten bigger and bigger, we've made new products, new modules, and what that means is that people are coming to our website for different problems….they interact with us in different ways and with different parts of our website, online and offline.”

Operationalizing the data

With a multi-product offering came the need to organize and operationalize lots of types of data. Ben had to think strategically about the interactions people were having with the brand and how he could summarize a collective set of actions that indicated someone had interest in a product. “We now have all these different suites of products, so how do we find those who are engaging with content and assets on our website that align with our other product suites they might not have bought yet?”

Signals of intent include visits to blog pages, attendance to webinars or trade shows, filling out a form, chatting to a chatbot, downloading an ebook, etc., and every event has a product or theme associated with it. “All of these things are just events – Person A doing this thing on this day,” says Ben. “And as long as you have that additional bit of metadata around the topic (product theme), you can start aggregating and rolling that up onto a person in terms of their product interests.”

With this insight, SDRs can go into sales conversations with a great deal of context, resulting in more meaningful interactions and better outcomes.

Retargeting unknown users

Ben offers sage advice about making the most of unknown website users. “The biggest thing to tap into is unknown users,” says Ben. “You’ve got hundreds of thousands of people visiting your website and you don’t know who they are, but if you are at least able to easily aggregate what they did in that session when they came, you can have a more compelling offer when you retarget them and try to get them back into your funnel.”

Throughout his experience, Ben has learned a key lesson: “Don’t get too hooked on these growth ideas and these growth hacks because you’ll become too dependent and they don’t always last.” Instead, Ben recommends finding out people’s pain points, putting a data-driven idea in motion (even if it’s scrappy), and making it work.

“Be relevant. You know you're taking up somebody's time, so make sure you shoot your shot properly.”