Thought Leaders in Artificial Intelligence: Gabe Larsen, VP of InsideSales Labs (Part 2)

Sramana Mitra: I’m going to probe deeper. You’re saying that all the touch points are being captured. Are you recording the phone calls and doing speech-to-text? What is the level of capturing of the engagement?

Gabe Larsen: We do actually record phone calls. It gets interesting, especially here in the States. You have to consider the legalities. We haven’t gone as far down in analyzing the recordings. I’m going to focus on the three main pillars. Let’s start with the phone, email, and account prioritization. Those would be the three areas we’ve probably gone the deepest on.

What can you capture on the phone call? Length of call, time the call was made, what happened in the phone call. You jump over to email. Did they download something in the email. Did they click-through? What happened on your website? I’m throwing out a couple of things. There’s a double-click on the phone in an email. We still found that those are two of the predominantly used communication tools in sales prospecting.

The third pillar is the entity that you begin to engage with. Who on the other side are you dealing with? Let’s talk about level and company size and how that fits into the communication methods. Is this the optimal buyer profile? The deeper we can go into figuring out the DNA of what great accounts look like and then we bring in the phone and email.

We don’t typically want to be calling people who could never buy from us because our price point is 10 times what they can afford. We don’t want to be calling the wrong person. In InsideSales, we typically work with sales leaders and sales operations leaders. It would be weird for us to be calling HR. Optimizing the who and the how is where we want to go deep.

Sramana Mitra: Some of it is engagement analysis, but there is also all kinds of data related to the target audience of the product and how this particular prospect fits in that. What length do you go to in that profiling?

Gabe Larsen: It gets to be pretty fun in the data area. I’d probably label it into three categories. One is descriptive data. That’s going to be who are the prospects and what characteristics do they have. We talked a little bit about that. The other then starts to feed into some of this activity data.

What actions have been taken against that? It’s not just about who. It’s also about what’s working. We also pull in some fun stuff around contextual data. People sometimes raise their eyebrows a little bit but there’re some prevailing conditions at any given time that a company is involved in that can actually affect buying behavior. Even the weather affects how people pick up the phone. That’s something that would also be in there.

Results data is certainly very important. I get that I called them, but how long was that conversation? What happened? The secret sauce for us is what we basically refer to as the cross-company data. This is one of big differentiators of InsideSales.

I like to draw the analogy to Amazon. If you’ve ever purchased something on Amazon, you probably fell for their recommendation engine. There are some really interesting things that feed into that. A lot of it is what you’ve done in the past. That’s certainly very important, but a lot of it is how people like you purchased.

This segment is part 2 in the series : Thought Leaders in Artificial Intelligence: Gabe Larsen, VP of InsideSales Labs
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