Data is essential to any growth strategy. When it comes to product-led growth (PLG), it’s about real-time data or, at the very least, ‘just-in-time’ data. “I think the biggest learning for me at DocSend was that data does matter,” says Alex Poulos, CMO at Crossbeam and former CRO at MadKudu, CMO at DocSend, CMO at Chartio, and VP Marketing and Customer Success at Support.com. “It does matter how you organize your data, how you provide access to data, and how quickly you can make decisions based on data.”
Alex has seen a shift in the way companies use data and notes its absolute importance when it comes to growth. “I like to say that the data stack is the new tech stack. Ten years ago, we were asking, ‘What’s your tech stack? What tools do you have?’ I think today we are asking, ‘What’s your data stack? How do you bring data together? What’s your data strategy?’”
Despite the importance of using data to gain insights, there is a data gap that inhibits some companies from reaching their full potential. “Often, for a go-to-market team to get access to data they must file a ticket to a data scientist team or a data engineer team, and then wait for two weeks to get a report or an insight or a chart, but by then the moment has passed,” explains Alex. “I would like to see more go-to-market teams owning their access to data and their decisions based on data.”
Using data to build personalized product-led tracks for customers
The first challenge Alex faced was unlocking and operationalizing the data. “We dealt with zero-party data, so every user who signed up for the product had to share some information with us – most importantly, their use case,” explains Alex. “Then we had first-party data, so product telemetry and the data we collect. And then we had second-party data from G2 and other web properties.”
Once the data was unlocked, Alex had to personalize that data to drive monetization, and a big lesson he learned was to separate the funnel. “My first challenge was when I realized that we were actually running a bifurcated funnel,” says Alex. “We had a self-serve funnel where users wanted to go through the product by themselves, try it out to realize the value, and then check out with a credit card by themselves. And then we had users that wanted to talk to someone in sales or someone in customer success. Maybe they had some questions, and they really wanted that human touch.”
Through this process, Alex gleaned some surprising insights. “The big learning for me was that not only did we have to put the user in the right funnel, but sometimes putting a user in their own funnel actually had a negative consequence when it came to them converting,” he explains. “For example, a lot of founders use DocSend to set up fundraising materials, and founders are legendary for not wanting to talk to sales. So, if the first thing that happened after they signed up for the product was a salesperson contacting them, that definitely didn't help. Founders wanted to sort things out by themselves and convert when they were ready.”
Predicting the likelihood of conversions with data
Using demographic and firmographic data, Alex was able to infer the probability of whether a person would convert. “We built two predictive models, one for self-serve and one we call sales-assist for enterprises, and we had a good understanding of how the experiences of the two funnels were completely different,” Alex says. “We deployed programmatic marketing tracks for self-serve, and for sales-assist, and we wanted to make sure that those users had access to our sales team.”
Alex explains how he used Intercom and HubSpot to facilitate the funnels, both inside and outside of the product. “We focused on product behaviors in Intercom – if you haven’t done something that we wanted you to, we had this in our product to go and do it,” says Alex. “What we did with HubSpot outside the product was focus on how to provide value for a use case. Fundraising is one of our use cases, so we shared a lot of information to HubSpot, like what a pitch deck should look like, or how long it should take to solicit VCs. So there was a lot of value not specific to the product, but around the use case – and this was personalized.”
Building hyper-personalized experiences
For Alex, it was important that personalization went beyond the email and Intercom tracks, but was incorporated in how they started conversations with leads.
“Our website was personalized, so knowing what [the customer’s] use case was and knowing whether they wanted a trial with us made the website experience very different,” says Alex. “And this is where Mutiny came in – it allowed us to personalize the website. So, say you’ve already had a trial with us, I’m not going to offer you a ‘Start a trial’ CTA, but I’m going to say, ‘Check out our pricing page’. If you are an SMB, the logos that I show you on our website will be relevant to your industry. So personalization was not just in the tracks, it was also in the website.”
The results of personalization were clear. “When we got personalization right, in some cases we doubled our conversion rates for that particular segment,” says Alex. “But the challenge is knowing what to talk about, knowing the particular persona at the particular point in time, and serving the right CTA.”
