How We Used AI to Increase HubSpot Email Conversions by 82%: A Case Study

We turned our standard nurture email flow into an AI-driven conversion powerhouse. Here’s what we did, what worked (and what didn’t), and what we learned along the way.

How We Used AI to Increase HubSpot Email Conversions by 82%: A Case Study

We turned our standard nurture email flow into an AI-driven conversion powerhouse. Here’s what we did, what worked (and what didn’t), and what we learned along the way.

AI to increase email conversion rate

When our marketing team began discussing how to strategically incorporate AI into our workflows, we knew we wanted big results. But here's the thing about big results: They don’t come from trying everything at once.

With limited resources and unlimited possibilities, we needed to hone in on which AI applications would deliver the biggest impact.

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Email marketing seemed like a natural starting point for us. We'd been running optimization tests on our nurture flows for years, but after a while, the gains became incremental by a few percentage points here and there.

We needed something that was a total game-changer. Something that had both meaningful influence on top-of-funnel metrics and practical usability across our marketing team. But what — and how?

In a recent Marketing Against the Grain episode, HubSpot VP of Marketing Emmy Jonassen and I share how we experimented with AI to transform our email performance. We’ll also explain how we achieved an 82% increase in conversion rates — plus, all the lessons we learned along the way.

Identifying the Challenge

First, let me explain what we were doing before AI. Like most marketing teams, we approached email personalization through segmentation — grouping leads based on similar characteristics, then tailoring content to those groups.

For example, if someone downloaded marketing-related content, we'd send them more marketing resources rather than sales content.

It wasn't a bad approach. But it was essentially educated guessing at the group level. We were saying, “People like you typically want this,” rather than understanding what each individual person was trying to accomplish. We wanted to do better than that.

The Hypothesis: Moving From Groups to Individuals

The more we looked at AI's...

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