Create a drip campaign for potential home sellers who filled out a form to get an estimate of their home’s value sent to them. Emails can stray slightly from the established brand. The primary end goal is to get sellers to talk to an agent, but driving users to blog content is also valuable
Best email had 60% Open Rate and 30% CTR
Planning/Strategy, Copy, Design, Building (SendGrid and Drip)
Research
I began by walking through the product end-to-end and creating buyer personas for home sellers. To deepen my understanding, I listened to phone calls between sales reps and home sellers and analyzed the emails of competitors.
Sequence, copy and sketches
Armed with my now vast knowledge of what would compel a home seller to speak to a real estate agent, I began crafting a story out of standalone emails. I already had an idea of what content lived where so it was fairly easy to work blog content into the campaign. Once the email topics had been vetted by the team, I proceeded to write copy and sketch out the look and feel of the entire sequence.
Design and Testing
The time to launch the emails was fast approaching, so I quickly finished the email designs in Drip based on the sketches I had made earlier. There were still a few specific elements (mainly CTAs) with variations that the team and I were torn between so we decided to A/B test those.
Metrics and Challenges
Of the series, the first email seemed to do the best in terms of open (60%) and click-through rate (22%), which is not uncommon in a sequence that contains a transactional email. The marketing emails started out a little below industry standards in early iterations, but after increasing the urgency in the subject lines, adding diverse visuals and more high-value CTAs (especially to blog posts), I was able to increase open rate and CTR to 25% and 5% respectively over the course of a month.
The biggest challenge was the technology: the emails were all built in Drip, which isn’t optimized to handle HTML emails. As a workaround, I used the company’s pre-existing SendGrid setup to build the emails and then imported them into Drip.
Finding a good balance between fewer long emails and more frequent shorter emails was also a challenge. I partially addressed this by segmenting the audience into mobile and desktop users. Mobile users got more frequent emails while desktop users got longer emails. This, however, wasn’t an optimal solution because it was based on the last email opened. As a follow-up, I would have liked to explore more segmentation options and use AB testing to determine the best cadence for the emails.