Prememoria: Reach is a sales enablement tool for hyper personalizing outbound emails at scale in order to save time while obtaining higher response rates.
In last week’s post we look at some of the slight but significant changes we made that improved our response rate from ~10% to ~16%. We specifically looked at the changes we made to the email structure that made it significantly more readable as well as the improved email subject line. This week we will look at how we started using email data to better target prospects and improve the response rate even further.
Our team exclusively uses MixMax for email sequences. MixMax provides us insights into the performance of the emails we’re sending. We can track open rates, response rates and even specifically the number of times a specific recipient opens an email.
We started using this data to retarget our prospects on LinkedIn. A recipient who opens our emails numerous times is probably interested in what we’ve been communicating. So we created an internal “rule” that anyone who opens an email more than 5 times (in a 3 stage sequence) will get contacted via LinkedIn. People are often busy or distracted. Introducing this additional contact step for interested prospects can sometimes get them to respond.
Additionally there are always people who never open our emails at all. It’s possible that in such cases our emails went to their spam folders or got buried as a result of poor inbox hygiene practices. Either way, they certainly won’t respond to us if they never read the emails in the first place. If a recipient hasn’t opened our email after the first stage of the email sequence, it’s highly likely they won’t open it after any stage of the sequence. Therefore we have created an internal “rule” that recipients with zero views after the first stage will be exited from the email sequence and contacted on LinkedIn.
This has two benefits. First, we reduce the number of unnecessary emails we’re sending as a team which improves the authority of our domain and the deliverability of our emails. Sending too many emails without responses can damage your domain reputation. Second, we give ourselves a second chance for our messages to be read by moving them to another channel, LinkedIn. Since they never read the first email we can reuse the personalization and send them the same email again.
By looking at the data we’ve been able to make better decisions about how to retarget our prospects when they either show intent or never saw our messages. In doing so we can intelligently increase the probability of getting responses from the same pool of prospects. In fact doing so has brought us to a ~20% response rate, all in. We’re constantly looking at ways to get smarter and more efficient with our outreach. Our next post will look at some of the strategies we’re using for creating a more complex and automated sales process.
