Personalized Sales Content = 50% Lift In Reply Rate

If you missed our recent post about personalizing outbound email at scale, we’ve been testing ways to make our outbound email content more personalized.

We launched our current process in early Feb and have since researched and deployed personalized content to over 1000s prospects on behalf of our customers.

How the personalized sales content process works.

Before we started, we knew that doing this process at scale would be our biggest challenge — personalization requires research and time. It’s easy enough for a sales rep to write a one-off, personal email to 10, 20, (maybe) 30 prospects, but doing more would be tedious and out of the question.

Our solution to this problem was to build a human-author-based system that integrates with our sales development platform.  The process is pretty simple:

• Software triggers a research / content task for one of our US-based, college-educated workers.
• The worker follows some simple steps to research the desired prospect, writes a short piece of content, and clicks “submit”.
• Another worker reviews the completed task for content, errors, etc.  If it looks good, they click “submit”.
• The content merges into an email and our customer automagically sends a prospect a personalized email.
• Repeat over and over and over!

(There are lots and lots of other details, including hiring and training workers, defining the task, etc…but you get the idea.)

We recognize that this process won’t scale to the moon, but it is working really well and should get us pretty far down the road.  So we’re focused on improving and scaling this process and then figuring out the next right moves.

The results so far.

We’ve seen a steady 40% to 50% lift in the reply rate of outbound emails containing personalized content vs. a control group of emails without it. This is a pretty big deal, especially considering that the process happens touch-free for our customers.

Getting to this point doesn’t necessarily imply that we’re “there” yet, but we’ve seen enough to know that we’re on the right track. We’ve also had a chance to test and refine some ideas, and we’ve learned quite a bit in just a month’s time. Three of our biggest takeaways from the process so far are as follows.

Do the work yourself first.

This is easily the most taxing part of the process, but arguably the most important step — you’ll learn by doing. We kept track of the research sources we used most often (LinkedIn, Twitter, the company website, etc.), created examples/guidelines of what we want the research to look like, and categorized different types of personalization to develop research priorities.

These learnings have given us a clear blueprint for improving, automating, and (eventually!) replacing this process into software.

Simplify.

The idea of simplifying work lies at the crux of RevBoss…it’s a key component of almost everything we do internally and for our customers, including personalized content.

We have a lot of ideas for going deeper in our research and including more, increasingly targeted personalized data, but it’s important to start with a process that works.

We initially struggled because we tried to perfect and over-complicate every aspect of the work. In reality, we’re in the early stages of building a product and it’s not going to look exactly like our final vision within the first month. So, we regrouped and refocused on the core of the product — personalized content — and got a lot more wins.

Test as much as possible.

Because this is a difficult process to scale, testing data comes at a slower pace — but, it’s important in the beginning to put as much as possible through the system.

Our biggest question before starting was, “Is this going to move the needle?” We had a good feeling that we knew the answer, but it took a bit of brute force to get enough data that gave us a clear yes or no. Once we hit a stride, it became increasingly easier to get more data.

What’s next?

We’ve done enough tests to know that personalized content improves prospect engagement and lifts reply rates when compared to template-driven robo-emails, so now we’re integrating the process into our application and expect to make it available to all of our customers very soon. 

Let us know if you want to give it try!