In today’s current economic state, revenue teams are hyper-aware of the need to maintain their existing customer base. Even more important is expanding those accounts. As companies implement stricter rules and budgets around acquiring new tools, finding opportunities through your existing relationships will be key.
That’s where Correlated comes in!
You may have strong ideas about when a current customer becomes eligible for expansion, but there’s nothing more annoying than pushing a customer to expand when in reality, they’re not ready yet. It’s happened to all of us, and it’s an extremely hard thing to get right.
How do Customer Lifecycle Scores work for Expansion?
To help prevent you from reaching out to the wrong accounts, or the right accounts at the wrong time, Correlated’s Customer Lifecycle Scores use an AI-powered propensity model to create informed scores based on customer behavior. This gives you the upper-hand when it comes to predicting which customers are ready to expand, convert, onboard, or even churn.
Extra busy today? To see the rest of this blog post summarized in one minute, check out the video below:
https://www.loom.com/share/8bf80a96a1c342d0b29a0fda90b3b957
The model also allows you to have a real say in the matter. Simply refine the model as it processes to get rid of any data points that you don’t want Correlated to consider in your score. The result? Full visibility into exactly what data is powering your expansion scores.
Once the model has been processed, you’ll see the top 25 success indicators that correlate with your expansion goal. Alongside this is a “shared by” percentage - This number tells you what percentage of already expanded customers share this same trait. Finally, a score between 1-100 will be assigned to all of your customers who have not yet reached your goal. As you can see, you’re able to both quickly score customers and explore indicators that drive those scores.
How to get started with Customer Lifecycle Scores
For an expansion use case, you can hit the ground running in a few quick steps:
Step 1. Define your expansion goal.
This can be as simple as your customers purchasing a new product, or adding more paid seats to their plan. If you only care about certain customers, add a filter to your goal, like market segment = enterprise.
Step 2. Let the model run and improve your score as necessary.
See any indicators with an extremely low “shared by” percentage? Or data that you know for a fact isn’t important? Just remove them from the model.
Step 3. When everything looks good, operationalize your expansion plays!
Correlated makes the hard part (aka actually acting on these scores) easy, by automatically scoring your customers who have not yet expanded and surfacing that score in the Playbook builder. Simply create a new Playbook and set your trigger conditions using the desired score.
Pro Tip: Use Correlated’s pre-made “High” bucket to automatically capture any customers who score between 80-100.
Once your conditions are set, add an action that your team will feel equipped to follow up on and craft a plan to expand. For example, send a Slack DM to the Account Owner or CSM, accompanied by important contextual data that they can use to construct their message.
Even better, add an additional action to port that ready-to-expand customer to a HubSpot list or Outreach sequence, if you want to automate the communication piece as well.
Sample Expansion playbooks you can deploy with Correlated
- Utilize product usage to determine inflection points based on how you price/package. For example, if you utilize seat-based pricing which customers are adding seats mid-contract?
- If you have a usage metric that you price on, which customers are expanding usage the fastest organically? Are they bumping up against credit limits?
- Map account owner/admin based on product usage activity. For active accounts in the long tail (ie. not named accounts), which have a clear customer owner/admin? Add those admins to a lifecycle campaign if they're part of a higher propensity/usage account.
- ICP fit plus "good" usage. If a self-serve customer is an ICP fit and has good usage but doesn't hit a spend threshold that warrants sales attention based on existing rules of engagement, add them to a sequence. Often self-serve customers will remain fully self-serve until they raise their hand to "talk to sales." We find that a proactive approach for high propensity accounts leads to shorter deal cycles and more pipeline.
Get started
You can sign up to learn more here.
Interested in other ways Correlated can help? Read more about how Reveal used Correlated to generate over $400,000 in revenue!
.jpg)
