Positive Customer Lifecycle Signals

Positive Customer Lifecycle Signals can typically be broken down into three types: conversion, expansion, and cross-sell. We'll walk through examples of how to create signals for each using our "ACE" Framework.

Step 1: Defining Conversion - Accounts or Users who are not paying

First, we want to define what it means for a user to be a candidate for conversion. Typically, this means filtering for users who aren’t paying yet. If your users aren’t explicitly tagged with paying or not, you can use Opportunity Stage is not Close Won as a rough proxy.

Now, we can start designing signals that are a good indicator of an intent to convert.

Activation - Is the user doing things that indicate that they have “activated” as a user?
Ex: User sign-in and invited another user

Capacity - Is the user approaching a cap that will require them to start paying?
Ex: Account has 50% seat utilization

Engagement - Is the user showing usage patterns that are positive?
Ex: User used X feature 10% more this week than last

Step 2: Defining Expansion - Accounts or Users who are paying and growing

Now, let’s define what it means for a user to be a candidate for expansion. This usually means filtering for users who are paying and haven’t just converted. An example filter here would be Opportunity Stage is Closed Won and Opportunity Closed Date is more than 1 month ago. Note that if your product is self-serve, not all paying customers have opportunities. In this case, use a different dimension to filter out paying vs non-paying customers.

Again, we can start designing signals that are a good indicator of an intent to expand.

Activation - Is the user doing things that indicate that they have “activated” as a paying customer?
Ex: Invited more than 2 people in the last week

Capacity - Is the user approaching a cap that will require them to move up in tier or pricing?
Ex: Account is hitting 80% of capacity

Engagement - Is the user showing positive usage patterns?
Ex: User used X feature 10% more this week than last

Step 3: Defining Cross Sell - Accounts or Users who are paying and expanding their use case

Not all companies have a cross sell motion, but if you have one, you can use a similar methodology to create a foundation of Signals. Users who are candidates for cross sell are already paying. An example filter you could use here is Opportunity Stage is Closed Won (or other proxy for paying customers).

So how do we discover if users might be candidates for expanding their use case? Typically, expansion can occur across two axes: new teams who control a different budget and new feature usage. Let’s use the same framework as before.

Activation - Is the user doing things that indicate that they have “activated” as a paying customer? Similarly to above, we aren’t interested in users who aren’t activated.
Ex: Signed in more than 5 times over the last month

Capacity - Is the user approaching saturation along one of the two axes - teams and feature usage?
Ex: User invited 20 other engineers and only has 5 more seats left or user tested out a feature and is 5 days away from the trial ending

Engagement - Is the user showing positive usage patterns? Like above, we want to find healthy users and accounts to cross sell into
Ex: User used X feature for the first time