Intent data is often sold as "leads." That causes marketing teams to think of it exclusively in the context of demand generation. While it's a powerful demand gen tool with numerous related use cases, Contact Level™ Intent Data has applications later in the customer lifecycle.
Common uses of intent data by customer success teams include:
Companies can use direct signals from the data as well as incorporate it into an orchestration process that includes important first-party data sets.
Direct signals: When intent data shows a current customer engaging with a competitor or taking action on content that indicates they're exploring alternatives, your success team should know. Most companies also recognize certain key roles where change often triggers changes in programs and vendors. Is every signal critical? Of course not. But make sure someone knows, and track the trend.
New opportunities: How many times has a loyal customer bought from a competitor simply because they didn't realize you could help them? Probably more than any of us would wish to admit! Intent data can help to identify those opportunities early.
R&D insights: Have new product ideas or feature enhancements to prioritize? By tuning up your intent data algorithm to add relevant signals, you can identify customers who are looking for related solutions and offer them the opportunity to help shape the offering and try it as an early adopter.
Customer intent data stack: You've already got important first-party data including app usage, ticket submissions, and abandoned carts. Combining those first party signals with contact level third-party data will help to anticipate problems and opportunities early enough to react.
Too often intent data is held by the demand generation team. They might not even stop to consider the value to their success colleagues. And the data feed might not be accessible beyond new logo marketing. For instance, intent data that's embedded in ABM software will never reach the customer support team.
When planning your customer lifecycle intent data implementation, keep these points in mind.
It seems obvious, but your data must be available to the success team. That could be managed in your CRM or CDP. It can also be simply achieved by requesting a separate stream of customer only activity, filtered for the signals that are important to them - and delivered directly to them.
If you only look at third-party data you'll probably miss important insights that lie at the intersection with your own first-party data. Data orchestration will be important to integrate and unify the full data stack, and to identify the important combinations that indicate something's likely to happen.
When your team does identify a risk or opportunity, their approach is critical. Awkward and clumsy could put the nail in the churn coffin. Helpful and artful could put you on the road to saving or growing the account. That takes the right playbooks, training and enablement support.
The most successful companies also get creative and look for opportunities to use contact level intent data creatively in other enterprise use cases.