Using Intent Data to improve retention and grow revenue

Customer Lifecycle™ Intent Data is a frequently overlooked opportunity to leverage data to optimize customer experience, reduce churn and proactively identify opportunities for up and cross selling.

Too often, though, the marketing or sales team that bought the data doesn't do a great job sharing access or insights with their colleagues in customer success. So it's an important opportunity - for those buying the data to brief their colleagues on what's available, and for those looking for more customer success insights to check with marketing and sales to find out if any data is available.

Either way, it's important to have playbooks to ensure that the data is surfaced for the right people at the right time - and with context so that it's effectively analyzed, interpreted and activated.

Here are some important points to keep in mind as you think about rolling out contact level™ intent data for customer success use cases.

Enablement Matters

There are many steps between data ingestion and activation.

  1. The tech stack has to support ingestion, unification and orchestration of a complete marketing data stack.
  2. Segments must be designed, tested and refined to automatically surface contacts who satisfy certain criteria based on observed activity from a recent rolling time period. For instance: certain levels of individual activity around certain topics, and combinations of 1st & 3rd party data; minimum numbers of active contacts within an account; recent technographics changes, etc.
  3. Plan the orchestration - what happens? Who's informed? What automatic steps occur? Depending on the segment you'll need to take certain steps. It might be as extreme as notifying the CEO (upon observing C-suite action from a top 10 account), to simply triggering an automatic email from a CSR - with many options in between.
  4. Enable the follow up - intent data provides sales intelligence in the form of signals that are subject to analysis and interpretation. Don't leave that up to colleagues with way too many tasks to complete and impossible email/Slack workloads. Push the dots close together with automated workflows which provide coaching and recommendations based on the inferences you draw from the customer's activity. In other words, if it's early in your customer's contract term with you, and the engagement is with an informational type of key term, then you might suggest an email template and relevant educational content to share. If it's a current customer engaging with a competitor for a capability you also sell, but not what they currently buy from you, you'll suggest an appropriate outreach plan. But if it's a large customer, nearing renewal notification deadlines, where multiple contacts are engaging with multiple competitors, you'll certainly suggest a very different approach.

There's tremendous power in customer lifecycle data, but it's sometimes lost in the handoff. Effective enablement is key to making it actionable for your success team.

Common Plays

You'll have ideas for various creative movements and playbooks. Here are a few common ones to get you started.

Churn Reduction

Contact level intent, particularly in combination with Contextual™ Technographic Data (for SaaS vendors) can be a very powerful tool for early indications of churn risk or competitive defection.

Granular data insights (vs. opaque "topic" taxonomies) which identify specific competitors, specific key terms, and contact job titles, help to analyze activity and discern between content intent and educational research vs. purchase intent.

This granularity also helps to discover possible risk from non-direct competitors. For instance, customers may investigate stopping using your type of product/service altogether. In that case, rather than traditional competitive signals, more top & middle of the funnel indicators can help to discover the risk of defection to other solution types.


Product usage billing is a common approach to upselling - particularly starting with freemium models. So many companies have a strong, built-in, upsell program. How can intent data help beyond that?

You can take various approaches:

  1. watch for activity around features you offer in higher level versions - and include current level as a filter in your segmentation criteria
  2. look for other departments horizontally in current customer companies that are looking for similar solutions - maybe you can get your current customer contacts on board to help with the lure of bundled discounts
  3. track higher level job seniority activity around aggregate capabilities that you can address vertically in the company

Referral Builder

If you have a partner program (products that you co-market) you might consider the value-add to customers and partners to create a stream of intent data that looks for strong signals which are relevant to the partners. Those would position you to share a recommendation with your customer, creating value in that relationship, and simultaneously identify a possible opportunity for the partner, building a strong tie there as well.

And you might have an arrangement that allows you to monetize those referrals that turn into paying customers.

cross sell

Whether you're a software company with various complimentary modules, a professional services company with various discipline expertise, or an industrial company with various product lines, it's always easier to sell more products/services to an existing customer than to source a new one.

Contact level intent data can help here.

A common play is to create parallel data streams for substantially different product offerings. As those are ingested into your tech stack for integration with all the components of your data stack and unification, then relevant actions from current customer accounts can be surfaced, with helpful enablement, for the right people. It's particularly helpful to build this enablement to leverage existing relationships in both companies.

Indirect Sales Channel

If you sell through indirect sales channel, than all these same plays can be run on indirect customers as well, with the orchestration managed through a channel sales manager.

If you've implemented a CDP with your indirect channel then this can be simplified and automated at scale.

Product Marketing

Many companies that expertly activate various tactical plays for intent data in customer success overlook the huge strategic value in aggregate data as well.

Product marketers can often glean insights into upgrade triggers and buying journeys for competitive review and new product research. This can inform messaging, onboarding, training, feature bundles, pricing and more.

Selfish Intent is Transparent

Are you willing to walk away if you haven't provided the value you owe a customer?

If not, then don't use intent data for customer success use cases. Your efforts will be transparently selfish, rather than genuinely helpful.

That will come off as creepy and high pressure. Which is particularly unwelcome by many of today's buyers.

But, if you're genuinely committed to using the insights to improve your customers' outcomes, and your business as a result, then customer lifecycle intent data offers a big upside.


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