Transforming Healthcare Go-to-Market: A Data-Driven Approach

Data transforms healthcare go-to-market by turning fragmented claims, clinical, and firmographic signals into a precise, prioritized target account list. Instead of guessing which health systems to pursue, teams can define an ICP, score accounts against it, and iterate as results come in — shortening sales cycles and focusing effort on the buyers most likely to convert. Here's the approach.

In the complex world of healthcare, we've seen firsthand how traditional go-to-market strategies often fall short (and have written about it!). But there's good news: the wealth of available healthcare GTM data offers a powerful opportunity to refine and optimize these approaches. Here's how that data can reshape go-to-market strategy in healthcare.

The Data Advantage in Healthcare

Healthcare is unique in the sheer amount of relevant data available. At Bonfire, we tap into several key sources:

• Medical and Rx claims data
• Social determinants of health (SDOH) data
• Provider survey data
• Non-healthcare data (e.g., contact information, CRM activity) used for healthcare data enrichment

This data gold mine allows us to get really specific about target patient populations. We can look at diagnosis codes, procedure codes, drug codes, demographics — you name it. It's like having a high-powered microscope for any specific healthcare market. Many healthcare sales intelligence tools draw on a few of these sources; combining all four is what makes the targeting precise.

Effectively Using an Ideal Customer Profile (ICP)

One of the most powerful applications of this data is in defining, refining, and acting upon your Ideal Customer Profile. We've found two main approaches work well:

• For companies still figuring things out: If you've got hypotheses about who your ideal customer is, great! We can turn those into lead scores and an efficient GTM strategy. We take your ideas, match them up with our data, and give you a quantifiable way to test your theories.
• For companies with established ICPs: If you've been around the block, we can get even more data-savvy. We'll take your customer understanding and create models that enable you to act on what you know. This could involve heuristics or even leveraging CRM history to determine what really makes a customer tick for you and the best GTM strategy moving forward.

Embracing Iteration

Perhaps the most important thing we've learned is the value of iteration. Data-driven go-to-market isn't about finding a perfect formula and sticking to it. Instead, it's about:

• Starting with your best data and hypotheses
• Creating measurable metrics and lead scores
• Testing these in the real world
• Refining your approach based on what you learn

The more you do this, the sharper your strategy gets. It's a continuous improvement process, and it can lead to some pretty impressive results.

Understanding the Money: Provider Economics

The economics are always important; to sell effectively in healthcare, you've got to understand the financial motivations of your potential customers. This could include:

• Fee-for-service reimbursement rates (which can vary wildly by region, provider, and payer)
• Value-based indicators and incentives (e.g., ACO affiliations, risk adjustments, patient risk scores)
• HEDIS measures for Medicare Advantage plans

This financial context allows you to tailor your value proposition to what really matters to each prospect. It's not one-size-fits-all in healthcare, and your approach shouldn't be either.

How to Build a Healthcare Sales Target List

Once your ICP is defined, building a healthcare sales target list is a matter of scoring real organizations against it. In practice, this is how to identify target accounts for healthcare sales using claims data. Pull the claims, SDOH, and firmographic data for accounts in your market, rank them by fit and opportunity, and layer in the provider economics below to sequence outreach. The result is a ranked list of target accounts, not a directory, so reps spend their time on the health systems most likely to convert. The foundation is account-to-claims mapping: tying claims activity to the specific organizations you sell to, so reps work from account-level claims data rather than raw provider files.

Wrapping Up

Healthcare is complex and relationship-driven. But that doesn't mean we can't be smart and strategic about how we approach it. By leveraging the amazing data at our fingertips and being willing to learn and adjust, we can cut through the noise and connect with the people who really need what we're offering.

At the end of the day, it's about getting innovative solutions to the providers, payers, and patients who need them most. And with a data-driven approach, we can make that happen faster and more effectively than ever before.

Bonfire was built as a claims data tool for sales reps who aren't analysts. Want to see your ICP turned into a ranked target account list? Explore the Bonfire product platform.

Frequently Asked Questions

How does data transform healthcare go-to-market?

Data replaces intuition-led targeting with a measurable process: define an ICP, score real accounts against it using claims, SDOH, and firmographic data, and iterate based on results. That produces a prioritized target list and shorter sales cycles.

How do I build a target account list for selling into hospitals and health systems?

Define your ICP, then rank organizations in your market by fit using claims and firmographic data, and sequence outreach using provider economics (reimbursement, value-based incentives, HEDIS). Refine the list as outreach generates feedback.

What data sources are used for data-driven healthcare GTM?

Four main sources: medical and Rx claims data, social determinants of health (SDOH) data, provider survey data, and non-healthcare data (contact and CRM activity) used for enrichment.

What is account-to-claims mapping?

Account-to-claims mapping links claims activity to the named organizations in your CRM, so reps get account-level claims data for healthcare sales instead of provider-level files they have to reconcile by hand.