How a clinical data platform prioritized its first payer buyer targets.

3Pillars performed a top-down market scoping and a bottoms-up sweep of 4,000+ health system and provider relationships, all run through the Aequalis Payer Insights Platform.

How the 3Pillars team identified where the buyers actually were.

Weeks 1-2 ran two analyses in parallel through the Aequalis Payer Insights Platform. A top-down read of the payer market to decide which LOBs and organization types were worth pursuing, and a bottoms-up read of the existing provider book to find latent payer relationships hiding inside 4,000+ active accounts. Aequalis powered both. The two views converged on a single defended list.

• A defended target list of 25 payer / Provider Sponsored Health Plan organizations, ranked from 50 enriched candidates by fit, size, and feasibility
• Account-level briefs covering LOB mix, member count, HEDIS posture, acquisition history, and buyer map
• A documented top-down + bottoms-up methodology the internal team can re-run when the book or the market shifts
• The Aequalis Platform refresh wired into the operating cadence

How the team built a payer go-to-market from a provider Sales engine.

Weeks 3-4 stood up the two motions the client did not yet have. A systematized outreach engine for payer buyers the Sales team had not engaged with historically, and a Pilot Support Program so the CS team could catch a signed contract clean. AI sat behind the build as drafting and templating support; the workflow itself stayed human-led.

• Systematized outreach engine. Email sequences, call scripts, talk tracks, objection responses, and one-pagers tuned by LOB and buyer role. New scripts built for payer personas the team had not historically engaged. Blended payer expertise with AI-native drafting support behind the scenes.
• Pilot Support Program. The operating wrapper for a signed pilot. Intake forms, training curriculum tuned to PSHP workflows, rollout reporting templates, success criteria, and a defined Sales-to-CS handoff moment. Closes the gap created when CS is engaged too late in the Sales cycle.

• Materials library. A central, versioned set of outreach and enablement assets so reps are not rebuilding from scratch on every conversation.
• Sales-to-CS handoff protocol. A checklist and meeting structure so nothing the rep learned during the Sales cycle is lost at signature. Cycle time cut from 4-6 weeks to 2.
• Operate handoff plan. Roles, refresh cadence, escalation paths, and the Week 5 handoff sequence specified before the team walks out of Week 4.

What gets built and how it runs.

Five workflows. The first three produce the target list, with the Aequalis Payer Insights Platform as the analytical engine across both top-down and bottoms-up. The fourth produces the outreach motion. The fifth produces the customer success motion. Each carries a human-in-the-loop checkpoint before output drives action.

How the work flows across the people who run it.

Pick a persona in the left nav to see how the engine changes that seat.

What the team was left with.

The 5-week engagement ended with a Sales motion the client team owns, a CS motion ready to activate, and a documented methodology that can be re-run as the payer market shifts. Aequalis powered the diagnostic. AI sat behind the build as drafting support. The forward question is where AI gets layered in next.

• Layering Medicaid managed care more deeply once MA traction is established
• Extending the methodology to ACO REACH entities and other risk-bearing organizations
• Re-running the bottoms-up sweep as new provider clients are added
• Using early pilot outcomes as reference accounts for the next priority tier

• Outreach feedback loop. Agents read and listen to Sales conversations, flag what is and is not landing, and propose updates to scripts, sequences, and materials. VP of Sales and VP Commercial approve. The library updates itself.
• CS phone and email training. AI-supported training that captures the language of high-performing CS conversations and uses it to onboard new CS team members.
• Utilization signal detection. Agents watch client utilization data and flag dips and growth signals before they show up in a quarterly review.
• Power-user identification. Agents surface the individual users inside each PSHP client who are driving adoption, so the CS team can empower them as internal champions.
• CS leverage. Net effect of the four above. A smaller CS team operating effectively against a growing book, which directly affects admin cost as the motion scales.