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Wheelhouse RPM

Real-time Propensity Modeling. Optimize for business value with every form submission.

Transmit the value. Keep the data.

The conventional approach to patient acquisition campaign optimization is to optimize for form submission. But form submissions and online appointment bookings don’t generate revenue – kept appointments and completed procedures do. Real-time propensity modeling enables healthcare providers to use their institutional data to generate a revenue-based propensity score every time a form is submitted – and to send that score to ad platforms, continuously optimizing campaigns in real time.

How it works

Propensity modeling is not new to healthcare.
Real-time propensity modeling is.

Most propensity models work in batches. A vendor builds an audience segment from demographic and behavioral signals, refreshes it every 30 to 90 days, and delivers a target audience. That is useful. But it operates at the population level, and it tells your ad platform nothing about the individual leads already arriving in your funnel.

A real-time propensity model works differently. The moment a prospect submits a form on your website, the model calculates their likelihood of converting and potential value as a patient, based on your historical outcomes and not industry averages, and transmits that predicted value to ad platforms in real time. Your campaigns are optimized continuously.

CapabilityWheelhouse RPMBatch Models
Scoring unitIndividual leadAudience segment
Refresh cycleEvery form submission30 to 90 days
Signal destinationAd platform optimization engineTargeting audience
Training dataYour confirmed CRM outcomesThird-party claims, proxies
Conversion lagFully solved at submissionPartially addressed
Privacy architectureBuilt into the data flowCompliance managed around

Why it matters

By the time you know
which prospects became patients,
your budget is already gone.

Drive value, not volume

Real-time propensity modeling transmits a predicted customer value at the moment of form submission, giving the platform the signal it needs to optimize for value not volume.

Compliance is the architecture, not the constraint

The scoring engine lives inside your HIPAA-compliant environment. What reaches ad platforms is a single numerical value. No health information crosses that line. Compliance and performance are the same mechanism.

Who it’s right for

If any of these describe your situation, real-time propensity modeling is worth understanding.

You run lead generation campaigns for a highly regulated industry

Your conversion cycle is measured in months. Your conversion signal is lead generation but there is a significant disconnect between lead and revenue generation.

Your CPL looks fine but downstream conversion rate does not

Low cost-per-lead is not a success metric if prospects do not convert. Real-time propensity modeling redirects the algorithm toward valuable patients.

You have been told you cannot share conversion data with ad platforms

You cannot share patient data. You can share a propensity score. The model lives inside your HIPAA-compliant environment. What is shared with ad platforms is a single numerical value with no health information and no compliance exposure.

You have institutional data you have not been able to use to optimize your advertising

If you have 12 or more months of prospect-to-patient data, you have a training set. That historical signal is the raw material that can be used to create a propensity model.

Try it yourself

Build your first propensity model.
No code. No commitment.

Walk through the structure, logic, and output of a real-time propensity scoring system, using a synthetic healthcare dataset or your own data if you have it.

Let’s talk

Want to see what real-time propensity modeling could do for your marketing?

Our team will walk you through what an implementation looks like for your funnel, your CRM history, and your compliance environment. No sales pressure, just a real conversation about whether this is the right capability for your business.

 

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