How to Project PI Marketing ROI Before Your Cases Settle

Most PI firms calculate marketing ROI the same way: wait for cases to close, then look backward. With a 6–18 month settlement timeline, the spend decisions you make in Q1 won't have an accountable return number until Q3 of next year—at the earliest.

That's not a data problem. It's a projection problem. Your firm already has the historical settlement rates, average case values, and attorney fee percentages needed to calculate a forward-looking return today. This is what Revenue Intelligence calls pre-settlement ROI—and here is exactly how to build it.

Why Waiting for Settlement Data Fails Marketing Strategy

Most PI firms track cost per signed case as their primary marketing metric. That is the right number for vendor decisions—it tells you which sources acquire cases most efficiently. But it doesn't answer the question managing partners actually ask.

A managing partner approving a $200,000 monthly budget isn't asking “what did a case cost to acquire?” They're asking “what will that acquisition return?” A $3,000 cost-per-case number says nothing about whether a case will produce a $60,000 settlement or a $250,000 one—or whether it settles at all.

Without a projected return, marketing directors defend spend by showing signed case counts. Managing partners approve budgets because the firm needs revenue—not because they understand what the current pipeline will produce. That is not a capital allocation process. It is a recurring act of faith.

Pre-settlement ROI converts that faith into a model.

The Five Inputs You Already Have

Building a pre-settlement ROI model does not require new data sources. Every input comes from systems your firm already runs. What's usually missing is the discipline to pull them together.

• Marketing spend by period. Total spend for the cohort period (e.g., Q1 2026 marketing spend), pulled from vendor invoices, ad platforms, and agency retainers.
• Signed cases attributed to that spend.Cases from your CRM tagged to lead sources during the same period. This requires clean source tagging—the prerequisite for any attribution work.
• Historical settlement rate.The percentage of your signed cases that ultimately settle with a cash payment, calculated from 12–24 months of closed case data in your case management system.
• Average settlement value by case type.Your own historical averages for auto accident, premises liability, and other case categories—not industry aggregates, which reflect a different case mix than yours.
• Attorney fee percentage.Your standard contingency fee rate, typically 33–40% of settlement. Use your blended average if rates vary by case type.

A Worked Example at Three Firm Sizes

Pre-settlement ROI works at any spending level. The mechanics are identical—only the absolute numbers scale. The example below uses a consistent 78% settlement rate, 35% attorney fee, and a case type mix of 70% auto accident ($95,000 average settlement) and 30% premises liability ($140,000 average), producing a weighted average settlement of $108,500.

The smaller firm at $50,000/month signs fewer cases at a higher cost per case, but the ROI model runs on the same inputs. At $300,000/month, scale drives more projected settled cases and proportionally higher fee revenue—with modest ROI improvement because the model assumptions are held constant.

In practice, larger firms often achieve better settlement rates through stronger case selection and intake screening, and may carry a different case type mix that shifts average settlement values. Your actual numbers will differ. The structure of the model does not.

The Settlement Rate Is the Most Important Input—and the Most Commonly Wrong

Most PI firms that attempt a pre-settlement calculation use an industry average settlement rate of “around 95%.” That number is misleading—it conflates different outcome definitions across different reporting methodologies.

For an accurate model, you need a firm-specific settlement rate that accounts for two distinct filters your cases pass through after signing:

• Post-sign rejection rate.The percentage of signed cases rejected during attorney review in the first 30–60 days after intake. This varies by lead source and ranges from 5% to 30% depending on intake screening quality.
• Settlement rate on kept cases. The percentage of attorney-reviewed cases that produce a cash settlement rather than litigated judgment, dismissal, or client abandonment.

Your combined rate—kept case rate × settlement rate on kept cases—typically runs 70–82% for mid-size PI firms. Firms with higher-intent lead sources (referrals, branded search) and strong intake screening run toward 80–82%. Heavy shared aggregator volume with limited intake screening runs 65–70%.

A 12-percentage-point difference in settlement rate changes your projected ROI by roughly 15–18%. Using the wrong baseline is not a minor calibration error—it determines whether the model supports budget approval or invites hard questions.

Pull your own 12–24 month settlement data from your case management system before relying on any external benchmark.

Running the Model by Lead Source, Not Just Firm-Wide

The firm-wide pre-settlement ROI is useful for partner conversations. The vendor-level view is where the model produces actionable intelligence.

Settlement rate and average settlement value vary by lead source because source type correlates with case quality and severity. Attorney and medical referrals consistently produce higher-severity cases with above-average settlement values. Mass-market TV and radio leads produce higher volume but lower average settlements. Aggregator leads vary significantly by vendor and list type.

When you run pre-settlement ROI by vendor, you may find that a vendor appearing competitive on cost per case—say, $3,200—produces cases with a 68% settlement rate and an $82,000 average settlement. A second vendor at $4,100 per case produces cases with an 80% settlement rate and a $112,000 average settlement. On cost per case alone, Vendor A looks 28% cheaper. On pre-settlement ROI per dollar spent, Vendor B projects to return 35% more.

Cost per case optimizes acquisition efficiency. Pre-settlement ROI optimizes capital allocation. Running both gives you the complete picture.

How to Present This Model to a Managing Partner

Pre-settlement ROI is not a substitute for actual settlement-based ROI. It is a confidence-building tool for the window between signing and settlement when standard ROI is unavailable.

The right framing in a monthly or quarterly review: “Here is the projected return from our Q1 signed case cohort, based on our historical settlement rate and case value data. If our portfolio performs within normal variance, we expect $6.50–$8.00 returned per dollar spent from Q1 marketing.”

That answer lets a managing partner approve Q2 spend decisions without waiting for Q1 cases to close. It moves the conversation from “we spent $X and signed Y cases” to “we spent $X and project to return $Y—here is the confidence interval.”

Three presentation standards make the model credible:

• Show the inputs and their sources. A projected ROI number without visible assumptions invites skepticism. Show the settlement rate you used, where it came from, and how many months of history it reflects.
• Show a range, not a point estimate. Apply a confidence interval (±10–15% around the base case) to reflect settlement rate variance. A range is honest and looks more rigorous than a single number.
• Track actuals against projections over time. As cohort cases close, compare actual settlement revenue against your projection. Accuracy improves over 12–24 months—and so does partner confidence in the model.

What Connects the Model to Real-Time Data

This calculation runs in a spreadsheet for a single cohort. The challenge is maintaining it as a live view across multiple vendors, case types, and rolling time periods.

With 30–50 cases per month across 6 vendors and 3 case types, manual model maintenance consumes meaningful time. It also degrades as data ages—settlement rates shift with changes in case mix, intake screening, and vendor quality. A model calibrated on 2024 data applied to a 2026 pipeline may be significantly off if your vendor portfolio has changed.

The Financial Intelligence layer in RevenueScale runs this projection automatically, pulling settlement rate and case value inputs from your case management system and updating projected returns as case outcomes are recorded. The model stays current without manual maintenance, and it runs at the vendor level so cost-per-case and pre-settlement ROI are visible together in one view.

Where to Start

If you've never run a pre-settlement ROI projection, start with one number: your historical settlement rate. Pull cases signed in a specific 12-month window and calculate what percentage settled with a cash payment. Apply that rate to your current pipeline. That's your first projection.

Most PI firms find this number is lower than expected—because the 95% industry average includes firm types with better intake screening than the average mid-size practice maintains. A realistic number makes the model credible. An inflated one becomes a liability the first time a case closes below projection in a partner meeting.

Use your own data. Run the model on a completed cohort first to verify accuracy. Then extend it to your active pipeline.

Firms that present pre-settlement ROI to their partners stop getting asked “what did we spend?” They get asked “what do we project to return?” That is a materially different budget conversation—and one that marketing directors who do this work consistently win.

If you want to see how this model applies to your specific vendor portfolio and case data, book a demoand we'll walk through the projections with you.