How to Project PI Marketing ROI Before Your Cases Settle

The most common reason PI managing partners give for not knowing their marketing ROI is the settlement lag. “We'll know when the cases close.” For a firm with a 6–18 month settlement timeline, that answer means marketing spend decisions today won't have an accountable ROI number until next year or the year after.

That answer is operationally understandable. It is strategically expensive. You cannot optimize marketing investment for future returns you refuse to project. And the projection is not guesswork—it is applied math on data your firm already has.

By applying your historical settlement rate, average case values, and attorney fee percentage to your current signed case pipeline, you can calculate a forward-looking marketing ROI today. This is what Revenue Intelligence calls pre-settlement ROI. Here is how to build it.

Why Waiting for Settlement Data Fails Marketing Strategy

Most PI firms track cost per signed case as their primary marketing output metric. That is the right metric for vendor decisions: which sources are acquiring cases most efficiently. But cost per case answers a different question than a managing partner is asking.

A managing partner approving a $200,000 monthly marketing budget is not asking “what did a case cost to acquire?” They are asking “what will that acquisition return?” Those are not the same question. A $3,000 cost-per-case number tells you nothing about whether the case will produce a $60,000 settlement or a $250,000 settlement, or whether it will settle at all.

Without a projected return, marketing directors defend spend by showing signed cases. Managing partners approve budgets because the firm needs revenue, not because they understand what the current pipeline will produce. That is not a confident 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 operates. What is usually missing is the discipline to pull them together and calculate the number.

• Marketing spend by period. Total spend for the cohort period (e.g., Q1 2026 marketing spend), pulled from your 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 the blended average across your case mix if rates vary by case type.

A Worked Example at Three Firm Sizes

Pre-settlement ROI works at any spending level. The mechanics are the same—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 still operates on the same inputs. At $200,000/month, scale produces more settled cases and proportionally higher projected fee revenue.

The ROI improvement with scale is modest—roughly 20 percentage points from $50K to $300K/month—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 ROI calculation use an industry average settlement rate of “around 95%.” That number is misleading because it conflates different outcome definitions across different reporting methodologies.

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

• Post-sign rejection rate.The percentage of signed cases that are 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%. Firms with heavy shared aggregator volume and limited intake screening may run 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 affects whether the model supports budget approval or raises questions.

Pull your own 12–24 month settlement data from your case management system before using 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 pre-settlement ROI 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 case severity. Attorney and medical referrals consistently produce higher-severity cases with above-average settlement values. Mass-market TV and radio leads often produce higher-volume but lower-severity cases with lower average settlements. Aggregator leads vary significantly by vendor and by the type of lists they generate from.

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 is 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 period 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 gives a managing partner the confidence to approve Q2 spend decisions without waiting for Q1 cases to close. It converts budget conversations 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 cases from each cohort close, compare actual settlement revenue against your projection. Improving projection accuracy over 12–24 months builds credibility with partners who were initially skeptical of the model.

What Connects the Model to Real-Time Data

The calculation above can be done in a spreadsheet for a single cohort. The challenge is maintaining it as a live view of your active pipeline across multiple vendors, case types, and 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 is always 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 have never run a pre-settlement ROI projection, the first step is pulling your historical settlement rate from your case management system. Pull cases signed in a specific 12-month window and calculate what percentage settled with a cash payment. That single number, applied to your current pipeline, produces your first projection.

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

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

The firms that present pre-settlement ROI to their partners do not get asked “what did we spend?” They get asked “what do we project to return?” That is a materially different budget conversation—and it is one that marketing directors who have done 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.