How One 25-Attorney PI Firm Cut $180K in Annual Vendor Waste With Revenue Intelligence

Marcus had been the marketing director at a mid-size personal injury firm for four years. The firm had 25 attorneys, a strong regional reputation, and a monthly marketing budget of $300,000 spread across seven lead vendors. By any external measure, the firm was doing well.

But Marcus had a problem he couldn't solve with the tools he had. Every month he spent roughly 15 hours pulling vendor reports, reconciling lead counts against intake records, and building a spreadsheet that showed the same thing it always showed: cost per lead, lead volume, and a rough estimate of conversion rates that was only as accurate as intake's manual tagging. Which was, in his estimate, about 65%.

He could tell the managing partner how many leads came in. He could tell him what each lead cost. What he could not tell him was what each vendor's leads actually cost the firm per signed case — and the managing partner had started asking that question directly.

The Before State: Seven Vendors, $300K per Month, and a Spreadsheet

Marcus's vendor portfolio was typical of a growing PI firm. Two digital agencies managing Google Ads and Local Services Ads, three direct lead aggregators covering auto accidents, slip-and-fall, and general personal injury, a TV and media buy, and a referral network partnership. Total: seven vendors, $300,000 per month.

His monthly report showed the following cost-per-lead numbers:

• Vendor A (Google Ads agency): $145 CPL, $48,000/month
• Vendor B (direct aggregator, auto): $62 CPL, $45,000/month
• Vendor C (direct aggregator, general PI): $38 CPL, $42,000/month
• Vendor D (LSA agency): $97 CPL, $35,000/month
• Vendor E (direct aggregator, slip-and-fall): $44 CPL, $40,000/month
• Vendor F (TV and media): $210 CPL (estimated), $52,000/month
• Vendor G (referral network): $285 CPL, $38,000/month

Based on these numbers, Vendors B, C, and E looked like the portfolio stars. Low cost per lead, high volume. Marcus had increased Vendor C's budget twice in the prior year based on this data.

Vendor G, at $285 per lead, looked like a candidate for the cutting room floor. Marcus had raised the question of eliminating it in two consecutive quarterly reviews.

He was, it turned out, drawing almost exactly the wrong conclusions.

Implementation: Two Weeks to Real Numbers

The firm's revenue intelligence setup took just under two weeks. The LeadDocket integration was the foundation — the platform connected directly to the firm's existing intake CRM, pulling lead source data, disposition records, and signed case dates automatically. No manual matching. No 65% attribution accuracy. Native integrations with LeadDocket and other major PI CRMs mean clean source-tagged data from day one.

Within 14 days, Marcus had clean attribution on every lead going back 18 months. For the first time, he could calculate cost per signed case by vendor — not an estimate, not an approximation based on partial intake data, but an exact number calculated from verified spend and verified signed case counts.

The numbers were not what he expected.

Month 1 Discovery: The Low-CPL Vendors Were the Most Expensive

The first cost-per-case report changed everything. Here is what the data showed:

• Vendor B (direct aggregator, auto): $62 CPL, $4,200 cost per signed case. Lead-to-sign conversion rate: 1.5%.
• Vendor C (direct aggregator, general PI): $38 CPL, $4,750 cost per signed case. Lead-to-sign conversion rate: 0.8%.
• Vendor E (direct aggregator, slip-and-fall): $44 CPL, $3,950 cost per signed case. Lead-to-sign conversion rate: 1.1%.
• Vendor D (LSA agency): $97 CPL, $1,940 cost per signed case. Lead-to-sign conversion rate: 5.0%.
• Vendor A (Google Ads agency): $145 CPL, $1,810 cost per signed case. Lead-to-sign conversion rate: 8.0%.
• Vendor F (TV and media): $210 CPL (estimated), $2,200 cost per signed case. Conversion: 9.5% (higher intent driven by brand awareness).
• Vendor G (referral network): $285 CPL, $1,425 cost per signed case. Lead-to-sign conversion rate: 20%.

The vendors Marcus had been scaling — B, C, and E — were the most expensive in the portfolio on the only metric that matters. Vendor C, the lowest cost per lead at $38, was producing signed cases at $4,750 — 3.3x more expensive than Vendor G, which Marcus had nearly cut entirely.

The referral network looked expensive on CPL because it was. But referral leads converted at 20% — one in five. The firm was spending $285 to get a lead that became a client one out of five times. The direct aggregator leads at $38 were converting at less than one in a hundred.

Months 2 and 3: The Case Quality Layer

The cost-per-case data was already enough to warrant a reallocation. But three months into the implementation, a second layer of data started becoming available: settlement outcomes on cases that had closed in the prior 12 months. This is the data that most PI firms never see — and it was about to make the picture even clearer.

Settlement value by vendor source told a story that reinforced the cost-per-case findings:

• Vendors B, C, and E (the low-CPL aggregators) were producing cases with average settlement values of $28,000–$34,000. After attorney fees and case costs, net to the firm was roughly $9,000–$11,000 per case.
• Vendors A and D (the digital agencies) averaged $78,000–$92,000 in settlement value. Net to firm: approximately $26,000–$31,000 per case.
• Vendor G (the referral network Marcus had nearly eliminated) averaged $134,000 in settlement value. Net to firm: approximately $44,000 per case.

A signed case from Vendor C cost $4,750 to acquire and netted the firm roughly $10,000. A signed case from Vendor G cost $1,425 to acquire and netted the firm roughly $44,000. The difference in return on investment between those two sources was not a matter of degree — it was a different business entirely.

Marcus had been optimizing for cost per lead. Cost per lead was pointing him in exactly the wrong direction.

The Decision: $30K per Month in Cuts, Reallocated to the Right Vendors

Armed with cost-per-case and settlement attribution data, Marcus brought a reallocation proposal to the managing partner. For the first time in four years, the conversation wasn't about leads or click-through rates or vendor relationships. It was a financial presentation: here is what each vendor costs us per case, here is what each vendor's cases net us in settled revenue, here is the reallocation that maximizes return on the $300,000 we are already spending.

The proposal was specific:

• Cut Vendor B by $15,000/month— reduce from $45,000 to $30,000, keeping only the highest-performing campaigns within the vendor's portfolio where cost per case was closer to $2,800.
• Cut Vendor C by $15,000/month — reduce from $42,000 to $27,000. Despite having the lowest CPL in the portfolio, cost per case was the highest. Keep only the campaigns with acceptable conversion rates.
• Increase Vendor G by $15,000/month — scale the referral network that was producing the lowest cost per case and the highest case quality. From $38,000 to $53,000.
• Increase Vendor A by $15,000/month — scale the Google Ads campaigns where cost per case was $1,810. From $48,000 to $63,000.

Total monthly spend: unchanged at $300,000. The managing partner approved the reallocation the same day. He later told Marcus it was the clearest marketing presentation he had ever received — because it was the first one that spoke his language. Cost per case and net revenue, not leads and click-through rates.

The Results: $180K in Annualized Savings and a Different Reporting Life

The $30,000 per month in budget shifts from high cost-per-case vendors to low cost-per-case vendors translated directly into measurable outcomes within one quarter:

• $30,000/month in recovered vendor efficiency — the reallocation produced approximately the same number of signed cases from the same total spend, but with a meaningfully lower average cost per case across the portfolio. Annualized: $180,000 in spend no longer going to vendors producing $4,000+ cost-per-case outcomes.
• Signed case count held steady — the fear that cutting high-volume aggregator spend would reduce signed cases did not materialize. Lower-volume, higher-converting sources replaced the lost volume almost exactly.
• Average case quality increased — with more budget flowing to Vendor A (Google Ads) and Vendor G (referral network), the average settlement value in the pipeline increased. Cases take 12–18 months to settle, so the full financial effect will compound over the next two years.
• Reporting went from 15 hours per week to 15 minutes. No more manual export-and-reconcile cycles. No more 65% attribution accuracy. The platform connected spend to cases automatically, and Marcus's weekly check-in became a 15-minute scan of the performance dashboard.
• The managing partner now receives a monthly cost-per-case report — one page, vendor by vendor, with trend data. He no longer asks for it. It arrives before he has to ask.

What Would Have Happened Without Revenue Intelligence

This is the part worth sitting with. Without cost-per-case attribution, Marcus was on track to continue scaling Vendor C — the $38 CPL vendor that was actually costing the firm $4,750 per case. He was on track to eliminate Vendor G — the referral network that was producing signed cases at $1,425 and netting the firm $44,000 per case. Both of those decisions were supported by the available data. Both were wrong.

The problem was not that Marcus was making poor decisions. The problem was that the metric he had available — cost per lead — was not correlated with the outcome that mattered. A lead that never signs is not cheap at $38. A lead that signs one in five times is not expensive at $285.

Cost per lead measures vendor pricing. Cost per case measures vendor value. Those are different things, and for this firm — and most PI firms managing multiple vendors — the gap between them was $180,000 per year.

The Broader Pattern

This is not an unusual story. In our experience working with PI firms, the vendor that looks best on a cost-per-lead basis is the worst performer on cost-per-case approximately 40% of the time. The inverse is also common: the vendor that looks most expensive on CPL is frequently the most cost-effective source of signed cases, because higher lead prices often reflect higher lead intent.

Shared lead aggregators achieve low CPL by distributing leads across multiple buyers. That lowers quality and conversion rates. Direct, exclusive digital campaigns and referral networks produce fewer leads at higher apparent cost — but convert at dramatically higher rates. The only way to know which pattern applies to your specific vendors is to track cost per case directly.

For a firm spending $300,000 per month across seven vendors, the spread in cost per case was enormous: from $1,425 to $4,750. That range is not unusual. What is unusual is being able to see it clearly enough to act on it.

What This Means for Your Firm

If you are managing $100,000 or more per month across three or more lead vendors, there is almost certainly a reallocation opportunity in your current data. The question is whether you can see it.

The math is simple. If even one vendor in your portfolio is running at $1,500–$2,000 per case above your portfolio average, and you are spending $15,000 per month with them, the annual cost of that misallocation is $30,000–$60,000. Multiplied across multiple vendors making similar comparisons, the number typically lands between $100,000 and $300,000 per year — in spend that is producing below-average returns on what is already your most significant budget line.

Marcus did not need a bigger marketing budget. He did not need more vendors. He needed to measure what was already happening and reallocate based on what the data showed. That single decision — moving $30,000 per month from vendors with $4,000+ cost-per-case outcomes to vendors with $1,400–$1,900 cost-per-case outcomes — is worth $180,000 annually without changing his total marketing investment by a dollar.

The data was always there. He just needed a system that could connect all of it.