The PE Pricing Diagnostic: A 90-Day Checklist

Every portfolio company has pricing value to unlock. The question is whether the opportunity is large enough to justify the intervention, and which lever produces the largest return for the effort required. A 90-day diagnostic answers both questions before any resource commitment.

This checklist is the diagnostic, in the sequence we run it.

What's at stake

At any given time, an operating partner is sitting on 8-12 portfolio companies with competing demands for pricing, sales, marketing, and product work. Trying to run full pricing engagements everywhere is financially and operationally infeasible. Trying to pattern-match without data leads to misallocated capital.

The 90-day diagnostic produces a scored prioritization across the portfolio. A portco showing 9% pocket-price leakage and no discount governance is a different investment decision than a portco with 3% leakage and tight governance. Running the same playbook on both destroys value.

Across a portfolio of eight SaaS portcos, the ROI of diagnostic work is typically 8-12x, because it redirects intervention dollars to the portcos where pricing work compounds.

The framework

1. Week 1-2: Pull the data before any meetings

Why it matters. Pricing diagnostics that start with executive interviews produce executive opinions, not findings. The data comes first.

What to do. Request 90 days of billing data, 24 months of CRM opportunity data, the current pricing page, and the last 50 renewed contracts. Cross-reference them before scheduling any interviews.

Common failure mode. Starting with a CEO interview. The CEO will describe pricing as intentional. The data will describe pricing as accidental. Run the data first, then test the narrative.

2. Week 3: Build the pocket-price waterfall

Why it matters. The waterfall is the single most diagnostic artifact. It reveals how much revenue leaks between list and collected, and where.

What to do. Quantify each leakage bucket: rep-level discounts, waived implementation fees, auto-renewing temporary discounts, extended payment terms, service credits. Rank by dollar impact.

Common failure mode. Building the waterfall at the company level and missing segment-level patterns. Enterprise leakage and SMB leakage are different problems.

3. Week 4: Audit discount governance

Why it matters. The waterfall tells you leakage exists. The governance audit tells you whether the company can stop it.

What to do. Review the deal desk workflow. Check approval thresholds. Pull the last 30 discount overrides. Quantify how many bypassed policy.

Common failure mode. Accepting the documented policy at face value. The real policy is what the workflow actually enforces.

4. Week 5-6: Diagnose packaging and tiering

Why it matters. Most mid-market SaaS portcos have packaging that looks intentional and is actually historical. Features sit in the wrong tier. Upgrade paths are unclear.

What to do. Map feature adoption by tier. Identify high-value features sitting in low-tier packages. Check whether upgrade triggers are visible to customers.

Common failure mode. Repackaging based on intuition rather than adoption data. The diagnostic work has to happen before any repackaging recommendation.

5. Week 7-8: Analyze renewal patterns

Why it matters. Renewal erosion is where quiet ARR decay hides. The diagnostic has to pull the renewal data specifically.

What to do. Pull the last 50 renewed contracts. Compare renewal ACV to prior-term ACV. Identify "loyalty discounts" and their frequency.

Common failure mode. Celebrating logo retention in the review without cross-checking net ACV retention. Logo retention can look strong while net ACV quietly decays.

6. Week 9-10: Segment the customer base

Why it matters. Pricing moves affect embedded customers and peripheral customers differently. Without segmentation, any recommendation applies a uniform lift that under-charges the embedded and over-charges the peripheral.

What to do. Build a behavioral segmentation on usage, feature adoption, and support intensity. Rank the customer base into three tiers: embedded, peripheral, at-risk.

Common failure mode. Segmenting by ACV because that's what the CRM reports. ACV is a weak proxy for price elasticity.

7. Week 11-12: Produce the prioritized action plan

Why it matters. The diagnostic ends with a ranked set of interventions tied to dollar impact and effort. Without that ranking, the findings become a slide deck that nobody acts on.

What to do. Rank interventions by expected margin impact and time-to-impact. Present the top three. Flag the risks. Recommend which can be internally run and which need external support.

Common failure mode. Producing a 40-page findings document with no prioritization. The CEO reads the first two pages and moves on.

Diagnostic questions

• Have you pulled 90 days of billing data before the first executive interview?
• Can you quantify the pocket-price gap in dollars, not percentages?
• Does the documented discount policy match what the workflow actually enforces?
• Are high-value product features correctly placed in tier structure?
• Does net ACV retention match the logo retention the board is hearing?
• Have you segmented the base by behavioral embedment, not just by ACV?
• Does the final deliverable rank interventions by dollar impact and effort?

Immediate next steps

• Request the four data sets (billing, CRM, pricing page, renewals) from your priority portco this week
• Schedule the CFO-CRO diagnostic meeting for week 4, after the data work is done
• Block the diagnostic timeline on the operating partner calendar: 90 days, non-negotiable
• Decide the output format before starting: a prioritized three-item plan, not a 40-page report

Common mistakes

• Starting with executive interviews. A $40M ARR portco diagnostic began with a CEO interview describing pricing as "fundamentally strong." The subsequent data pull revealed 11% pocket-price leakage. The interview-first sequence wasted two weeks.
• Missing segment-level patterns. A $55M ARR portco diagnostic produced a company-level waterfall that missed an 18% leakage rate specifically in the mid-market segment.
• Accepting documented policy as real policy. A $30M ARR portco had a documented 10% discount approval threshold. The actual override rate was 34%. The documented policy was theater.
• No prioritization in the deliverable. A $45M ARR portco received a 60-page diagnostic with 14 recommendations. The team implemented none of them because nothing was ranked.

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Run the free assessment or book a consultation to apply this framework to your specific situation.