Before you buy a tech company,
know which problems you can fix — and which ones you can't.
This report compares revenue process benchmarks across five tech subsectors — side by side, on the same six dimensions. You'll know which gaps are structural and fixable post-acquisition, which are market characteristics that won't change, and which value creation lever to pull first in the 100-day plan.
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What you'll be able to do after reading this
Six things no other benchmark gives you. Each one answers a question that matters during diligence, in a board meeting, or in the first 100 days post-close.
Tell the difference between fixable and structural
A cybersecurity company's 38% POC close rate is fixable in 3–6 months. A telecoms company's 11-month deal cycle is not. The report shows you how to tell the difference — across all five subsectors, on the same framework.
Stop comparing telecoms targets to SaaS benchmarks
Magic Number ranges from 0.38x (telecoms) to 0.64x (SaaS). Quota attainment from 48% to 70%. These are not management failures. They're different markets. The report gives you the right benchmark for each one.
Know which value creation lever to pull first
Pricing change: 90 days. Pipeline qualification: 3–6 months. Signal redesign: 6–9 months. The report sequences each lever by time-to-impact and EBITDA effect — so your 100-day plan starts with the highest-return fix.
Run a revenue process DD in 18 questions
If a target can't answer these 18 questions, their revenue process was never designed. That's more risk than the topline suggests. The full checklist is in the report — ready to use in your next data room review.
See the same root cause play out across three sectors
Three case studies. Cybersecurity, fintech, vertical SaaS. Different symptoms. Same Dimension 1 root cause. The report shows how one upstream break creates different downstream failures — and what to look for in your portfolio.
Score M&A readiness on a 6–30 scale
25–30 = acquisition-ready. 18–24 = operational gaps. 12–17 = structural issues. 6–11 = turnaround. The report maps each band to typical multiples and hold-period requirements so you can price the fix into the deal.
Four things this report will change about how you evaluate deals
Preview of what's inside. Each finding changes a question you'll ask in diligence.
Revenue process breaks are fixable. Market characteristics are not.
A 38% POC close rate in cyber is a signal architecture problem. Fixable in 3–6 months. An 11-month deal cycle in telecoms is how that market works. Priceable, not fixable. The report gives you the framework to tell the difference — before you sign the LOI.
Conversion efficiency varies 3× across subsectors — and that's normal
Magic Number: 0.38x in telecoms, 0.64x in SaaS. Quota attainment: 48% to 70%. These aren't management failures. They're different sales motions. A telecoms target at $420K per AE is median. The same number in SaaS is top quartile. The report shows the right comparison for each sector.
Pricing model change is the fastest value creation lever — 90 days to revenue impact
In every subsector, shifting from per-seat to the right model adds 14–30 points of NRR. For a $20M ARR company, that's $2.8M–$6M in annual revenue — from customers you already have. No new sales hires. No product changes. The report shows which model works in each sector.
The root cause is upstream in 70% of cases — but the symptom always shows downstream
Signal architecture or pipeline structure is the actual root cause in ~70% of companies with revenue process problems. The symptom shows up in conversion, pricing or forecast accuracy. Fixing Dimension 4 without diagnosing Dimension 1 wastes 6–12 months of your hold period.
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18 questions for your next data room review
If a target can't answer these, their revenue process was never designed. That's operational risk the topline doesn't show. Full checklist in the report.
D1 Signal Architecture
Can the CRO name their highest-converting signal source and what share of pipeline it generates? Or is signal detection accidental?
D2 Pipeline Structure
What's the pipeline contamination rate? Can they tell stale deals from time-locked ones? Is staging built for their sales motion — or copied from a template?
D3 Conversion Mechanics
Does win rate analysis exist by deal size, stakeholder count and source? Is quota set against sector benchmarks — or generic SaaS averages?
D4 Pricing Realisation
Is pricing aligned to how the buyer measures value? Which model drives highest NRR? Does expansion happen automatically — or need a sales motion every time?
D5 Retention & Expansion
Is GDR tracked by cohort? What share of NRR is automatic versus sales-driven? Do they know which customer profiles expand and which plateau?
D6 Process Discipline
What's forecast variance over the last four quarters? Is revenue split by new logo versus expansion? Can they explain their forecast method — or does the number just come out of the CRM?
🚩 RED FLAG: If the data room has pipeline and revenue data but no win rate by source, no contamination metrics and no cohort-level retention — the revenue process was never designed. The operational risk is higher than the numbers suggest.
From benchmark to portfolio action
This report shows where each subsector stands. The Portfolio Diagnostic shows where each of your companies stands — and what to fix first.
This Report Gives You
The Portfolio Diagnostic Adds
Portfolio Diagnostic
Each portfolio company scored against its subsector. Dependency maps. Value creation levers sequenced. Board-ready roadmap. Delivered by Michael Williamson — 25 years of P&L accountability across O2/Telefónica, Vodafone, Symantec and Equifax.
Enquire About a Portfolio Diagnostic →Or email directly: Michael.Williamson@techgrowthinsights.com
"The report tells you where the market stands. The diagnostic tells you where your companies stand — and which gaps are yours to fix."— Michael Williamson · TechGrowth Insights