Leads routed to reps who left. Duplicates inflating the forecast. Deals closed but never billed. None of it reaches your forecast, so nobody has counted it. The average finding is $220,000 per quarter. We find it. We price it. We fix one.
Guaranteed: $250,000 found and one fix delivered, or you pay nothing
$220Krevenue leak found per quarter
78%of AI tools run on bad data
18%of won deals with no approved quote
Signal 2 of 10 · Lead routing
The other nine signals cover attribution, duplicates, stage discipline, quote approval, billing lag, renewals, and enrichment.
One engagement. Company anonymized under NDA.
Free, no signup
See What Is Visible From Outside.
We read your public web tags and DNS records and name the Go-to-Market tools we can identify from outside. The useful part is what we cannot see: seats, adoption, contract value, and every forecasting and quoting tool in your stack. That gap is what the audit reads.
No install, no upload, no email required. We read what is public, then tell you what it means.
Your resultWaiting
Enter your domain to see what's visible from outside.
Takes a few seconds. Nothing is stored.
— to —your benchmark range
—tools visible
46 to 60
Companies your size typically run 46 to 60 GTM tools. Most leaders can name maybe 20, and cannot say which overlap.
Seats, contracts, logins, and the forecasting and quoting tools that leave no public trace are invisible from outside. That is what the audit reads.
8tools visible from outside. The rest is what the audit reads.
We will show you what the audit finds in the rest of your stack. No pitch.
Want the full breakdown and the tools we found?
Optional. The scan above is yours to keep either way.
What we found
How we read your stack
We read three things from public signals: how much of your stack we could account for, whether any category has duplicate tools, and which foundations are present.
What we cannot see
Estimated from public signals. It can miss tools and can flag one you already cancelled.
Four more free tools, no signup.Accounts Payable analyzer reads your finance export and finds ghost tools you are still paying for.
·Lead-to-Cash health score scores where revenue leaks between your tools.
·AI readiness score scores whether your stack can support the AI you are about to buy.
·AI visibility audit reads what ChatGPT and Perplexity say about you.
The Problem
Three Problems Nobody Has Priced.
Every Go-to-Market leader is dealing with these right now. You own the systems that generate revenue, and nobody has put a dollar figure on what they are losing.
Revenue Leaking Quietly
Leads routed to reps who left
Leads arriving with no lead source
Duplicates inflating the pipeline
Deals closed but not yet billed
Your forecasting tool never sees any of this
Tool Sprawl Nobody Can See
Tools inherited through acquisitions
Subscriptions bought on credit cards
Auto-renewals happening silently
Seats paid for and never used
Nobody owns the complete picture
Your AI Initiative Will Miss Its Number
New leads land behind a broken routing rule
Scoring models trained on duplicates
Enrichment on an expired API token
No measurement of revenue impact
The growth target is real. The foundation under it is not.
Why This Quarter
You Are About to Pour High-Octane Fuel Into a Car That Needs an Oil Change.
Your AI initiative is funded and the growth number is committed. Here is the arithmetic nobody ran before the budget was approved.
01
AI does not clean your data. It multiplies it.
Every AI tool in the Go-to-Market stack either raises volume or automates a decision, and both run on whatever is already in your CRM. A content engine that doubles inbound sends twice as many leads into the same routing rules. A scoring model trained on a 12% duplicate rate scores the same person twice.
02
The defect rate holds. The volume goes up.
If 18% of qualified leads sit unworked today, that percentage does not improve when volume doubles. It applies to a bigger number. The better your AI programme performs at the top of the funnel, the more expensive the leak underneath it becomes.
03
The programme misses, and nobody can say why.
The CRO promised 10%. It lands at 4%. The postmortem blames the vendor, the model, or adoption. The actual cause was three routing rules and a duplicate merge rule that nobody looked at, because looking at them was not anyone's project.
04
This is not a competing project. It is insurance.
Three weeks and $15,000 against a multi-quarter programme with a seven-figure budget. It delays nothing, because the fixes are measured in hours and sequenced ahead of a rollout measured in quarters.
78%of companies that have bought an AI Go-to-Market tool score below 5 out of 10 on data quality. The tools are not the problem. The inputs are.
The Audit
Five Components. One Report.
Delivered in three weeks. Each component informs the next: the Lead-to-Cash signals explain the AI Readiness gaps, and Stack Discovery feeds the Return on Investment Scorecard. A system, not a checklist.
1
Lead-to-Cash Health Score
10 Salesforce health signals audited via secure read-only access. Every red signal gets a dollar-value revenue impact estimate. This is where the largest numbers come from.
Complete inventory from Accounts Payable, single sign-on, contracts, and shadow interviews. Every tool: cost, users, integrations, renewal date.
3
Return on Investment Scorecard
Every tool scored on usage, impact, integration depth, and cost. Keep, Review, or Cut per tool, with a dollar value on each call.
4
AI Readiness Score
Three-dimension assessment: data quality, integration depth, process maturity. Tells you what will break your AI rollout before you spend the budget on it.
30, 60, and 90-day prioritized action plan with savings estimates and change management messaging per tool. One item on it is already done when we hand it over.
How It Works
Three Weeks. Five Hours From You.
And one fix live before we leave. You end with a dollar figure on every finding, a roadmap ranked by effort, and the highest-value item on it already done. No engineering work, read-only access only.
$250,000 Found. One Fix Delivered. Or You Pay Nothing.
Combined annual tool savings and recoverable pipeline. And you do not walk away holding a to-do list. Before the engagement ends we implement the highest-value fix we find, so you have a result in hand and not just a report. Backed by 15 years of doing this work at real companies.
Best fit: $30M+ revenue, 25+ Go-to-Market tools, and an acquisition, a new CRO or CMO, or a raise in the last 18 months
A Real Example
The same engagement, in full.
One engagement, company anonymized under NDA
$110M software company. The routing leak was the largest finding. It was not the only one.
We ran ten diagnostic checks against their Salesforce database. The routing rules still pointed at reps who had departed after an acquisition 14 months earlier. Every lead assigned to those queues went unworked from the day it arrived. Nobody had noticed, because the leads never became opportunities, so they never showed up in a forecast or a revenue leakage report. The fix: update four routing rules. Two hours of work, done before we left.
Then we pulled the Accounts Payable export. Right there: Salesloft. 85 licenses. $38,000 per year. But the company uses Outreach for sales outreach. Cross-referencing the single sign-on system showed 12 active users, 14% adoption. The tool came with the same acquisition. IT thought Marketing owned it. Marketing thought IT owned it. Cancel this month. Zero migration. $38,000 back.
312
Leads routed to departed reps, fixed in 2 hours
$3.6M
Pipeline now being worked that was invisible
$38K
Duplicate sales tool, cancelled same day
$136K
Additional tool savings in Year 1
Total Year 1 impact
Tool savings + recoverable pipeline
$3.77M
Pricing
Lead-to-Cash Diagnostic
$2,500
one week
Test the methodology before you commit to the full audit. We run the ten health signals against your CRM and come back with a number on each.
For companies too complex for a flat audit, built through acquisitions, running 100+ products, or needing execution alongside the diagnosis, not just a report.
✓All five audit components, scoped to your structure
Best fit for Enterprise: $500M+ revenue, multiple acquisitions, or a stack this audit alone won't fully size.
Built by an operator who spent 15 years doing this manually.
For fifteen years I ran Go-to-Market technology at Freshworks, Amazon, and TikTok, which mostly meant being the person asked to justify $2M in tool spend with a spreadsheet and a weekend. I built Prune so that answer takes three weeks instead of three months, and comes with numbers instead of opinions.
"I spent fifteen years managing Go-to-Market tech stacks at some of the world's fastest-growing companies. Every year I wished there was a way to know which tools were actually earning their place. There was not. So I built it."
Gaurav Palande · Founder, Prune
$100M+
ARR impact from end-to-end Go-to-Market system transformations
$8M+
Annual savings identified and captured across engagements
30+
Industry-leading Go-to-Market tools governed at scale
15 yrs
Operator experience running the stack, not advising it from outside
Where that experience came from
Freshworks
Amazon
TikTok
Synopsys
Apple
Polycom
At Atlassian, the Head of Lifecycle Marketing Operations hired a full-time Go-to-Market Architect. It took that person three months just to document their lead flows and present findings to leadership. That is the standard approach today: expensive hire, long ramp, one company's data. Prune delivers the same readout in three weeks, with dollar values on every finding, and a guarantee behind it.
Presented at Demand & Expand, May 2026
What People Ask Before Saying Yes.
No, and you should keep all three. Clari scores the deals that made it into your pipeline. Gong analyzes the conversations that happened. Zylo tells your CFO what the stack costs. Prune finds the revenue that never entered any of them.
A lead routed to a rep who left never becomes an opportunity, so it never enters a forecast and no revenue leakage report will surface it. The same applies to duplicate records inflating your numbers, leads arriving with no source attached, and closed deals waiting on a manual billing step. Those sit upstream of everything a forecasting tool measures. Most clients keep what they have and use Prune to make sure the data feeding it is real.
Yes. The ten health signals are Lead-to-Cash concepts, not Salesforce features. Null lead source, routing lag, duplicate rate, stage distribution, closed-won completeness, contract-to-billing lag, renewal visibility and enrichment coverage all exist in HubSpot and are all readable through its API. Only the query syntax changes.
That is common at enterprises and it does not block the audit. There are three ways to run it, and you pick:
1. Read-only integration user. Fastest. Fifteen minutes to set up, no write permissions at any point.
2. You run it, we interpret it. We send your admin a query pack, they run it inside your environment, and they send back the results. Prune never receives access to your CRM.
3. Screen share. Your admin runs the queries live while we take notes. Nothing leaves your environment at all.
Option two is what most security-conscious companies choose, and it produces the same findings.
Yes. We use read-only access only. We never write to, delete from, or modify your Salesforce or marketing automation system. Finance and single sign-on data is exported by your team and shared directly. We sign a mutual non-disclosure agreement before any data is shared, and all client data is deleted 90 days after the engagement closes.
Because it reads two public sources. The vendor tags on your web pages surface marketing automation, chat, scheduling, analytics and intent tools. Your DNS records, specifically the SPF entries that authorise services to send email for you, surface your CRM, sales engagement, e-signature, billing and support tools. Together that is a good share of a typical stack.
What it cannot see is the part that costs you money: how many seats you bought, how many people actually log in, and what each contract is worth. It also misses forecasting, quoting and reporting tools, which neither send email nor appear on your website.
Three short asks close the gap: an Accounts Payable export from Finance (5 minutes) reveals every tool you actually pay for, a single sign-on export from IT (5 minutes) turns that list into an adoption picture, and a read-only Salesforce user from RevOps (15 minutes) runs the ten Lead-to-Cash signals. That is why the audit carries a guarantee and the free scan does not.
The full five-component audit is $15,000, flat, delivered in three weeks. That is the price regardless of how large your stack turns out to be or how much we find.
If you want to test the methodology on one component first, a targeted diagnostic is $2,500 and the fee is credited in full if you continue to the audit. We do not bill hourly and we do not take a percentage of what we find, because a fee tied to the size of the finding gives us a reason to inflate it.
This is the fair version of the objection, and it is why the highest-value fix is implemented inside the engagement rather than handed to you as a recommendation. You end with a result, not a backlog.
Beyond that, the roadmap is deliberately sequenced by effort. The findings that produce the largest numbers are usually the cheapest to fix: a routing rule, a duplicate merge rule, a validation rule on Close Won, an expired enrichment token. The 30-day column is measured in hours of work, not quarters. What sits in the 90-day column is optional and clearly marked as such.
Do both, in that order, and do not slow the AI initiative down for it.
The reason is arithmetic. An AI content engine that doubles inbound volume sends every new lead into the same routing rules, the same duplicate records, and the same enrichment gaps that are already there. If 18% of qualified leads are sitting unworked today, that percentage does not improve when volume goes up. It compounds. Three weeks of diagnosis ahead of a multi-quarter AI programme is not a competing project. It is what makes the growth number the programme was funded against achievable.
The highest-value fix is included in the audit. Beyond that, once we have identified what to cut, consolidate, or repair, we can help you get it done. Scope and pricing depend on what is needed, and we will talk through it after the readout.
Zylo and CloudEagle tell your CFO what the stack costs, and help negotiate contracts. Prune tells your Go-to-Market Technology leader what it earns, and where your pipeline is breaking. Different buyer, different question, different output. Most companies benefit from both. Zylo surfaces the spend number; Prune builds the business case for what to do about it.
You pay nothing. The threshold covers annual tool savings and recoverable pipeline combined, and it is grounded in 15 years of running this analysis at real companies. At any software company above $30M revenue with 25 or more Go-to-Market tools, we have consistently found well above it. If your situation looks like it may not qualify, we will tell you before you pay anything.
Prune is a Go-to-Market Stack Intelligence company using a service-led approach right now. Every audit builds the benchmark dataset that makes the next audit sharper. We are building toward a continuous monitoring platform on Salesforce. Clients who sign today receive the human-expert version of something that will eventually run automatically. The methodology, the benchmark data, and the guarantee are the same regardless.
Find out what your forecast is missing.
Twenty minutes. We will walk you through what we find in systems like yours and what it is usually worth. Then you decide if you want the full read.