Wovly · Benchmarks for B2B SaaS

Benchmark your sales performance. Privately.

The first benchmarking platform for B2B SaaS sales teams using differential privacy to make individual company data mathematically impossible to reverse-engineer. Connect Salesforce or HubSpot, see real-time benchmarks against your true peers, and contribute data that even we can't read.

Native Salesforce & HubSpotSOC 2 Type IIDifferentially private, ε published
The problem

Every CRO is flying blind.

01The QBR

You walked into your last QBR and tried to explain a 24% win rate. Was that good? Bad? Normal for your stage and ACV? Nobody at the table actually knew.

02The “benchmarks”

The benchmark reports you've seen are self-reported surveys from a few hundred companies, published once a year, with cohorts so broad they're meaningless. Series A averaged with public companies. Horizontal SaaS with vertical.

03The locked truth

Meanwhile your CRM holds the answer for the entire market. It's just locked inside thousands of separate Salesforce and HubSpot instances that nobody is willing to share. Until now.

The product

Real benchmarks. Real cohorts. Real time.

Cohorts that actually match you

Slice benchmarks by ARR band, ACV, sales motion (PLG, inbound-led, outbound-led), buyer segment, and vertical. See yourself against 30–60 companies that look like you — not 800 companies that don't.

ARR · ACV · motion · segment · vertical

The metrics that matter

Win rate by stage, sales cycle length, pipeline coverage ratios, ramp time for new AEs, discount depth, deal slippage, multi-year deal frequency, competitive win rates, ACV trends. The numbers your board actually asks about.

9 core metrics · refreshed continuously

Connect once, updated continuously

Native Salesforce and HubSpot integrations. No CSV uploads, no monthly survey emails. Benchmarks refresh as the market moves — hourly for most metrics, daily for slow-moving cohorts.

Hourly refresh · zero manual upload

Built for RevOps, trusted by Security

Read-only access. Scoped permissions. SOC 2 Type II. Deployable as a customer-hosted connector if your security team requires it. The connector is documented before you click install.

SOC 2 Type II · GDPR · customer-hosted option
The privacy layer

Your data goes in. Your data does not come out.

A mathematical guarantee, not a promise.
Data flow · simplified
ε = 1.0  ·  δ = 10⁻⁹  ·  (ε, δ)-DP
01 · Source
Your CRM
Read-only connector reads opportunity, account, and stage history. No raw data persists.
salesforcehubspot
02 · Synthesis layer
Differential privacy & aggregation
Per-contributor noise calibrated to bounded sensitivity. Outputs a statistical synthesis of the pool, not a transformation of your records.
Laplace mechanismcomposition trackingk-anonymous cohorts
03 · Output
Cohort benchmarks
Aggregate truth, win rates, cycle lengths, conversion curves, for the cohort that matches you.
N ≥ 30 cohortsrefresh 1h
For any neighboring contributions D, D′ that differ by one company:Pr[M(D) ∈ S] ≤ e^ε· Pr[M(D′) ∈ S] + δThe math closes the path back.

Most “anonymized” data isn't. Strip the company name and a determined analyst can still reverse-engineer who's who from the patterns. We don't anonymize your data. We synthesize it.

When your CRM data enters our pipeline, it passes through a differential privacy layer that generates a statistical synthesis of the entire contributor pool. The synthesis preserves the aggregate truth of the market, win rates, cycle lengths, conversion curves, with mathematically verifiable accuracy. But it makes any individual company's contribution impossible to extract, even by us, even with unlimited compute, even with access to every other company's data.

The benchmarks you see are correct. The path back to any single contributor is closed.

Mathematically provable

Differential privacy is the same standard used by the U.S. Census Bureau, Apple, and Google to protect billions of records. We publish our epsilon values.

No raw data storage

Your CRM data is synthesized at ingestion. The original records never persist on our infrastructure.

Auditable

Our privacy guarantees are documented, peer-reviewed, and verifiable by your security team before you ever connect.

The data co-op

Contribute to see. See because you contribute.

The benchmarks are only as good as the companies in them. That's why this is a co-op, not a survey. You connect your CRM, contribute your data to the synthesized pool, and get full access to the benchmarks in return.

Every new contributor sharpens the picture for everyone. Companies that don't contribute don't get access. Period.

Contributing companies
+14 this week
340
Opportunities benchmarked
closed + open, trailing 24mo
2.8M
Pipeline in synthesis pool
live aggregate
$12.4B
Distinct cohorts available
N ≥ 30 minimum
87
Live · synthesizingupdated 14:32 UTC
Use cases

What CROs use this for.

Board prep

Walk in with cohort context for every metric.

Replace defensiveness with a credible plan. Show the board where you sit in your true peer group and what gap you're closing, with the math behind it.

“Our win rate is 28%, the cohort median is 31%, and here's our plan to close the gap.”
Forecasting

Calibrate against this quarter, not last year.

Anchor your pipeline coverage and conversion assumptions to what's actually happening in the market right now, not an industry survey published 9 months ago.

“Cohort coverage ratio is 3.6×. We're at 3.2×. Forecast haircut: −12%.”
Sales ops

Diagnose execution vs. market.

When ramp times slip or discount depth jumps, find out whether it's your team or the whole market shifting. Stop blaming the wrong thing.

“Discount depth is up 4pts. Cohort is up 5pts. Not us, market.”
Connects with
Salesforce
HubSpot
Compliance
SOC 2 Type II
GDPR
CCPA
ISO 27001 · in progress
Backed by
Investor One
Capital Two
Founders Three
Early access

The market knows your numbers.
Now youcan know the market's.

We're onboarding design partners now. Cybersecurity, devtools, and vertical SaaS companies at Series B and later get priority access.

Differentially private from day one · ε published