Sales-Led Conversion
Review lead-to-opportunity-to-win rates, lead-source differences, and email, phone, and LinkedIn outreach metrics while excluding figures with unclear origins.
Written and reviewed by Eric Han · Co-founder & CTO, reopt
Key takeaways
- Most public stage rates are old or opaque. The widely repeated 13% MQL-to-SQL figure could not be traced to an original source.
- Lead sources differ sharply. Implisit's 2014 data show 3.6% lead-to-win conversion for referrals versus below 0.1% for lead lists, events, and email campaigns.
- Follow-up emails generate 58.6% of sequence replies. Looking only at the first email understates sequence performance.
- A 0.45% reply rate is per message sent; 3.43% and 4.5% are per recipient. They are not directly comparable.
- Dreamdata reports a 272-day B2B customer journey. Short pilots cannot readily measure closed-won outcomes.
Stage Conversion
| Metric | Value | Context | Evidence |
|---|---|---|---|
| Lead → opportunity | 13%, 84 days | Hundreds of companies, 2014 | Implisit / Salesforce, C |
| Opportunity → win | 6%, 18 days | Same source | C |
| New-business win rate | 18–19% | Ebsta / Pavilion 2025, UK and US technology companies; own wording says 18%, secondary citation 19% | C |
| Sales cycle | New business 91 days; expansion 52 days | Same source | C |
Implisit's 6% and Ebsta's 18–19% differ in opportunity definitions and period; do not treat them as identical metrics. Ebsta / Pavilion 2023 also reports deteriorating 2022 trends: win rates −15%, cycles +32%, deal values −32% year over year (3.2 million opportunities, C).
Lead Sources
Implisit 2014 is old but unusually explicit about denominators.
| Source | Lead → opportunity | Opportunity → win | Lead → win | Time from lead to win |
|---|---|---|---|---|
| Website | 31.3% | 5% | — | About 75 days |
| Webinar | 17.8% | 2.5% | — | — |
| Employee / customer referral | — | — | 3.6%, highest | 97 days |
| Social | — | — | — | 40 days |
| Lead lists / events / email campaigns | — | — | Below 0.1% | — |
Excluded Figures
| Figure | Reason for exclusion |
|---|---|
| MQL → SQL 13% | Attributed variously to Salesforce and First Page Sage; not verified in either original |
| Demo-request MQL → SQL 40–60% and similar | Repeated secondary citations |
| Customer-referral win rate 40%; win-rate tables by ACV | Agency estimates without samples or methods |
| C-suite CPL $278 | The cited page does not contain the value |
Repeating a popular number can anchor the entire plan to an unsupported assumption. Prefer recent cohorts from your CRM.
Outbound
Cold Email
| Source | Value | Denominator | Sample |
|---|---|---|---|
| Belkins 2026 | 0.45% | Messages sent | 7.53 million messages, 2025 |
| Instantly 2026 | Mean 3.43%; upper quartile 5.5% | Recipients | Sample not stated |
| Hunter 2026 | 4.5% | Recipients | 31 million messages |
All come from email tools or agencies (C).
Belkins' sequence analysis reports stage reply rates of 0.59% at step 1, 0.30% at step 3, 0.34% at step 4, and 0.28% at step 6; follow-ups produce 58.6% of all replies. It states meeting conversion reaches about 0.2% after step 3, twice steps 1–2, but does not identify the denominator. Another article on the same data reports more than 1,200 meetings from 7.53 million messages, approximately 0.016% per message (calculated). This is a lower bound from “more than 1,200” and a single agency, but provides a planning starting point.
- Step 10.59%
- Step 30.30%
- Step 40.34%
- Step 60.28%
Hunter reports the following differences by campaign characteristic; they do not establish causal effects.
| Condition | Lower | Higher |
|---|---|---|
| Campaign size | 500+ people: 2.4% | 21–50 people: 6.2% |
| Custom attributes | None: 3.6% | Two: 5.6% |
| Open tracking | Enabled: 4.4% | Disabled: 7.4% |
| Number of messages | One: 3.3% | Three: 6.8% |
Comparing Channels
The source is the same Belkins article; LinkedIn reply data are from Expandi as relayed by Belkins.
| Channel | Connection / reply | Sample | Source and caveat |
|---|---|---|---|
| Phone | Connection 18.6% | Over 46,000 calls, eight projects | Belkins; denominator differs from email |
| 5.04% | 112,005 sequences, 33 projects | Belkins; denominator differs from email | |
| 0.45% | 7.53 million messages | Belkins; messages sent | |
| LinkedIn first-degree messages | Replies 12.22% | Expandi; over 15 million contacts | Connection requests: 7.95% |
| Cold calls | Success 2.7% | Cognism, over 200,000 calls | Success definition undisclosed |
Paid Inbound
A Dreamdata 2026 press release reports 12-month closed-won ROAS of 121% (1.21×) for LinkedIn, 67% (0.67×) for Google search, and 51% (0.51×) for Meta. These use the company's attribution model, and Dreamdata sells B2B attribution tools. Do not treat this as experimental channel-comparison evidence.
The customer journey is 272 days, including 220 before pipeline entry. Ad pilots are therefore too short to judge on wins. Use leading indicators such as opportunity creation initially, applying historical CRM win rates downstream.
Relationships and Win Rates
Ebsta / Pavilion 2023 reports win rates of 29% for small deals with 1–3 contacts, 48% for midsize deals with 7–9, and 42% for enterprise deals with 10–12. These are conditional associations, not causal effects.
In a survey, 67% of B2B buyers said they prefer purchasing without a salesperson (Gartner 2025 survey, n=646, via reporting). This is not conversion behavior.
Simulation Inputs
| Stage | Input | Evidence and conditions |
|---|---|---|
| Sent message → meeting | Mean 0.016%, | Belkins: more than 1,200 meetings from 7.53 million messages, calculated, C; lower bound and one agency |
| Meeting → win | Mean 18%, | Ebsta / Pavilion new-business win rate, C; opportunity-based, so a weak proxy |
| Lead → opportunity; opportunity → win | 13%, 6% | Implisit 2014, C; old data, prefer your CRM |
Do not use MQL-to-SQL 13%, demo requests 40–60%, customer-referral wins 40%, or C-suite CPL $278. Explore intervals in Worked Scenario 5.
Korean figures from Recatch include inquiry-to-meeting around 9–42.9% and opportunity-to-contract 4.04% (C), covered in Korean Cases.
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