How the score is calculated
Last updated: 22 May 2026
Short page linked from the autoresponder email and from the privacy policy, so the curious can verify the score they got.
The 8 inputs
- Connections per day — your average new connection requests sent
- Acceptance rate — % of those requests that get accepted
- Restricted recently — any account restriction in the last 90 days
- Reply rate — % reply rate on cold outbound messages
- Account count — 1 vs 2-3 vs 4+ accounts in the outbound pool
- IP rotation — none / VPN / residential / managed automation
- Personalization tier — template / first-name / AI-rewritten / manually researched
- Account age — <6mo / <1y / 1-2 / 2-4 / 4+ years
Weighting
Each input becomes a 0-10 subscore. The subscores are weighted:
| Input | Weight |
|---|---|
| Volume | 1.5 |
| Acceptance rate | 1.2 |
| Reply rate | 1.4 |
| Account pool | 1.0 |
| IP rotation | 1.0 |
| Personalization | 1.4 |
| Account age | 0.8 |
Then:
- flat -15 if the account was restricted recently
- flat +3 if Sales Nav is in use
- flat -5 if monthly tool spend > $500 AND reply rate < 5%
Final score is the weighted average normalized to 0-100.
Verdict bands
| Score range | Verdict |
|---|---|
| 0-24 | Critical |
| 25-49 | At risk |
| 50-74 | Fragile |
| 75-100 | Healthy |
Where the numeric thresholds come from
- Volume ceiling 20-25/day: derived from observed restriction events on LinkedIn outbound platforms in 2024-25
- Acceptance bands (25-35% healthy): industry baseline reported by multiple managed-outbound vendors
- Reply rate 5-12%: B2B cold LinkedIn benchmark from 2024-25 operational data (Apollo, Lemlist, Lavender)
- Restriction recovery + second-restriction interval: pattern observed on dozens of restricted accounts BIGM has touched
The thresholds are calibrated against operational data, not a single research paper. As the diagnostic accumulates more real submissions (see the Cold Outreach Cemetery for the in-progress primary dataset), the calibration will update.
What the tool does NOT do
- It does not call LinkedIn or scrape your profile. You self-report numbers; honesty in = useful out.
- It does not predict ban dates. The "ban risk: high" type language is a heuristic read on the combination of signals, not a clock.
- It does not capture data without consent. The score is computed server-side from the answers you submit; we only log the result against an email if you submit one via the email-gate form.