Confidence Scoring
Each dormant detection includes a confidence score (0–100%) that tells you how reliable the signal is. Scores are calculated deterministically from your job data — no AI, no black boxes.
No Contact detector
Section titled “No Contact detector”Fires when: No completed job in 12+ months.
Confidence is based on recency and history depth:
| Condition | Base score |
|---|---|
| Last job 12–15 months ago | 70% |
| Last job 15–24 months ago | 85% |
| Last job 24+ months ago | 95% |
| +10% if client had 3+ jobs before going dormant | Bonus |
| +5% if client had 5+ jobs before going dormant | Bonus |
A client with 6 jobs who last booked 18 months ago scores 90% (85 + 5 for 5+ jobs).
Price Erosion detector
Section titled “Price Erosion detector”Fires when: Average job value dropped 30%+ compared to earlier jobs.
Confidence considers the size and consistency of the decline:
| Condition | Base score |
|---|---|
| 30–50% decline from peak | 65% |
| 50%+ decline from peak | 80% |
| Decline sustained across 3+ jobs | +15% |
| Only 2 total jobs (one big, one small) | Cap at 50% (may be scope change, not erosion) |
A client with 5 jobs averaging $2,000 who last two averaged $800 (60% drop) scores 80% (80 + 0, since sustained needs more jobs).
Seasonal Lapse detector
Section titled “Seasonal Lapse detector”Fires when: Client who previously booked in a specific season missed their usual window.
Confidence depends on how many seasons of data exist:
| Condition | Base score |
|---|---|
| Missed 1 expected season, 2+ years of history | 60% |
| Missed 2+ consecutive expected seasons | 85% |
| Only 1 prior season on record | Cap at 50% (not enough history) |
| Client had exact month +-1 week multiple times | +10% |
A client who booked every April for 4 years but missed this April scores 85% (60 + 25 for 4 years of data).
Handling false positives
Section titled “Handling false positives”If a detection doesn’t make sense for your market:
- Dismiss the detection — it stays hidden unless you manually re-run detection.
- Dismissed clients may re-appear on future scan if the signal strengthens.
- You can also adjust detection parameters (coming in a future update).
Why deterministic scoring matters
Section titled “Why deterministic scoring matters”No AI means:
- Results are identical every run — no hidden prompt changes
- Zero cost — no LLM tokens burned on detection
- Auditable — you can verify the math against your own job history
- Instant — detection runs in milliseconds, even at 5,000 clients
Related
Section titled “Related”- Dormant Detection — overview of all three detectors
- Importing CSV — add more job history for better scores