Fintra Feature
Lead scoring you can actually explain
What lead scoring in Fintra does
Black-box lead scores erode trust: a rep cannot see why a lead is a 90, so they ignore the score. Fintra scores leads deterministically (six independent factors, each with a fixed maximum, summing to 0–100) and shows the factor breakdown, so every point is explainable and reps prioritize with confidence.
- Six factors: source, value, stage, recency, completeness, engagement
- A pure function of the lead’s data: reproducible every time
- A factors JSON that explains exactly why the score is what it is
- A suggested next best action grounded in what drives the score
The six factors
| Factor | Max | Example |
|---|---|---|
| Source | 15 | Referral 15, outbound 5, other 3 |
| Value | 20 | Bigger estimated deals score higher |
| Stage | 25 | Proposal 20, qualified 16, new 5 |
| Recency | 15 | Recent activity beats a cold streak |
| Completeness | 15 | Email, phone, and contact name on file |
| Engagement | 10 | More logged touchpoints, more points |
No AI dependency required
From score to action
Because the score is factor-based, Fintra can point at the specific thing to fix or do next: add the missing phone number, break the stall, follow up on a cold lead. The score is not just a ranking; it is a to-do list ordered by impact.
Questions people ask
How does Fintra score leads?
Fintra sums six independent factors (source, value, stage, recency, completeness, and engagement) each with a fixed maximum, to produce a 0–100 score. It is a pure function of the lead’s data, so the same inputs always produce the same score, and a factors breakdown explains every point.
Is the lead score a black box?
No. Unlike opaque AI scores, Fintra’s model is deterministic and factor-based, and it exposes the breakdown of how each factor contributed. A rep can see exactly why a lead scored what it did, which is why they actually act on it.
Does lead scoring require AI or an API key?
No. Scoring is computed from the lead’s own fields with no external model dependency, so it works reliably, is testable against known vectors, and never returns two different answers for the same lead.
What is a next best action?
It is the concrete step most likely to advance the lead, derived from what is driving or dragging the score, for example, adding a missing contact detail, following up after a cold streak, or moving a stalled deal forward. The score doubles as a prioritized to-do list.
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