Analytics & BI · Sales performance
Management couldn't tell which teams really worked their leads and which let them go cold — the CRM's activity counts looked busy either way. I built a lead-work-density & temperature engine, per team and per manager, that counts only real effort, tracks whether every lead is warming or cooling, and shows exactly where follow-up breaks down.
The problem
The CRM showed "activities", but it counted cancelled tasks and five-second missed calls. So a team that barely touched its leads looked just as busy as one that worked them hard — while leads quietly went cold and nobody noticed until the deal was lost.
First, count only real work
Only finished actions of the right categories count. Cancelled and rejected tasks are dropped.
Only outbound client calls with over 30 seconds of conversation. Missed and short calls don't pad the score.
Incorrect and technical leads are flagged out, so a team's numbers aren't inflated by junk records.
What I built
Leads, activities, calls, visits and test drives are cleaned into real-effort facts per lead. A temperature engine then snapshots every lead every day, normalizes its funnel stage to a 0–1 scale, and compares it to where it was a week ago — labelling it warming or cooling.
Everything rolls up into a scorecard per team and per manager: how hard they work each lead, how fast they follow up, and whether their leads are heating or cooling.
Lead temperature
Every day, each lead's funnel stage is scored 0–1 (negative for "interest lost") and compared with a week earlier. That single comparison sorts every lead into one of six temperature states — and the 7-day dynamics tells you whether the whole base is heating or cooling.
The result
Every team on one screen: how densely they work each lead, how fast they follow up, and whether their leads are warming or cooling. The laggards stop hiding behind padded activity.
| Team | Leads | Density | Acts/day | Follow-up gap | Temp | 7-day trend | Bad leads |
|---|---|---|---|---|---|---|---|
| Team North | 9,544 | 2.27 | 0.04 | 14.3d | 15.4% | ↓ −28.1% | 0.16% |
| Used Cars | 19,517 | 1.74 | 0.08 | 10.3d | 10.3% | ↓ −26.2% | 1.68% |
| Team Central | 3,734 | 2.25 | 0.07 | 13.5d | 11.3% | ↓ −35.6% | 2.92% |
| Team East | 3,643 | 3.45 | 0.13 | 7.8d | 11.6% | ↓ −28.8% | 1.56% |
| Team South | 2,296 | 5.57 | 0.19 | 5.8d | 6.5% | ↓ −26.2% | 0.65% |
| Team West | 1,518 | 5.05 | 0.14 | 7.1d | 7.0% | ↓ −27.5% | 0.40% |
| Team Premium | 2,562 | 3.90 | 0.10 | 13.2d | 2.5% | ↓ −23.2% | 0.16% |
| Team Flex | 216 | 0.82 | 0.02 | 25.8d | 60.6% | ↑ +12.4% | 0.74% |
| Total | 46,332 | 2.47 | 0.08 | 11.0d | 11.4% | ↓ −28.3% | 0.74% |
The point
Four hard-to-game signals combine into one objective effectiveness read per team and per manager. No more arguing about who "works hard" — the numbers say it.
The outcome
Quantified results (more leads worked, conversion lift, faster follow-up) — add real numbers.
Built to be trusted
Stack & role
Sole data engineer — metric design, the temperature algorithm, data-quality and deployment.
I'll turn your CRM activity into an honest, per-manager scorecard — real effort, lead temperature, and follow-up speed — so coaching goes where it counts.
Book a strategy call →