How to Calculate ₹ at Risk for Your Sales Pipeline
TL;DR
Formula: (avg deal value × grade conversion rate) summed over overdue leads. For 10-rep Indian B2B SMB: typically ₹2–5 lakh weekly baseline. Compute manually for 2 weeks; automate with Leadkaun past that.
The bet behind the playbook.
₹ at risk is the single metric that turns sales reviews from activity debates into money conversations. It makes abstract 'overdue follow-up' concrete. Reps work differently when they see their own number. Managers coach differently. Reviews become conversations about recovery.
Gather these before you start.
- 90 days of closed-won deal data
- Grade system in place (even manual)
- Defined staleness SLA per grade
Run it in order.
- 01
Compute avg deal value per industry
Pull last 90 days of closed-won. Sum deal values ÷ count. Example: real estate team sees avg GCV ₹45 lakh.
- 02
Compute conversion rate per grade
For each grade, count leads that closed ÷ total leads at that grade over same 90 days. Example: Grade A = 10%, Grade B = 5%, Grade C = 2%.
- 03
Compute ₹ per stale lead by grade
Multiply avg deal value × conversion rate. Grade A real estate: ₹45L × 10% = ₹4.5L per stale lead.
- 04
Count stale leads by grade (per rep)
Past SLA: Grade A 24h, Grade B 48h, Grade C 7d. Count per rep.
- 05
Sum: ₹ at risk = Σ(count × ₹ per grade)
Example: 4 Grade A stale × ₹4.5L = ₹18L. Plus 8 Grade B × ₹2.3L = ₹18.4L. Total rep: ₹36.4L.
- 06
Surface in Monday manager review
Open stand-up: 'Team: ₹4.2L at risk. Priya: ₹1.8L, Rajesh: ₹1.2L, Mohan: ₹1.2L.' Discuss recovery plans per rep.
- 07
Surface in rep Morning Brief
Rep version: '₹1.8L to recover today — top 3: [lead names]'. Frame as opportunity, not blame.
Where teams usually slip.
- Using best-case deal values instead of medians — inflates the number, reps tune out
- Shaming reps publicly with the number — destroys adoption
- Tracking only ₹ at risk without pairing with ₹ recovered
Questions teams ask mid-rollout.
Keep rolling.
How to Reduce Your Lead Response Time (Speed to Lead)
Cut the gap between a lead arriving and a rep making first contact. Get every lead into one ranked place, grade it on arrival, alert the assigned rep on new Grade A, hold a response SLA per grade, and start each day on the overnight hot leads. Track first-contact time per rep and size the gap with the missed-revenue calculator.
How to Find Where You're Losing Deals in Your Pipeline
Losing deals feels random until you make it visible. Track where leads go stale by grade and stage, why deals are lost (price, competitor, no response), and which rep and source the ₹ leaks from — then fix the biggest leak first. Leadkaun turns 'we're losing deals' into a ranked, rupee-valued list.
This is the product behind the page.
Every lead graded A–F, a live Priority Queue per rep, and the ₹ at risk surfaced in real rupees — set up the same day.
Want this running automatically?
Leadkaun automates the workflow above the same day — no spreadsheet maintenance, no manual updates, no ops overhead.