At a glance
Executive Summary
15-month operational snapshot across all BD channels
Total leads processed
110,176
Jan 2025 – Mar 2026
15-month period
IPD conversions
2,095
Surgeries completed
↑ Best: May 2025 (526)
Overall conversion rate
1.90%
Industry avg est. 2–4%
↓ Below benchmark
Lead wastage
75,303
Junk + dead + closed
68% of all leads lost
Top performer: Mayank Panday converts at 5.21% on 1,594 leads — 2.7× the company average. His playbook should be documented and replicated across the team.
Source arbitrage: Referral leads convert at 67.6% vs. ProData at 0.17%. Yet ProData receives 12,357 leads. Reallocating even 20% of ProData spend to Referral programs could yield 40× more conversions.
Dead weight: Three BDs — Sanjana Sharma, Rajesh Kumar, Avinash Singh — collectively handled 13,419 leads and produced zero IPD conversions. This represents ₹Xm in wasted BD cost.
Data anomaly: BD 503 (Saurabh Chaudhary) shows 99.07% conversion on 324 leads — statistically impossible. Data integrity audit required before investor reporting.
Conversion pipeline breakdown
Where leads end up across 110,176 total
Monthly performance — lead volume vs. IPD conversions
15-month trajectory with conversion rate overlay
Trend
Team performance league table
Ranked by conversion rate
| # | Team Lead | BDs | Leads | IPD Done | Conv % | Junk % | Rating |
|---|
Pipeline analysis
Conversion Funnel
End-to-end lead journey from acquisition to surgery
Leads in
110K
Total acquired
Active pipeline
~3.5K
Still workable
OPD done
85
Consultations
IPD done
2,095
Surgeries
Wasted
75K+
Junk + dead
Full status distribution
All 110,176 leads by final status
Junk analysis
37,200 leads marked Junk — the single largest status. Combined with 890 Duplicates and 1,214 Invalid Numbers, 35.7% of all leads never had a chance.
Stage conversion rates
Junk→IPD: Of non-junk leads, conversion jumps to 2.98%
Pipeline leak: 15,054 leads stuck at DNP Exhausted — potential recoverable pool with re-engagement
Individual performance
BD Scorecards
Complete individual performance metrics for all business development managers
Tier 1 — Star performers (Conv ≥ 5%)
Tier 2 — Above average (Conv 2–5%)
Tier 3 — Below average (Conv 0.5–2%)
Tier 4 — Critical (Conv < 0.5% or zero)
Team intelligence
Team Analysis
Performance breakdown by team lead — efficiency, quality, and output
8
Active teams
2.69%
Best team conv
0.42%
Worst team conv
36%
Avg junk rate
Team conversion rates
IPD done as % of total leads
Team junk rates
% leads marked Junk/Dup/Invalid
Team efficiency matrix — IPD done vs leads managed
Bubble size = number of BDs in team
Detailed team comparison
Time series
Monthly Trends
Growth trajectory, conversion consistency, and seasonal patterns
Peak month (IPD)
May '25
526 conversions, 3.54% rate
Peak volume
Jan '26
25,762 leads in one month
Worst conv rate
Dec '25
0.83% — 11,873 leads
Avg monthly conv
2.19%
Across all 15 months
Monthly lead volume
Total leads acquired per month — note scale explosion in Jan 2026
IPD conversions by month
Conversion rate trend
Monthly junk lead volume
Raw volume of Junk/Dup/Invalid leads — tracks lead quality over time
Monthly data table
| Month | Leads | IPD Done | OPD Done | Junk | Conv % | Junk % | Trend |
|---|
Channel intelligence
Source Quality
ROI analysis by acquisition channel — where leads convert vs. where budget is wasted
Best source (conv)
67.6%
Referral — 34 leads, 23 IPD
Highest volume
Facebook
66,372 leads, 1,680 IPD
Worst ROI
ProData
12,357 leads, 0.17% conv
Hidden gem
Inbound
9.0% conv, lowest junk (15%)
Conversion rate by source
Only sources with ≥10 conversions shown at scale
Volume vs. conversion matrix
Bubble size = lead volume
Source ROI analysis table
Ranked by conversion rate — quality over quantity
| Source | Total leads | IPD done | Junk leads | Junk % | Conv % | Assessment | Action |
|---|
Strategic shift: Facebook produces 80% of all leads but at 2.53% conversion. Google, with 2,104 leads, achieves 3.9% — 54% better conversion at a fraction of the volume. Increasing Google Ads budget while cutting ProData/Pro-Data-2 (combined 16,892 leads, 0.23% avg conv) could improve overall conversion rate by 0.5–0.8 percentage points.
Due diligence
Risk & Anomalies
Data integrity issues, concentration risks, and operational red flags
🔴 Critical risks
Data integrity — BD 503: 321 IPD Done on 324 leads (99.07%) is impossible in normal operations. Likely causes: bulk status migration, test accounts, or deliberate manipulation. Risk to investor reporting: HIGH.
Zero-conversion BDs (3 staff, 13,419 leads): Sanjana Sharma (8,067 leads), Rajesh Kumar (3,843), Avinash Singh (1,509) — all show 0 IPD Done over the full 15-month period. This represents significant operational expenditure with zero output.
Concentration risk: Hardeep Bhargav's team manages 46,449 leads (42% of total). If this team underperforms or key BDs leave, it could devastate pipeline.
🟡 Medium risks
Revenue tracking disabled: IPD_TotalPayment totals ₹12,000 across 110K leads. Revenue is not being recorded in CRM, making true financial performance invisible. Business may be healthy but untracked.
Conversion rate decline: After peaks in May–June 2025 (3.5–4.5%), the rate has not recovered, averaging 1.3–1.6% from Aug 2025 onward. Volume is up but quality is down.
ProData / Pro-Data-2 dependency: Combined 16,892 leads at 0.23% conversion. These are likely purchased data lists — extremely poor ROI and a significant cost centre.
🟢 Positive signals
Referral channel: 67.6% conversion — if even 200 referral leads/month can be systematically generated, it would match current total IPD Done.
BD performance distribution
Histogram — number of BDs at each conversion rate bracket
Anomalous records — flagged for audit
| BD / Entity | Leads | IPD Done | Conv % | Flag | Recommended action |
|---|---|---|---|---|---|
| Saurabh Chaudhary (BD 503) | 324 | 321 | 99.07% | Data error | Immediate audit of 321 IPD Done records |
| Sanjana Sharma (BD 508) | 8,067 | 0 | 0.00% | Zero output | Performance review / reassignment |
| Rajesh Kumar (BD 522) | 3,843 | 0 | 0.00% | Zero output | Performance review / reassignment |
| Avinash Singh (BD 477) | 1,509 | 0 | 0.00% | Zero output | Performance review / reassignment |
| BD 513 (unnamed) | 1,276 | 15 | 1.18% | No name | Map to correct staff record |
| IPD_TotalPayment field | 110,176 | — | ₹12,000 | Unused | Enforce revenue entry at IPD Done status |
| ProData + Pro-Data-2 | 16,892 | 36 | 0.21% | Low ROI | Reduce spend, redirect to Referral/Google |
Strategic recommendations
Action Plan
Prioritised initiatives to improve conversion rate and operational efficiency
Target conversion rate
3.5%
Achievable within 6 months
Potential IPD uplift
+1,760
At 3.5% vs current 1.9%
Quick wins available
5
Implementable in 30 days
Immediate actions (0–30 days)
1
Audit BD 503 data records
Investigate the 321 IPD Done records under Saurabh Chaudhary. Determine root cause — bulk migration error, test data, or manipulation. Correct the dataset before any investor or board presentation.
Critical · Data integrity
2
Enable revenue tracking (IPD_TotalPayment)
Make revenue entry mandatory when setting status to IPD Done. Currently ₹12,000 recorded across 2,095 surgeries — clearly broken. Without this, no real financial P&L is possible.
Critical · Revenue visibility
3
Performance review: 3 zero-output BDs
Sanjana Sharma, Rajesh Kumar, Avinash Singh have processed 13,419 leads over 15 months with zero conversions. Initiate PIP or reassignment. Reassigning their leads to Tier 1 BDs could yield 160–200 additional conversions.
High · People
Short-term initiatives (30–90 days)
4
Cut ProData spend, invest in Referral programme
ProData + Pro-Data-2: 16,892 leads, 36 conversions (0.21%). Referral: 34 leads, 23 conversions (67.6%). Build a structured patient referral incentive programme — even 500 referral leads/month would outperform ProData entirely.
High · Channel ROI
5
Replicate Mayank Panday's playbook
At 5.21% conversion on 1,594 leads, Mayank converts 2.7× the company average. Conduct a structured interview, document his call script, follow-up cadence, and objection handling. Roll out to Tier 3/4 BDs as a training programme.
High · Performance
6
DNP Exhausted re-engagement campaign
15,054 leads are stuck at DNP Exhausted. A structured WhatsApp/SMS re-engagement sequence targeting these leads — especially those with Fund Issues (2,344) and Out of Station (3,480) — could recover 2–3% at minimal incremental cost.
Medium · Lead recovery
90-day conversion rate roadmap
Projected improvement from implementing all 6 initiatives