At a glance
Executive Summary
15-month operational performance across all BD channels · Surgery counts based on Surgery_Date (ground truth)
Total leads
110,176
Jan 2025 – Mar 2026
Surgeries (w/ date)
1,244
Avg 83/month · Peak 120
Surgery_Date filled
IPD Done (status)
2,096
852 missing Surgery_Date
Data gap exists
Lead wastage
68%
75,303 junk/dead/closed
Critical
Top BD: Mayank Panday converts at 5.21% on 1,594 leads — 2.7× average. His process should be documented and trained across teams.
Best source: Referral converts at 67.6%. ProData (12,357 leads) converts at 0.17%. Reallocating even partial ProData budget to referral incentives could double IPD output.
Real surgery rate: Surgery_Date shows ~83 surgeries/month on average, not the 526 that lead-date grouping suggested. May 2025 peak was 120. Current run rate is ~77/month (Jan–Mar 2026).
Zero output: Sanjana Sharma (8,067 leads), Rajesh Kumar (3,843), Avinash Singh (1,509) — 13,419 leads, 0 IPD Done across 15 months.
Pipeline breakdown
110,176 total leads
Monthly surgeries by Surgery_Date
Ground truth — actual surgery dates recorded in CRM
Note: 852 IPD Done records have no Surgery_Date filled. These are excluded from this chart. Target: 200/month.
Team league table
Ranked by conversion rate — click headers to sort
| Team Lead | BDs | Leads | IPD Done | Conv % | Junk % | Rating |
|---|
Pipeline analysis
Conversion Funnel
Where 110,176 leads end up — full status breakdown
Leads in
110K
IPD Done
2,096
1.90% of total
Active pipeline
~3,500
Workable
DNP Exhausted
15,054
Re-engage pool
Junk + Dead
75K+
68% wasted
Full status distribution
Junk breakdown
DNP Exhausted (15,054) is a recoverable pool. A structured WhatsApp re-engagement sequence could convert 2–3% = 300–450 additional IPDs.
Non-junk conversion: Removing junk/dup/invalid leads, conversion jumps to 2.98% — showing the real BD capability is higher.
Individual performance
BD Scorecards
All BDs ranked — click any column header to sort
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 by team lead — efficiency, junk quality, and conversion output
Active teams
8
Best team conv
2.69%
Amit Shukla's team
Worst team conv
0.42%
Abhishek Kashyap
Avg junk rate
36%
Team conversion rates
Team junk rates
Team detail table
Click headers to sort
| Team Lead | BDs | Leads | IPD Done | OPD Done | Junk | Junk % | Conv % | Rating |
|---|
Channel intelligence
Source Quality
ROI by acquisition channel — where leads convert vs. where budget is wasted
Best conv source
67.6%
Referral — 34 leads
Highest volume
Facebook
66,372 leads · 2.53%
Worst ROI
ProData
12,357 leads · 0.17%
Hidden gem
Inbound
9.0% conv · low junk
Conversion rate by source
Volume vs. conversion
Bubble size = lead volume
Source ROI table
Click headers to sort
| Source | Leads | IPD Done | Junk | Junk % | Conv % | Assessment | Action |
|---|
Clinical intelligence
Disease Mix
Treatment and category breakdown — lead volume, conversion rates, and revenue opportunity
Top treatment
Lipoma
38,398 leads · 951 IPD
Best conv treatment
Gynecomastia
18,247 leads · 2.95%
Top category
Aesthetics
71,243 leads · 2.32%
Underperforming
Proctology
10,564 leads · 0.27%
Category mix — lead volume
Category conversion rates
Treatment breakdown
Click headers to sort
| Treatment | Category | Leads | IPD Done | w/ Surgery Date | Conv % | Opportunity |
|---|
Gynecomastia + Lipoma + Circumcision account for 68,685 leads (62% of total) and 1,796 IPD Done (86% of all conversions). These 3 treatments are the core business — protect and grow these campaigns.
Proctology (Piles, Fissure, Fistula) has 10,466 leads but only 28 IPD Done (0.27%). This category needs a different funnel — possibly doctor referral rather than digital ads.
Geographic intelligence
Circle Analysis
Performance by city/region — lead quality, conversion rates, and geographic opportunity
Top circle (volume)
Delhi
34,349 leads · 1.91%
Best conv circle
Hyderabad
1,856 leads · 2.53%
Most IPD (volume)
Mumbai
736 IPD · 2.18%
Underperforming
Bangalore
7,031 leads · 0.84%
Lead volume by circle
Conversion rate by circle
Circle performance table
Click headers to sort
| Circle | Leads | IPD Done | Junk | Junk % | Conv % | Priority |
|---|
Delhi + Mumbai + Pune account for 88,428 leads (80%) and 1,896 IPD (90%). These three circles are the business — BD allocation and campaign spend should reflect this concentration.
Bangalore has 7,031 leads — 4th largest circle — but only 0.84% conversion vs 2.18% for Mumbai. Either lead quality from Bangalore campaigns is poor, or BD coverage is inadequate.
Time series
Monthly Trends
Real surgery counts by Surgery_Date · Lead volume · Conversion patterns
Peak surgery month
Jun 2025
120 surgeries
Avg surgeries/month
83
Based on Surgery_Date
Current run rate
~77/mo
Jan–Mar 2026 avg
Target gap
+123/mo
To reach 200/month
Surgeries per month (Surgery_Date)
The real picture — target line at 200
Monthly lead volume
IPD Done by update_date
Status-change date — for comparison only
Monthly data table
Click headers to sort
| Month | Leads (by Lead_Date) | Surgeries (Surgery_Date) | IPD Done (update_date) | Junk | Junk % |
|---|
Strategic roadmap
200 IPD/Month Target
Current run rate: ~77/month · Gap: 123 surgeries · Achievable in 4–6 months
Monthly surgery target
200
surgeries per month · from ~77 today
Current
~77
Jan–Mar 2026 avg
Gap
+123
Per month needed
Timeline
4–6 mo
With full execution
Where the +123 comes from
Fix Surgery_Date data entry+25–40
Redeploy zero-output BD leads+20–30
Cut ProData → Referral shift+15–25
Scale Inbound / Google Ads+10–20
DNP re-engagement campaign+10–15
BD training from top performers+8–15
Total potential uplift+88–145
6-month action plan
1
Make Surgery_Date mandatory (Month 1)
852 of 2,096 IPD Done records have no Surgery_Date. This is ~41% of all conversions invisible in reporting. Enforce the field as required when setting status to IPD Done. Immediately shows the real monthly number — likely already at 110–130 but unreported.
+25–40 visible/month
2
Reassign zero-output BD leads (Month 1)
Sanjana Sharma (8,067 leads, 0 IPD), Rajesh Kumar (3,843, 0 IPD), Avinash Singh (1,509, 0 IPD). Reassigning future leads from these BDs to Tier 1 performers like Mayank Panday (5.21%) or Abhishek Kashyap (3.21%) should yield +20–30 IPD/month on those lead volumes.
+20–30 IPD/month
3
Cut ProData, build referral programme (Month 1–2)
ProData + Pro-Data-2 together: 16,892 leads, 36 IPD (0.21%). Referral: 34 leads, 23 IPD (67.6%). Introducing a patient referral incentive — even ₹500–1,000 per successful referral — and targeting 300–400 referral leads/month would generate 200+ IPD from referral alone at current conversion rates. Start with existing patient WhatsApp outreach.
+15–25 IPD/month
4
Scale Google + Inbound channels (Month 2–3)
Google Ads converts at 3.9% — 54% better than Facebook. Inbound calls convert at 9.0% with only 15% junk rate. Both are severely underfunded vs. Facebook. Shift 20% of Facebook spend to Google Ads and set up a dedicated inbound call team. Target 500 additional Google leads/month = 20 extra IPD.
+10–20 IPD/month
5
DNP Exhausted re-engagement (Month 2–3)
15,054 leads are at DNP Exhausted. Many will be at Fund Issues (2,344) or Out of Station (3,480) — these are not lost, just paused. A WhatsApp broadcast sequence with a limited-time offer or EMI payment option, re-targeting these leads, could convert 2–3% = 300–450 additional IPD from this pool alone over 3 months.
+10–15 IPD/month
6
BD training: replicate top performers (Month 3–4)
Mayank Panday (5.21%), Kapil Sharma (3.68%), Abhishek Kashyap (3.21%) are converting at 2–3× the company average. Document their call scripts, follow-up cadence, and objection handling. Run a 2-week structured training for all Tier 3/4 BDs. Lifting their average from 0.8% to 1.5% across 30 BDs on ~40,000 leads = +280 additional IPD/month at scale.
+8–15 IPD/month (growing)
Projected 6-month trajectory to 200 IPD/month