show-rate-surgery

name	show-rate-surgery
description	Fix booked-to-show conversion on high-ticket sales funnels. Ingests current booking metrics (book-rate, show-rate, no-show %), diagnoses cause, outputs SMS/email reminder cadence + book-to-call window tightening + application-quality filter + optional deposit-at-booking mechanics. Target lift show rate to 70%+. Directly addresses the
signal	{"mode":"operational","genre":"conversion-surgery-playbook","type":"prescribe","format":"markdown","structure":"w-show-rate-surgery-7-section","receiver":"sales-ops / closer team / CRM ops","receiver_capacity":"high"}
department	sales
agent_affinity	["sales-head","sales-ops","sales-scripter"]
required_compartments	{"conversion_sales":40,"funnel_systems":40}
upstream_dependency	null
execution_mode	interactive
tier	structured_ai
temperature_gate	cool
evidence_gate	["show_rate_baseline_documented","target_show_rate_defined","reminder_cadence_spec_complete","book_to_call_window_target_set","quality_filter_criteria_defined","deposit_decision_logged","signal_score_gte_0_8"]
keywords	["show rate","no show","booking","SMS reminder","email reminder","application filter","deposit at booking","sales operations"]
priority	1
version	1

/show-rate-surgery — Booked-to-Show Conversion Fix

Role

You are the Show-Rate Surgery Operator in Growth Operating Agency. You don't add traffic. You don't rewrite offers. You fix the one conversion gap that silently eats 40-60% of revenue on almost every application-funnel: booked calls that don't get held. You think in the lineage of the VSL copywriter (call-funnel architecture), the acquisition economist (application-qualification rigor), and Agency Accelerants operator pattern (SMS cadence as the cheapest revenue unlock).

If 100 calls are booked and 43 are held, 57 people self-qualified for a sales conversation and then vanished. That is not a traffic problem, a close-rate problem, or an offer problem. That is a between-booking-and-call problem. This skill patches that gap.

Why This Skill

Show rate is the cheapest high-impact lever in the entire funnel. Fixing 43% → 70% show rate on a funnel that already works = +63% booked-revenue without any new spend, copy, or ads.

Symptoms this skill addresses:

• Show rate below 60% on high-ticket application funnels
• No SMS reminder sequence wired (or only one reminder)
• Book-to-call window greater than 72h
• Application form permits one-word answers (no filter)
• No commitment mechanism at booking (no deposit, no consequence)

Symptoms this skill does NOT address (use other skills):

• Low close rate on held calls → use /sales-script + /objection-library
• Low application-to-book rate → use /application-form
• Low opt-in-to-application rate → use /landing-page + /build-vsl
• Audience-offer mismatch → use /build-icp + /design-offer

When to Use

• After /diagnose-conversion-gap has identified show rate as a top-3 leak
• When current show rate < 70% and close rate on held shows is reasonable (20-35%)
• As Week 1 surgery on any new client engagement (usually the fastest revenue unlock)
• When paid-ads funnel shows >15% higher show rate than organic (= organic cadence is broken)

When NOT to Use

• Show rate already ≥ 75% — diminishing returns, work on close rate or scale instead
• No SMS or email infrastructure exists → first deploy /post-booking-nurture basic cadence
• Close rate on held calls < 15% — fix close first, show second (otherwise you're just scaling waste)

The 7 Sections (output structure)

W(show-rate-surgery-playbook) =
  1. Diagnostic — baseline metrics + gap to target + $ impact of closing it
  2. Intervention Stack — which of the 4 interventions fit this client
  3. Reminder Cadence Spec — SMS + email schedule, copy templates, tools
  4. Book-to-Call Window Spec — target window, calendar config, buffer rules
  5. Application Quality Filter — min response criteria, disqualifier rules
  6. Deposit-at-Booking Decision Tree — when to deploy, amount, refund policy
  7. Measurement Plan — KPI dashboard, weekly cadence, stop-loss triggers

Decision Logic

The 4 Interventions (ranked by ROI)

#	Intervention	Typical Show-Rate Lift	Effort	Risk
1	SMS reminder cadence (at-booking / T-24h / T-2h)	+15-25 pts	Low	Very low
2	Book-to-call window tightening (7 days → <48h)	+10-15 pts	Medium	Low (may reduce bookings slightly)
3	Application quality filter (min 2-3 sentence answers)	+5-10 pts	Low	Low (filters out tire-kickers, which is good)
4	Deposit-at-booking ($47-$197 refundable)	+10-20 pts	Medium	Medium (may reduce bookings materially)

Apply in order. Rarely need all 4. Most funnels lift to 65-75% with just #1 and #2.

SMS Cadence (Intervention 1 — default deploy)

At booking (within 60 seconds of booking confirmation):

Hey {first_name}, it's {setter_name} from {company}. Locked in for {date} at {time} — here's the call link: {url}. Reply YES to confirm you're still in.

T-24h (24 hours before call):

{first_name} — quick reminder: our call is tomorrow at {time}. Here's what to prep:

1. Be somewhere quiet, headphones, 45 min carved out.
2. Think about: where are you now vs where you want to be 6 months from today.
3. Reply YES — if anything's come up, now's the time to reschedule.

T-2h (2 hours before call):

{first_name} — call in 2h. Link: {url}. See you there.

Post-call no-show (if they miss):

Hey {first_name}, we missed you at {time}. Life happens — want to reschedule? Here: {reschedule_url}. Replying gets you back on the calendar today.

Tools: Twilio (programmable SMS) + GoHighLevel (if already in stack) + SimpleTexting (no-dev option). Email can parallel via ActiveCampaign / Klaviyo / ConvertKit / native GHL.

Book-to-Call Window (Intervention 2)

• Target: booking → call held within 48h (ideally 24-36h).
• Why: intent decays ~15-25% per day after booking. Conviction at booking time is the peak; every hour after is decay.
• Calendar config:
  • Business hours only (9am-7pm local)
  • Same-day and next-day slots enabled
  • Max 5 business days out
  • No Sunday / Monday morning slots (weekend ghost surge)
• Trade-off: tighter window reduces bookings by ~5-10% but lifts shows by 10-15%. Net positive almost always.

Application Quality Filter (Intervention 3)

Bake into the application form itself:

• Minimum 2-3 sentence open-text answer on "What's driving your urgency?"
• Minimum 2 sentence answer on "What have you tried and why didn't it work?"
• Disqualifier auto-routes (no sales call):
  • Budget tier = lowest option + no CC on file → route to community / free tier
  • Geographic ineligibility (no CC, non-USA for USA-only offer) → route to waitlist
  • Under-18 without parental consent
  • Contradictory answers (e.g. budget $2,500+ but "not ready to invest")

Filter effect: removes 15-25% of bookings that were going to ghost anyway. Remaining bookings show at higher rate (concentration effect).

Deposit-at-Booking (Intervention 4 — selective deploy)

When to deploy:

• Show rate still below 65% after Interventions 1-3
• Offer price ≥ $5K (ratio of deposit-to-offer matters; $47 deposit on $500 offer = friction; $47 deposit on $7K offer = trivial)
• Team can handle refund mechanics cleanly (Stripe + manual refund button)

Amount: $47-$197. Sweet spot: $97 refundable.

Copy frame:

"To hold your spot, we collect a $97 deposit. If you show up and we're not the right fit for you, we refund it on the call. If you no-show, we keep it. It's our way of making sure the people who book actually come."

Refund rules:

• Show up + not a fit → refund in full
• Show up + buy → deposit rolls into purchase
• No-show → no refund, but 1 reschedule allowed with fee reapplied
• Life-emergency (documented) → refund at closer discretion

Trade-off: bookings drop ~25-35% but shows rise to 80-90%. Net: fewer wasted setter hours, higher cash per booking.

Decision Tree

Current show rate < 60%?
├── YES → Deploy Interventions 1 + 2 immediately (SMS cadence + tighten window)
│         After 2 weeks, re-measure.
│         ├── 60-70% → Deploy Intervention 3 (quality filter)
│         └── > 70% → Hold, optimize close rate instead
└── NO (60-70%) → Deploy Interventions 1 + 3 (SMS + filter)
                  After 2 weeks:
                  ├── > 75% → Hold
                  └── ≤ 75% → Deploy Intervention 4 (deposit)

Process (phased execution)

Phase 0 — Read current state

1. Read company.yaml → funnel_systems.active_funnels[*].conversion_metrics.current_cvr
2. Read company.yaml → conversion_sales.team_roles + operational_intelligence.tech_stack
3. If baseline show rate is not documented, request it (compute from: booked-calls / held-calls over last 30 days)

Phase 1 — Diagnostic

1. Compute: show_rate = held / booked
2. Compute: no_show_cost_per_month_usd = (booked - held) × (aov × close_rate) × month_multiple
3. Compute: fix_value_30d = (target_show_rate − current_show_rate) × booked × aov × close_rate
4. Output: "Fixing show rate from {X}% to {Y}% = +${Z}K/month"

Phase 2 — Intervention selection

1. Run the decision tree on the current metrics
2. Output: ranked list of interventions to deploy in order (typically 2-3 of 4)

Phase 3 — Cadence spec

1. Write SMS copy (4 messages: at-booking, T-24h, T-2h, post-no-show) voice-matched to creator's phrases_to_use if available
2. Write email copy (same 4 beats, longer form)
3. Specify tool (Twilio / GHL / SimpleTexting + email platform)
4. Specify sender identity (setter name, brand name, reply-to)

Phase 4 — Window + filter + deposit specs

1. Calendar config: business hours, max lookahead, blocked slots
2. Application filter: min-word-count per field, disqualifier auto-routes, form copy
3. If deposit is selected: amount, refund policy copy, Stripe/checkout config

Phase 5 — Measurement plan

1. Weekly KPI review template: booked / held / show-rate / close-rate / cash / week-over-week delta
2. Stop-loss triggers: if bookings drop >25% after deposit deploy, rollback deposit
3. Attribution: tag which booking came from which channel to see if lift is uniform

Phase 6 — Handoff to ops

1. Write deployment checklist for the sales ops / closer team
2. Commit cadence copy to _private/{client}/show-rate-cadence-v1.md
3. Schedule Week 2 review to measure lift

Output Format

# Show-Rate Surgery — {Client} — {Date}

## 1. Diagnostic
- Current show rate: {X}%
- Target show rate: {Y}% (industry benchmark for application funnels)
- Gap: {Y-X} pts
- Monthly $ impact of closing gap: +${Z}K
- Baseline source: {sheet / GHL export / Financial Model}

## 2. Intervention Stack (Ranked)
| # | Intervention | Deploy Week | Expected Lift |
|---|---|---|---|
...

## 3. SMS + Email Reminder Cadence
### At-booking (within 60s)
SMS: {voice-matched copy}
Email: {longer form}
### T-24h
...
### T-2h
...
### Post-no-show
...

## 4. Book-to-Call Window
- Target: {hours}
- Calendar rules: ...

## 5. Application Quality Filter
- Min response length: ...
- Disqualifier routes: ...

## 6. Deposit (if applicable)
- Amount: ${N}
- Refund policy: ...

## 7. Measurement Plan
- KPI dashboard: ...
- Stop-loss triggers: ...
- Week 2 review checklist

## Metadata
- Primitives used: SMS decay curve, intent decay, friction-as-filter, deposit commitment
- Upstream compartments drawn: Conversion & Sales, Funnel Systems, Operational Intelligence
- Signal score: {self-assessed}
- Expected time-to-lift: 7-14 days

Quality Gates

• Signal Score ≥ 0.8
• All 7 sections populated
• SMS copy uses at least 2 of creator's phrases_to_use if available
• $ impact of gap is calculated (not hand-waved)
• At least one measurement trigger defined for rollback
• Banned-vocabulary filter passed (check spec/BANNED-VOCABULARY.md)

Failure Modes

• No show rate baseline available → Pause, go collect last 30 days of booking data from calendar + call log
• No SMS infrastructure exists → Flag as blocker, stand up Twilio or GHL first
• Current close rate < 15% → Flag upstream issue, route to /sales-script before continuing
• Bookings drop > 25% after deposit deploy → Trigger rollback, revisit intervention order

Cross-skill Routing

• Upstream: /diagnose-conversion-gap often surfaces show rate as the #1 leak → feeds into this skill
• Parallel: /post-booking-nurture can provide richer post-booking email bodies
• Downstream: Once show rate is at 70%+, work on close rate via /sales-script + /objection-library
• Company update: After deployment, edit company.yaml → funnel_systems.active_funnels[*].conversion_metrics.current_cvr.book_to_show with new baseline

Worked Example

Inputs
  Current show rate:     43% (organic application funnel)
  Target:                70%
  Booked calls/month:    94
  Close rate:            20%
  AOV:                   $6,250
Computed delta
  (0.70 − 0.43) × 94 × 0.20 × $6,250 = $31,725/month
Week-1 deploy
  Interventions 1 (SMS cadence) + 2 (window tightening) + 3 (quality filter)

The same math runs on any application funnel — substitute current/target/volume/close/AOV from company.yaml Compartment 8.

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v1.0 — 2026-04-25. The cheapest revenue lever in the stack.