TOMOGO! Weekend Zero-Booking Analysis

Report Date: 2026-04-27 | Data: through 2026-04-26 | For: Analysis Meeting

1. Executive Summary

ALERT

3 consecutive zero-booking days (Apr 24-26)

Weekly bookings dropped -77.4% (W1: 3.1/day to W2: 0.7/day). CPO surged to ¥196,274 (+368%). ROAS collapsed to 8.8%.

Bookings (W2 avg)
0.7/day
-77.4% vs W1
CPO (W2)
¥196K
+368% vs W1
Meta Installs (W2)
7
-67% vs W1 (21)
Female Installs
2
-85% vs W1 (13)

2. What Happened

Operational Changes Applied (~Apr 20)

Two key Meta Ads changes:

  1. Landing page destination switch — Creative ad sets redirected from Tour Detail pages to the LP at explore.tomogo-travel.com/book-your-tour. Full-switch test to evaluate LP conversion performance.
  2. Ad set consolidation — Reduced from 3 test ad sets (Post x Detail Page) to Segment A only (highest CVR & bookings). Segments B and C (split by creative messaging axis) were paused, and their budgets were reallocated to Segment A.

Rationale: Based on last-click attribution, concentrate reach on the segment with proven conversion. LP switch is an intentional test — the LP's original CVR was not high, so we're running a clean A/B by switching all traffic at once and monitoring the trend.

3. Root Cause Analysis

Hypothesis A: Female Install Collapse Highest Impact

GenderW1 InstallsW2 InstallsChangeW1 PurchasesW2 Purchases
Female132-85%10
Male85-38%31

Key insight: Female impressions actually increased (+12.6%) while installs crashed -85%. This points to creative fatigue or the destination change specifically disrupting women's path to install.

This aligns with the "Women Discover → Men Book" hypothesis — when women stop installing (top-of-funnel), men's downstream purchases also decline.

Hypothesis B: Core Segment (35-44) Stopped Converting

AgeW1 InstallsW2 InstallsW1 PurchasesW2 PurchasesCost Change
35-449330±0% (¥185K both weeks)
25-347301+16%
55-644000+7%

Male/35-44 accounted for 3 out of 4 total purchases in W1. This entire segment went silent in W2 despite identical spend.

Hypothesis C: Meta Delivery Throttling

Apr 25 Meta cost was -42% vs Apr 20. The decline started Apr 23 and bottomed on Apr 25. Stories placement took the biggest hit (-54%). Likely caused by budget pacing adjustments after the ad set consolidation reduced auction diversity.

Hypothesis D: Japan-Based Users (Tourists) Stopped Converting

CountryW1 PurchasesW2 PurchasesW1 CostW2 Cost
US11¥272,738¥273,491
JP20¥17,765¥21,397
AU10¥92,519¥88,292

JP was the most cost-efficient segment in W1 (2 purchases on just ¥18K — tourists already in Japan with high intent). The LP destination change may have disrupted their short conversion path.

4. Most Likely Explanation

Combined effect of three factors:

  1. Ad set consolidation reduced audience diversity — Female installs collapsed -85%, breaking the top-of-funnel
  2. LP destination switch sent all traffic to a page with historically low CVR — particularly impacted high-intent JP users
  3. Meta delivery reduction compounded the above from Apr 23, bottoming Apr 25 (-42% cost)

These factors cascaded: fewer women discovering TOMOGO! → fewer men booking → zero-booking weekend.

5. Deep Dive: Female Install → Booking Lag Correlation

To assess whether the female install collapse (Hypothesis A) impacts not just this week but future weeks, we analyzed the lag correlation between female installs and total bookings using historical data (Feb 1 - Apr 26, 2026; 85 days).

Rolling 7-Day Lag Correlation r = 0.70 (Strong Positive)

Lag (days)Correlation rStrengthInterpretation
0 (same day)0.09NoneNo same-day effect
30.16Weak
50.30ModerateEffect starts building
70.47Moderate-StrongClear 1-week connection
100.66Strong
120.70Strong (Peak)Female Install peaks ~2 weeks before Booking
140.69Strong

Finding: Female installs correlate most strongly with total bookings 10-14 days later (peak r = 0.70 at lag +12 days). Same-day correlation is near zero (r = 0.09).

This quantitatively supports the "Women Discover → Offline Propagation → Men Book" two-layer hypothesis. The time gap represents the offline word-of-mouth cycle.

Weekly Aggregation Confirms the Pattern

LagCorrelation rInterpretation
Same week0.14None
+1 week0.40Moderate
+2 weeks0.64Strong
+3 weeks0.70Strong

Weekly Data: Actual Progression

WeekFemale InstallsBookings 2 Weeks Later
Feb 234523 (Feb 16)
Feb 924227 (Feb 23)
Mar 23223 (Mar 16)
Mar 161211 (Mar 30)
Apr 6185 (Apr 20)
Apr 1313? (Apr 27) Expected: low
Apr 202May 4: Risk of further decline

Supporting Evidence: Female Install → Male Purchase (Meta-attributed) is Negative

LagrInterpretation
0 days-0.08The female-to-male connection is not captured within Meta's attribution window — indirect evidence that the path runs through offline channels (word-of-mouth → brand search → booking)
7 days-0.13
14 days-0.20

Caveats:

6. Additional Analysis: Female Funnel Metrics Comparison — Reach vs Click vs Install

Does increasing female reach drive more bookings? We compared four female metrics (Reach, IMP, Click, Install) against total bookings at various lags to find out.

All Female Metrics → Total Booking Lag Correlation (Rolling 7-day)

MetricLag 0Lag +5dLag +7dLag +10dLag +12dLag +14dLag +21dInterpretation
Female Reach-0.13-0.13-0.020.070.04-0.030.25Near-zero correlation
Female IMP-0.04-0.010.100.180.150.070.30Weak positive only
Female Click-0.56-0.77-0.73-0.64-0.60-0.58-0.37Strong negative at all lags
Female Install0.090.300.470.660.700.690.80Strong positive (leading indicator)

Three key findings:

  1. More female reach/impressions does NOT increase bookings (r near 0). Ad exposure volume alone is insufficient.
  2. More female clicks correlates with FEWER bookings (r = -0.77). The Feb-Mar TikTok high-spend period generated massive clicks but not bookings. Clicks do not equal quality engagement.
  3. Only female installs positively predict future bookings (r = 0.70). The act of installing the app — a behavioral commitment — is what triggers the offline propagation cycle that leads to male bookings.

Weekly Data: The Apr 20 Paradox

WeekF. ReachF. ClickF. InstallBookingsNote
Feb 2201,8982,81834516High installs → booking peak 2 weeks later
Mar 16213,0545,6931223Highest reach, yet installs collapsed
Mar 30162,4457,997811Most clicks — bookings plummeted
Apr 20145,6468,68425Reach up, clicks at all-time high, installs collapsed → zero bookings

The Apr 20 week paradox: Female reach was +18% WoW, clicks hit a monthly high of 8,684. Yet bookings collapsed to 5 (with three consecutive zero days). The decisive factor: female installs dropped to just 2.

"More reach = more bookings" is false. Whether women install the app is the only leading indicator that matters.

Implications for Booking Strategy

Strategic implications:

  1. Optimize female ads for Install, not Reach or Clicks — Reach optimization and click optimization do not drive bookings
  2. Change creative evaluation criteria — The winning creative is not the one with the highest CTR, but the one with the highest Install CVR
  3. Female Install is the "2-week booking forecast" — Incorporate into weekly monitoring; trigger alerts when installs decline
  4. Re-evaluate Seg B/C impact — Seg B/C may have been more effective at driving female installs. Check per-segment, per-gender install data before and after the consolidation

7. Discussion Points for Today

#TopicKey Question
1LP test decisionContinue the LP test or revert? What's the threshold for reversal?
2Seg B/C revivalIf female install collapse is linked to ad set consolidation, should we partially restore Seg B/C?
3Creative refreshImpressions up but installs down = creative fatigue signal. When do we introduce new creatives?
4JP segment strategyShould we design dedicated targeting for tourists currently in Japan? (highest efficiency segment)

Proposed immediate actions: