Travel agents and OTAs show tentative payer interest, but proof of retention lift is still missing.
1
Who buys and who uses
Is there a clear customer?- otaPayerOTAs show the strongest intent and conversion but want evidence it lifts retention.
- travel agentPayerAgents show real interest but resist paying for what they already do manually.
- leisure travelersEnd userTravelers like the idea but see it as a free utility, not something to pay for.
- business travelersEnd userBusiness travelers see this as solved already by their own tools or assistants.
2
Bottom-up market
SOM, not a TAM slide| Segment | Market size | Price | Per year | Reachable revenue |
|---|
| leisure travelersEnd user | 95,083estimated | — | | — |
| business travelersEnd user | 56,082estimated | — | | — |
| otaPayer | 6,991estimated | $325founder | × 12 | $27,264,900 |
| travel agentPayer | 5,618estimated | $55.00founder | × 12 | $3,707,880 |
3
Cost to acquire
Unit economics| Segment | CPC | Conversion | Cost per sign-up | Sign-ups/mo | Payback (mo) | Difficulty |
|---|
| leisure travelers | $3.81estimated | 3.00%default | $127 | 7.87 | — | 21.4 |
| business travelers | $3.14estimated | 3.00%default | $105 | 9.55 | — | 24.1 |
| ota | $8.43estimated | 1.00%default | $843 | 1.19 | 2.6 | 47.1 |
| travel agent | $8.95estimated | 1.00%default | $895 | 1.12 | 16.3 | 50.6 |
4
Willingness to pay
Any signal beyond the founder?| Segment | N | Would pay | Might pay | Median price | Interest /5 | Intent |
|---|
| leisure travelers | 50 | 20%±11.1 | 0% | $0.00 | 2.32 | 27.8 |
| business travelers | 50 | 12%±9 | 0% | $0.00 | 2.46 | 26.7 |
| ota | 50 | 10%±8.3 | 64% | $160 | 3.24 | 50.4 |
| travel agent | 50 | 22%±11.5 | 40% | $55.00 | 3.04 | 47.4 |
5
Objections, and our answer
Do they know their risks?| ota30 No proof it drives repeat bookings | Not yet answered. |
|---|
| 10 Already have free reminder alternatives | Not yet answered. |
|---|
| travel agent21 already sends reminders personally | Not yet answered. |
|---|
| 15 need proof of retention/usage before paying | Not yet answered. |
|---|
6
What changed
Learning velocity| Run | What changed | Would pay | Intent |
|---|
| v6 → v7Same panel | pitch · ota | -12 pts | -3.9 |
| v5 → v6Same panel | pitch, price line · ota | +12 pts | +2.3 |
| v4 → v5Different panels | pitch, price line · ota | -16 pts | -2.7 |
7
Recommended first spend
What does the next cheque buy?otaPayer
$1,000/mo → 1.19 sign-ups at $843 each
leisure travelers ranks first on intent over difficulty but carries no price. The first spend goes to the highest-ranked segment that can generate revenue.
OTAs offer the clearest payer identity and the strongest modelled intent, even though payback stretches over a year. Travel agents run close behind with nearly identical economics but slightly softer conviction. The trade-off is OTA scale against agent familiarity with the manual task LeaveBy replaces.
Confirms: 0.59+ sign-ups in month one, at $1,686 or less each. Kills it: under 0.30 sign-ups, or a cost per sign-up above the price.
Clearing the confirm threshold would show OTAs convert at a rate that justifies wider ad spend on this payer. Falling below the kill threshold would mean the wedge into OTAs is too costly to pursue at this price and channel.
Biggest unresolved risk: The brief cannot yet confirm that any payer segment believes LeaveBy measurably improves booking retention.
8
Assumptions register
Where does each number come from?| Market size, revenue | estimated | Monthly search volume: a proxy for a population, not a count. Revenue is a ceiling. |
|---|
| Price | founder | What the panel was quoted. Uzers knows price, not margin. |
|---|
| CPC | estimated | Paid search only. No organic or sales-led acquisition modelled. |
|---|
| Conversion | default | Sign-ups assume a $1,000 budget. Payback is gross, not margin. |
|---|
| Panel evidence | 50 AI personas | A difference smaller than the margin of error beside it is not a result. |
|---|
Synthetic pre-validation. The panel is AI personas, not users, and every reaction is a prediction. Real-campaign results replace these estimates.Reach figures on this run are placeholder values from the stub source, not Google Ads data.
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leisure travelersEnd user
Appendix · ranked 1
Travelers like the idea but see it as a free utility, not something to pay for.
The math
| Market size | 95,083estimated | |
|---|
| Price | — | |
|---|
| Reachable revenue | — | market size × price × 12 |
|---|
| CPC | $3.81estimated | |
|---|
| Conversion | 3.00%default | |
|---|
| Cost per sign-up | $127 | CPC ÷ conversion rate |
|---|
| Monthly budget | $1,000default | |
|---|
| Sign-ups/mo | 7.87 | budget ÷ CPC × conversion rate |
|---|
| Payback (mo) | — | cost per sign-up ÷ price |
|---|
| Difficulty | 21.4 | |
|---|
The panel
| N | 50 | personas who answered, not personas asked |
|---|
| Would pay | 20% | 95% margin of error ±11.1 points |
|---|
| Might pay | 0% | |
|---|
| Median price | $0.00 | |
|---|
| Interest /5 | 2.32 | |
|---|
| Intent | 27.8 | |
|---|
Objections, and our answer
22 Not the customer, agent/business buys this
“I'm not the customer — travel agents are, and I don't book through them anyway, I just book directly online”
14 Already have a person who tells me
“I already text my agent and he tells me when to leave—why would I need some app I've never heard of when I have a person I trust who books my trips anyway”
14 Already solve it myself, don't need it
“I already check my flight status obsessively and set my own alarms—I don't trust anyone else's timing calculations anyway, and I'm not paying for what I can do myself”
Synthetic pre-validation. The panel is AI personas, not users, and every reaction is a prediction. Real-campaign results replace these estimates.Reach figures on this run are placeholder values from the stub source, not Google Ads data.
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business travelersEnd user
Appendix · ranked 2
Business travelers see this as solved already by their own tools or assistants.
The math
| Market size | 56,082estimated | |
|---|
| Price | — | |
|---|
| Reachable revenue | — | market size × price × 12 |
|---|
| CPC | $3.14estimated | |
|---|
| Conversion | 3.00%default | |
|---|
| Cost per sign-up | $105 | CPC ÷ conversion rate |
|---|
| Monthly budget | $1,000default | |
|---|
| Sign-ups/mo | 9.55 | budget ÷ CPC × conversion rate |
|---|
| Payback (mo) | — | cost per sign-up ÷ price |
|---|
| Difficulty | 24.1 | |
|---|
The panel
| N | 50 | personas who answered, not personas asked |
|---|
| Would pay | 12% | 95% margin of error ±9 points |
|---|
| Might pay | 0% | |
|---|
| Median price | $0.00 | |
|---|
| Interest /5 | 2.46 | |
|---|
| Intent | 26.7 | |
|---|
Objections, and our answer
24 Not my purchase, agent's tool
“I'm not a travel agent or OTA—this is built for a business model I'm not in. My buffer system works fine for the handful of flights I take monthly.”
12 Already have a human handling it
“My EA already handles this — she sends me the calendar invite with the departure time calculated. I don't need to think about it. This solves a problem I've outsourced.”
11 Already have my own system
“I already have a spreadsheet that works fine and I know exactly how to adjust it for traffic, flight delays, terminal chaos—I built it for my own reality, not some algorithm that doesn't know Ben Gurion like I do.”
Synthetic pre-validation. The panel is AI personas, not users, and every reaction is a prediction. Real-campaign results replace these estimates.Reach figures on this run are placeholder values from the stub source, not Google Ads data.
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otaPayer
Appendix · ranked 3
OTAs show the strongest intent and conversion but want evidence it lifts retention.
The math
| Market size | 6,991estimated | |
|---|
| Price | $325founder | |
|---|
| Reachable revenue | $27,264,900 | market size × price × 12 |
|---|
| CPC | $8.43estimated | |
|---|
| Conversion | 1.00%default | |
|---|
| Cost per sign-up | $843 | CPC ÷ conversion rate |
|---|
| Monthly budget | $1,000default | |
|---|
| Sign-ups/mo | 1.19 | budget ÷ CPC × conversion rate |
|---|
| Payback (mo) | 2.6 | cost per sign-up ÷ price |
|---|
| Difficulty | 47.1 | |
|---|
The panel
| N | 50 | personas who answered, not personas asked |
|---|
| Would pay | 10% | 95% margin of error ±8.3 points |
|---|
| Might pay | 64% | |
|---|
| Median price | $160 | |
|---|
| Interest /5 | 3.24 | |
|---|
| Intent | 50.4 | |
|---|
Objections, and our answer
30 No proof it drives repeat bookings
“I need to see actual repeat booking lift before committing to another monthly tool—the premise that staying on their phone increases bookings is logical but unproven in our market, and I'm not running a pilot on assumptions.”
10 Already have free reminder alternatives
“I already call my clients the day before with pickup times, it works fine and costs me nothing. This is replacing a phone call with an app notification and charging me $325 for it.”
6 Third party dilutes our brand/data ownership
“I don't own the relationship with the traveler if LeaveBy sends reminders on WhatsApp—that engagement metric goes dark for me, and I can't see if they're opening my app or booking with someone else next time.”
Synthetic pre-validation. The panel is AI personas, not users, and every reaction is a prediction. Real-campaign results replace these estimates.Reach figures on this run are placeholder values from the stub source, not Google Ads data.
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travel agentPayer
Appendix · ranked 4
Agents show real interest but resist paying for what they already do manually.
The math
| Market size | 5,618estimated | |
|---|
| Price | $55.00founder | |
|---|
| Reachable revenue | $3,707,880 | market size × price × 12 |
|---|
| CPC | $8.95estimated | |
|---|
| Conversion | 1.00%default | |
|---|
| Cost per sign-up | $895 | CPC ÷ conversion rate |
|---|
| Monthly budget | $1,000default | |
|---|
| Sign-ups/mo | 1.12 | budget ÷ CPC × conversion rate |
|---|
| Payback (mo) | 16.3 | cost per sign-up ÷ price |
|---|
| Difficulty | 50.6 | |
|---|
The panel
| N | 50 | personas who answered, not personas asked |
|---|
| Would pay | 22% | 95% margin of error ±11.5 points |
|---|
| Might pay | 40% | |
|---|
| Median price | $55.00 | |
|---|
| Interest /5 | 3.04 | |
|---|
| Intent | 47.4 | |
|---|
Objections, and our answer
21 already sends reminders personally
“I already call my clients the day before their flights and remind them personally - that's why they come back to me, not because of some app they'll forget about”
15 need proof of retention/usage before paying
“I need to see actual client retention numbers first—the math looks good if this actually keeps people coming back, but a WhatsApp reminder doesn't feel like enough to compete with the OTA's push notifications they already get.”
8 not worth the monthly fee
“Another $55 monthly is $660 a year that comes straight out of my margin, and I'm not convinced my customers need a WhatsApp reminder from a bot when they need a person to call if something goes wrong.”
Synthetic pre-validation. The panel is AI personas, not users, and every reaction is a prediction. Real-campaign results replace these estimates.Reach figures on this run are placeholder values from the stub source, not Google Ads data.
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