B2C · Feature Launch · Loyalty · PRD · GTM · Roadmap
Architecting a loyalty program from zero — personas, PRD, roadmap, engineering sprints, and GTM, end to end.
PM — Full Product Lifecycle, Stay-N-Sleep Rewards Team
Company
Stay-N-Sleep (vacation rental marketplace, similar to Airbnb)
Feature
Stay-N-Sleep Loyalty Program
Stage
0-to-1 feature launch
Deliverables
Executive Summary, Personas, Hypothesis, PRD, Roadmap, User Flow, Engineering Sprints, GTM Strategy
The brief
Stay-N-Sleep had a retention problem hiding behind a growth story. Business travelers — their fastest-growing segment — were booking once and not coming back. Guest inquiries about a loyalty program had spiked over six months, and the executive team knew that retaining an existing customer costs five times less than acquiring a new one.
The ask: join the newly-formed Stay-N-Sleep Rewards product team and build a loyalty program from scratch. Not a concept. A fully specified, launch-ready product — complete with personas, a validated hypothesis, a PRD, a phased roadmap, engineering sprint breakdown, and a go-to-market plan.
The tagline we built the program around: “Business Is Complicated. Rewards Shouldn't Be.”
The users
The Frequent Business Traveler
34, Sr. Account Executive, Chicago · Travels 2–3x per month
Goals: Earn rewards for repeat stays, access curated local experiences, feel recognized for loyalty
Pain Points: Corporate tools feel rigid, hotel loyalty programs are entrenched, doesn't want to decode complex rewards
“I travel too often to waste time on clunky booking tools. Reward me, keep it smooth, and make the trip feel worth it.”
The Corporate Travel Manager
41, Company Travel Manager, New York City · Manages travel for a large organization
Goals: Reduce travel friction, improve visibility into bookings and spend, offer employees better options without losing financial control
Pain Points: Limited visibility into off-platform bookings, hard to reconcile costs across teams, platforms promise easy but deliver complexity
“If I can't track it, report on it, and explain it to finance, it's not a good travel solution.”
Hypothesis statement
“We believe that the frequent business traveler has a need to be recognized and rewarded for their loyalty.
We can address this by developing a program that rewards repeat stays and experiences.
We will know this is true when repeated bookings increase by 20%.
We believe this because of a documented spike in guest inquiries about loyalty rewards over the past six months.”
Validation & experiment
Experiment Type
Concierge loyalty experiment with 500 users — manually delivering the reward experience to validate demand before building the full system.
Feature to Test
A badge reward redeemable after every 2nd completed booking. Single feature, single variable, clean signal.
Prioritization Rationale
One feature, one test. Scope was deliberately constrained to isolate whether the reward mechanic itself drove repeat booking behavior — before layering in notifications, tiers, or additional incentives.
MVP features
$75 booking credit earned automatically on every 2nd completed stay. Visible in the user's profile as a badge showing total stays and available credit. Simple, transparent, and zero friction to understand.
A one-tap redemption button surfaced directly on the booking screen. The discount applies instantly — no code entry, no separate redemption flow, no friction between earning and using.
Credits expire after 6 months if unused. Credits do not accumulate — the current credit must be used or expire before the next one is earned. Keeps the program simple and creates a soft urgency to rebook.
Removed from MVP: Push notifications, experience booking incentives, and additional reward types — all deprioritized to Phase 2 to keep Sprint 1 focused and testable.
PRD highlights
A repeat business traveler opens the app, sees they have loyalty credit, searches for a 1-bedroom condo, selects dates, applies the reward at checkout, and completes the booking in under 5 minutes.
“As a repeat business traveler, I want to easily see and use my loyalty credit at the time of my choosing.”
Metric
What It Measures
Baseline
Target
Sign-up Rate
Customers opting into the loyalty program
0% (new product)
>50%
Redemption Rate
$75 credit is attractive and being used
0% (new product)
>80%
Repeat Booking Rate
Revenue growth from increased booking frequency
30% (without loyalty)
>50% (with loyalty)
Visual roadmap
Phase 1
Badge intro with $75 credit redemption. Core reward mechanic, profile badge, checkout redemption button. Goal: validate that the reward drives repeat booking behavior.
Phase 2
Push notifications and in-app alerts for earned credits. Experience booking incentive — extend the reward to Stay-N-Sleep Experiences, not just lodging. Goal: increase redemption rate and expand reward surface area.
Phase 3
Build an algorithm to enhance experience recommendations based on traveler history and preferences. Goal: make the loyalty program feel tailored, not transactional.
Phase 4
Introduce reward tiers with higher credits for higher booking frequency. Goal: drive long-term retention and create status-based loyalty for the highest-value travelers.
Variation A — Frequent Business Traveler
MVP Sprint #1 Breakdown
Owner
Task
Considerations
Milestone
Front-end Engineering
Create Badge
Badge clearly visible in UI with stay count and credit amount
MVP Sprint #1
Back-end Engineering
Discount Calculation Logic
Implement logic to calculate correct loyalty discount per booking count
MVP Sprint #1
Front-end + Back-end
API Integration
Connect UI discount display with back-end calculation logic
MVP Sprint #1
QA Engineering
Testing
Validate discount calculation accuracy and badge display across device sizes
MVP Sprint #1
GTM strategy
Target Users
Jim Hare — Frequent Business Traveler. Daniel Brooks — Corporate Travel Manager. Both segments activated through different messaging: travelers receive the reward value prop, managers receive the visibility and control story.
Monetization Strategy
Increased revenue through higher booking frequency. The loyalty credit is not a cost center — it's a retention investment. Each $75 credit issued drives a repeat booking worth significantly more in revenue and LTV.
Marketing Channels
Owned media only at launch — email, in-app notifications, and push notifications. Zero paid acquisition spend. The program sells itself to users already on the platform.
Campaign Success Metric
Repeat booking rate increase of 20% within the first 90 days of launch.
Customer Adoption Plan
In-depth program explainer and FAQ delivered via email at sign-up. Frictionless onboarding — users are enrolled automatically, no separate sign-up required.
Support & Optimization
After 90 days, optimize loyalty incentives and messaging based on adoption and repeat booking data. Collect qualitative signal via in-app survey to inform Phase 2 feature prioritization.
What I learned
The most clarifying constraint on Stay-N-Sleep Rewards was the decision to remove notifications from the MVP. It felt like a risk at the time — how would users know they had credit? But keeping Sprint 1 to a single testable mechanic meant we'd get a clean signal on whether the reward itself drove behavior, not whether our notification copy was good. That sequencing discipline is something I carry into every product build.
The dual-persona structure — traveler and travel manager — also sharpened the GTM strategy in ways that a single-persona approach wouldn't have. The traveler needs to feel rewarded. The manager needs to feel in control. Those are different messages to different buyers in the same product, and treating them as one audience would have produced a weaker launch for both.
Building the full stack — hypothesis through GTM — in a single product cycle reinforced something I believe deeply: the roadmap is only as good as the hypothesis that precedes it, and the GTM is only as good as the personas that inform it. Every section of this project was load-bearing.