Case Study
FinTech / Loyalty Rewards
Real work-product visual from the engagement: the behavior loop connecting customer spend to platform revenue.
Loyalty Rewards Platform: proving the economics behind a behavior-driven rewards system.
The platform already had a defined concept: customers spend at participating merchants through Raast payments, the platform tracks progress toward a spending threshold, and a reward unlocks once they hit it. The mechanics made intuitive sense. What was missing was proof that the economics actually worked, whether the model created real merchant value rather than just giving away margin on spending that would have happened anyway.
What We Did
01
Business Model & Behavioral Reframing
Reframed the platform from a generic loyalty system into a behavior-shaping system, and changed the core economic question from "how much does the merchant give away in rewards?" to "how much incremental gross profit does this create relative to what the merchant spends to participate?" Separated baseline spending from genuinely incremental behavior across frequency lift, basket expansion, wallet-share shift, and cannibalized spend.
02
Market Segmentation & Customer Baselines
Built category-specific baseline behavior instead of one generic average customer, testing merchant economics against real purchasing patterns across three segments.
Fast Food / QSR
4 visits/mo × PKR 800 AOV
40% of mix
Cafes / Beverage
3 visits/mo × PKR 1,200 AOV
35% of mix
Grab-and-Go
5 visits/mo × PKR 650 AOV
25% of mix
03
Financial Model & Scenario Planning
Built a three-year economic model spanning customer/merchant growth, GMV, reward economics, CAC, margins, and break-even, modeled across Conservative, Realistic, and Aggressive scenarios rather than one optimistic forecast. This surfaced six primary economic drivers: threshold completion rate, frequency lift, basket expansion, merchant ROI, repeat reward-cycle participation, and merchant retention.
04
Pricing & Monetization
Evaluated redemption-based, SaaS, and hybrid pricing before landing on a hybrid model: merchant SaaS subscriptions plus transaction-linked platform fees, balancing recurring revenue with participation in the value the platform actually creates.
05
Pilot Validation Framework
Designed a 4–8 week pilot framework targeting the exact assumptions with the lowest confidence before real-world data: threshold completion, incremental spend, frequency lift, adoption, repeat behavior, and merchant economics, rather than treating unproven assumptions as settled facts.
06
Merchant Pitch Framework
Structured the commercial narrative merchants actually hear: Hook → Problem → Current Inefficiency → Solution → How It Works → Merchant Value → Risk Reversal → Pilot Ask, making the platform sellable without requiring a merchant to understand the full financial model.
The Merchant ROI Framework
The central commercial question: "If I'm a merchant, what do I pay and what do I actually gain?" This framework turned a complex financial model into something usable in real merchant sales conversations and pilots.
Incremental Spend→
Incremental Gross Profit→
Reward Cost→
Platform Fees→
Net Merchant Gain
Modeled Realistic Behavioral Case
15%
FREQUENCY LIFT
8%
BASKET EXPANSION
~22.75%
TRUE INCREMENTAL SPEND LIFT
Also modeled: 6% wallet-share shift and 25% cannibalized spend (spending that would have happened anyway). All modeled assumptions requiring pilot validation, not measured results.
3-Year Realistic Model (Modeled)
| Metric | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| Active Users | ~51,748 | ~105,370 | ~168,000 |
| Active Merchants | 77 | 286 | 761 |
| GMV | ~PKR 100.3M | ~PKR 586.8M | ~PKR 1.43B |
| Incremental GMV | ~PKR 22.8M | ~PKR 133.5M | ~PKR 324.2M |
| Platform Revenue | ~PKR 2.62M | ~PKR 21.34M | ~PKR 78.17M |
| EBITDA | ~(PKR 5.41M) | ~PKR 3.89M | ~PKR 47.11M |
Modeled break-even around Year 2, under the "Realistic" scenario. All figures are projected outputs of the financial model, not achieved results — There is no confirmed revenue, users, signed merchants, or funding at this stage.
Modeled Merchant ROI (By Scenario)
2.67×
CONSERVATIVE
3.33×
REALISTIC
3.95×
AGGRESSIVE
Modeled merchant ROI multiples depend directly on assumptions about incremental behavior, merchant margins, completion, and adoption — presented as scenario outputs, not guaranteed or achieved returns.
FOCUS: ECONOMIC VALIDATION, NOT A CONFIRMED RAISE
There is currently no confirmed fundraising target, closed round, or achieved traction for Paylo, revenue, users, signed merchants, and funding all remain unconfirmed. What's defensible: Paylo moved from a promising rewards concept dependent on broad, unvalidated assumptions to a structured economic and go-to-market system, showing exactly how customer behavior, merchant ROI, platform monetization, and break-even interact, with the specific assumptions a pilot needs to validate clearly identified rather than hidden inside an optimistic headline forecast.
Behavioral Economics Model
Market Segmentation
3-Year Financial Model
Scenario Analysis
Pricing Strategy
Merchant ROI Framework
Pilot Design