In developing Flipdish's loyalty program features, should the focus be on maximizing customer retention or increasing average order value for partner restaurants?

Introduction

The trade-off we're examining today is whether Flipdish's loyalty program features should focus on maximizing customer retention or increasing average order value for partner restaurants. This scenario involves balancing the interests of end customers, partner restaurants, and Flipdish's own business goals. I'll analyze this trade-off by considering various factors, including user behavior, business impact, and technical feasibility.

Step 1

Clarifying Questions (3 minutes)

• Business Context: I'm thinking Flipdish's revenue model likely involves taking a percentage of each order. Could you confirm if this is correct, and if there are any other significant revenue streams we should consider?

Why it matters: Understanding the revenue model helps prioritize between retention and order value. Expected answer: Primarily percentage-based, with potential additional services. Impact on approach: A higher reliance on order volume might shift focus towards retention.

• User Impact: Based on typical food delivery patterns, I'm assuming we have both frequent and occasional users. Can you share any insights on the current split between these user segments?

Why it matters: Different user segments may respond differently to loyalty features. Expected answer: Roughly 30% frequent users, 70% occasional. Impact on approach: A higher proportion of occasional users might favor AOV-focused strategies.

• Technical Feasibility: I'm thinking we might need to integrate with various POS systems. How complex is our current integration landscape with partner restaurants?

Why it matters: Technical complexity could impact the feasibility of certain loyalty features. Expected answer: Moderate complexity with a few major POS integrations. Impact on approach: More complex integrations might limit certain loyalty program options.

• Resource Constraints: Considering this is a significant feature, I'm assuming we have a dedicated team. Can you give me an idea of the team size and composition we're working with?

Why it matters: Resource availability affects the scope and timeline of potential solutions. Expected answer: Cross-functional team of 5-7 members. Impact on approach: A smaller team might necessitate a more focused, phased approach.

• Timeline Pressure: Given the competitive nature of food delivery, I'm guessing there's some urgency here. What's our target timeline for rolling out these loyalty features?

Why it matters: Timeline affects the depth of experimentation and iteration we can do. Expected answer: Aiming for initial release in 3-4 months. Impact on approach: A tight timeline might favor simpler, more immediately impactful features.