You're the PM for Uber Eats. What goals do you set for your team?

Introduction

Setting effective goals for Uber Eats is crucial for driving growth and ensuring customer satisfaction in the competitive food delivery market. To approach this product success metrics problem effectively, I'll follow a structured framework that covers core metrics, supporting indicators, and risk factors while considering all key stakeholders.

Step 1

Product Context

Uber Eats is a food delivery platform that connects restaurants, delivery partners, and customers. It operates within Uber's broader ecosystem, leveraging the company's existing technology and user base.

Key stakeholders:

1. Customers: Seeking convenient, quick food delivery
2. Restaurants: Looking to expand their reach and increase sales
3. Delivery partners: Seeking flexible income opportunities
4. Uber: Aiming to diversify revenue streams and increase platform stickiness

User flow:

1. Customers browse restaurants and menus in the app
2. They place an order and make payment
3. Restaurants receive and prepare the order
4. Delivery partners pick up and deliver the food
5. Customers receive their order and can rate the experience

Uber Eats fits into Uber's strategy of becoming a super-app for transportation and delivery services. It competes with other major players like DoorDash and Grubhub, differentiating itself through Uber's existing user base and technology infrastructure.

Product Lifecycle Stage: Growth to Maturity. Uber Eats has established a strong market presence but continues to expand into new markets and add features to stay competitive.

Step 2

Goals

Step 3

North Star Metric

Proposed North Star Metric (NSM): Monthly Active Eaters (MAE)

Definition: The number of unique customers who place at least one order through Uber Eats in a given month.

Calculation: Count of unique user IDs that completed an order in the past 30 days.

This metric best captures success because it reflects the platform's ability to attract and retain customers, which is crucial for long-term growth and profitability. It also indirectly indicates the health of other aspects of the business:

• For customers, it shows the platform's ability to meet their needs consistently
• For restaurants, it represents a growing customer base
• For delivery partners, it suggests steady work opportunities
• For Uber, it indicates the success of the Eats division in contributing to overall company growth

Hypothetical data: If MAE increases from 20 million to 22 million over a quarter, it would indicate strong growth and customer satisfaction. A decline might suggest increased competition or user experience issues that need addressing.

Breakdown of North Star Metric

MAE can be broken down into its component parts:

Formula breakdown: MAE = f(New Customers, Returning Customers) New Customers = f(Marketing Effectiveness, First-time User Experience) Returning Customers = f(Customer Retention, Order Frequency) Customer Retention = f(Service Quality, Restaurant Selection) Order Frequency = f(Promotions and Loyalty Programs, App Engagement)

Step 4

Supporting Metrics

Step 5

Guardrail Metrics

Customer Satisfaction Score directly impacts retention and word-of-mouth growth. If it drops below 4.5, it could lead to customer churn and negatively impact MAE.

Restaurant Commission Rate affects the platform's ability to maintain a diverse restaurant selection. If it exceeds 30%, restaurants may leave the platform, reducing food options and potentially decreasing MAE.

Delivery Partner Earnings ensure a stable workforce. If earnings drop too low, it could lead to longer delivery times and unfulfilled orders, negatively impacting MAE.

Contribution Margin is crucial for Uber Eats' sustainability. If it falls below 10%, it might lead to reduced investment in the platform, affecting features and marketing that drive MAE growth.

Step 6

Trade-off Metrics

1. Order Volume vs. Average Order Value

   • Trade-off: Increasing order volume through promotions might decrease AOV
   • Balance: Focus on increasing order frequency for high-value customers while running targeted promotions for others

2. Restaurant Selection vs. Delivery Time

   • Trade-off: Adding more restaurants might increase delivery times due to wider geographic spread
   • Balance: Optimize delivery zones and use predictive algorithms to manage restaurant onboarding

3. Customer Acquisition vs. Customer Retention

   • Trade-off: Focusing on new customer acquisition might neglect existing customer needs
   • Balance: Allocate resources based on customer lifetime value predictions, ensuring a mix of acquisition and retention efforts

Step 7

Counter Metrics

1. Food Quality Complaints

   • Purpose: Ensures focus on order quality, not just quantity
   • Avoiding pitfalls: Prevents chasing growth at the expense of customer experience
   • Actions: If complaints increase, implement stricter quality controls and restaurant feedback systems

2. Delivery Partner Churn Rate

   • Purpose: Monitors the stability of the delivery workforce
   • Avoiding pitfalls: Prevents focus on customer acquisition leading to neglect of delivery partners
   • Actions: If churn increases, review compensation structure and improve support systems

3. App Crash Rate

   • Purpose: Ensures technical stability as the platform scales
   • Avoiding pitfalls: Prevents rapid feature development from compromising app performance
   • Actions: If crash rate increases, prioritize technical debt and infrastructure improvements

Strategic Initiatives

1. AI-Powered Personalization

   • Rationale: Improve user experience and increase order frequency
   • Impact: Could increase MAE and AOV by tailoring recommendations
   • Challenges: Requires significant data analysis and algorithm development

2. Virtual Restaurant Incubator

   • Rationale: Expand unique food offerings and support local businesses
   • Impact: Could increase restaurant selection and customer engagement
   • Challenges: Requires careful vetting and potential investment in kitchen spaces

3. Sustainable Packaging Program

   • Rationale: Address growing environmental concerns and differentiate from competitors
   • Impact: Could improve brand perception and attract eco-conscious customers
   • Challenges: Requires coordination with restaurants and potential cost increases

Conclusion

Emerging technologies like autonomous delivery vehicles and drone delivery could significantly impact Uber Eats' operations and metrics. Success metrics may need to evolve to include factors like environmental impact and integration with smart home devices for automated ordering.

Expand Your Perspective

• How might cultural differences in various markets affect the relevance of these metrics?

• What role could blockchain technology play in enhancing transparency and trust in the food delivery ecosystem?

• How might the rise of ghost kitchens and virtual brands impact Uber Eats' strategy and metrics?

Related Topics

• Multi-sided platform strategy

• Data privacy and ethical use of customer information

• Integrating sustainability into core business metrics

• Balancing gig economy dynamics with worker protections

• Leveraging network effects in food delivery platforms