Is it better for Chegg to invest in AI-powered study tools or enhance human expert-led solutions?

Introduction

The trade-off between investing in AI-powered study tools or enhancing human expert-led solutions is a critical decision for Chegg's future. This scenario involves balancing technological innovation with the proven value of human expertise in education. I'll analyze this trade-off by examining product understanding, metrics, experimentation, and decision-making frameworks to provide a strategic recommendation.

Step 1

Clarifying Questions (3 minutes)

• Context: I'm thinking about Chegg's current market position in the edtech space. Could you share how our market share compares to competitors offering similar services?

Why it matters: Helps understand competitive pressure and urgency for innovation Expected answer: Chegg has a strong position but faces increasing competition Impact on approach: Would influence the balance between maintaining current offerings and investing in new technologies

• Business Context: Based on our revenue model, I assume subscription services are our primary income source. How does the revenue split look between our various products and services?

Why it matters: Identifies which areas of the business might be most impacted by this decision Expected answer: Majority revenue from subscriptions, with growing income from digital services Impact on approach: Would help prioritize which aspects of the product to focus on for enhancement

• User Impact: Considering our user segments, I'm curious about the breakdown between high school, undergraduate, and graduate students. What's the current distribution, and how has it been trending?

Why it matters: Different user segments may have varying needs and preferences for AI vs. human expertise Expected answer: Majority undergraduate, with growing high school segment Impact on approach: Would influence the design of solutions to cater to specific segment needs

• Technical Feasibility: Regarding our AI capabilities, what's our current level of in-house expertise versus reliance on third-party solutions?

Why it matters: Determines the feasibility and timeline for developing advanced AI tools Expected answer: Mix of in-house and third-party, with growing internal capabilities Impact on approach: Would affect the speed and cost of implementing AI solutions

• Resource Allocation: Thinking about our current team structure, how are our engineering and subject matter expert teams currently allocated between AI and human-led solutions?

Why it matters: Indicates current resource balance and potential for reallocation Expected answer: More resources currently in human-led solutions, but growing AI team Impact on approach: Would influence the speed and scale of potential shifts in focus