For Samba TV's addressable TV advertising platform, how should we balance increasing ad load for higher revenue versus maintaining viewer experience?

Introduction

Balancing ad load and viewer experience on Samba TV's addressable TV advertising platform presents a critical trade-off. We need to optimize revenue while maintaining user satisfaction. I'll analyze this challenge through multiple lenses, considering stakeholder impacts, metrics, and experimental approaches.

Step 1

Clarifying Questions (3 minutes)

• Context: I'm assuming Samba TV operates on smart TVs and streaming devices. Is this correct, or are there other platforms we need to consider?

Why it matters: Impacts the scale and types of ad inventory available. Expected answer: Primarily smart TVs and streaming devices. Impact: Focuses analysis on connected TV ecosystem.

• Business Context: Based on industry trends, I'm thinking addressable TV ads are a high-growth revenue stream. How does this align with our overall revenue mix and growth targets?

Why it matters: Helps prioritize this initiative against other business objectives. Expected answer: Significant growth driver, 30-40% of revenue. Impact: Would justify more aggressive ad load testing if true.

• User Impact: I'm assuming we have different viewer segments based on content preferences. Can you share insights on how ad sensitivity varies across these segments?

Why it matters: Allows for targeted ad load strategies. Expected answer: Sports viewers more tolerant, drama viewers less so. Impact: Would lead to segment-specific recommendations.

• Technical: Considering the real-time nature of TV, I'm curious about our current ad insertion capabilities. How granular can we get with personalized ad loads?

Why it matters: Determines feasibility of sophisticated targeting. Expected answer: Household-level targeting possible, working on individual. Impact: Influences complexity of proposed solutions.

• Timeline: Given the competitive landscape, I'm thinking this is a high-priority initiative. What's our target timeline for implementing changes?

Why it matters: Affects the scope and ambition of proposed experiments. Expected answer: Aiming for Q4 holiday season. Impact: Would prioritize quick wins and iterative approach.