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Product Management Trade-off Question: Unity Ads balancing higher revenue with ad relevance for mobile games
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Vinay

Updated Dec 4, 2024

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Should Unity Ads prioritize higher-paying but potentially less relevant ads or maintain stricter targeting?

Product Trade-Off Hard Member-only
Trade-Off Analysis Metrics Definition Experiment Design Mobile Gaming Digital Advertising Ad Tech
User Experience Product Strategy Mobile Gaming Ad Monetization Unity

Introduction

The trade-off question at hand is whether Unity Ads should prioritize higher-paying but potentially less relevant ads or maintain stricter targeting. This scenario involves balancing revenue optimization with user experience and advertiser satisfaction. I'll analyze this trade-off by examining the product ecosystem, stakeholder impacts, and potential outcomes, ultimately providing a data-driven recommendation.

Analysis Approach

I'd like to outline my approach to ensure we're aligned on the key areas I'll be covering in my analysis.

Step 1

Clarifying Questions (3 minutes)

  • Context: I'm assuming Unity Ads is a significant revenue driver for Unity. Could you confirm if this is correct and provide a rough percentage of overall revenue it contributes?

Why it matters: Helps gauge the impact of any changes on Unity's financial health. Expected answer: 30-40% of revenue Impact on approach: Higher percentage would necessitate more cautious experimentation

  • Business Context: Based on current market conditions, I'm thinking advertiser demand might be fluctuating. How stable has advertiser demand been over the past quarter?

Why it matters: Influences the urgency of optimizing for higher-paying ads Expected answer: Slight decline in demand Impact on approach: Might lean towards exploring higher-paying ads if demand is declining

  • User Impact: Considering user engagement metrics, I'm curious about the current ad relevance scores. What's the average relevance score for ads shown in the past month?

Why it matters: Establishes a baseline for current targeting effectiveness Expected answer: 7/10 relevance score Impact on approach: Lower scores might justify maintaining stricter targeting

  • Technical: Given the potential for increased ad inventory, I'm wondering about our current ad serving capacity. How close are we to maxing out our current infrastructure?

Why it matters: Determines if we can handle increased ad volume Expected answer: Operating at 70% capacity Impact on approach: High capacity utilization would require infrastructure investments

  • Timeline: Considering Q4 is often crucial for ad revenue, I'm thinking this decision might be time-sensitive. How soon does leadership expect to see results from this initiative?

Why it matters: Influences the scope and pace of experimentation Expected answer: Results expected within 2-3 months Impact on approach: Short timeline might necessitate faster, smaller-scale tests

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