Why are TripleLift's programmatic direct deals seeing a 20% lower fill rate compared to the previous quarter?

Introduction

TripleLift's programmatic direct deals are experiencing a 20% lower fill rate compared to the previous quarter, indicating a significant performance issue that requires immediate attention. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term and long-term implications for the business.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be seasonal factors at play. Has this 20% drop been consistent across all advertiser verticals, or are some more affected than others?

Why it matters: Helps identify if this is an industry-wide trend or specific to certain sectors. Expected answer: Variation across verticals. Impact on approach: If consistent, focus on internal factors; if varied, investigate vertical-specific issues.

• Considering recent product updates, I'm curious if there have been any changes to the deal setup process or targeting options. Have we introduced any new features or modified existing ones in the past quarter?

Why it matters: Identifies potential internal causes for the fill rate drop. Expected answer: Some product changes implemented. Impact on approach: If yes, focus on recent changes; if no, look at external factors or gradual shifts.

• Thinking about market dynamics, has there been any significant shift in competitor offerings or pricing strategies that might be affecting our competitiveness?

Why it matters: Helps understand if external market forces are impacting our performance. Expected answer: Some changes in competitor landscape. Impact on approach: If yes, focus on market positioning; if no, look more closely at internal factors.

• Considering data integrity, I'm wondering if there have been any changes to how we measure or calculate fill rates. Has the definition or measurement process for fill rates remained consistent?

Why it matters: Ensures we're comparing apples to apples and not dealing with a data anomaly. Expected answer: No changes in measurement. Impact on approach: If changed, investigate data discrepancies; if consistent, focus on performance factors.