"Attributed revenue, ROAS, conversion rate - traditional marketing metrics track efficiency but often miss the signals that reveal which customers drive growth. Today, first-party customer data is more accessible and valuable than ever. And when combined with AI, it opens the door to a new era of customer-centered performance measurement. Customer analytics shifts the focus from channels to customers, framing analysis and activation around engagement, growth and predicted value."
"Where traditional measurement falls short, customer analytics delivers Media mix modeling (MMM) and attribution modeling are critical tools for understanding: These approaches help answer "How should I spend?" but not "Who should I target?" MMM rarely provides enough depth around customer segment performance and attribution assigns value at a level that isn't actionable for real-world targeting. Both approaches measure past efficiency but do little to explain which customer groups drive outcomes or where growth opportunities exist."
Traditional marketing metrics such as attributed revenue, ROAS and conversion rate measure efficiency but often miss which customers drive growth. First-party customer data combined with AI enables customer-centered performance measurement. Customer analytics shifts focus from channels to customers by organizing customers into segments based on past and predicted behavior, framing analysis and activation around engagement, growth and predicted value. Connecting historical behavior with forecasted outcomes allows smarter targeting decisions and action prioritization. Media mix modeling and attribution explain spending efficiency but lack actionable segment-level insights. Testing customer segments across channels identifies who drives incremental demand and where targeting should shift.
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