Marketing Analytics

Marketing analytics is the study of data garnered through marketing campaigns in order to discern patterns between such things as how a campaign contributed to conversions, consumer behavior, regional preferences, creative preferences and much more. The goal of marketing analytics as a practice is to use these patterns and findings to optimize future campaigns based on what was successful.

Marketing analytics benefits both marketers and consumers. This analysis allows marketers to achieve higher ROI on marketing investments by understanding what is successful in driving either conversions, brand awareness, or both.  Analytics also ensures that consumers see a greater number of targeted, personalized ads that speak to their specific needs and interests, rather than mass communications that tend to annoy.

Marketing data can be analyzed using a variety of methods and models depending on the KPIs being measured. For example, analysis of brand awareness relies upon different data and models than analysis of conversions. Some popular analytics models and methods include:

• Media Mix Models (MMM): Attribution models that look at aggregate data over a long period of time.
• Multi-Touch Attribution (MTA): Attribution models that provide person-level data from across the buyer’s journey.
• Unified Marketing Measurement (UMM): A form of measurement that integrates various attribution models including MMM and MTA into comprehensive engagement metrics.