Marketing Metrics to Measure

Image: Medium

Analytics Metrics & Analyzing Results

Chapters 12 and 13 of Marketing Analytics discusses the role marketing metrics play in analytics and how the results of A/B tests and experiments should be correctly analyzed. Both chapters discuss vital points that relate back to the overarching themes of the book—that of analyzing data and relating that to an effective marketing strategy.

Metrics and More Metrics

Chapter 12 of Marketing Analytics discusses many of the vital metrics that play a part in marketing analytics. Marketing analytics metrics are defined as measures of a data-driven project to maximize marketing effectiveness. Marketing analytics metrics provide brands and businesses with valuable insights that range from customer leads to consumer preferences. Only if marketers fully understand the vital metrics will they be able to optimize their marketing campaign performance and budget

There are three sort of stages to marketing analytics metrics: identifying the metrics to use, analyzing those metrics, and then taking improvement actions. It’s first important to identify the metrics which will align with the goals set forth for the campaign. Then the metrics much be analyzed and compared with other, existing metrics in order to determine whether the campaign performed well. And in the final stage appropriate adjustments must be made in order to keep the campaign performing well or get it to the point where it does perform well.

Image: Stukent

The Campaign Life Cycle

Another part of managing marketing analytics metrics is seeing how it influences each stage of the campaign’s life cycle. An example of a campaign life cycle can be seen in the image above but the general cycle revolves around three stages: design, implementation, and evaluation.

Design is the process of designing the campaign elements, which also includes outlining the metrics that will be most useful in tracking the success rate of the campaign. The second stage, implementation, is the distribution of the campaign and usually a good time to perform experiments like A/B tests. In the final evaluation stage the campaign results are analyzed and pegged against the goals the campaign wanted to achieve.

“Few managers appreciate the range of metrics by which they can evaluate marketing strategies and dynamics. Fewer still understand the pros, cons, and nuances of each.”

—Paul W. Farris

Metrics to Measure

Among other elements that determine a campaigns success, ensuring the right metrics are selected and tracked during the campaign’s course is one of the most important. The metrics selected should support the overarching goals of the campaign and the priorities of the company behind it. Metrics can be either strategic or support metrics and then can be broken down into further subcategories.

Many of the metrics marketers look to fall under support metrics, these include a variety of brand, customer, digital, and development metrics. Working in the marketing department of an e-commerce company, I can say that many of the metrics I look to fall into the digital marketing metrics category. This category includes vital metrics such as conversion rate, unique visitors, referrals, bounce rate, and much, much more.

Analyzing Results the Right Way

Continuing on in the Marketing Analytics book, chapter 13 discusses how to analyze statistical data from experiments, including A/B tests. The chapter discusses two ways to statistically analyze results from A/B tests, those include: T-Tests and Bayesian statistical applications. Then for the purpose of analyzing results of an experiment, ANOVA and ANOVA contrasts can be used to see whether an experiments hypothesis was correct or not.

The fact of the matter is, only if a marketer knows how to effectively determine which metrics fit their goals and how to accurately analyze those metrics will their campaigns be considered a success. By utilizing valuable metrics and analyzing them right, any campaign is sure to succeed!