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Measurement and analysis is the backbone of any successful digital marketing strategy. But traditional analytics gives all visitors the same weight and as a result, lack insight into how people behave over time. Measuring this behavior and common characteristics among groups of users can lead to insight that helps drive campaign strategy.
This is why cohort analysis should be a key tool when you are measuring any marketing campaign. First, let’s define the term:
Cohort analysis is a subset of behavioral analytics that takes the data from a given eCommerce platform, web application, or online game and rather than looking at all users as one unit, it breaks them into related groups for analysis. These related groups, or cohorts, usually share common characteristics or experiences within a defined timespan. Cohort analysis allows a company to “see patterns clearly across the lifecycle of a customer (or user), rather than slicing across all customers blindly without accounting for the natural cycle that a customer undergoes.” Source: Wikipedia
At Nanigans, we’ve developed a cohort analysis tool specifically for Facebook advertising campaigns that empowers advertisers to understand and compare the value generated by ad placements and customers in the days, weeks, and months after initial ads are delivered.
For example, in the cohort analysis below, the advertiser is comparing revenue generated by weekly groupings of Facebook ad placements during the 15 days after the ad campaign went live. In this screenshot we can see the total number of purchases generated by each cohort, and easily surface details about groups of users within this ad campaign. A darker shaded cohort cell indicates better performance, and the point at which text turns from black to white indicates when these cohorts generated a positive return on ad spend.
We can see clearly that the November 25th group of users represented the highest volume of purchases, as well as the largest revenue from the included time period.
Some other key callouts from this cohort analysis, which may help you evaluate your own:
Within Nanigans Ad Engine, advertisers can immediately dive into Performance Analysis to further investigate why some groups of users performed well and why others did not.
After identifying your top-performing ads (based on revenue, or any other key metric you are using to judge campaign performance), take these steps to find out why they performed differently:
In Nanigans Ad Engine, this is as easy as sorting your table and viewing the attributes you would like to see. Running this analysis not only gives you perspective on what creative, targeting, and other attributes you should use in your next campaign, but also tells you which creative did not perform well so you can be sure not to use it next time.
Want to see Cohort Analysis in action? Contact us today for a demo.Contact Us Today