Ecosystem changes are forcing brands to adapt their marketing strategies.
- Tried and true marketing strategies will be seriously challenged with log file sunset, cookie demise, and privacy regulation
- 1:1 marketing will go from difficult to nearly impossible
- Cohort analysis will emerge as the new path forward
If you’re not familiar with the term cohort, you’re not alone. But, it will begin to play a more critical role in your digital marketing strategy moving forward.
We consider cohorts to be one of the 4 C’s of impending obstacles marketers will face with the landscape transformations upon us. The other 3 being cookies, clouds, and clean rooms. To learn more about those, check out ‘Un-platform’ Your Tech Stack by Avanti Gade.
In its simplest form, a cohort is a group of users who share a common characteristic, identified by particular actions, behaviors or demographic make up. You might think, “well that sounds like a segment”, which it does. The terms cohorts and segments are often used interchangeably, particularly when doing analysis, but they are in fact, not the same. To be considered a cohort, a group of users must be bound by a common event and time period. However, a segment of users can be created with almost any condition as a foundation; it doesn’t have to be time and event-based. There are some that even consider a segment to be a marketing concept that allows you to take action upon a cohort. As our Machine Learning Engineer, Andreea Anicai, describes it, “you can think of a cohort as the intelligence, and a segment as the vessel that delivers that intelligence wherever you desire.”
When it comes to analysis, cohorts will play an important role in future-proofing your marketing strategy as you prepare for the changes ahead. The “breaking down” of a dataset into cohorts is usually informed by some logic or algorithm, aimed at revealing underlying patterns that might not be immediately obvious. The tremendous importance of this type of analysis comes down to one word; privacy. Cohort analysis is not done on the 1:1 user level; it respects consumer privacy and can be relied on as more privacy regulations emerge. You will find cohort sizes of 50, 100 or 150 when you work within clean room environments like Google Ads Data Hub, Facebook Advanced Analytics and Amazon Marketing Cloud, among others. It’s highly unlikely that user-level data will be made available within many of these clean rooms, so cohort analysis is the currency to unlock the insights they can offer.
While privacy is at the forefront, there are many other benefits of cohort analysis to include:
- Improving customer retention and lifetime value. If users within a cohort have one defining shared feature and they exhibit a particular behavior, it can help inform what prompted that behavior.
- Delivering a more personalized user experience and targeted strategy. Because cohorts are bound by a common event and time period, it allows you to offer a more meaningful, relevant experience to a consumer than an audience defined by a sole attribute or characteristic.
- Simplification and actionability of user segmentation. While building segments is often a manual and time consuming process involving boolean logic, cohort analysis can be driven by clustering, allowing the data to reveal the customer personas that inherently live within a population of consumers that you can easily action upon.
While cohort analysis might be a relatively new term in our industry, it’s one you need to get on board with. In addition to it benefiting consumers from a privacy standpoint, it could also be one of the most effective ways to gather information regarding customer behavior and how they interact with your brand or product.
And while it may be hard to let go of the dream of 1:1; those that embrace the reality of 1:50, will be at an advantage in the market and find themselves well-positioned for the future.
Contribution from Andreea Anicai, Machine Learning Engineer at Habu