In digital marketing, personalization is the name of the game. No element of advertising has more power to engage users and push consumers down the conversion funnel than personalized content that demonstrates an understanding of the consumer’s interests, behaviors, and values. If you have any experience with digital or ecommerce marketing, you’ve probably become aware of terms like “target audience,” “persona,” “segmentation,” and others, all of which are key for personalization. Cohort audiences take the concept of personalization to the next level, using information from both first- and third-party sources to create detailed associations between users, enabling marketers to target smaller groups of shoppers with highly specific ads.
What are cohort audiences, and how are they different from the other terms used to describe groups of consumers? Let’s explore the idea of cohorts, discuss why they’re helpful, and then dive into some examples.
What Are Cohort Audiences?
Cohort audiences are similar to audience segments or demographic groups in that they share a common set of criteria. However, cohorts go deeper than audience segments, unifying a group of users according to shared experiences. Think of cohorts as the next level of specificity in your audience personas: they share demographic and psychographic qualifiers, but they also share an event or key experience.
How are Cohorts Different from Audience Groups, Personas, or Segments?
To be clear: all cohorts are segments or groupings of an audience, but not all groupings of users are cohorts. Time and shared experience are the critical factors for establishing cohort groups.
Why Do Marketers Use Cohort Audiences?
As we explained above, personalization has become the be-all, end-all of digital marketing. There are several reasons for that, including the fact that ecommerce and digital retail have evolved to a point where their users expect a high level of treatment and service. That includes providing users with relevant advertising. Nothing frustrates today’s online shoppers like being treated like a faceless number instead of someone with unique interests and needs.
Research indicates that consumers can tell when they’re not receiving personalized content, and they are willing to punish brands that don’t offer personalized experiences. A 2017 report from Accenture said that 41% of shoppers have switched to a competitor brand because of poor personalization. These losses amounted to $756 billion for enterprises in the United States.
For brands, this means that a lack of personalization can be the end of a business. That’s why marketers make use of cohorts — they provide a degree of personalization that speaks not just to interests or values but to specific shared experiences that have shaped people into who they are. Demonstrating that level of understanding can go a long way in developing customer trust and positive brand perception.
Of course, you don’t need a transformative life experience to create cohorts. The “shared experience” between users in a cohort can be as simple as the time interval they signed up for a brand’s emails.
How Do Marketers Use Audience Cohorts?
Most digital marketing tools, such as AdRoll’s Marketing Platform, include functionality to help you create cohort criteria, group users into meaningful cohorts, and analyze data related to how those groups interact with your business. Google Analytics is another standard tool for cohort analysis.
Digital marketers typically use cohort audiences for two primary purposes.
Having a group defined by a specific shared trait or experience can help promote a particular product that might be especially relevant to that group. For instance, if you noticed an influx of users signing up for your emails immediately after announcing a new product, you might use a cohort audience composed of people who signed up after the audience to create a campaign that provides those users with a high degree of detail about that product. You can use these smaller groups to gauge why users might have signed up and predict what they might find interesting on your website.
Likewise, you could create a cohort group from a set of users who share both traits and experiences. For example, consider an outdoor gear brand that just hosted a special event explicitly related to rock climbing. You might identify a cohort of women aged 25-40 who attended that event as the most likely customers for a line of women’s climbing shoes. This is another tactic marketers can use to discover more specific information about their customers.
2. Understanding user behavior
Cohort audiences can also help build upon what you know about your audience. Using a tool like AdRoll’s marketing platform, marketers can review a report about audience trends concerning a metric like churn. While analyzing churn, you might separate “churned” shoppers out into cohorts defined by specific traits. This can help make inferences about why shoppers might have stopped interacting with the brand.
For instance, a cohort could include users who signed up for a special event and churned afterward. In this case, some explanations for the churn could be that the event didn’t meet their expectations, or perhaps they lost interest if the content they received afterward was not related to the event.
Make a Difference to Your Bottom Line
Cohort audiences can’t do everything — sometimes, the degree of specificity assigned to these groups can make it difficult to glean accurate information about users, and cohorts aren’t especially useful for making creative decisions about content intended for large groups. It can also be challenging to collect data that allows for valuable cohorts — it might involve researching surveys or other tactics that aren’t practical for smaller brands.
Still, cohorts provide opportunities for marketers to improve their strategies and develop highly targeted campaigns that can make a difference for your bottom line. With a strong understanding of cohort analysis, you can reach more customers more effectively, leading to more conversions and a more efficient strategy.
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Last updated on January 11th, 2023.