Overview
Follow this article to learn how audience segmentation works in Audiense Insights.
Audience segmentation helps you move beyond viewing your audience as a single group by identifying smaller communities that share similar characteristics. Rather than analyzing everyone together, segmentation uncovers meaningful clusters based on either relationships or shared interests, helping you better understand the different communities within your audience.
These audience segments can support more informed marketing decisions, improve audience targeting, and reveal opportunities that may not be visible when analyzing the audience as a whole.
What Is Audience Segmentation?
Audience segmentation is the process of dividing a larger audience into smaller groups based on common characteristics.
In Audiense Insights, segmentation is performed automatically using data-driven clustering algorithms. Instead of manually defining these groups, Audiense identifies naturally occurring communities based on how audience members relate to one another or the interests they share.
This process helps reveal patterns that may otherwise remain hidden, allowing you to better understand the different types of people that make up your audience.
Segmentation vs. Filtering
Although they are often confused, filtering and segmentation serve different purposes.
Filtering is the process of defining the audience you want to analyze. You select criteria such as location, biography keywords, accounts followed, or other profile attributes to determine who is included in the report.
Segmentation, on the other hand, begins after the audience has already been created. Rather than applying additional filters, Audiense automatically identifies meaningful subgroups within the selected audience using clustering algorithms.
In other words:
- Filtering determines who is included in the analysis.
- Segmentation discovers how that audience naturally groups together.
This distinction is important because segmentation is entirely data-driven and does not rely on predefined assumptions.
Why Is Segmentation Important?
Understanding the unique communities within an audience provides insights that are difficult to discover by looking at the audience as a whole.
Segmenting an audience can help you:
- Tailor content for different audience groups.
- Improve campaign targeting and return on investment.
- Strengthen lead generation strategies.
- Discover niche communities and new market opportunities.
Rather than treating every audience member the same, segmentation helps you understand the characteristics that make each group unique.
Segmentation Methods in Audiense Insights
Audiense Insights offers two segmentation methods, each designed to answer different types of research questions.
The method you choose depends on whether you're interested in understanding relationships between people or similarities in their interests.
| Segmentation Method | Based On | Algorithm | Best For |
|---|---|---|---|
| Interconnections | Relationships between audience members | Louvain | Discovering communities, professional networks, and closely connected groups |
| Affinities | Shared interests based on followed accounts | K-means | Building personas, identifying fandoms, and understanding interest-based audiences |
Regardless of the method used, each audience member belongs to only one cluster. Audiense automatically assigns each person to the cluster that best represents their observed behavior.
Interconnections Segmentation
Interconnections groups people according to how they are connected to one another.
Rather than looking at interests, this method analyzes the relationships between audience members. If users follow or interact with one another, Audiense identifies those relationships and groups them into communities using the Louvain community detection algorithm.
This approach is particularly effective for identifying tightly connected communities, professional networks, local groups, and communities where relationships between members are an important part of the analysis.
How to Interpret the Graph
In an Interconnections graph:
- Each node represents an audience member.
- Lines (edges) represent follower relationships between audience members.
- Larger nodes indicate members with more connections.
- Larger clusters represent communities with more members.
By default, Audiense automatically generates between 4 and 10 clusters, although additional clusters (up to 20) can be requested if needed.
Affinities Segmentation
Affinities groups audience members based on shared interests rather than direct relationships.
Instead of asking "Who knows whom?", this method asks "Who follows similar accounts?"
Using the K-means clustering algorithm, Audiense analyzes following behavior to identify users with similar interests, even if they have no direct relationship with one another.
This approach is well suited for understanding consumer interests, identifying brand personas, discovering fandoms, planning media strategies, and analyzing larger audiences.
Unlike Interconnections, Affinities allows you to control the level of segmentation by selecting between 2 and 20 clusters or by using Audiense's recommended number based on your audience size.
How to Interpret the Affinities Graph
Within an Affinities graph:
- Nodes represent both audience members and the influencers they follow.
- Connections illustrate shared interest patterns.
- Larger nodes indicate accounts with more connections.
- Larger clusters represent larger audience groups.
Because this visualization focuses on shared interests, it often reveals communities that would not be visible through relationship-based analysis alone.
Choosing a Segmentation Method
Both segmentation methods provide valuable insights, but they answer different questions.
Choose Interconnections when you want to understand how people within your audience are connected. This method is ideal for identifying communities, professional networks, local groups, and influence patterns.
Choose Affinities when your goal is to understand shared interests and behaviors. This method is especially useful for creating audience personas, identifying fandoms, planning partnerships, and developing media or influencer strategies.
If you're unsure which approach to use, consider the primary question you're trying to answer. If relationships between audience members matter most, Interconnections is likely the better choice. If you're interested in understanding what your audience has in common, Affinities is generally more appropriate.
Access Audience Segmentation
The segmentation options available depend on your Audiense subscription.
- Free Insights and X Marketing plans include Interconnections segmentation.
- Audiense Insights plans include both Interconnections and Affinities.
After defining your audience during report creation, simply choose your preferred segmentation method.
If you select Affinities, you'll also choose the desired number of clusters before launching the report.
Interconnections automatically determines the number of connected communities and does not require manual cluster selection.