Segments
Last updated
Last updated
A Segment in Presight is a way to categorize, group, or filter data to derive more specific insights and take targeted actions. Segments allow you to break down large datasets into smaller, meaningful groups based on specific criteria, making it easier to analyze patterns, trends, or behaviors that are relevant to your business.
A Segment represents the qualitative attributes of data, while a Metric quantifies it. Metrics gain true significance when placed within the context of relevant segments. For example, a revenue figure of $3,000 alone offers little insight. However, when analyzed within the context of segments—such as City and Time—the metric becomes meaningful: "The revenue for New York in January is $3,000." This contextualization enables more insightful analysis, providing a clearer picture of business performance and trends.
Segments can be created in two main ways within Presight: by using data columns from your existing tables or by building custom segments through logical groupings using Presight’s intuitive features.
The simplest form of a segment is a data column from an uploaded table. These segments use existing values in your data to categorize or filter records. For example:
Customer Segment based on a "Region" column, grouping users from different geographical areas.
Product Segment using a "Product Category" column, which divides your data based on product types or categories.
Custom segments offer more flexibility by allowing you to create groupings based on logical conditions, calculations, and filters. Presight provides various tools to build custom segments tailored to your needs:
With the Column Editor, you can transform existing data columns or create new ones by applying formulas or transformations. This allows you to define segments based on logical, such as creating a Product Category segment by grouping different Products into their respective categories.
The Table Builder feature lets you customize how your data is displayed, grouped, or filtered. You can create custom views of your data that represent specific segments, such as showing only active customers or transactions within a particular date range.
Presight enables you to create segments using formulas that break down data based on calculated values or expressions. For example, you can segment all Registered Users based on whether or not they ever placed an order.
You can also build segments using Boolean filters, allowing you to define conditions such as IN or NOT IN segments. This makes it easy to filter out data or group records based on whether they meet specific criteria. For instance, you could create a segment for customers IN a specific loyalty program or exclude customers NOT IN a certain demographic.
Presight also allows you to create segments based on existing metrics that can be broken down into buckets. This type of segmentation divides metric values into defined ranges, making it easier to analyze data distributions and group similar values together. For example:
Revenue Segments: Break down revenue into buckets such as $0-$500, $501-$1,000, and so on, to identify customers based on their purchase levels.
Engagement Segments: Segment users based on their engagement scores (e.g., low, medium, high) derived from a metric that calculates overall number of activities.
This approach is highly useful for visualizing and comparing different levels of performance, engagement, or spend, and enables you to target specific groups with tailored strategies.
Segments help you analyze data more effectively by focusing on the aspects that matter most to your business. They enable you to:
Understand user behavior across different groups.
Target marketing campaigns to specific customer segments.
Compare performance across regions, product categories, or time periods.
Create personalized experiences by drilling down into specific customer traits.
With Presight, you have the tools and flexibility to define segments in a way that drives better insights, sharper focus, and more impactful business decisions.
