Customer Segmentation

Customer segmentation built around your next campaign

Q: What is customer segmentation?

Customer segmentation groups customers by shared characteristics, behavior, lifecycle stage, or value. Teams use these groups to choose audiences, tailor marketing programs, and compare how different treatments perform.

Q: What are the main types of customer segmentation?

Common types include demographic, geographic, behavioral, value-based, lifecycle, and predictive segmentation. For example, high-value customers in a particular region whose purchase frequency has declined combine geographic, value, and behavioral criteria. The attributes available in your data determine which segments you can build.

Q: What is the difference between customer segmentation and audience building?

A segment defines the criteria for a group, such as customers who purchased in the past 90 days. An audience is the set of customers matching those criteria. Database segments calculate that audience when run; real-time segments maintain membership as profiles change. Delivery to a marketing channel follows its configured activation workflow.

Q: Why does identity resolution matter for customer segmentation?

Fragmented or duplicate records can distort audience counts and separate useful history from the customer it belongs to. Amperity resolves identity across connected customer data to give segmentation a more consistent view of each person. Results still depend on the source data and configuration.

Q: How does Amperity make customer segmentation self-service for marketers?

Marketers can define criteria in the visual Segment Editor. Where available, the AI Assistant can draft segments in natural language for review and saving. Technical users can also use SQL. Each approach works with the data and permissions available to the user; activation requires a supported, configured destination.

Q: How do self-updating customer segments work?

Database segments recalculate membership when they run, and recurring campaigns can deliver refreshed audiences on a configured schedule. Real-time segments instead re-evaluate membership as inbound events update profiles. Neither approach means every downstream platform receives updates instantly; delivery depends on the configured workflow and destination.

Choose who to reach using resolved profiles, purchase history, and the customer attributes available to your team. Build and review audiences in Amperity, then send them to configured marketing destinations.

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Customer segmentation for more relevant campaigns

Prioritize audiences for growth

Use purchase history and configured predictive attributes to find audiences for cross-sell and repeat-purchase programs. Test which offers and treatments work for each group.

Plan retention around customer behavior

Combine available lifecycle, value, and engagement attributes to identify customers for retention programs. Use those audiences to tailor loyalty and win-back outreach.

Manage overlap and exclusions before activation

Compare segment overlap and define who to include or exclude from a campaign. Apply configured audience rules across supported destinations to reduce conflicting outreach.

Move from an audience question to a reviewed segment

Give marketers tools to explore customer data, define an audience, and check its size and composition before activation. Technical teams configure the data and destinations those workflows depend on.

Put precise customer segments to work across high-impact use cases

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Re-engage high-value customers before they lapse

Use available purchase history, engagement, and predicted value to identify customers who may be disengaging. Define separate retention and win-back audiences, then configure journeys around each group’s needs.

Align loyalty journeys with customer status

Build loyalty audiences using the points, tiers, and engagement attributes available in your profiles. Choose batch or real-time segmentation according to the data and timing your journey requires.

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Suppress recent purchasers and manage audience overlap

Define recent purchasers as an exclusion audience for acquisition campaigns where that approach fits your strategy. Deliver updates through configured destinations on the cadence each workflow supports.

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Find more customers like your best customers

Create seed audiences from resolved customer profiles, using value and predictive attributes where configured. Send those audiences to supported ad platforms for their lookalike or audience-expansion workflows.

From trusted customer context to coordinated activation, end to end

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Build audiences on trusted customer context

Amperity resolves identity across the customer data you connect. Use a unified customer profile to bring available history and attributes together before deciding whom to reach.

Create segments with the tools your team needs

Use the visual Segment Editor to define audiences without SQL, or use SQL for more technical requirements. Where available, the AI Assistant can draft segment criteria in natural language for you to review, refine, and save.

Understand audience value before activation

Inspect audience size, historical revenue, attribute breakdowns, and overlap using configured segment insights. Use those findings to review targeting choices before sending an audience to a campaign.

Keep audiences current through configured workflows

Database segments produce an audience when they run, using the data available at that time. Real-time segments maintain membership as events update profiles. Send audiences through the activation workflows and destinations configured for each use case.

Find your next audience with Pér

When enabled for your team, Pér, Amperity’s AI agent for customer data, helps you explore audience opportunities using data available to you. It can propose audience-building work for your review and approval before making changes in Amperity. Browse the prompt library for a starting point, then adapt the question to your campaign.

Explore Pér prompts

Real results from smarter customer segmentation

BECU

Amperity helped BECU unify 37 data sources and turn 297 million records into 4.1 million profiles across its business lines. BECU reports saving more than 50 hours each week on outbound execution.

Read the BECU story

Servco

Servco brought fragmented customer data together with Amperity to support marketing and business insights.

Read the Servco story

Luxury retailer

An anonymous luxury retailer reported 439% better segmentation results with Amperity’s CLV model and identified more than 16,000 new purchasers.

Read the luxury retailer story

Ready to see customer segmentation in action?

Request a demo and see what better segmentation looks like for your data, your stack, and your team.