Amperity is an enterprise customer data platform built specifically for retail, hospitality, and consumer brands that need to unify fragmented customer data from dozens of systems — loyalty programmes, e-commerce platforms, POS systems, mobile apps, and call centres — into a single, AI-resolved customer profile that drives personalisation, retention, and lifetime value growth.
Product Overview
Amperity's core technical differentiator is its probabilistic identity resolution engine: in industries like retail and hospitality, a single customer may exist as dozens of separate records across CRM, loyalty, e-commerce, and in-store POS systems — with slight variations in name spelling, different email addresses, multiple household members sharing an account, and both online and offline transaction histories. Amperity's ML-based identity resolution uses hundreds of identity signals to merge these disparate records into a single 'gold record' for each customer — achieving match rates significantly higher than deterministic matching alone. This unified profile becomes the foundation for personalised marketing, retention programmes, and LTV analysis. Amperity's Predicted Customer Lifetime Value model scores each customer's future revenue potential, enabling marketing teams to target acquisition spending and retention investments at the highest-value segments. Its built-in connector to major data warehouses (Snowflake, BigQuery) and activation platforms (Braze, Salesforce Marketing Cloud) makes it a central hub in the modern retail data stack.
Key Features
- AI Identity Resolution: ML-based probabilistic matching across hundreds of signals — resolve fragmented customer records from dozens of sources into unified profiles.
- Predicted Customer LTV: ML-scored lifetime value predictions for every customer — prioritise acquisition, retention, and win-back investments by predicted value.
- 360° Retail Customer Profile: Unified profile combining loyalty, e-commerce, POS, app, and contact centre data — complete cross-channel customer view.
- Audience Segmentation: Build ML-enriched audiences for activation — combine behavioural, transactional, and predicted value attributes.
- Warehouse & Activation Connectors: Native connectors to Snowflake, BigQuery, Braze, and Salesforce Marketing Cloud — activate profiles across the full stack.
Best For
Enterprise retail, hospitality, and consumer brand marketing teams that need AI-powered identity resolution to unify fragmented customer records from multiple systems — and activate unified profiles for personalisation and LTV-based marketing.
Pricing
Custom enterprise pricing based on customer profile volume. Enterprise positioning. Contact for demo.
Key Integrations
Snowflake, BigQuery, Redshift, Braze, Salesforce Marketing Cloud, Google Ads, Facebook Ads, Klaviyo, Epsilon, LiveRamp
Pros
- Probabilistic identity resolution achieves match rates that deterministic CDPs cannot match in retail
- Predicted LTV scoring enables value-based marketing investment decisions
- Purpose-built for retail and hospitality — templates and models specific to consumer brand use cases
- Enterprise-grade data governance and privacy compliance built for regulated retail environments
Cons
- Enterprise pricing and implementation complexity — significant investment before realising value
- Primarily optimised for retail and hospitality — less suitable for B2B or SaaS business models
- Requires mature data infrastructure and significant historical transaction data for ML models to perform well
