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Lexer

Ecosystem

Retail-focused CDP that enriches customer profiles with purchase history, lifetime value, and loyalty data.

Lexer is a CDP built specifically for retail, fashion, and consumer goods brands. The platform integrates deeply with retail-specific data sources: POS systems, e-commerce platforms, loyalty programs, and wholesale order systems. This retail focus means Lexer's profile schema is oriented toward customer metrics that matter to retail operators: RFM scores (recency, frequency, monetary value), product category preferences, store versus online channel mix, and loyalty tier.

The Lexer Customer Data Platform unifies online and offline purchase data, which is a common gap in purely web-focused CDPs. A shopper who buys online and in-store has a unified view of their total purchase history, not a fragmented record split across systems.

Lexer's Insights tool surfaces population-level behavioral analytics on top of individual profiles, which helps merchandising and buying teams understand which product categories are growing in share of wallet across customer segments. This analytic layer is separate from the profile API but complements it.

The Profile API returns enriched customer records with RFM metrics, product category preferences, loyalty status, and predicted next purchase date. For AI agents, the RFM data is particularly actionable: an agent can check recency and frequency before deciding whether to surface a win-back offer or an upsell, calibrating the approach to the shopper's current engagement level.

Why This Matters for UCP

Lexer provides agents with retail-specific customer profiles including RFM metrics and unified online and in-store purchase history, giving UCP checkout flows the loyalty and behavioral context needed to surface relevant promotions for retail and fashion brands.

UCP Capabilities

identity linkingproduct discovery

UCP Endpoint

Ecosystem — Endpoint not yet publicly available

Integration Example

// Lexer Profile API: fetch retail-enriched customer profile with RFM metrics
// Agents use RFM scores and loyalty data to calibrate UCP checkout offers.

const LEXER_API = 'https://api.lexer.io/v2';
const apiKey = process.env.LEXER_API_KEY!;
const datasetId = process.env.LEXER_DATASET_ID!;

// Look up customer by email
const profileResp = await fetch(
  `${LEXER_API}/datasets/${datasetId}/customers/lookup`,
  {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${apiKey}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({ email: shopperEmail }),
  }
).then(r => r.json());

const customer = profileResp.customer;

// RFM metrics
console.log('Recency (days since last purchase):', customer?.recency_days);
console.log('Frequency (order count):', customer?.order_count);
console.log('Monetary (lifetime spend):', customer?.lifetime_value);

// Loyalty and tier
console.log('Loyalty tier:', customer?.loyalty_tier);
console.log('Loyalty points:', customer?.loyalty_points);

// Category preferences
const topCategories = customer?.category_preferences
  ?.sort((a: any, b: any) => b.share - a.share)
  .slice(0, 3)
  .map((c: any) => `${c.name} (${(c.share * 100).toFixed(0)}%)`);
console.log('Top categories:', topCategories);

UCP Status

Ecosystem

Tags

cdpretailrfmpos-integrationloyaltyfashionconsumer-goods

Pricing

paid

Added 2026-04-24
Verified2026-04-24
Documentation

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Reviews

★★★★★4.7 (3 reviews)

These are illustrative examples to show what reviews will look like. Submit your own experience below.

ML

M. Lee

Backend Developer · Mar 3, 2026

★★★★

Works well for our use case. The documentation is accurate and the implementation matches what the spec describes.

RK

R. Kapoor

Platform Engineer · Jan 15, 2026

★★★★★

Integrated in an afternoon. Solid implementation with no unexpected edge cases in production.

JS

J. Santos

Senior Engineer · Feb 28, 2026

★★★★★

Integration was straightforward. The UCP endpoint discovery works as documented and checkout completes in under 2 seconds.

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