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ES Loyalty 4.6.1 release notes

Features in this release​

Member Scoring and Intelligence (MSI) — Additional Scores​

Overview​

This release adds several new machine learning–derived probabilistic metrics to the Member Scoring and Intelligence (MSI) feature. Scores are derived from the entire membership base, enabling both membership-wide and individual analysis. You can use these scores to create audiences and target members based on different probability levels.

New metrics:

  • Propensity to Buy (PTB): Predicts the likelihood that an individual member will make a purchase within a set duration.
  • Customer Lifetime Value (CLV): Predicts the monetary value an individual member will generate over a set duration.

This release also includes general UX and quality improvements.

Why it's valuable​

Your marketing team can instantly segment loyalty members based on key metrics — like propensity to buy and customer lifetime value — through a guided AI interface. It's the fastest way to build smarter audiences and power more relevant campaigns.

What it does​

This feature helps you create and manage segmentation scores for propensity to buy and customer lifetime value. An AI engine guides you through the creation process, including scoring methods, segment options, and saving results.

How you benefit​

Member Scoring and Intelligence puts advanced segmentation in the hands of every marketer — no SQL or data science required. You get quick access to meaningful member insights, reusable scoring models, and campaign-ready segments that improve targeting and drive results.

Customer Lifetime Value (CLV)​

In the context of a loyalty program, Customer Lifetime Value (CLV) represents the predicted total revenue that a member will generate throughout their entire relationship with the program. CLV helps identify high-value members and guides strategic decisions about resource allocation, retention efforts, and personalized engagement strategies.

For the Scoring and Intelligence feature, the CLV score includes members with at least N purchase transactions and considers both historical spending patterns and predicted future behavior to estimate the long-term value of each member.

When setting up the CLV score, you must define minimum thresholds for days and transactions, and select one of the following calculation methods:

  • Top-line revenue: The total amount spent by members, regardless of cost or promotions. Useful for market sizing, segmentation, or when loyalty strategies are driven by overall sales volume. Revenue figures are easy to interpret and widely available.

  • Profit margin: Accounts for the actual profitability of each member by factoring in costs, discounts, and product margins. This is more granular and aligns the score directly with the bottom line — ideal for optimizing costly retention offers and understanding true member value. Margin-based CLV is especially useful in campaigns that feature margin-sensitive offers, such as discounts or private-label product promotions.

Sample output — CLV predictive score:

MetricValue
Average predicted 12-month CLV$9,714
Median predicted 12-month CLV$8,315
tip

A large majority (over 98%) of members fall into the "High Value" or "Medium Value" categories, indicating that most active members contribute substantial predicted revenue. Member CLV values in the sample are concentrated between $8,000 and $10,000, with some clustering at much lower or higher levels — highlighting meaningful segmentation opportunities. Sample seed members have predicted values between $8,000 and nearly $9,800 over the next 12 months, all in the "Very High Value" category.

Propensity to Buy (PTB)​

The MSI Propensity to Buy (PTB) model combines advanced feature engineering, temporal modeling, and production-grade MLOps to help marketers identify customers most likely to purchase — reducing wasted spend and maximizing conversion lift.

The model uses a forward-looking design that ensures complete separation between historical features and future outcomes, guaranteeing real-world accuracy and eliminating a common pitfall in predictive modeling.

Carefully engineered RFM (Recency-Frequency-Monetary), volatility, temporal, and trend features capture customer rhythm, momentum, and consistency — for example, comparing 3-month versus 6-month spend trends to detect acceleration or slowdown.

The feature focuses on conversions within the top deciles: the 20% of scored customers who drive 60–70% of future sales. For marketers, this means better buyer discrimination, reliable targeting confidence, and fewer false positives — reducing waste from pursuing the wrong customers by up to 40%.

Sample output — PTB member segmentation (next 30 days):

SegmentPredicted likelihoodMember count
High Propensity65%–99%150,913
Medium Propensity40%–65%82,390
Low PropensityBelow 40%486,076

Key observations:

  • Most members fall into the Low Propensity segment, indicating a strong opportunity for reactivation or nurturing campaigns.
  • The High Propensity segment represents members most likely to purchase soon — ideal targets for priority offers and high-value communications.
  • The model's high accuracy, recall, and precision support confident segmentation for targeted marketing.

The PTB feature is not just a generated model — it constitutes a complete predictive marketing platform, built on:

  • Perfect temporal integrity
  • Elegant feature design
  • Real-world business impact

The MSI Propensity to Buy model sets the benchmark for AI-driven loyalty and personalization: measurable, scalable, and scientifically sound.

Display MSI and other aggregations in Member Console​

Overview​

This feature makes Extended Member Data (EMD), Member Aggregations, and MSI scores available in the Member Management section of the Console, giving loyalty teams a richer view of member behavior for service and troubleshooting.

Why it's valuable​

Gives loyalty teams a unified view of member behavior to power more personalized service.

What it does​

Consolidates Extended Member Data and configurable Member Aggregations — such as Spend, Rewards, and Redemptions — into an enhanced Other Information section in the ES Loyalty Console.

How you benefit​

Quickly surface key performance signals and trend insights for each member, enabling more personalized service without leaving the member profile.

Details​

The Extended Member Data accordion has been renamed to Other Information and now includes additional tabs:

  • Extended Member Data tab: Displays custom member attributes such as segmentation flags and business metadata.

  • Member Scoring & Intelligence tab: Shows applicable MSI scores, including score type, distribution method, last generated date, and score value.

  • Member Aggregations tab: Displays aggregated activity data. The available Aggregation Name options are set in configuration and can include Spend, Rewards, or Redeem for a selected period type (such as Month or Year). The number of periods displayed is also configurable. If no data is available for the selected aggregation, the panel displays No Data Available.

Transaction History API enhancement​

Overview​

This enhancement updates the transaction history API to support richer transaction histories for members, benefiting both member-facing endpoints and internal roles such as sales representatives.

Why it's valuable​

Enables faster, more efficient access to comprehensive member transaction activity, improving productivity for field and sales teams, and for member endpoints that require richer transaction histories.

What it does​

Allows multiple transaction types to be requested in a single API call, returning a unified dataset for a member's activity instead of requiring separate requests.

How you benefit​

Reduce API traffic and internal development effort while giving members richer transaction history and sales representatives a complete, real-time loyalty history view.

Details​

A client built an external website that allows sales representatives to retrieve loyalty member information using the CUX API. The GET transaction history endpoint is used to retrieve a member's transaction history.

Previously, retrieving multiple transaction types required separate API requests, which increased development overhead and degraded API performance.

With this enhancement, transaction types are passed as a list in a single API call, returning all requested transaction types in one response. The client's internal developer configures a method to retrieve, process, and display the data on the sales rep–facing website.

Next Period (Tier) Status​

Overview​

For clients using program tiers, this feature exposes the next projected tier status for members, available for both external member-facing visibility and internal use across channels and endpoints.

Why it's valuable​

Gives marketers and members forward-looking visibility into tier progression, strengthening engagement and motivating continued activity.

What it does​

Shows the next projected tier and the date the qualifying threshold was achieved, directly in the member profile. This data is also available through Data Warehouse feeds, CUX/POS APIs, DIG, SFMC, and the Loyalty Gallery.

How you benefit​

Surface proactive tier insights across channels to enable personalized tier-nudging campaigns and more compelling loyalty experiences that drive incremental earning and retention.

Details​

The next projected tier status is displayed as Next Period Status in the Member Tiers Program accordion section on the Member details page. The Achieved On date shows when the member met the threshold for that tier status.

This data can be:

  • Transmitted through a Data Warehouse Feed
  • Included in CUX and POS API call responses
  • Synchronized to DIG and SFMC
  • Displayed in the Loyalty Gallery

Member Lookup Partial Search — CUX API​

Overview​

This API feature enables partial member searching outside of the ES Loyalty Console, improving the speed and quality of service for agents and sales representatives.

Why it's valuable​

Speeds up member lookups and supports real-world workflows where teams rarely have full identifiers on hand, improving service responsiveness and efficiency.

What it does​

Enables agents and sales representatives to search by partial member account numbers, business names, external identifiers, and Extended Member Data. The feature uses wildcard logic to return all relevant matches, while restricting numeric searches to the last four digits to prevent excessive results.

How you benefit​

Locate members faster, reduce manual effort, and enable frontline and sales teams to quickly retrieve rich loyalty profiles without needing exact details.

Details​

Previously, agents could search on business name, tier name, or EMD — but only exact matches were returned. With this enhancement, partial search is enabled in the CUX API. Sales representatives no longer need to enter a full member account number or business name.

Entering a search term triggers a wildcard query that returns all related matches. For example, searching for ABC returns:

ABC
ABC Corporation
abc_corporation
abc corporation

External identifiers and account numbers are matched on the last four digits to prevent an excessive number of records from being returned.

Tier Period Scheduling enhancement​

Overview​

For clients using program tiers, late-received transactions near benefit period boundaries can cause tier transition errors. This enhancement provides configurable flexibility to account for such transactions and improves tier transition accuracy for members.

Why it's valuable​

Ensures members receive the correct tier status and rewards even when end-of-period transactions are processed after the calendar resets, protecting program integrity and member trust.

What it does​

Captures and applies late-processed transactions to the actual date and time they occurred, maintaining accurate tier qualification and reward calculations across period boundaries.

How you benefit​

Deliver fair, reliable tier outcomes that motivate high-value member behavior, reduce service friction, and strengthen confidence in your loyalty program's rewards experience.

Details​

This enhancement prevents a transaction from being incorrectly assigned to the next period due to delayed processing of end-of-period transactions.

Example scenario:

A member has Gold status on December 31, which qualifies them for the highest tier earning rate. They complete a large transaction on December 31, expecting Gold-tier rewards and tier retention into the new period.

Previously, the transaction might be batched but not processed until January 1 — the first day of the new period. Because the transaction wasn't recorded for December 31, the member's tier status dropped (for example, to Bronze) in the new period, and rewards were calculated at that lower rate.

With this enhancement, the transaction is applied to December 31 — the date it actually occurred. Tier status and rewards are adjusted accordingly at the Gold level.

Integration and Business Guides​

Overview​

These guides support the implementation and usage of productized integrations between ES Loyalty and its partners.

  • Integration Guides are primarily intended for ESI Technical Solution Architects (TSAs), though they can be shared with client-side technical administrators. They cover setup, configuration, and operations for each integration.
  • Business User Guides are client-facing documents that describe the functionality enabled by each productized integration.

Why it's valuable​

Provides clear business and technical playbooks to help enterprise loyalty teams quickly activate gamification and advanced campaign orchestration with confidence.

What it does​

Delivers dedicated Business User and Integration Guides for CataBoom™ gamification and Optimove™ CDP, covering use cases, setup steps, data flows, and configuration details for rewarding gameplay and triggering personalized messaging via real-time and batch pipelines.

How you benefit​

Accelerate deployment of high-impact engagement experiences and automated campaigns, reduce implementation friction, and empower both marketers and developers to maximize value from ES Loyalty ecosystem integrations.

Available guides​

Four guides are available in this release:

  1. Gamification (CataBoom) Business User's Guide
    Written for client business users. Describes the integration between ES Loyalty and the CataBoom™ gamification and rewards platform at a high level. Covers CataBoom functionality, supported game types, how game consent works with offers, game settings, and use cases.

  2. Gamification (CataBoom) Integration Guide
    Intended for TSA team members. Covers how to configure CataBoom™ game mechanics and the required webhooks so that loyalty members who earn gameplay receive bonus points reflected in the loyalty member console. Client technical teams can also use this guide to understand the setup process.

  3. CDP (Optimove) Business User's Guide
    Provides client business users with an overview of the Optimove™ integration with ES Loyalty, specifically for using Optimove's Email Service Provider (ESP) feature, OptiMail™, alongside campaign features. Enables targeted email messaging to members based on specific actions and events.

  4. CDP (Optimove) Integration Guide
    Helps TSA members and client technical teams understand the technical aspects of the integration, including syndication via real-time APIs and daily batch feeds directly to Snowflake. Covers how to set up scheduled and triggered messaging to members.

You can check out these guides in the Platform Integrations and Technical Integrations sections of the documentation.

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