ES Loyalty Boost 2.7.1 release notes
These release notes cover features introduced or enhanced since ES Loyalty Boost 2.7.
What's in this release
- Audience Enhancement (enhancement)
- Scaling — Qualify Performance Envelope (infrastructure)
- Global and Offer-Level Control Configuration Feature (enhancement)
Enhancements
Audience Enhancement
The Audience features in ES Loyalty Boost v2.7.1 require ES Loyalty v4.1.1 or later to be installed.
Overview
Previously, Boost used its own Audience Selector — configured on a tab in the Excel Offer Pool file — to define inclusion logic at the Offer Template and Slot levels. This was used exclusively for Boost purposes.
This enhancement replaces that method with the ES Loyalty Audience feature set. Users can now access active ES Loyalty Audiences when configuring slot-level audience inclusion logic, and assign an Audience to an Offer Template directly via the Excel Offer Pool.
How targeting logic works
When selecting offers, the effective audience is the intersection of the audience defined at the offer level and the audience defined at the slot level. The following examples illustrate how this works:
| Slot-level audience | Offer-level audience | Result |
|---|---|---|
| Everyone | Everyone | Everyone is included |
| Employees only | Everyone | Employees only |
| Everyone | Cherry pickers excluded | Everyone except cherry pickers |
| Everyone except employees | Everyone except cherry pickers | Everyone except employees and cherry pickers |
| Ontario residents | Everyone | Ontario residents only |
| Ontario residents | Quebec residents | No members included — the two audiences cancel each other out |
| Employees only | Non-employees only | No members included — the audiences nullify each other |
| Members linked to a financial partner | Members not linked to a financial partner | No members included — the audiences nullify each other |
Details
This feature improves functionality and the user experience for Console users with access to ES Loyalty Boost, Audience Builder, and Audience Recommender. Audiences can be assigned to Offer Templates via the Excel Offer Pool to automate and optimize marketing tactics through self-service.
This feature also enables use of more advanced Recommender Audiences that were not previously possible in Boost. Note the following:
- Only audiences in the same business unit are available.
- Audience names are listed in alphabetical order in the dropdown.
- Audiences generated using Gen AI through Audience Builder are marked with a star icon (✦) next to the audience name.
See also:
- Boost — Audience Enhancement PRD
- Audience Enhancement Feature — Confluence
- ESLoyaltyBoost_OfferPool_Template.xlsx
Global and Offer-Level Control Configuration Feature
The treatment for the global control group and offer-level control group is now configurable per client. Configuration is set at the account level rather than the campaign level and is managed by Exchange Solutions rather than the client directly.
Global control group — supported modes:
| Mode | Behavior |
|---|---|
NO_OFFER | No offer is generated in the campaign_targeted_offer table for the account |
RANDOM | Members receive randomly assigned offers |
Offer-level control group — supported modes:
| Mode | Behavior |
|---|---|
NO_OFFER | No offer is generated in the campaign_targeted_offer table for the account. The normal control offer used for measurement is still created but is not visible to the member. |
REPLACEMENT | A replacement non-competing offer is provided when an offer is selected as a control offer |
See also:
Infrastructure
Scaling — Qualify Performance Envelope
A new ES Loyalty environment was created under a DevOps account to establish a production-like baseline for capturing accurate performance metrics. All associated backend stacks — including Snowpipe, Analytics, and Boost — were deployed to this environment.
Test configuration:
Performance tests were run using the following parameters to simulate realistic production conditions:
- Large-scale member audience
- Large product catalog
- Up to 50 transactions per member
- A realistic number of generated offers
- Validation that offers were correctly created from the campaign for a sample set of users meeting the offer selector criteria
Tests began with a smaller audience and scaled up to conditions representative of the largest clients by member base and offer volume. Each member received 10 offers (10 slots) per iteration.
Additional factors accounted for in testing included sharding policy, batch size, payload size, and replacement offers.
Sample audience breakdown (Phase 1 — 3,000,000 total members):
| Employee | Linked | Cherrypicker | Age | Province | Total |
|---|---|---|---|---|---|
| Y | Y | — | < 30, 31–50, > 50 | ON, BC | 4,500 |
| Y | N | — | < 30, 31–50, > 50 | ON, BC | 25,500 |
| N | L | — | < 30, 31–50, > 50 | ON, BC | 300,000 |
| N | N | Y | < 30, 31–50, > 50 | ON, BC | 3,000 |
| N | N | N | < 30, 31–50, > 50 | ON, BC | 2,667,000 |
| Total | 3,000,000 |
See also: