Loyalty in 2026: Why Your "Points for Purchases" Program is Dying

Agentic Commerce Is Reshaping Multi-Channel Selling with Jorrit Steinz of ChannelEngine

Author

Brent Peterson
March 13, 2026

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Loyalty in 2026: Why Your "Points for Purchases" Program is Dying

By Brent W Peterson

In 2012, loyalty meant simple punch cards. Today, it’s an $18B+ industry—yet true customer loyalty has dropped to 29%. Why? Because most brands are running "rebate systems," not loyalty programs.

"Spend, earn, discount" is now just table stakes. To win in 2026, you must pivot from transactional rewards to Engagement Hubs.

The New Playbook:

  • AI-Personalization: Use propensity modeling to anticipate churn and personalize experiences in real-time.

  • Experiential Rewards: Exclusive access and community building beat a $5 discount every time.

  • Zero-Party Data: Use your program to collect insights that inform product development, not just email subject lines.

  • Values-Based Connection: Look at KEEN Corps—they reward volunteerism just like revenue. When customers feel part of a movement, they don’t just buy; they belong.

The tech is ready—from Smile.io and Rivo to Antavo and Zinrelo. The hurdle isn't the software; it’s the strategy. Stop chasing transactions and start building a relationship your customers actually care about.

Our Latest Episode:

Agentic Commerce Is Reshaping Multi-Channel Selling with Jorrit Steinz of ChannelEngine

Text-based attributes have always been the hardest part of managing product data at scale. Different languages, different materials, slashes, inconsistent formatting, and every marketplace has its own requirements for how that data should look.
Jorrit Steinz of ChannelEngine explains how AI is changing that. Instead of manually mapping messy text attributes to marketplace-specific formats, ChannelEngine uses AI to generate a recommendation. All the merchant has to do is validate and click OK.
And the next step? Autopilot. Jorrit describes a future where merchants verify the first batch of mappings, build trust in the output, and then let AI handle the rest without manual intervention.
This is where product data management is heading. Not replacing humans, but removing the repetitive, tedious work that slows down marketplace expansion.

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