Energy & fuel retail — B2C loyalty

Choosing a Loyalty Platform for a Global Energy Retailer

Ran the complete evaluation of the B2C loyalty platform for a global energy retailer's consumer business: defining the criteria, assessing the candidates against the real operating requirements, and producing a defensible recommendation.

Client
Global energy major — retail / mobility business
Role
Enterprise architect — platform evaluation and target-state architecture

The challenge

Fuel and convenience retail loyalty has an unusual shape: very high transaction frequency, low value per transaction, identity that must resolve across forecourt, store, app and payment, and earn-and-burn rules that marketing expects to change without an engineering release. Choosing a platform on feature comparison alone tends to produce a decision that looks defensible on paper and fails on the operating characteristics that actually matter.

Approach

  • Defined and agreed the evaluation criteria before assessing any candidate, so scoring could not be reverse-engineered to a preferred answer.
  • Grounded the assessment in the client's real transaction volume, frequency and identity-resolution requirements.
  • Separated capabilities the platform determines from those that are an integration or process concern in any case.
  • Assessed operability — how rules change, who changes them, and what a change costs — not only functional fit.
  • Documented the reasoning so the decision could be revisited as requirements moved.

Innovation

  • Weighted the evaluation toward operating characteristics — transaction profile, identity resolution, rule-change cost — rather than feature checklists, which is where loyalty platform decisions usually go wrong.
  • Made the criteria a deliverable in their own right, agreed and signed off before scoring began.

Outcome

  • Complete evaluation delivered with a documented, defensible recommendation.
  • Decision criteria agreed and recorded, so the choice remains reviewable as requirements change.
  • Target-state architecture defined alongside the platform recommendation rather than deferred to implementation.

Recommendations

  • Agree the criteria before you see the demos. Criteria written after a demo tend to describe that demo.
  • For loyalty, the transaction profile matters more than the feature list. High-frequency low-value programmes fail differently from high-value ones.
  • Ask how a marketing rule change actually gets made, and what it costs. That question separates platforms faster than any feature comparison.
  • Write down why you chose. The reasoning is what lets you revisit the decision without restarting the evaluation.

Technology

  • Loyalty platform evaluation
  • SAP Customer Experience
  • Event-driven integration
  • Customer data modelling

Want the working artefacts?

The account above is the whole story. If you want the material behind it — data models and partitioning, sizing inputs, load-test design, the decision frameworks as something you can actually apply — we will send the appendix for Choosing a Loyalty Platform for a Global Energy Retailer to a work address. Client identities stay masked either way.

Facing something similar?

If any of this maps onto a problem you are carrying, we are happy to talk it through — no obligation, and you will get a straight answer about whether it is worth doing.

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