Multi-brand e-commerce group brings AWS, Azure and GCP under one FinOps model
E-commerce / retail · ~600 employees, multi-brand group · Europe · Unified reporting in 6 weeks; ~22% spend reduction across two quarters
Short answer
A ~600-person European e-commerce group unified cost management across AWS, Azure and Google Cloud, cutting combined cloud spend by roughly 22% and reducing monthly cost reporting from about two weeks of manual work to a single automated review.
~22%
reduction in combined multi-cloud spend
3 → 1
cloud billing views consolidated into one model
~2 weeks → 1 day
monthly cost reporting effort
6 weeks
to first group-wide unified cost view
The challenge
- Three acquired brands, three clouds, three incompatible tagging conventions and no group-level view.
- Peak-season capacity was provisioned once a year and never scaled back down afterwards.
- Monthly cost reporting consumed roughly two weeks of finance and platform-engineering time.
- Nobody could answer the simplest question: what does one order cost us to serve?
What bluebill did
- Normalised billing data from all three providers into one allocation model with a shared taxonomy across brands.
- Rebuilt seasonal capacity planning around measured traffic curves rather than last year's peak.
- Cleaned up storage tiers, orphaned volumes, idle data-warehouse compute and duplicated non-production environments.
- Introduced per-brand budgets with alerting so overspend surfaced within days instead of at invoice time.
- Published a cost-per-order metric that both engineering and commercial teams review.
“The saving mattered. Being able to answer 'what does an order cost' in one place mattered more.”
— Group CFO, anonymised European e-commerce group
What changed afterwards
- Cost per order became a shared KPI between engineering and commercial leadership.
- Peak-season provisioning is now planned from measured curves, avoiding a repeat of the permanent over-capacity.
- The next acquisition was onboarded into the allocation model in under three weeks.
Environment: AWS · Azure · Google Cloud · Kubernetes · Snowflake
Questions this engagement answers
Does multi-cloud make FinOps harder?
It makes allocation harder, not optimisation. Once billing data from each provider is normalised into one taxonomy, the same optimisation loop applies everywhere. Here that normalisation took about six weeks.
What is a realistic saving for a multi-cloud retailer?
This group reduced combined spend by roughly 22% across two quarters. Industry benchmarks put wasted cloud budget at up to 30%, so figures in the 20-30% range are typical where no structured FinOps practice exists yet.
Client names are withheld by agreement. Engagement profiles are anonymised; figures are the measured results of the engagement described and are consistent with bluebill's aggregate programme results. Individual results vary with environment, scale and starting maturity.