Building the commercial case for customer intelligence
UMG's direct-to-consumer merchandise stores measured success by drop revenue. A release landed, sales spiked, and that number closed the conversation. Nobody tracked or owned what happened in between: how fans moved through the store, why they abandoned, and what pushed them to leave one-star reviews on Trustpilot. The warning signs were public, but the structure to act on them didn't exist.
Six functions each held part of the picture. Marketing owned acquisition, CRM owned retention, Customer Service owned complaints, Analytics owned transactions, eCommerce owned the store business and Tech owned the platform. None of them shared a view of the customer journey or agreed where it was breaking down.
Leading a newly created insight function, I started with data the business already had: Shopify sales, Zendesk tickets, CRM, marketing analytics, on-site feedback and the Trustpilot ratings. None of it had been brought together. I mapped every source against the full journey, from first encounter to post-purchase resolution. The map showed where each function's view began and ended, and what fell between them.
Because every function contributed to the map, no one could dispute the gaps it exposed. It gave the organisation a shared picture it had never had.
I then brought Marketing, CRM, Analytics, Customer Service, eCommerce and Tech to agreement on what to measure and who owns it, reconciling six sets of priorities. The Trustpilot ratings supplied the urgency, and the map supplied the common ground.
The lesson I took forward: measures only change behaviour when leadership rewards teams for working across them. The framework started that shift. It didn't finish it.
This is the work of the Fractional Insight Lead: measures your teams trust and use, and the case to invest in them.
Tell me where you're starting from. A short note is enough.
