Better product discovery

EE ran eight top-level navigation items with unclear boundaries: 'Why EE', 'Network', 'Help', and five product categories competed for attention. Customers hunting for coverage, upgrade eligibility, or account help often clicked three menus before finding the right path or abandoned to call support.

My JTBD research identified three core missions: shopping for devices and plans, managing existing accounts (My EE), and getting help and network status. I led discovery that included clickstream analysis showing high bounce rates from nav, support ticket tagging revealing 'could not find coverage checker' as a top issue, and stakeholder workshops mapping business priorities against customer intent. Constraints: rebrand was launching in parallel so nav had to accommodate new product naming; back-end content management required minimal restructuring. Success metric: task completion rates above 70% for top ten customer journeys.

I ran tree testing with 200+ participants across twenty high-frequency tasks (finding coverage checker, comparing pay monthly plans, checking network status, understanding upgrade eligibility). Three options were considered. Keep eight menus with relabelling: rejected, because tree tests showed structural confusion, not only labelling issues. Mega-menu with all options visible: rejected for mobile complexity. Three clear buckets (Shop, My EE, Help) with supporting sub-navigation: what tested highest for task success.

I owned the key IA decisions: 'Shop' carried all acquisition paths (phones, SIM-only, broadband, business); 'My EE' grouped account management, bills, and upgrades for existing customers; 'Help' contained network status, coverage checker, contact options, and troubleshooting. I moved coverage checker from buried under 'Why EE / Network' to visible under 'Help', I validated through card sorting with 150 participants. Sub-navigation used consistent patterns: product type, then contract type, then device or add-ons.

Validation approach: tree testing showed task success improvement from 52% to 78% for coverage tasks, 61% to 82% for upgrade paths, and 48% to 74% for network status checks. A/B tested the redesign in prototype with 300 users before production rollout.

Tree testing and task success scores gave us clear evidence: the three-bucket structure improved completion rates across all twenty tested tasks. Coverage checker usage increased 34% in the first quarter after launch because I moved it from buried under Why EE / Network to Help › Coverage checker: the same IA change that raised task success on coverage tasks from 52% to 78% in tree tests. Support contacts related to 'cannot find information online' dropped 22% in the same period.

Because I moved high-intent tasks into Help where shoppers already look, average clicks to task completion fell from 4.2 to 2.8 across measured journeys, cutting support noise without over-promising on acquisition (Shop conversion improved a modest 3–4 points consistently across mobile and desktop).