What's the highest-impact entry point for a multi-channel ad platform?
Metigy needed to build a unified multi-channel ad management tool for small business marketers running ads across Google, Facebook, Instagram, and TikTok. These users were spending hours switching between native platforms to check analytics, manually compiling reports, and "checking analytics" was their least-enjoyed task.
But building everything at once wasn't feasible. The question: where do you start a 0→1 product to deliver the most value fastest?
75 Users Answered
I ran a quantitative survey with 75 potential users. Among the 32 "advanced users" managing multiple ad channels, the data pointed clearly: analytics checking was the most painful task, and reporting was voted the most important feature for an all-in-one platform.
The entry point wasn't assumed. It was discovered.
Analytics checking ranked as the most painful task
Reporting ranked most important for an all-in-one platform
Mapping user needs from survey data to dashboard requirements
Eight iterations before committing to hi-fi.
From the survey data, I mapped user needs to dashboard requirements, gathered reporting patterns from native platforms and competitors, and rapidly produced lo-fi prototypes. 8 iterations with cross-functional input from the Ads squad and data team before reaching consensus on the right structure.
Testing with 6 Real Users
"Ease of Use" was rated the most important factor, so I chose high-fidelity prototypes for testing. Collaborated with PM and Researcher to craft non-leading questions, and recruited 6 users (4 advanced, 2 novice) managing multi-channel paid ads.
High-fidelity prototype used for usability testing
Structured approach to capturing and analysing feedback
Insights mapped directly to prototype locations for targeted iteration
"There are many reporting platforms out there and they seem to focus only on making beautiful graphs."
What Worked
Consolidated reporting highly valued. No more jumping between platforms. Comparison cards immediately appealing for identifying best-performing channels.
What Needed Change
Users had different goals depending on business stage, so one-size-fits-all metrics wouldn't work. Core value prop was saving time: users wanted commentary and insights, not just charts.
Interpretation over visualisation.
The biggest insight from testing: the platform's value wasn't in displaying data. It was in interpreting it. The market was full of tools making "beautiful graphs." Users wanted to know what their data means and what to do about it.
I designed two features that turned raw data into actionable intelligence:
AI Insights Panel
Analyses dashboard data and surfaces actionable insights with next steps. Not just "your CTR dropped" but "your CTR dropped because X, consider doing Y."
Keywords & Topics
Analyses search keywords, comments, and reactions across channels to surface content strategy opportunities, turning audience behaviour into creative direction.
Testing also revealed that one-size-fits-all metrics fail because users have different goals depending on business stage. I designed differentiated dashboards: early-stage users see awareness metrics, while advanced users get rich ROI and conversion data with goal-based filtering.
Early-stage user dashboard: awareness and engagement focus
Advanced user dashboard: rich ROI and conversion metrics
The complete multi-channel ads creation flow
The company didn't survive. The work did.
Metigy went into administration before the product could fully launch. But the project validated a critical product hypothesis and produced a comprehensive design ready for engineering.
This project demonstrated the full 0→1 arc: from quantitative discovery (75 users) through iterative design (8 rounds) through usability validation (6 users) to a strategic insight that reframed the entire product's value proposition. The company's outcome doesn't change what the design process proved.
