Consumer Next’s card data could answer almost any question about how people spend, if you could reach it. It had built its name selling that data to hedge funds, through a platform made for analysts. Globe Ant’s 2022 discovery found the bigger market elsewhere: strategists at brands with data needs but no data team.
Take Mila, the business strategist the research was built around. Her question is simple: what is my market share against my competitors, and how is it changing? The data held the answer. Getting it meant asking for it.
The waitThree weeks to one number.
The question went out to a boutique data firm, which wrote the boolean queries by hand and built a dashboard around them. The answer came back 2 to 3 weeks later, by my own account.
The platform offered no shortcut. Walk Vision 1.0 the way Mila would and every step asks her to know something about the platform before it tells her anything about her market.
How long is three weeks?
Each square is one day of waiting for the boutique data firm: 14 for two weeks, 7 more for three. Against it, the screen that took the wait’s place.
Before · 2 to 3 weeks Self-reported
Solid: two weeks. Hatched: up to three.
Vision 2.0 · one screen
The do-it-yourself route: Vision 1.0, redrawn as wireframes. Every query also spent one of a limited number: “Remaining Queries: 97”.
Three weeks of someone else’s booleansor one screen she reads herself.
The designOne screen, the answer in words.
I designed Vision 2.0’s screens and modules around Mila’s questions instead of the data tables: her competitors, her industry, her customers. Every screen is the same stack. The rail and the controls stay put, the filter bar arrives already set to her competitive set and her time frame, and the card under it answers one question. Below the chart, the insight is written out in a sentence.
That only works if every question has the same shape underneath. We wrote real questions in users’ words and took them apart into a page metric, then filters, breakdowns and dimensions. The filter bar is that model, made visible.
One screen, three lenses
The three are not steps on a path. Each reads the same card data a different way: who she competes with, where her customers also shop, and how many come back.
The three Vision 2.0 screens the product designs shows on, redrawn in vector. One illustrative dataset with fictional brands, so the three screens agree.
The outcomeA product ready for new buyers.
Investors and corporate teams had lived on separate platforms. NextVision merged them on one log-in, and each audience kept its own way in: investors in Signal, Cohort, Macro and Fundamentals; brands in their competitors, industry and customers. Underneath, the filtering, the slicing and the way a chart is built are the same, so a view learned in one place works everywhere.
The unified platform laid the foundation for Consumer Next to evolve its product and reach the new buyers behind the $43 billion opportunity. A self-serve reporting tool I designed meant users stopped waiting for an analyst to pull a report, by my own account.
The modules
Six questions, one stack.
My Industry, drill. Redrawn; figures illustrative.
- My CompetitorsSpend against her competitive set, side by side.Product designs
- My Industry, drillThe industry’s makeup, top brands, growers and decelerators.Product designs
- RetentionHow many customers come back, month by month.Product designs
- Demographic performanceAge, income, channel and region, by cohort.Product designs
- Cross ShopWhere her customers also buy.Product designs
- Share of WalletHow much of their spend she gets, by income.Product designs