Money Map - Turning Store Data into Spatial Insights
Retail stores generate massive amounts of data - but most of it is trapped in dashboards, tables, and reports.
I wanted to change that.
What if instead of analyzing spreadsheets, store managers could simply look at their store and instantly understand what’s working - and what isn’t?
The Money Map was built to answer that question.
About Nexite
Nexite is a retail analytics platform that brings physical stores into the world of data. By tracking item-level interactions - such as when a product is seen, picked up, tried on, or purchased - it enables retailers to understand customer behavior inside the store and optimize merchandising decisions in real time.
Overview
The Money Map is a core feature in Nexite’s platform and mobile app, designed to help retailers understand store performance spatially - not just through numbers, but through where things happen in the store.
It combines real-time data (traffic, sales, picks, try-ons) with a visual map of the store, allowing users to identify high- and low-performing areas instantly.
In the mobile app, this goes one step further:
Visual Merchandisers (VMs) and store managers receive actionable recommendations directly on the map, helping them improve store layout and product placement based on Nexite’s smart suggestions.
The Starting Point
When I joined the project, the map experience was very limited:
-
A static 2D map built in Figma
-
No real connection between store layout and KPIs
-
Difficult for users to understand performance context
At the same time, Nexite’s platform already tracked rich behavioral data like:
-
Seen
-
Picked
-
Tried-on
-
Sales
But there was no intuitive way to connect this data to physical space.
The Idea
My goal was simple:
Turn store data into something you can see.
Instead of reading dashboards, users should be able to:
-
Look at the store
-
Instantly understand what’s working and what’s not
Key concept
A 3D map with KPI overlays, where:
-
Each area (zone) is color-coded
-
Different KPIs can be visualized dynamically
-
Users can drill down into zones and products
-
And on mobile:
-
Receive recommendations directly on the map
-
Understand what to change and where without leaving the context of the store layout
Designing the 3D Map
One of the first critical decisions was defining the exact 3D angle.
It needed to:
-
Show depth (for spatial understanding)
-
Keep readability (like a 2D map)
-
Work consistently across stores
I chose a consistent isometric angle, balancing clarity and spatial depth.
Working with 3D designers
I created clear guidelines for external designers and collaborated closely through multiple iterations.
We explored different:
-
Angles
-
Levels of detail
-
Visual styles
Until we reached a result that:
-
Felt realistic
-
Stayed clean and readable
-
Worked across both desktop and mobile
The First Problem: Reality vs Design
Once users started working with the map, we discovered a major issue:
Stores are not static
Furniture moves constantly:
-
Visual merchandising changes
-
Seasonal layouts
-
Ongoing adjustments in-store
This created a serious operational problem:
-
The 3D maps quickly became outdated
-
Required continuous redesign
-
Not scalable across many stores
The Solution: Abstract the Store
Instead of trying to perfectly replicate reality, we changed the approach:
From:
Full 3D store (walls + furniture)
To:
3D shell + abstract zones
We kept:
-
Walls
-
Key structural elements (entrance, fitting rooms, etc.)
And removed:
-
All furniture
-
All dynamic elements
The store became a stable canvas, while the data (zones + KPIs) remained dynamic.
Why This Worked
1. Scalability
No need to update maps every time the store changes.
2. Stability
Zones remain consistent even when layouts shift.
3. Clarity
Users focus on performance, not visual clutter.
4. Actionability (especially on mobile)
The map is not just analytical — it’s operational:
-
VMs and store managers get clear recommendations on specific zones
-
They can act immediately to:
-
Move items
-
Change displays
-
Improve layout
This turns the map from a diagnostic tool into a decision-making tool.
5. Flexibility
Same map supports multiple KPIs:
-
Traffic
-
Sales
-
Picks
-
Try-ons
Users can switch KPIs and instantly explore different insights.
Final Experience
The final Money Map experience includes:
Spatial visualization
-
3D store layout (clean, isometric)
KPI heatmaps
-
Color-coded zones (hot → cold)
Interactions
-
Click a zone → see performance
-
Drill down → view products and actions
-
Switch KPIs → see different behaviors instantly
Smart recommendations (Mobile)
-
Tasks and suggestions appear directly on the map
-
Highlight where action is needed
-
Guide users on how to improve store performance
Cross-platform
-
Fully adapted for:
-
Desktop (Portal)
-
Mobile (App)
-
Key Learnings
1. Don’t overfit reality
Trying to perfectly mirror the store created complexity and maintenance issues.
2. Abstraction is powerful
Removing details (furniture) actually improved:
-
Usability
-
Scalability
-
Performance
3. Spatial context changes everything
Seeing data in place (not in tables) creates immediate understanding.
4. From insight to action
The biggest shift was not visualization — but enabling users to:
-
Understand a problem
-
Act on it immediately in the same interface
5. Systems thinking matters
The solution wasn’t just design — it required alignment with:
-
Data (zones, KPIs)
-
Operations (store changes)
-
Engineering (map rendering, interactions)
Impact
The Money Map transformed how users interact with store data:
-
From reading reports → to seeing performance
-
From numbers → to spatial insight
-
From insight → to action (via recommendations)
-
From static dashboards → to interactive exploration