Merchandising App
Tracking the effectiveness of product placements enables managers to gain insights into customer engagement and make data-driven decisions, thereby optimising their merchandising strategies.
Developed by
FootfallCam
App language
English
Help
Legal Info
By accessing and using the app, you agree to App Center’s Terms of Service and App’s Terms of Service and Privacy Policy.
Collections
Most Popular
Retail Chains
Event ROI Evaluation
Event Potential Forecast
Key Features
Measure Engagement
Track customer interactions with different product placements and areas using heatmap analytics.
Simulate Scenarios
Test various merchandising strategies with AI-driven simulations to predict shopper behaviour.
Compare Performance
Analyse engagement differences across multiple store layouts and locations for data-driven decision-making.
Part of FootfallCam V9
V9 Enterprise
Most Popular
This is suitable for companies that require in-depth in-store shopper analytics and shopping behaviour insights through AI-driven simulations.
Optimise Product Placement with AI-Powered Simulations
Transform your in-store strategy with AI-driven simulations. FootfallCam Merchandising App uses shopper path analytics and predictive modelling to simulate the engagement of different product placements within your store. With thousands of simulation iterations, retailers can test new layouts and compare engagement between locations - ensuring the most effective merchandising strategy for maximising sales.
Testing Different Product Placements in the Same Store
Simulate multiple product placements within a single store layout. By visualising expected customer interactions in heatmap format, businesses can identify the most effective configurations before making physical changes.
Comparing Engagement Across Different Store Locations
Provides comparative simulations to analyse engagement in different locations. This allows businesses to tailor merchandising strategies based on regional shopping behaviours and customer preferences.
Classify Your Shopper Profiles Based on In-Store Path Tracking
Track and analyse shopper movement patterns to categorise customer profiles. Understand browsing behaviours and tailor merchandising strategies to different shopper segments.
Department
Merchandising
KPI
Product Placement Optimisation
Merchandising App
Optimise store merchandising layout using AI simulations to maximise shopper engagement and sales performance.
What You’ll Need
- Footfall and customer engagement data captured by FootfallCam people counters
- Training Data :
- Store Data
- Staff Data
- Sales Data
- Floorplan with Product Placement
Use Case in Action
FootfallCam Lab
Business Challenge
At FootfallCam Lab, store managers struggled to determine optimal product placements. Without clear shopper engagement insights, merchandising decisions were based on assumptions, leading to inefficient layouts and missed revenue opportunities.
Solution
By implementing FootfallCam’s AI-powered simulations, FootfallCam Lab identified 30% higher engagement zones, optimising shelf placements and improving product visibility, resulting in a 15% increase in conversion rates across test stores.
*This is a fictitious company and a hypothetical use case.
