Use cases, Retail

A New Category Manager: In-Store Analytics

Retailers seeking to support their category managers are increasingly turning to advanced technology solutions to enhance decision-making and efficiency.

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Challenge

Retailers know that positioning higher-margin products in high-visibility areas and second point of sales can increase awareness and profitability. But manual and less accurate in-store solutions struggle to deliver precise data on the three most important issues for making the most of in-store displays and category layout:

Dwell time
View direction
Engagement rates

Optimizing Merchandising with Subcategory Analytics

Retailers need insights into store dynamics to boost engagement and sales. Belgium's Amoobi used Xovis 3D sensors to enhance a major retailer's performance.

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Solution

Mapping customer journeys across in-store touchpoints is already considered best practice for hybrid retailers. Replacing resource-intensive solutions for optimizing categories and subcategories can be a quick win if the replacement can accurately:

Differentiate between engaged shoppers and passersby
Calculate conversion rates based on precise customer data
Indicate opportunities for improving the visibility of category shelves
Track customers' engagement with designated shelves
Qualify and quantify category and subcategory dwell times

Bald man with a beard in a t-shirt, smiling warmly at the camera in a black and white portrait.

We have identified, that one of the key issues was to set the right and effective workforce planning not only towards the cost savings but also with respect to the overall customer experience.

Milan Morávek Chief Sales & Customer Service Officer, O2 Slovakia

Benefits

Adding an automated solution to category management efforts can help retailers achieve maximum turnaround quicker. The result is:

The acceleration of the trial-and-error process
No additional labor costs associated with manual observation
An expansion in basket sizes
Effectively managing inventory cost based on actual consumer demand

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A dynamic retail complex features supermarkets, clothing stores, and transport hubs with bustling activity.

Frictionless Checkout

Automation helps balance customer flow and prevent loss at self-service zones
Measure Customer Engagement

Measuring customers’ in-store dwell times can boost sales of higher margin products
Improving Store Layout

Accurate store traffic data helps retailers optimize layout and product placement
View Direction

Retailers can boost revenue by measuring in-store attention
Customer Counting

Optimal staff and layout depend on real-time customer engagement data
Optimizing Product Positioning / Assortment

Retailers looking to support their category manager are turning to tech
Real-Time Waiting Analytics

Retailers need a robust queue management system to eliminate friction points
Preventing Queue Formation

Queuing up can become a costly friction point for brick-and-mortar retailers
Expanding Sales with Demographic Data

Understanding gender-specific shopping trends helps retailers optimize resources.
Customer Centric Staff Allocation

Retailers need a robust queue management system to eliminate friction points
Staff Exclusion and Sales Performance

Real-time KPIs help retailers optimize performance across all locations
Use-Based Cleaning

Smart Retail requires Smart Cleaning to enhance customer experience
Group Shopping Analytics

Shopping habits change with company, aiding retailers in boosting sales
Window Shopping Analytics

Tracking capture rates from window shoppers can boost store performance

A New Category Manager: In-Store Analytics

Optimizing Merchandising with Subcategory Analytics

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