Spencer’s, an American retail company, was struggling with overloading with manual processes while shelves auditing. The company decided to invest in smart solutions to take off this burden from the in-store managers. Read how AI-driven solutions benefited the general in-store sales of this brand.
Meet Our Client
Spencer’s is a North American mall retailer with over 600 stores in the United States and Canada. Their stores offer gag gifts, clothing, band merchandise, sex toys, room decor, collectible figures, fashion and body jewelry, and fantasy and horror items.
Case Study Shortcut
Challenge
Manual and Time-Consuming Shelf Audits
In-store managers and field surveyors had to manually verify shelf compliance, including checking planograms, prices, and SKUs.
These repetitive processes were highly labor-intensive and consumed valuable time that could otherwise be spent on sales-related activities.
AI-based solution able to reduce the efforts required to conduct shelf analytics
Shelf auditing done manually was prone to mistakes, such as incorrect product placement or price labeling.
Even small errors could negatively impact sales performance, as improper product visibility or pricing deters customer purchases.
Lack of Real-Time Insights and Optimization
Decisions regarding shelf layout were often based on intuition or delayed data, preventing timely optimization.
The dynamic nature of in-store customer behavior required faster, data-driven responses that were impossible under the manual auditing model.
Goal
Spencer’s was looking for a partner able to design and implement the AI-based solution for signing compliance and shelf analysis.
The desired tool should have been equipped with a user-friendly UI to make the usage easy for non-technical users.
- Reducing the amount of manual analysis
- Speed up of the shelf analysis processes
- Decrease its prone to errors
- Optimization of product positioning
Outcome
Computer Vision solution delivered by Addepto equipped Spencer’s in-store managers with an easy-to-use visualization dashboard to make smarter, data-driven decisions.
Previously, they decided about goods placement solely based on observations and intuition, and they couldn’t implement instant changes when noticing the planogram needed to be adjusted. The everchanging in-store situations and dynamic data flow about customers’ preferences make it difficult to keep up with planogram optimizations and correctly set compliances. With Computer Vision actively gathering and analyzing in-store objects, the efforts were significantly reduced.
Before
- Cost- and Time-consuming Retail Audits
- Manual Data Analysis
- Costly In-Store Operations
After
- Speed Up Retail Audits
- Product Placement Optimization in Real-Time
- Increasing Customer Satisfaction
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Case Study Details
Approach
Computer Vision for In-Store Shelf Monitoring
- Developed advanced Computer Vision models to detect: product presence and placement, in-store product signage, shelf compliance against the store's planogram, automated visual recognition replaced subjective human observations.
Real-Time Compliance Analysis
- Compared live in-store data with predefined compliance requirements from a central database.
- Enabled instant validation of whether shelves met visual merchandising standards, including SKU presence and price tags.
User-Friendly Web Dashboard
- Delivered a mobile- and desktop-friendly web application for in-store and regional managers.
- Presented visual results via intuitive dashboards, allowing managers to: easily assess compliance status, identify issues quickly, take immediate corrective actions.
