About
StoreTech provides advanced people counting and retail analytics solutions purpose-built for UK retailers, from independent shops with 1–20 locations to national chains with 200+ stores. The platform captures real-time footfall data to give retailers accurate visibility into customer traffic patterns, peak trading hours, and overall store performance. At its core, StoreTech bridges the gap between in-store activity and business outcomes. Retailers can measure conversion—the ratio of visitors to purchasers—just as precisely as e-commerce teams track online funnels. By combining footfall data with point-of-sale figures, StoreTech surfaces missed sales opportunities and highlights when and where to focus selling effort. Demand-based scheduling is a standout capability: managers can align staff rotas to actual traffic patterns rather than guessing based on availability, striking the optimal balance between labour costs and customer experience. The platform also quantifies the impact of visual merchandising changes, store layout updates, and marketing campaigns by correlating them directly with footfall trends. Built for retail store managers, area managers, operations leads, and marketing teams, StoreTech's real-time dashboard delivers live performance data as it happens. With nearly three decades of retail expertise, StoreTech is a trusted partner for retailers seeking data-backed decisions over gut feel.
Key Features
- People Counting & Footfall Analytics: Accurately tracks every visitor entering your store, providing hourly and daily traffic data to reveal your busiest periods and uncover trends over time.
- Conversion Analytics: Combines footfall and sales data to calculate your true in-store conversion rate, highlighting missed opportunities and showing how effectively browsers become buyers.
- Demand-Based Staff Scheduling: Aligns staff rotas to real customer traffic patterns, ensuring the right number of people are on the floor during peak hours without over-spending on labour.
- Marketing & Campaign Impact Measurement: Correlates footfall trends with promotional campaigns, visual merchandising changes, and store layout updates to quantify what's actually driving customers through the door.
- Real-Time Performance Dashboard: Delivers live footfall, sales, and conversion data in a single platform built for store managers, area managers, and retail operations teams.
Use Cases
- A regional fashion retailer uses StoreTech to identify peak footfall hours and realign staff rotas, reducing labour costs by 15% while improving customer service during busy periods.
- An independent homeware store measures the footfall impact of a window display refresh and a local radio campaign, confirming which drove more visitors before committing to repeat spend.
- A national grocery chain uses conversion analytics across 150 stores to benchmark performance, flag underperforming locations, and replicate best practices from top-converting branches.
- A retail operations manager uses real-time footfall dashboards to monitor daily store performance remotely, replacing subjective end-of-day reports with objective, data-driven summaries.
- A multi-site clothing retailer uses demand scheduling to ensure every store is correctly staffed during seasonal sales peaks, maximising conversion opportunity without exceeding payroll budgets.
Pros
- 27+ Years of Retail Expertise: StoreTech brings nearly three decades of hands-on retail analytics experience, making the platform highly tailored to real-world store management challenges.
- Scalable for Any Retail Size: Purpose-built solutions for both independent retailers with a handful of locations and national chains with 200+ stores, ensuring the product fits your growth stage.
- Actionable Conversion Insights: Unlike raw traffic counters, StoreTech connects footfall to sales outcomes, giving managers a clear, data-backed view of store performance and missed revenue opportunities.
- Reduces Labour Cost Guesswork: Demand scheduling aligns staffing directly to customer traffic, helping retailers cut unnecessary labour spend while maintaining high service levels.
Cons
- UK-Focused Offering: StoreTech is primarily tailored to UK retailers, which may limit its applicability for international or non-UK retail operations.
- Physical Retail Only: The platform is designed exclusively for brick-and-mortar stores and does not offer analytics capabilities for e-commerce or omnichannel environments.
- Pricing Not Publicly Listed: No pricing information is available on the website; retailers must book a demo to receive a quote, which can slow down evaluation for budget-conscious teams.
Frequently Asked Questions
How does StoreTech's people counting technology work?
StoreTech uses sensor-based hardware installed at store entrances to accurately count every person entering and exiting. The data is fed into a real-time analytics platform where it can be viewed alongside sales figures, staffing schedules, and campaign data.
What size retailers does StoreTech serve?
StoreTech serves UK retailers across the full spectrum—from independent businesses with 1–20 stores to regional and national chains with 20–200+ locations. Each tier has tailored solutions suited to their operational complexity and data needs.
How is conversion rate calculated by StoreTech?
Conversion rate is calculated by dividing the number of sales transactions by the total number of store visitors (captured via people counting) over a given time period. This mirrors how e-commerce conversion is measured, giving brick-and-mortar retailers the same analytical clarity.
Can StoreTech measure whether a marketing campaign increased footfall?
Yes. By tracking footfall data before, during, and after a campaign period, StoreTech allows retailers to directly correlate marketing activity with changes in visitor numbers, providing clear evidence of marketing ROI beyond just sales uplift.
How does demand scheduling help reduce labour costs?
StoreTech analyses historical footfall patterns to identify the busiest and quietest periods of each day and week. Managers can use this data to build staff rotas that match customer demand, avoiding both overstaffing during quiet times and understaffing during peaks.
