In-store Analytics Solutions

The most powerful “aha moments” that our retail partners discover with shelf digitization don’t just tweak KPIs. They redefine how retailers operate. ⁉️⁉️ “66% of what we thought was out-of-stock… wasn’t.” A major grocer discovered that most “missing” items were misplaced in-store. That single insight dramatically improved e-commerce fulfillment and reduced substitutions. 🥬🥬 “Fulfillment speed increased by 50%.” With precise item-location data, stores introduced optimized picking paths—what one exec called “Google Maps for associates.” 🎽🎽 “Our oversight scaled from 4 stores a day to 40.” Merchandising leaders now review entire chains remotely—10Xing visibility and accelerating in-store strategy from weeks to hours. 😄😄 “Our staff is 90% happier.” With automation handling tedious checks, store teams regained 25–50 hours per week to focus on customers—improving morale, service, and sales.

Using Computer Vision and Operational AI for Retail-Occupancy Analytics. Traditional retail analytics often fall short. Operational AI offers a smarter solution: 𝗚𝗮𝗶𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲 𝗮𝗻𝗱 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗰𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝗱𝗮𝘁𝗮: - Understand foot traffic patterns and consumer behavior. - Identify peak traffic hours and make data-driven decisions. - Optimize store layouts and staffing levels. 𝗖𝗿𝗲𝗮𝘁𝗲 𝗮𝗻 𝗲𝗻𝗴𝗮𝗴𝗶𝗻𝗴 𝗮𝗻𝗱 𝗽𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝘀𝗵𝗼𝗽𝗽𝗶𝗻𝗴 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: - Tailor your offerings and promotions based on real-time data. - Improve queue management and reduce waiting times. - Provide a seamless and convenient shopping journey. 𝗜𝗻𝗰𝗿𝗲𝗮𝘀𝗲 𝗳𝗿𝗼𝗻𝘁𝗹𝗶𝗻𝗲 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗮𝗻𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆: - Analyze footfall trends, queue lengths, and conversion rates. - Improve staffing allocation and scheduling. - Optimize workflows and reduce operational costs. Video: Teknoir #ComputerVision #AI #Industry40 #DigitalTransformation #Retail #RetailTech #ConsumerInsights #SmartRetail #CustomerExperience #AIinRetail #RetailInnovation #QueueManagement

Every coffee served now comes with a data point. This coffee shop isn’t just brewing lattes. It’s tracking customer dwell time, staff efficiency, and movement patterns using AI video analytics. The NeuroSpot Barista Staff Control and Monitoring Module may sound like something from a sci-fi startup deck, but it’s real, and it’s changing how we measure frontline productivity. Here’s the kicker:   ↳ It’s not about replacing humans.   ↳ It’s about rethinking how we observe, learn, and improve the in-store experience in real-time. From a CMO’s perspective, this is where physical meets digital. ↳ Imagine personalizing offers based on how long a customer stayed.   ↳ Or improving staff allocation by understanding peak idle windows.   ↳ Or tracking which menu board design kept customers lingering longer. This is what the next era of retail looks like. AI acts as a silent observer, while marketing functions as a live operator.  Video credit: @cheatdaydesign  #AIinRetail #SmartMarketing #CMOThoughts #StoreAnalytics #DTC #RetailInnovation #CustomerExperience #MarketingOps #AIForGrowth

Tally Charts to Tech: Our Retail Data Story! 6 years ago, our first Lone Design Club pop-up started in a borrowed frozen yoghurt shop on Brick Lane. We tracked everything manually (think footfall click counters, tally charts on notepads etc) - far from today's sophisticated analytics! Having grown up in the digital world of Shopify and Instagram metrics, we knew data mattered. Those early spreadsheets (with questionable formulas 😅) seem hilarious now, looking at how our platform automatically delivers 360 degree insights to brands and landlords. What hasn't changed - the need to understand customers. I get asked a lot - The brands using the data the best, what is most important and why? Here's what matters most: 📍 Measuring Pop-Up Success & Future Location Strategy – Brands compare sales data vs. footfall insights to identify the best next retail location before committing to long-term leases. 🌍 Strengthening Omnichannel Strategy – Retail sales performance is compared to online engagement, helping brands refine their eCommerce & in-store strategies for a seamless customer journey. 📊 Optimising Store Layout – Brands track footfall patterns and dwell time to refine their store layout and product placement for higher engagement. 🎯 Targeted Marketing & Promotions – Age and demographic data help brands tailor offers and promotions to their ideal customer profile. 👥 Enhancing Staffing & Customer Service – Peak-time analytics allow brands to adjust staffing levels to maximise sales and in-store experience. By combining real-time retail insights with flexible spaces, we can remove the barriers for brands entering physical retail while giving landlords high-performing, growth-focused tenants. Read the full story here: https://lnkd.in/eU7eq-Ca #RetailEvolution #RetailTech #RetailAnalytics