Real-Time Insights: The Transformative Power Reshaping Retail

Real-Time Insights: The Transformative Power Reshaping Retail

With the rapid advancement of technology, data generation is increasing exponentially. According to IDC's data:

  • The volume of data generated in 2024 will reach 140 zettabytes
  • By 2025, this figure is expected to rise to 185 zettabytes. To put this rapid growth into perspective: this figure was only 2 zettabytes in 2010.

So, how can we harness this massive volume of data effectively?

Organizing and interpreting big data to transform it into actionable insights has become one of the top priorities and investment areas for companies today. In the fast-paced retail landscape, staying ahead of the competition requires more than just understanding historical data—real-time insights are essential. Real-time insights enable retailers to make instant decisions based on current data, leading to more responsive and adaptable business strategies.

By integrating artificial intelligence, IoT, and cloud computing, businesses can generate real-time insights that enhance customer service and enable rapid adaptation to market conditions, providing a significant competitive edge.


4 Critical Roles of Real-Time Insights in Retail


Shopper Experience

Retailers can optimize customer journeys by monitoring shopper behavior across both physical and digital channels in real-time. For instance, a user browsing an e-commerce site who adds items to their cart but doesn’t complete the purchase can be immediately offered a discount to encourage conversion.? In physical stores, analyzing which sections customers spend more time in allows for targeted promotions in those areas. Additionally, commercial marketing activities can be planned for low-traffic areas to drive engagement across the entire store, ensuring a more balanced shopping experience.


Inventory Management

Real-time data enables retailers to instantly monitor shelf stock levels, planogram compliance, and display investments, allowing for quick responses to demand-driven changes. By efficiently managing inventory, retailers can prevent lost sales due to stockouts and avoid the costs associated with overstocking.


Dynamic Pricing

By instantly analyzing demand and supply, you can determine the most optimal pricing strategies. For example, during periods of high demand for a popular product, you can manage prices to increase profitability, or as a brand, you can actively plan your pricing and promotional strategies by monitoring competitors' price levels and promotions in real time.


Route Optimization

Retailers can optimize their supply chain by analyzing weather, traffic conditions, and other transportation factors. Brands, on the other hand, can manage the route efficiency of their sales personnel by utilizing data on how much time their teams spend on various operational tasks at sales points, along with other transportation-related data.


Real-time Insight Generation Processes


Data Collection

With today's IoT technologies, nearly every product serves as a data generation source. Sensors, web and mobile applications, and social media platforms all contribute to this process. Additionally, with the advancement of image recognition technologies, data can now be generated from photos or videos, focusing on objects or individuals. In this process, data is collected in real time, and through a digitized process, the data flow is automated and transferred to systems.


Data Processing & Storage

The errors in the collected data are filtered and cleaned, transforming it into a more analyzable format through ETL processes. This allows the data to be stored in a manner that facilitates faster processing.


Application of Analytical Methods

Insights are generated through the application of data analytics methods. The analytical methods used are tailored to the specific needs and encompass a wide range of techniques. These methods can range from basic analytical techniques to advanced analytics such as AI and Machine Learning. However, to summarize the analytical processes briefly:

  • Descriptive Analytics: Describes data from past and current situations. Analyses such as the sales trend over the past 12 months or the percentage of locations where a product is available fall under descriptive analytics.
  • Predictive Analytics: Involves forecasting what might happen in the future based on the data. For example, predicting sales for the next three months is an application of predictive analytics.
  • Prescriptive Analytics: This process aims to recommend the best action plan to achieve the predicted optimal outcome.

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Visualization and Presentation of Insights

The results of the analysis are presented in the form of graphs, dashboards, and reports to enable managers and teams to make quick decisions. The critical aspect here is to determine how frequently and when the smallest update or change in the data source will be reflected on the dashboard. It should be set up in a way that allows decision-makers to intervene in issues or immediately take advantage of opportunities.

The real-time insight generation process enables fast and accurate decision-making. The success of this process relies on selecting the right data sources, using effective data processing techniques, and presenting the results in a meaningful way. Real-time insights help businesses gain agility, respond quickly to customer expectations, and gain a competitive advantage.


REM People helps retailers and brands stay ahead in the competition by enabling them to track their investments in products and shoppers in real time. It offers end-to-end digitalized solutions through IoT, AI, and image recognition technologies.



Would you like to be part of this revolution?


REM inStore: Retail Execution Monitoring Platform

  • Retail Merchandising Operations Management
  • In-store Inventory, Price & Expiration Date Tracking
  • Field Team Route Compliance Follow-Up
  • Call-to-Action & Task Management


REM e-Store: Digital Execution Tracking Portal

  • Digital Retail Execution Tracking (E-com & Marketplaces)
  • Price Tracking Daily
  • Page Lay Out Tracking Daily
  • Visibility Compliance Tracking Daily


REM Insert: Retailer Leaflet Tracking Portal

  • Retailer Discounter Leaflet/Brochure Tracking
  • Price Tracking
  • Promotion Type Tracking
  • Offer Tracking


RVL eyeQ: Camera-Based Visitor Analytics & Merchandising Tracking Platform

  • Storefront Analytics (Footfall)
  • Shopper Basket (Sales) Conversion Calculation
  • Instore Analytics
  • Retailer Shelf Tracking
  • Store Design & Visual Merchandising Tracking



For more information contact to: [email protected]



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