Retail analytics solutions open infinite opportunities before retailers. Enterprises can embrace this shift to solve complex problems and simplify the path to purchase.

Retailers have started to realize the importance of automating their processes and increasing the efficiency of their everyday operations. It is estimated that by 2023, online sales will account for about 25% of the overall retail industry. Customers expect the same digital experience in offline physical stores.

Hence reducing human intervention and implementing a contactless shopping model across each stage of the buyer’s journey will give brands a competitive advantage. It is essential to deliver a personalized, frictionless, data-driven, and connected shopper experience. Retail automation powered by retail analytics solutions is the alchemical elixir for small retailers to compete with vanguard brands. Automation sits at the core of retail analytics and the NexGen environment it enables.

Top use cases for automation & data analytics in retail

The next step in the retail transformation journey is the shift towards a sustainable, data-led, and results-driven model. A slow market, increasing operational costs, and an overburdened supply chain will create significant bottlenecks for retailers in the future. Other than this, retailers will also have to execute a consumer-centric business model. This is where retail automation can help streamline end-to-end operations and reduce human efforts and errors.

#1 Invoice processing

Processing invoices is a time-consuming and mundane task that restricts the productivity of in-store promoters. The retail workforce is constantly surrounded by heaps of paperwork and spends unproductive hours on mundane tasks. As a result, human involvement in this department continues to dilute efforts. Retail process automation and robust digital applications can help collect information, segregate data, and process bills faster without human errors.

#2 New product launches

As new products come along, old assortments need to be updated. Attributes such as pricing, stock quantity, and basket sizes are often subject to change. Using automated retail sales management software, stakeholders can continuously track purchase patterns, propensity, customer feedback, basket sizes, etc. This will help them tweak product rates, manage inventory, and adjust pricing and promotions in real-time for higher sales.

#3 Sales and BI analytics

In an increasingly data-driven landscape, it is important for retailers to track and analyse their in-store sales data for improved decision-making. Automated BI analytics tools can provide real-time actionable intelligence based on customer preferences and user behaviour regarding a particular product, visual merchandising, or in-store branding. Additionally, Denave’s retail analytics solutions can help with predictive analytics, which supports stock optimization.

#4 Store planning & inventory optimization

Tracking on-shelf user behaviour and the basket size of individual customers will allow retailers to strategically place products and optimize pricing. It will also simplify sales cycles by helping customers complete the purchase early. When the customers can find relevant products without any hassle, it becomes a high-selling point.

Retail analytics solutions will help analyse the organization of stores to fit customer expectations, improve user experience, and boost profits.

#6 Logistics & supply chain management

Logistics and supply chain management is at the core of successful retail execution. The primary objective of a retail setup is to take products from suppliers and deliver them to the customers. However, there are several processes involved in this transition, including inventory level monitoring, shipment, order tracking, and return processing. By deploying retail analytics solutions, companies can automate supply chain processes and improve collaboration between suppliers, distributors, and customers.

Conclusion

The past two years of the covid-19 pandemic have accelerated the adoption of retail automation as it helps to decrease operational costs and improve pace. Retail analytics combined with automation technology can help retailers to organize complicated organizational tasks, such as compliance and retail audit regulation. When mundane activities are automated, in-store promoters can allocate their time and resources to complex and strategic roles.