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Emerging Trends in Enterprise Data in Indian Retail

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By Bhavin Kothari, CIO & Head – Supply Chain & Logistics, ace turtle

Much has been written about data privacy being a major concern worldwide. Yet, few people may be aware that 82% of consumers are open to sharing personal data to enjoy better shopping experiences. This has been revealed in PwC’s recent ‘Global Consumer Insights Pulse Survey’.

It has often been mentioned that data is the new oil. Not surprisingly, data has emerged as the most crucial asset for the retail industry, especially enterprise data. To elaborate, enterprise data is all the information that retailers garner vis-à-vis customers. This includes the customer’s purchase history, loyalty forms, punched feedback, footfalls, real-time inventory levels, sales, trends from social media platforms and weather patterns in specific locations.

To enable accurate and more efficient decision-making, however, this enterprise data should be action-driven as well as result-oriented. To develop actionable insights from the relevant data, it is first necessary to institute strong data and analytics functions.

Coming back to the retail industry, India’s retail segment is expected to grow at 10%, touching around $2 trillion by 2032 as per the report of RAI.2 Given its growth potential, here are some key upcoming trends in enterprise data in the domestic retail segment:

Big Data and Analytics: Big data and analytics assist retailers in obtaining insights into customer trends and behaviour. By examining large sets of data, retailers are well-positioned to discover new opportunities, enhance service offerings, ensure better inventory management and optimize their overall operations to drive higher sales. Big data analytics also helps retailers in generating greater efficiencies across diverse business functions, facilitating judicious decision-making in product offerings as well as in pricing and marketing strategies.

Today, brick-and-mortar retail stores are equipped with digital cameras that track the products picked up from shelves by customers, taken to trial rooms and finally converted into sales. The captured data on footfalls, conversions and final product purchases are relayed into the system in real-time, later helping drive sales.

The rise of Omni channel retail: Omni channel denotes the practice of offering customers a seamless shopping experience across diverse retail channels, including online, in-store and via mobiles. By blending online and offline channels and integrating data collected from all modes, retailers provide personalized experiences to customers. An Omni channel approach has become indispensable in the post-pandemic period since changing consumer habits means most buyers first research products online, before deciding to buy them, either online or by visiting brick-and-mortar stores.

To capitalize on this trend, however, retailers need to build user-friendly mobile apps and websites, which enable prospective customers to browse and check products online before making any purchase decision. Omni channel is critical for ascertaining customers enjoy a seamless shopping experience, beginning with browsing and product discovery right up to the purchase and delivery of goods and well beyond.

The adoption of AI: AI is being deployed by organized retailers for automating tasks, improving decision-making and delivering more personalized experiences to customers. The rapid rise of ChatGPT is also being utilized by retailers to create product descriptions for seasonal offerings of their brands.

Additionally, AI-enabled digital assistants and chatbots are utilizing data analytics to make intelligent price and product recommendations that ensure an enjoyable shopping experience. These recommendations are based on consumers’ browsing and purchase history that help detect patterns in buying preferences.

The emergence of cloud computing: Thanks to cloud computing, storing and processing huge amounts of data is easier and more affordable. As a result, retailers find it convenient to adopt digital technologies that were not feasible earlier due to the higher upfront costs. Besides simplifying workflows, lowering IT costs and improving customer experiences, a cloud-based system leads to faster, more-informed decision-making that provides real-time, integrated solutions.

Inventory and warehouse management have also become very convenient. Monitoring, managing and maintaining inventory is a challenging task for retailers. This is particularly true when retailers need to manage numerous store locations in real-time to track and assess their inventory. Through retail cloud services, however, real-time data is available to monitor and track the inventory 24×7. Cloud computing also eliminates any need for manually syncing the inventories across different stores.

Similarly, retailers don’t need to be physically present at warehouse locations for inventory management. Instead, warehouse inventories can be remotely managed from anywhere as the retail cloud allows real-time access to stock volumes at any location.

The rising use of mobile devices: Backed by cheap data rates, the ubiquity of mobile devices has made them the primary medium for consumers to interact with retailers. Therefore, retailers have realized the significance of collecting and analyzing mobile data to deliver more personalized consumer experiences.

Privacy and data security: The ever-rising importance and volume of data have made it imperative for retailers to safeguard the privacy of customers while simultaneously ensuring robust data security. With consumer sensitivities in mind, retailers in India are investing in encryption technologies and secure data management systems while also ensuring compliance with domestic data protection laws. Maintaining consumer trust and protecting their data is indispensable for promoting sustainable growth in retail.

Sharing & Monetization of data: Consumer data can be shared and monetized by retailers to enhance the customer experience while generating revenue. As per EY, data can be leveraged as an alternative revenue source by retailers via supplier insights, providing services such as warranties and financing, advertiser collaborations and partnerships with banks to launch co-branded promotional offers.

Sharing and monetization of data between organizations belonging to different industries can help improve the lives of consumers and benefit the companies. For example, based on the economic profile of different consumer segments, locations or regions and their purchase preferences for durables or automobiles or gadgets, retailers can plan expansion of their store network. This helps retailers to go closer to their customers and cater to their evolving needs.

To implement these measures, retailers must have the requisite tools and processes in place to garner, manage and decode company data so it can be used gainfully. The appropriate staff with relevant skills and understanding should also be available to extract insights from captive data and successfully utilize it to boost the bottom line. If all the relevant boxes are ticked, retailers can offer the most engaging and enjoyable shopping experience to customers.

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