The Role Of Cloud Computing And Data Analytics In Reviving the Retail Sector

Analysing massive volumes of data on customers, product trends, and supply chains generate insights that can lead to better decision-making and improved customer experience
The Role Of Cloud Computing And Data Analytics In Reviving the Retail Sector
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5 min read
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The economic repercussions of the COVID-19 pandemic have not yet fully unfolded and industries are bracing themselves for the impact. However, as activities slowly resume, the retail sector will play a vital role in kickstarting economic recovery. To thrive in today's economic climate, retailers are realizing the need to leverage the power of data and technology. Retailers, consumer packaged goods (CPG) manufacturers and e-commerce companies produce enormous amounts of data. Aggregated from various channels, such as online and mobile transactions, data exchanges, social media and the Internet-of-Things, the retail industry's data resource is waiting to be tapped.

A report from Nasscom and EY predicts the Indian retail sector will reach $1.4 trillion by 2024. Moreover, with the retail sector's rapid movement to online platforms, India's online retail sales are projected to generate total revenue of $60 billion by the end of 2020.  Driven by changing consumer behavior and the emergence of the digital economy, India's retail sector is set to witness artificial intelligence and data-led disruption opportunities, particularly in the organized retail and e-commerce sector.

The shift in purchase behavior of consumers was further reinforced due to lockdown and quarantine measures. Consumers have shifted to online shopping options for safety and security reasons. Responding to demands, retailers have listed their operations on various e-commerce platforms or mobile apps to serve their customers. As the situation gets better, cloud computing and data analytics will play a major role in the transformation of the retail sector.

Gearing up for Cloud Computing and Data Analytics

Analysing massive volumes of data on customers, product trends, and supply chains generate insights that can lead to better decision-making and improved customer experience. However, data analysis can be complicated with legacy systems and data silos. Poor data infrastructure and data management can hinder the implementation of analytics solutions, jeopardize data security, and prevent real-time data sharing.

To overcome these obstacles, retailers are turning to cloud solutions and technologies to break down barriers to the easy flow of data, realize analytics capabilities and unlock data-driven insights.

Here are some ways how cloud computing and data analytics can help retail and CPG companies better serve their customers, decrease costs, and increase profits.

Predictive Analytics

Retailers and CPG companies need data insights to build elasticity and scale into areas such as supply chain, inventory, logistics and staffing. Faster product life cycles and increasingly complicated operations are pushing retailers to identify bottleneck areas in the supply chain to maximize profits and reduce costs.

With advanced analytics and data modeling, companies make better predictions about when specific items will be in demand and help them make faster and better supply chain decisions. The ability of cloud technologies to natively ingests immense volumes of granular, semi-structured and fragmented data from every phase of the supply chain, is crucial for predictive analytics. With real-time visibility into supply and distribution networks, retailers can decrease inefficiencies in the supply chain and anticipate item availability. With on-demand concurrency, retailers can run a host of models in parallel without performance degradation issues.

In-depth View of Data

Most of the business decisions successful global retailers make aren’t global—they are hyperlocal. Decisions are made at the regional or even individual store level about what type of inventory to stock based on the weather or local trends, how many salespeople are needed during holiday periods, or which suppliers to use based on pricing and logistics.

Structured and semi-structured data from different sources and channels are consolidated into a centralized repository, allowing both universal and granular views of business and customers. This facilitates easier data modeling and predictive analytics that can help make data-driven decisions. Through cloud and data analytics solutions, retailers have an in-depth view of their data to drive performance and efficiency.

Customer Reach

Marketing departments have a colossal task: to personalize the promotion and sales of their products and services for every potential buyer out there. E-commerce streams produce massive volumes of data on consumer behavior that can help marketers deliver what buyers want and when they want it. However, due to outdated systems and fragmented information silos, retailers are unable to leverage this data for targeted marketing.

Cloud data platforms give marketers a single source of data aggregated from various internal and external sources. Armed with this massive trove of information, retailers have the ability to devise targeted marketing efforts and create personalized products and offerings.

Today, the ease and convenience of shopping experience is just as important for consumers. For consumers, this convenience means having a seamless and personalized shopping experience through multiple channels. To respond to consumer demands, retailers are combining online stores and physical brick and mortar shops, which paves the way for omnichannel and hybrid sales models.

As retailers seek to improve products and services and utilize e-commerce platforms and mobile applications, using IT solutions for data gathering and analytics has become imperative. With the help of these solutions, retailers can make data-driven decisions around pricing, services and marketing communications, which will help improve customer experience, deliver value and achieve business goals.

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