Big Data Analytics: Transforming The Arena of Retail Industry

In today’s world, customer personalization is highly important to running any business. Customers expect a seamless experience for their purchase; otherwise, they generally shift to a different retailer. By using retail analytics and merchandising analytics, retail merchants can improve their customers’ buying experiences and enhance their sales.

What is Retail Data Analytics?

Retail analytics is defined as a process that utilizes big data to optimize price, supply chain movement, and boost customer loyalty. “Big data” refers to a large amount of data used for revealing patterns, associations, and trends associated with human behaviour and interactions. It referred to the three key factors: Volume, Velocity and Variety.
In the retail industry, Big Data helps to understand customers’ shopping habits as well as proves beneficial in attracting new customers. The introduction of Big Data analytics in the retail industry provides valuable and better insight to retailers, which helps them make the right decisions.
Firstly, with big data analytics, retailers can understand their customers’ buying patterns. Secondly, whether it’s about creating a buzz on social media trends or making sure stock matches seasonal demands, big data analytics allows them to know exactly how much stock a company needs ahead of time.
In this article, we will learn more about how Big Data analytics plays a vital role in transforming the retail industry.

How Does Big Data Benefit the Retail Industry?

• Personalized customer experience

By getting customer data, retailers can understand the behaviour and buying patterns of customers at both collective and individual levels. By utilizing data analytics, retailers can divide their customers on the basis of their shared characteristics and create a detailed profile for them while considering the demographics they belong to, their purchase history, and individual preferences. By utilizing such detailed information, retailers can offer personalized recommendations to their customers, product discounts, etc. to enhance the customer experience.

• Predict consumer demand

In this transforming retail industry, predictive analysis allows retailers to predict the changing trends of marketing and customer behaviour. By collecting historical data, retailers can make the right predictions and determine how new trends will impact customer behaviour. By getting accurate data on customer demands, companies can forecast their potential sales. In this way, retailers can stock adequate inventory and avoid losses due to wastage.

• Quick decision-making to improve the supply chain

A retail brand needs to handle the various steps of the supply chain. For this, they need to make an immediate decision which is possible when businesses have required data related to channels and segments linked with their supply chain. By grabbing enough information about brand popularity it becomes easy to manage the supply chain which results in high ROI. Retail companies can utilize data analytics for monitoring events and making immediate decisions.

• Customer journey analytics

Customer journeys are highly complicated and turning around into various in-person and digital channels. Retail data Analytics bring out valuable data from those customer journeys and analyze it to provide insights into customer behaviours. You can utilize big data analytics to determine:-

• Different channels that are most likely used by customers
• Touchpoints where they most like to engage with
• Marketing materials on which they like to respond
• Stages of the customer journey that results in a great impact on customer satisfaction

By using such information, retailers are able to streamline their customer journeys, build impactful marketing campaigns, provide better customer services and enhance customer experiences.

• Improve sales with optimal Pricing

By utilizing advanced analytics companies can gauge how customers are responding to the price level of different products and predict how changing prices will impact their sales. In this way, retailers can set a competitive price for their products and maximize their sales. Also, they can provide discounts or a combo of popular products to grab customer attention and increase their sales.

Wrapping Up

Smart retailers are now shifting to Big Data Analytics in Retail Industry to stay competitive in the market. It proves beneficial in understanding customers in a better way and offering the best solution to ensure customer satisfaction. At Ksolves, we understand how big data and analytics can predict from driving data and connect customers to your brand and ensure an effective supply chain for creating new and unique user experiences.
Ksolves is one of the fastest-growing software companies which has been backed by a highly experienced team of Big Data professionals to deliver the best-in-class services. Our professionals can create and execute strategies that help in optimizing the retail value chain to improve customer experience. If you want to implement Big Data Analytics in retail business then connect with our experts today.

Frequently Asked Questions (FAQs)

How does data analytics prove beneficial in managing multiple locations of Retail Chains?

By using Big Data Analytics, retail chains and businesses can understand the product demands in different geographic locations. By grabbing information about customer spending, retailers can provide better services in specific regions and stock the products efficiently.

Where does big data become a limitation for the retail industry?

With big data, the retail industry is facing the biggest challenge, which is dirty data, like data filled with errors, incomplete values, duplication, and data silos. All these things make it difficult for retailers to manage and analyze the data. Apart from this, scarcity is another issue that comes with data science.

How does big data analytics benefit retailers?

With data analytics, retailers can prevent fraudulent activities, retain customers, improve the customer experience, and much more.