Big data enables retail companies to create personalized customer recommendations based on their shopping experience.

The relevance of big data is only rising in every sector. The retail industry is not holding back on this front as well! No wonder big data use cases across the retail industry, today, abound.

Over the last few years, the retail industry has witnessed a shift of paradigm in its operations. In the internet-era, customers have changed the way they shop for their needs. Today, they approach different stores at the same time, compare prices and products, and then make their final purchase decision. This has resulted in a power-shift from retail aggregators to customers. To stay in business in this competitive phase, retail companies are looking at different ways to engage with customers and also manage their resources efficiently. Big data seemingly holds the potential to provide companies with applications to manage customer engagement and resources efficiently. Further, in this article, we look at three of the most successful big data use cases in retail.

1. Understanding Customers & Learning Shopping Habits

Now that the customer is in power, retail companies should focus on understanding each customer individually to offer her a more personalized experience. Big data can help retailers to understand their customers by tracking their transactions, browsing behavior, preference for specific products, shopping trends, and social media habits. This way, retailers can cater to the customers in a more personalized way via targeted advertising, product recommendations, and pricing. 

2. Analyzing Brands & Providing Better Product Recommendations

In order to provide customers with better product recommendations, it is essential that retailers understand each brand separately. Big data can analyze a brand’s social approval using social media analysis and brand website traffic analysis. The conversions from a product’s landing page to checkout also provide an insight into the level of consumer appreciation of the brand. This data can further help retailers to provide accurate product recommendations to a customer and increase conversions.

3. Building Promotional Strategies

Retailers invest a lot of their resources into advertising and other promotional campaigns in the hope of boosting sales. However, sales could be driven better if these advertisements reach the right customers. Big data can help evaluate the needs of a customer segment by bringing into consideration the buying practices of a consumer and other relevant but often missed information like, let’s say, the upcoming weather conditions. This data can be used to supply relevant advertisements to prospective buyers and consequently drive sales. US hotel chain, Red Roof Inn, employed big data techniques for light cancellation analysis and weather conditions. The company then used this data to send out offers on accommodation accordingly. This strategy eventually led to a 10% growth in its business.

In conclusion, big data has immense potential to help retailers stay ahead of their competition and offer better services to their customers. Apart from the above big data use cases, there are many other specific applications of big data in retail that can drive sales revenue and also take customer retention upward.