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Big Data Changes Retail Featured

Big Data Changes Retail Markus Spiske

Even before the current pandemic, the retail industry was going through a rapid transformation. The changes in this industry have significantly affected shopping behavior and have had massive changes in the retail sector. According to a survey conducted in 2019, 92 percent of the retail leaders were found to view reinventing the customer experience as the top priority. However, with the new reality of the COVID-19 pandemic, we have all been forced to accommodate the new changes. One of the critical changes that can be seen is the adoption of technology that includes big data strategies, artificial intelligence and machine learning. These technologies are used to understand the needs of the customers better and respond to them accordingly. Big data gives retailers ways to differentiate their brands through increased personalization for better customer service and demand forecasting. Here are some ways that big data is changing the retail sector.

  1. Personalization

Product or service personalization is one of the major selling points for retailers. It is about using customer data to anticipate, shape and provide what the customers want. Some retailers use artificial intelligence to help customers find their ideal products faster. For instance, the beauty retailer Sephora uses Color IQ, an AI-based system, to scan customers’ faces in the store and provide personalized recommendations for concealer and foundation. This allows customers to easily shop for the perfect products, with the online store shoppers finding the perfect products or new brands even when the store is closed.

  1. Customer service

Nothing turns off customers like lousy customer service. That is why businesses are doing everything within their power to enhance customer experience. One of the approaches that organizations have taken to enhance customer experience is AI-powered customer experience insights. Data analysis is used to trace aspects such as product returns and identify products with a high return rate. With this knowledge, retailers can redesign their products to avoid similar occurrences in the future. Furthermore, personalized customer messages can be designed with the help of AI, leading to increased retention and better messaging.

  1. Engagement

Retailers can use big data to increase customer engagement. Poshmark, one of the leading social marketplaces for fashion and home goods, uses big data to inform nearly every business decision and provide users with a tailored customer experience that addresses their individual needs. This company uses data to identify buying trends, which informs intelligent search results and connects users with the sellers that have what they are searching for. Data can be used to identify the challenges that users of a particular product face and educate them accordingly. This will increase engagement and enhance their experiences.

  1. Forecasting

Big data has become an essential tool in forecasting. Big data supports customer experience through predictive analytics, ensuring the products that certain customers want are available in time. Through predictive analytics, retailers can tap into the insights regarding customer behavior to determine the volume of products that should be stocked and at which locations. Knowledge of trends informs staffing decisions and marketing strategies as well as investment efforts.

As big data dependence keeps rising for retailers, there is little doubt that customer experience will become key to success. This means that as much data as possible will become crucial in driving revenues and enhancing customer loyalty. To ensure this stays relevant in the fast-changing business environment, retailers must explore big data and other related technologies such as AI and machine learning, which have already proven to be the most valuable assets.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

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