To understand the customers' changing needs and respond to their desires correctly, businesses must take advantage of big data and other related technologies like artificial intelligence and machine learning (AI and ML). This will help them differentiate their brands through increased personalization, customer service, and demand forecasting. With the business ecosystem that has turned out to be highly complicated, retailers will be taking advantage of opportunities offered by big data to understand the changes in the landscape and provide customers with an elevated experience.

Personalization is becoming one of the selling points for many businesses. It can only be achieved by using customer data, anticipating and shaping what the customer desires. Due to its importance in enhancing customer satisfaction, most retailers, such as those in the apparel and beauty space, are using it to help customers find their products faster. Sephora, one of the users of this technology, uses AI and big data analytics to scan the face of the customer and shade library to offer recommendations that reduce the time that can be used to search for products. 

Although the massive data that comes from daily operations can be challenging to manage, it can also be a blessing if used well by retailers. With AI-powered customer insights, customer experience can be transformed for the better. With the correct data, you can always overcome customer service challenges that often cause loss of customers and business. Your merchandising team can analyze data regarding product returns and identify the specific products or brands that are having an issue.  Armed with this knowledge, you can remove that specific product from the shelf or return it to the manufacturer to avoid issues with the customer. Data can also come in handy when you want to send personalized messages to the customer, leading to better customer retention.

According to Gartner, the volume of data will rise by over 800 percent in the coming years. This will include 80 percent of the unstructured data. As such, retailers need to have a concrete big data management solution that can help retrieve and process data from different sources. This solution can help retailers gather real-time insights for faster decision-making while generating actual value for the business.

Thanks to machine learning advancements, the internet of things, and artificial intelligence, predictive analytics help enhance accuracy and insightful data to the users. This will help businesses increase sales and make marketing teams more practical through access to precise data needed to make marketing decisions. All these are necessary for determining the lifetime value of a customer. When it comes to identifying issues and trends that may affect business operations, predictive analytics, which is one of the key elements of big data, is highly beneficial. It can help retailers identify issues with a brand and reasons why customers might leave it behind. This is critical information that can allow business owners to take action and improve the experience of the customer.