Big Data

Why analytics is a key tool for retail

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analytics retailSuccess in retail is contingent on offering the customer the right product in the right environment. Matching the two can be hard, since no two customers are the same, and external forces as diverse as catwalk trends and the weather affect demand and purchasing decisions.

In the digital age, consumers interact with stores and service providers through multiple channels: in-store, online and mobile, as well as via phone and social media. At each point, retailers gain an insight into individual customer behaviors through data. That data creates rich picture of an individual’s purchasing habits. Tapping into this rich data source is becoming increasingly key to predicting future customer behavior, driving loyalty and increasing revenues.

Predictive analytics software, such as IBM Predictive Customer Analytics, can take customer data from multiple cloud or on-premises data sources to create truly personalized interactions, thereby boosting purchases, wallet share and loyalty. The role of IBM Predictive Customer Analytics is to take customer data, apply predictive analytics and deliver the best action to front-line systems so retail businesses can use the data to deliver an exceptional customer experience.

For example, take a customer that has been using a department store’s mobile app to search for high-end TVs. Say the customer also has a loyalty card, and historically has reacted positively to double-points offers. A few days later, the customer walks into one of a store and alerts the company’s marketing system of her presence via GPS. Seeded by predictive customer analytics, the marketing system uses the customer’s search history and preference for double-points offers to send a personalized offer while the customer is in the store. This helps the customer make a buying decision and increases overall satisfaction and loyalty. The store is more likely to make a sale.

It’s also important to recognize changes in buying patterns and taste, or a groundswell for the next big retail phenomenon. Analysis of social media can give early insights into such changes or trends, but noticing patterns in such a vast array of unstructured data is difficult without help. IBM Social Media Insight for Retailing is a cloud solution that helps merchandisers by analyzing a range of social media sources and internal data.

For example, a cycling retailer may use Insight software to monitor cycling-related topics. Cycling clothing for children may be an increasingly popular theme. The merchandiser looks for social media insights about its own cycle clothing range for children, to discover their customers feel let down by a limited selection. This may prompt the retailer to launch a range of cycling clothing aimed at children, backed by a social marketing campaign, with the knowledge that there is consumer demand. Without the powerful analytics tools looking at social media, this market opportunity might otherwise be missed, especially if previous sales were low.

The ability to analyze and understand customer behaviors and market trends is key for success in highly competitive retail markets.

IBM offers a range of analytics tools which help retail companies gain insights from customer behavior and retail data so they can make smart merchandising decisions that boost revenue growth.

Learn more about IBM Cloud retail solutions.

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