According to whichPLM, artificial intelligence (AI) is going to revolutionize retail.
With AI, retailers will be able to have more structure to data collection, predictive analytics, and then application, and give them more insight into what’s to come in the industry. Especially through predictive analytics provided by AI, retailers will become more aware of and invest in breakthrough technologies to provide better customer service, make better pricing decision, personalize messages across campaigns, make product recommendations, and utilize other methods to run a better business.
Here are some benefits retail decision makers can expect from predictive analytics via AI solutions:
- Better pricing decision: whichPLM says that AI solutions help businesses develop data-driven insights on factors such as likeability and brand image without any foggy guesswork. AI helps develop predictive analytics for businesses, which can help “reduce and increase price during different seasons to create an optimal revenue effect.”
- Personalized messaging: With AI, automation can be used as a means of providing analytics for validation, which enables retail marketers to target product catalogs and use other methods to attract their key audience.
- ‘Promotions Advisor:’ With the predictive analytics provided by AI solutions, retailers are able to make sense of the lifestyles and habits of consumers, whichPLM says. “These behavioral traits reflect interesting purchase trends of the consumer, which otherwise would be almost impossible to know without a direct interaction with the customer.”
- Product recommendations: According to whichPLM, predictive analytics gathered by AI technologies can help retailers make better product recommendations for consumers. Chatbots, for example, can “help in understanding and predicting consumer behavior,” which used to be “one of the esoteric areas of study for marketers.
- Inventory and supply chain efficiencies: AI solutions can help retailers better predict industry demands for “every product, consumer type, and season of sale,” whichPLM says. “This helps them from being overburdened by excess inventory and to avoid the hassle of complexities involved with supply chain management. Similarly, they can forecast the slug in demand for products, allowing them to maintain modest inventory.”
- Detection of fraud: whichPLM says predictive analytics provided by AI technologies are especially important for e-tailers; data can unveil fake buyers and suppliers, and help retailers avoid associating with them.
- In-store sales: While many consumers are shopping and doing product research via mobile devices nowadays, retailers can use predictive analytics gathered by AI solutions to promote in-store sales “by optimizing over the existing footfalls” whichPLM says. “Data analytics combined with visual perception, heat mapping, and cognitive computing informs the retailer about where, when and how a consumer is likely to pick a product. This can help retailers in promoting relevant products, without any historical data of the shopper.”
- Customer service: Predictive analytics are able to lend a hand to customer service representatives in retail spaces to handle customer complaints; for example, whichPLM says they help “the agent across the phone, chat or email by indicating the problem of the griever ahead of time. This reduces time spent on each support ticket and enhances the customer service experience for the shopper, associated with the brand.”