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Retail Predictive Analytics

A recent report by GlobalData recommends artificial intelligence (AI) and machine learning as the next step retailers need to take in order to obtain maximum profitability. AI and machine learning are penetrating nearly every industry and the retail sector is no different. Technology like predictive analytics are already making waves in retail, driven by increased competition and digitization of the marketplace. This changing face of retail gives businesses a unique opportunity to create a new AI-powered, engagement focused retail market – with the needs of the consumer at its core.

Operationalizing Retail Engagement Strategies.

Retailers are already capturing hordes of data every day about consumers. From social media sentiments, to the duration of time consumers spend in-store, applying AI-powered technology can help the retail industry respond to the shifting business landscape and changing consumer needs. With these tools, retailers can transform their data to inform and operationalize their consumer engagement strategies. AI not only has the potential to assist consumers with product recommendations, but can actually predict shopping habits, helping retailers engage with consumers by understanding their approach, before it happens.

Defending Brand Advocacy

Predictive analytics can also alert retailers to those consumers at risk of brand defection. Monitoring the keywords consumers are searching, which competitor sites they’re visiting and what content they’re viewing, can alert retailers to when a consumer is indicative of a high intent of defection. Monitoring at-risk consumers with ongoing behavior and purchasing patterns, allows retailers to program their immediate response to competitive situations and reduce consumer churn rate.

Contextualizing Retail Insights with Machine Learning

AI and machine learning can provide key value in all areas of retail. Combining intent signals and pre-purchase research patterns with past practices and behaviors presents a complete view of a buyer’s intent. This greater level of insight into the actual behaviors of consumers, gives retailers the power to predict demand, optimizing supply and stock levels. Utilizing data gleaned from consumer social media platforms, industry trends, and individual preferences, machine learning algorithms can generate deeper insights at a more granular level. These insights can then be translated into contextually relevant messages for consumers, aiding retailers in customized marketing campaigns.

 

As the AI-powered transformation of the retail sector is currently driven by larger industry players, the future of retail will be dictated by those AI use-cases that are effective. With smaller retailers looking to the strategies of the larger industry players for guidance, those that fail to implement AI-powered solutions risk lagging behind the competition.

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