While the path ahead is unknown, it is the continuous reinvention of the landscape and how brands adapt and evolve that will define the next era of retail. These strategies can help retailers plot a steady course and find their way through uncharted territories.
Over the last 10 years, developments in retail data analytics have been especially useful in assisting marketers in extracting maximum value from retail customer and consumer data. Now it’s time for brands to make the shift from knowing their customers to truly understanding them with the help of Consumer Insights.
Learn how retailers can use AI in retail and consider data-driven insights on how target consumers respond to given scenarios and offers and use that context to inform future consumer engagement and increase new customer acquisition with the help of consumer analytics pulled from Oracle Retail Consumer Insights.
Join our webcast, on April 7th at Noon Eastern Time, to see how to mine mountains of retail data to understand the characteristics of the best customers and get ahead of new patterns that are currently developing in the retail world, by using Consumer Insights and retail science.
Diginomica interviewed Jeff Warren, VP of Retail Solutions Management at Oracle Retail, at NRF 2020 and found that retailers are looking for an AI-driven assortment and price strategy. With the launch of Oracle Retail Consumer Insights, AI in retail is no longer just a buzz word.
Learn how by taking owned customer data and bolstering it with third-party contextual intelligence, Oracle Retail Consumer Insights helps retailers fully appreciate who their most loyal, profitable, influential customers really are and move to the next practice in identifying potential customers that possess similar attributes.
Retail success relies on understanding customers. See how the new Oracle Retail Consumer Insights solution provides an unprecedented level of insight for retail marketing teams seeking to better understand existing customers and optimize new retail customer acquisition campaigns.
Retailer scenarios on the impact of returns on price optimization using AI in retail and machine learning approaches for forecasting returns, OLS regression, Logistic regression, Random forest, Gradient boosting and Neural networks from the Oracle Retail Science team.