Narrow net margins and a highly competitive environment constitutes the industry of retail and marketing. Huge amounts of data, especially within high-frequency online retail, makes this an ideal landscape for AI. Intelligent planning and operating systems can help companies enhance their capabilities and small efficiency gains can translate into big net income results and competitive advantages.

The value of AI in retail is magnified, however, it will not replace employees. It will alter their role and augment human capabilities. Implementing AI and ML systems can assist merchandise planners by taking over planning tasks and similar autonomous tasks across the supply chain and store operations. By processing huge amounts of data, AI systems can be developed to help sharpen promotions, prices, inventory allocations and improve customer engagement. This leaves employees with more time for useful and engaging tasks that require more creative thinking, making the best use of human skills and expertise.

The areas where the sector of retail and marketing can benefit from AI are ever-expanding.

Areas of AI application in Retail & Marketing

  • Customer analytics from acquisition to loyalty programs employs AI to a very large extent in order to optimize marketing actions while cutting down costs.
  • Personalizing customer experience through digitalization and customer behavior analysis is slowly becoming the norm for online retailers.
  • Predicting supply and demand is one of the applications heavily leveraging AI technologies as it impacts many parts of the businesses and helps reduce cost as well as manual labor.
  • Data-driven advertisement allows to efficiently target your online audience with relevant content taking into account factors like demographics, personal interests as well as the stage of the customer journey a specific user is at.

Use cases

Recommender system
Recommendation engines are very powerful tool to provide a personalized shopping experience for the customers
Lead qualification
Focus on acquiring the right customers is paramount to ensure low acquisition cost and high customer lifetime.
Inventory prediction – timing of purchases
Inventory depletion due to customer demand should be balanced by the purchase of new inventory.
Churn prediction – proactive measures
An algorithm defining which customers are going to leave, thus empowering marketing team to take proactive measures
Customer targeting
Running marketing campaigns for carefully selected customers can be automated, boosting ROI while minimizing marketing spends
Warehouse assignment
An algorithm processing shipment requests and assigning them to a warehouse based on its location and how the inventory fits the clients' needs
Price prediction
Determining the best price for a product by performing market analysis and product comparison will keep the company attractive for the customers
Demand forecasting – inventory
Anticipating future demand is important as inventory needs to be bought several weeks or months in advance.

Meet the senior advisor

Christian Villumsen

Christian Villumsen

Retail & Marketing, 2021.AI

Christian is a passionate Senior Advisor with 20 years of experience within the Fintech market. He has a proven track record in Fintech, Credit & Market Risk, Compliance, Project, Program, and Portfolio Management. Previously, he worked as a Director at Saxo Bank and spearheaded the Global Enterprise Risk initiative. in

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