Machine Learning in Retail

The pressures of retail are extreme. Retailers have empowered consumers with increased expectations. There is a need to have accurate forecasts and inventory to deliver the right customer at the right time with maximum operational efficiency. Retail is transforming through the use of machine learning.

Knowledgeable Consumers

  1. Predict next customer CRM state (e.g. Active, New, Churn, Re-Active) to inform the strategy of future marketing comms
  2. Utilize survey data to determine sentiment across your entire customer base
  3. Predict number of days for next order
  4. Discover the most effective product to show each customer based on customer behavior
  5. Attribute the value of digital marketing spend appropriately across the right channels/campaign

Product and Supply

  1. Machine learning Forecasting: using a range of historic data sources to inform the level of future demand
  2. Forecast returns: Predict the probability of return  for every item purchased through all channels
  3. On-shelf availability: drive corrective action by inferring potential lost sales situations at the earliest opportunity by SKU
  4. Promotions: Discover the best promotion strategies for the best SKUs helping you to achieve targeted revenue or volume
  5. Price Optimization: learn the optimal price points influenced by a multitude of factors

Operational Efficiency

  1. Pinpoint the best sites (to open, expand, reduce, or close) based on strategic goals without cannibalization of existing store sales
  2. Forecast staffing needs for fulfilling orders, customer service, shipping as demand changes each day
  3. Improve by minimzing the time to deliver a shipment
  4. Predict channel volumes: e.g. call center or in-store footfall. Helps to predict staff resources required for any given trading day
  5. Determine how much staff you will need based on foot traffic for any given calendar day

Want to learn more how machine learning can transform your retail business?

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