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.

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Knowledgeable Consumers

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

Product and Supply

Demand Forecasting with AI: leveraging data sources to inform future demand
Returns Lookahead: look at all channels and predict the probability of return from each
On-shelf availability: drive corrective action by inferring potential lost sales situations at the earliest opportunity by SKU
Promotion optimization: achieve targeted revenue and volumes with identification of the best promotion strategies by SKUs
Price optimization: learn the optimal price points influenced by a multitude of factors (e.g., item, brand, location)

Operational Efficiency

Pinpoint the best sites (to open, expand, reduce, or close) based on strategic goals
Fulfill orders, customer service, shipping as demand changes each day by forecasting staffing demand
Improve by minimizing the time to deliver a shipment
Determine how much staff you will need based on foot traffic for any given calendar day