Machine Learning Powered Solutions for Retail

Using Data for a Competitive Edge

The modern day retail landscape is incredibly competitive, with companies being compelled to make better use of consume data to achieve improvements to their sales and operations strategies.

Retailers want a better understanding of their current consumer behaviours, they want to be able to generate predictions on the data they collect to create meaningful and impactful outcomes.

Utilizing machine learning is one of the primary ways in which retailers are adapting to have a competitive edge.

While typically machine learning involves a high cost and time investment, PI.EXCHANGE's solutions allow technical and non-technical users to automatically build complete prediction machine learning pipelines and generate valuable predictions.

Use Cases

Powerful Retail Use Cases

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Customer Churn Prediction

Predict if A Customer is Likely to Churn and When

PI.EXCHANGE’s Customer Churn Prediction solution allows retailers to identify customers likely to churn in the future, giving them an opportunity to proactively address it ahead of time. Keep customers from churning and retain revenue that would otherwise be lost.

Predict churn probabilities for each customer

Increase customer loyalty and revenue

Decrease customer churn rates

Customer Lifetime Value Prediction

Predict Amount Spent By A Customer in a Given Period

PI.EXCHANGE's Customer Lifetime Value Prediction solution allows retailers to identify customers that will produce the most revenue over a given time period. Increase loyalty of customers that drive majority of revenue and gain an advantage over competition.

Generate CLV predictions for each customer

Determine revenue over a given time period

Increase loyalty among high-value customers

Demand Forecasting

Forecast Future Customer Demand

PI.EXCHANGE's Demand Forecasting solution allows retailers to identify future market demand, and gain a clear view of product quantities required. Maximize profit margins by reducing understocking and overstocking with optimal inventory management.

Identify product quantities required to meet future market demand

Reduce excess stock and stockouts

Maximize profit margins with optimal device and equipment inventory

Customer Segmentation

Group Customers Into Natural Segments

PI.EXCHANGE’s Customer Segmentation solution allows retailers to group customers into natural categories based on demographics, behaviour and preferences. Increase marketing effectiveness by developing targeted strategies.

Pinpoint groups of customers with similar identifying features

Develop effective targeted marketing strategies

Increase revenue with more efficient offerings