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A key target for consumer goods companies is getting the right products in the right stores at the right time.
In this webcast we will showcase how you can improve product range and reduce out-of-stock incidents, using a combination of forecasting and product-recommendation techniques.
We'll take you through the process of building statistical models and combining the outputs into a report that advises sales reps on the order quantities they should be targeting, and the products which offer the best opportunity for the retailer to extend the product range.
What we will cover:
- Introduce the CRISP-DM process for analytics projects
- Discuss forecasting and recommendation methods and some of the considerations when choosing which models to use
- Consider how to evaluate the model, and monitor performance against the key business goals
Is it for you?
- Do you want to increase your sales and improve availability by making the most of the data you have available?
- Is your organization looking to become more data-driven and looking for opportunities to use statistical and machine learning techniques to deliver business value?
- Do you want to understand the process steps involved in analytics projects and see how they were applied in a real use case?