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Using ANAI, citizen data scientists and other developers with limited machine learning expertise can easily ingest data, generate insights and build/train ML models.
Build AI-based recommendation engines for consumers to get product recommendations as around 91% of the consumers are more likely to place an order after getting a relevant recommendation.
Automate and optimize warehouses for better product movement and tracking to increase efficiency and ultimately improve the customer experience.
Predict demands by training ML models on the past data and letting it forecast for the future through time series analysis leading to a better demand prediction and preparation for it.
Optimize prices using past user data to give better deals to each and every user to increase user engagement and chances of the user placing an order.
The right metric to look at can be a difficulty and might lead to building models which are irrelevant to the use case.