AI use cases WildFire implemented in marketing

Client: Small pharma company

Problem: A small pharma company wanted to increase the market share of their product. The following were their goals.

– Increased market share

– Increased revenue

– Increased profits

Our solution: We worked with their teams to collect all the data including current and future pricing, current market share, current and new distribution channels, competition data and other historic data. We built 3 different machine learning models which optimizes each of the above goals. The models were based on time series analysis using LSTM (RNN).

Results: These models helped their marketing teams to better focus on the different strategies which could help them achieve their goals.

Client: Large size bank

Problem: A large bank was looking to segment their customers based on historical transactions. They had following goal.

– Segment customers based on their past transactions

– Better marketing

Our solution: We worked with various stakeholders and their innovation team to process all the data and using machine learning was able to segment customers into different categories based on purchase history and other bank transactions.

Results: The bank was able to target their customers better with relevant offers and services.

 


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