USE CASES

Retail Analytics:
Demand Forecasting
 
Our client needed to quickly develop a forecasting engine that would lessen the adverse effects of risks by determining the demand for its products in the future. Demand forecasting is an estimate of sales during a specified future period based on a proposed marketing plan and a set of uncontrollable and competitive forces.
 
Our experts built a customized forecasting engine using a combination of traditional techniques and the latest machine learning algorithms such as neural networks, gradient boosting, and ensemble stacking. The engine was designed to improve over time through learning algorithms, rapidly adapt to the changing internal and external dynamics affecting sales, and handle massive amounts of point-of-sale data with minimal human intervention. 
 
Price and Sales Analytics:
Price Optimization and Value Engineering
 
Facing sales growth headwinds in a highly competitive industry, our client was looking to identify ways to drive growth through optimizing their pricing strategy. 
 
Our experts developed a multi-pronged approach to tackle this challenge: a) Developed price elasticity models to optimize prices for products, portfolios, and channels based on market conditions and target contribution margins, b) Established competitive price benchmarking strategy using insights from cross price elasticity, c) Leveraged customer's price sensitivity to recommend proper timing, frequency, and depth of both event-driven and ongoing markdowns, and d) Used discrete choice modeling to map out a long-term value-engineering pricing strategy in order to identify product attributes that represented the highest consumer willingness to pay yet lowest cost to produce. 
 
 
Marketing Analytics:
Sentiment Analysis / Voice of Customer
 
Our client had recently introduced a new product that wasn't performing as well as expected. They were searching for answers but needed to do this efficiently and quickly. 
 
Our experts conducted a sentiment analysis using keyword and natural language processing. Sentiment analysis is instrumental in social media monitoring as it allows us to gain an overview of the wider public opinion behind certain topics. Combining machine learning and artificial intelligence, our experts quickly helped the client understand the tonality of conversations (positive, negative or neutral);  and used opinion mining of followers on social media to get the picture of what people were talking about and how they perceived the new product. 
 

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