Companies that can target specific consumers in real-time based on factors including their current location, past purchasing history, and demographic information with strategic offers planned using pricing revenue optimization gain significant marketplace separation over companies that continue to use conventional retail marketing tactics. Mosaic brings world-class predictive ML analytics and model development capabilities to our clients in the retail sector, enabling them to be more data-driven in all facets of their business for a competitive advantage.
Retail executives need to think more like tech companies, using AI and machine learning not to just predict how to stock and staff their stores, but also to dynamically recommend products and set prices at the individual consumer level.
Meeting customer expectations is more difficult than ever, more and more of market share goes to companies who are able to perceive needs rather than react. Whether e-tailing or selling in brick-n-mortar stores, inventory planning is a promising area for predictive analytics,
In post 2 of 4 on biometric modeling, we discuss how sporting teams and goods manufacturers can segment their consumer base using biometric insights.
This is post 1 of a 4-part series focusing how data science can incorporate biometrics for sporting good manufacturers and professional sports teams.
Mosaic writes an in-depth view on the synergies between design thinking & data science. We also examine how these two disciplines can be used together.
Unsupervised learning approaches are very powerful when applied to customer segmentation.
Optimizing seasonal staffing and resourcing is a key challenge for many industries, especially when the exact timing of high-volume activity can change based on complex factors.
Mosaic was engaged by a leading hotel chain to assess the best way to predict future demand for hotel rooms across their various properties.
Retail inventory optimization is a great candidate use case to apply machine learning & deliver immediate business value.
In this whitepaper, we examine how different companies can attack the dispatch routing optimization problem using ML & AI.