Dynamic pricing

Our dynamic pricing solution is designed to help retail and insurance companies optimize their pricing strategies through the use of advanced AI and machine learning methods. Here are the key details of our offering:

Purpose and Goals Our dynamic pricing solution aims to empower retail and insurance companies by optimizing their pricing strategies to maximize revenue, margin, and customer satisfaction. The goal is to provide a comprehensive, adaptable, and efficient pricing model that responds to market conditions, competitive dynamics, and customer behavior.

Solution Overview Our solution employs a dynamic approach to pricing, leveraging AI and machine learning to set optimal prices for products. This approach takes into account numerous factors such as market dynamics, competitor pricing, seasonality, and customer characteristics. The core components of our solution include:

Data Processing: Efficient handling and processing of large datasets to ensure relevant and timely data input. Advanced ML Algorithms: Use of sophisticated machine learning algorithms to predict demand and set optimal prices. Optimization Algorithm: A comprehensive end-to-end solution that directly returns the optimal price by solving an optimization problem based on estimated demand curves and various constraints.

Key Benefits Our dynamic pricing solution offers several advantages:

Captures Non-Linear Relationships: Can capture complex relationships between price and demand, including issues of data scarcity. High Accuracy: Provides higher accuracy in price setting by considering a wide range of factors. Direct Results: Eliminates the need for additional processing, delivering direct and actionable pricing recommendations. Customization: Tailors the pricing model based on company-specific requirements and circumstances. Commercial Offering Our business model is centered around a modular accelerator that serves as an implementation project rather than an end-to-end product. Key aspects include:

Cross-Functional Team: We provide a team capable of handling end-to-end development, which can be integrated with the client's internal team. Pre-Built Accelerators: Utilize pre-built accelerators to expedite deployment and integration. Flexible Pricing: Time and material (T&M) consumption or fixed-budget options Proven Track Record: Reference projects, such as our work with a pharmacy chain, demonstrate our ability to deliver significant revenue and margin improvements.

Engagement Model Our engagement model typically follows these steps:

Proof of Concept (POC): Initial development of a demand model using our accelerators to evaluate price elasticities. Minimum Viable Product (MVP): Development of an end-to-end solution generating prices ready for production deployment. A/B Testing: Design and execution of test deployments to measure and evaluate results. Roll-Out: Full deployment of a robust pricing solution across the client's operations.

Accelerators We offer several accelerators to speed up the development and implementation process:

Dynamic Pricing Best Practices: Knowledge base and detailed architecture of our AI dynamic pricing approach. Demand Forecasting Accelerator: Facilitates the development of time-series based use-cases, enhancing data preparation and model integration. Data Platform Infrastructure Accelerator: Enables quick deployment of complex multi-provider systems, allowing data teams to focus on use-case development rather than infrastructure provisioning.

Our solution integrates various data sources and ensures real-time pricing adjustments, providing a comprehensive and competitive edge in dynamic pricing for retail and insurance sectors. By deploying our solution within the client's existing Azure platform, we ensure transparency, security, and control, empowering clients without vendor lock-in