Manthan Introduces AI-Powered Prescriptive Pricing Enabling Intelligent Pricing Decisions
Manthan enables retailers to intelligently price products based on AI-powered insights and in alignment with their business objectives.The solution prescribes the optimal price for every product and accelerates execution of price changes.
Manthan, a global leader in AI-powered analytics solutions and a recognized innovator with a deep focus on new age technologies such as AI, ML and NLP, introduces another trendsetting utility for retailers in the form of intelligent pricing. Manthan’s latest innovation is a path-breaking algorithmic price optimization solution that aligns business objectives with everyday pricing decisions.
The science of understanding variables that impact pricing, and predicting the optimal price that aligns with business objectives is complex. It involves extracting insights by analyzing a variety of internal and external data including demand patterns, sales data, customer data, shopper behavior indicators, event history, promotional data, inventory data, seasonal data, weather data, and so on. Leveraging these insights to derive optimal pricing for each product, at scale increases the complexity manifold. Not only is the process time and effort intensive, it is also a challenge to predict the outcome of the price change with accuracy.
The prescriptive pricing solution from Manthan simplifies this for business users by analyzing business context, processing millions of data points, slicing and dicing data using powerful AI and machine learning algorithms and automatically providing accurate pricing recommendations. For instance, a category head who may be experiencing a shortfall in sales can aim to reverse the trend and meet sales targets by optimizing pricing or offering a 'price off' for products across regions, channels and store groups, for a limited period to boost sales.
Once the objective is specified, the solution automatically analyzes all the relevant variables like existing inventory, demand, sales trend and past purchase. It also estimates price elasticity using historical demand and price variations. Based on the context, the system calculates short term demand using the price elasticity, seasonality, promotional details and other relevant data points, for a given price and recommends the optimal price for each SKU, across channels. The system will also surface outcomes like, potential sales uplift and margins for the recommended price change.
Additionally, the solution provides business users with the flexibility to simulate other outcomes easily and make the most appropriate decision to meet the stated objective. It also helps accelerate execution of price changes by automating work flows and integrating with other enterprise systems. The application self-learns and adapts over time to improve outcomes and enhance the quality and accuracy of prescriptions.
“With AI and ML, the system can analyze varied business contexts, historical impact of price changes and evolving customer scenarios to recommend optimal pricing. This is a big step forward in the way retailers make pricing decision,” said Seema Agarwal, VP & Head - Retail Analytics, Manthan.
Manthan will be showcasing its prescriptive analytics solutions at booth #4311 of the National Retail Federation (NRF) Annual Convention and Expo at the NY, between Jan 14-16. Please Click here to book an appointment with our best in class retail analytics experts, schedule video demonstrations and interactions.