Dynamic pricing or price optimization is the concept of offering goods at different prices which varies according to the customer's demand. The pricing of the commodity can be done on the basis of competitor's pricing, supply, demand and conversion rates and sales goals. The practice of Dynamic Pricing is being widely adopted in E-Commerce. Machine learning algorithms should be able to efficiently automate pricing decisions to maximize profits, as they can perform pricing decisions using sophisticated calculations and predictions, by putting all available data into perspective, and change their pricing strategy to best adapt to a dynamic environment. Dynamic pricing, a strategy which enables businesses to provide flexible prices for products and services is now catching on across hospitality, retail, travel and entertainment industry segments.
Travel planning can be time consuming and frustrating. With constantly fluctuating prices, securing the cheapest flights and hotels seems more like an urban myth. But it's not just big providers that may struggle with setting the right price. Airbnb hosts face the same uncertainty in how to set flexible listing prices in response to changing market demands. The fancy economic term for this dilemma is "dynamic pricing," and several startups, along with Airbnb itself, have tapped into the market.
IBM Dynamic Pricing enables merchandisers to create and optimize pricing strategies in real time to out-price the competition. This cloud-based offering automatically recommends an online retailer's optimal response. It combines web data, such as page views and cart abandonment--along with sales, inventory and the latest competitive pricing information--and uses pricing intelligence to recommend the optimal pricing action to achieve your business goals.
As IOT Data proliferates one of the game changing use cases which it enables is dynamic pricing. As assets get instrumented one can have usage based pricing of assets on lease. We are already seeing disruptions in pricing model in the automotive industry where sensor data which is a proxy for driving habits is fuelling usage based insurance premiums. Flutura has been working with Utility companies which is one of the industries in Industrial Internet/IOT category undergoing fundamental shifts because of deregulation and increased instrumentation of the grid. Pricing in the utility industry is a very crucial lever and there is a lot of headroom for Utility companies to innovate on their pricing levers using data science.