Leveraging AI for dynamic pricing

Using AI for dynamic pricing can help businesses make profitable decisions by accurately gauging the price to be displayed to the customer that can guarantee a purchase.

Dynamic pricing, also called real-time pricing, is an approach to setting the cost for a product or service that is highly flexible. The objective of dynamic pricing is to adjust the price of a particular product in such a way that it results in the customer buying the product and at a price that is the most profitable for the company. Airline companies and e-commerce players use dynamic pricing to show different prices for the same product depending upon the customer. However, businesses can face the issue of low conversion rates if the price is not set right. Similarly, businesses try to fluctuate the price frequently to attract the customer, but this can prove counterproductive as the customer can keep waiting for a long time for the price to reach his desired amount. The use of AI for dynamic pricing aims at setting the price in such a way that it has a high chance of product sales in the first instance.

Reading the customer’s mind by using AI for dynamic pricing

Artificial intelligence can help understand the customer’s preferences, such as the products they are interested in, the time of the day they are most likely to buy, and the maximum price they are willing to pay for a product. The application of AI for dynamic pricing is as follows:

Creating customer groups

Artificial intelligence can help with customer segmentation. It can help businesses divide customers into groups based on their broader preferences but still having slight variations. For instance, e-commerce businesses can use AI algorithms that can analyze data such as internet search preferences, social media activity and collate data from other sources such as the individual’s activity on a competitor’s website to sort people into groups. All the data collectively combined, also can be referred to as big data, can help provide a better understanding of homogenous groups. These groups help businesses with accurate customer segmentation, which can be utilized for dynamic pricing.

For example, big data can be used to sort customers into two groups regarding their mobile phone preferences. They can be placed into Android or Apple users based on their historical data. Thus, the business can use customer segregation to show individuals only their preferred products. This can help retain customers on their website for long periods.

Understanding unique preferences

The individuals can be further divided into subcategories based on their individual preferences using AI tools. The algorithm can analyze the search and buying patterns of the individual, the time and day they spend on the purchases, and the price they are willing to pay for a particular product. Additionally, the AI algorithm can analyze the previous purchase history of the individual to price the product in a manner that can result in a purchase from the individual and fetch the business the maximum price.

For example, if an individual searches for products at weekend nights online, an e-commerce business can use this data to send notifications about products the individual is interested in, during that particular time. Similarly, the product can be priced according to the purchase history of the individual for the same product or similar products. This can increase the chances of the individual buying the product.

Using AI for dynamic pricing can help improve the chances of sales for businesses, thereby increasing their profits. They can get more precise at displaying prices to individual customers that can guarantee a purchase. The technology provides long term benefits for businesses as individual user data increases with time, and the system improves in predicting what price is right for the customer.