What are the principles and methods of personalized pricing strategy?

However, if we set a threshold: Bob only needs to pay 40 yuan for the first purchase, but it takes two weeks to get the goods. This threshold separates the value of watching movies from the value of movie content. Therefore, Lucy won't feel unfair: because Bob has to pay the cost of delaying the viewing time. At the same time, Bob is also very happy: he is willing to sacrifice the value of "watching movies at the first time" to save 20 yuan money. In this way, the video store can let Bob and Lucy buy at the first time, pay the highest price in their hearts, and be satisfied at the same time without any unfair feeling.

The future of personalized price

The failure of Amazon makes many people pessimistic about the application prospect of personalized pricing in e-commerce. Amazon itself said: "This method (personalized pricing) is stupid because it is easy to be found." They think that customers are more likely to impersonate low-priced payers on the Internet. When customers know that Amazon offers low prices to new customers, they register new users one after another, hoping to get lower prices.

Although there are few successful cases of personalized pricing in e-commerce field so far, it is undeniable that e-commerce websites have natural advantages in implementing personalized pricing compared with physical stores. They can collect a large number of rich customer purchase data, have mature personalized technology to identify customer preferences and willingness to pay, and can easily present different prices for different customers. For example, in physical stores, product prices are the same, and personalized pricing is mainly carried out by issuing coupons; But on the retail website, the prices of products do not need to be the same, which is convenient to present different prices to different customers.

As we mentioned earlier, one of the reasons why people are pessimistic about the application of personalized pricing in e-commerce is that customers can easily disguise themselves in the network, and they can get low prices by changing their vests. However, the premise of this concern is that customers can easily identify the mechanism of personalized pricing of merchants. Just like the price discrimination of airlines, the mechanism of personalized pricing does not only rely on simple principles, but gradually develops into a complex mechanism.

As mentioned in the previous example, "Victoria's Secret" once discriminated the price according to gender, but the latter mechanism has taken into account factors such as purchase history, enterprise inventory, product cost and promotion budget restrictions. Customers may easily know that pretending to be a male or a new user is profitable, but they can't know what kind of shopping history can get a discount on a product.

To say the least, even if customers finally know this mechanism, enterprises also provide a "threshold" for personalized pricing, so that customers can readily accept different prices.

Considering the inherent advantages of e-commerce and the increasingly complex pricing mechanism, we are optimistic about the prospect of personalized pricing in the field of e-commerce. In the near future, not only personalized pricing tools will be more widely used in e-commerce and other fields, but also the historical purchase data of customers will be shared by various e-commerce websites, so that enterprises can capture the changes of customers' willingness to pay more accurately and quickly. When customers buy fashion pioneer Chanel movies on Amazon and give them favorable comments, then buy chanel no.5 on perfume websites, the prices presented to them will be different from other customers. The price of goods on the website, just like air tickets, may change with every transaction of every customer every minute.

Combination of Location-Based Service (LBS) and Personalized Pricing

When you walk into Starbucks, location-based applications such as Foursquare and Shopkick allow you to "check in" on your smartphone. As a regular customer of Starbucks, Starbucks may provide you with a voucher of $65,438 +0 or free coffee. The "sign-in" of users using smart phones is not only a customer loyalty programs, but also can collect user behavior data. For example, merchants can use coupons or points to encourage users to provide more detailed information, such as what goods they bought or how much they spent when they checked in.

For example, the same two users come to Starbucks to buy coffee every day, but the time when they come to Starbucks is completely different from the drinks they buy: Tom buys a cup of American coffee every morning, and Susan buys a cup of lemon tea or China tea every noon. Then, the coupons offered by Starbucks should be different: we can give Tom a new coupon for uncooked coffee and Susan a coupon for boxed white tea. These users' behavior information can let merchants provide personalized electronic coupons for users.

With the rise of location-based service applications, merchants' understanding of consumers is not only about who spent how much money on what goods. LBS adds an important dimension of user behavior. Now we can know who bought what goods when and where and how much they spent. Beijing Bartender Training School can help us build a more comprehensive consumer interest and behavior map.

On this comprehensive interest and behavior map, personalized pricing and promotion for customers can effectively help businesses maximize profits and send the right discount information to the right consumers at the right time and place.