Give me something and I’ll give you something. The exchange of money and goods is quid pro quo. But in the era of social media, customers can also pay in a different way: with their behavior, for example. A hotel in Miami is lighting the way in this regard. Life House has opened its first two hotels in Miami. Guests can book a room there in the same way they would at any other hotel. As an alternative, they can make sure to keep their room tidy, consume little electricity and share their great hotel experience with their friends on Facebook and Instagram. On their next visit, this has a magical effect on their bill. They pay less than other guests.
Social pricing for the younger generation
The advantage for the hotel: while most hotels treat their sophisticated regular customers best, Life House rewards those who behave as desired. The more room service they order and the more they book excursions through the hotel, the more discounts they get. After all, they are making themselves visible. In this way, anonymous guests become guests with personal profiles. First, Life House founder Rami Zeidan uses the information collected to determine the actual value of a guest using an algorithm. Secondly, this information is used to make the guest even more personal offers during their next stay. And to ask them to pay on a very individual basis. Scott Berman, Partner at PricewaterhouseCoopers Hospitality & Leisure Group, refers to the hotel’s sales strategy as “next generation” in the Wall Street Journal.
Individual pricing strategies are even making headway in Germany. Many hotels have invited influencers to write about their visit in the past. This strategy was not always successful, as sometimes no reporting took place and sometimes the smell of surreptitious advertising was just too strong. It therefore makes much more sense to motivate real guests to report on social media. Some are already doing this but without strategically rewarding the social super-guests. “Hotels are increasingly looking at how many followers a guest has,” observes Marcel Hollerbach, CMO at Productsup. Price reductions for this are often indirect—in the form of an upgrade to a larger room, for example.
Purchasing power and the motivation to buy: determining the right price using hard facts
E-commerce is also used to evaluate customers in different ways and to offer them products and prices that suit their specific needs. Instead of the factor of social behavior, the motivation to buy is used for this. One example of this is flight and travel portals. “They base their prices on how motivated a customer is to travel,” says Hollerbach. Such pricing strategies lead to rising sales.
Retailers require a consumer’s personal data, as this provides insight into their willingness to pay. This includes, for example, the hardware and software used, socio-demographic data such as age or gender, as well as previous buying and surfing behavior. These things can be determined using the user’s “fingerprint” in the form of a cookie or their IP address. This makes it possible to determine which user is involved and when they last searched for the trip. “The user can only trick the sales algorithm by logging in from another browser,” says Hollerbach.
Location coordinates can also be used to determine the perfect price for the consumer. Instead of focusing on the individual user, the emphasis here is on determining their belonging to a certain group of consumers. For example, prices may depend on one’s occupation or place of residence. Depending on where a user is, they will be offered the respective price. In a richer city like Munich, for example, the price is higher than in a smaller city with a lower per capita income.
Social reward systems meet sociodemographic behavior
The individual pricing strategy is also suitable for brick-and-mortar shops. Digital price tags are already being used in stores for so-called “dynamic pricing”. This is used to adjust the price of a product to current market conditions. Items can be discounted to be sold faster. Or the price can be reduced within the context of a local marketing campaign. But these prices are not personalized. Not yet. Hollerbach takes a look to the future: “If digital price tags could recognize a customer’s membership in a bonus program, the retailer could suggest individual prices.” Purchasing behavior and the points they collect would provide the basis for this. Social reward systems and sociodemographic behavior would therefore be combined.
The bottom line:
Whether social or sociodemographic, dealers have options for asking different customers to pay different prices. And more and more strategies are being devised to do this. It is important, however, that consumers do not get the impression that they are being spied on, as is the case with the Chinese Social Credit System. This would not work in Germany anyway. For example, the Klout score was killed off not least because of the General Data Protection Regulation (GDPR), which took effect in May 2018. This score was used to indicate the influence of social media users. It is therefore better and more GDPR-compliant to only use data that is required for evaluation in a clearly defined area.