Personalized pricing: will it work?
The personalization is what defines the business today. The automated solution helps enterprises to treat each customer as an individual. Some may use it for clients benefit, some will make the most out of the information moneywise. Which strategy will give the advantage in the long run?
The globalisation impacts to every part of the business. On one side globalisation caused the standardisation of the goods, creating extended clients profiles, re-modeling the services and many more, while it triggered the personalised approach to each of the clients on the other side. Using the Big Data companies have the access to the personal information like gender, income and education level, marital status and can even picture the lifestyle of the customer. Clearly, consumers get better-shaped customised products. At the same time, it has an effect of personalised and dynamic pricing. However, let's deal with one at the time.
The pricing strategy is essential to all businesses, as it is an excellent opportunity to boost the revenue. Everybody is acquainted with the supply-demand theory and the price equilibrium. Nevertheless, customers have different purposes of purchase various products and services and value them differently. For example, one may wish to pay for the plasma TV more than other. In this case if I am keen on movies and like spending time at home the value of the big and quality TV for me is higher than for the girl next door, who prefers to spend time outdoors and use her mobile phone to watch the movies. It is not a hard science to figure out for the companies that they can raise the price for me, and I will still buy the product. Thus, one type of the dynamic pricing is selling the same product with a different price for various groups of people. The concept is thin ice to walk on after Robinson-Patman Act of 1936 has described it as a "price discrimination". Some of the airline companies in states have been convicted for the price differentiation upon the groups. Nevertheless, it is hard to prove that the price discrimination took place on the basis of classifications such as gender, race, etc. The dynamic pricing based on groups can look pretty at first but will not serve the company well in the future. However, the loyalty benefits are the based on groups as well, but are completely legal and help to retain the client.
Moreover, if time is not everything, time is always money. The dynamic pricing by time is a usual technic used in a travel industry, for example. The season, time of the day, of the week, competition level on the market at the moment of the purchase affect the prices. Not only the airlines tickets, hotels, and travel agencies use it. In fact, Uber does not hide the dynamic rates it implements. Being remarkably transparent with the flexible charging system, the company published the pricing model and explained how it works to the customers. So-called "surge pricing" is affected by weather and the holiday seasons which accounts for only 10% of the Uber rides overall. Boston team noticed the undersupply of the cars on Friday's and Saturday nights after 1 AM, and they run an experiment increasing the rates on the weekends night motivating drivers to stay on the road till 3 AM. As the result, stating that the supply curve is elastic, the two-third of the unfulfilled requests were eliminated. The same pricing model was implemented through the company satisfying the demand while being the low-price leader.
So far the dynamic pricing is understandable by the customers and people can take an advantage of it. It is easy to predict that the price will rise with the demand and drop after the holidays, for example. This knowledge gives consumers some the flexibility and choice. The personalised pricing is different. It always existed and created the loyalty of the clients. It is the same technique as in the marketplace, but without the face-to-face integration. E-commerce already fully implements the personalised pricing algorithms. The only thing needed is the smart data analysis. Once the customer's preferences are identified, the company can make the tailored discount offers. Let's take the Grammarly.com for example. Grammarly is a writing enhancement platform for students and writers. The company successfully determines who the potential client is and sends the personalised offers just in time. If the student is interested in service and enters the website, after the trial period he will get the offer to purchase the membership. Moreover, the student will get the personalised offer at the beginning of the study year motivating him to make a purchase.
Personalised pricing will be implemented by retail as well. In the connected future, the smartphone will share owners preferences with shops around. It will allow to get the customised offers from the clothing, grocery, well any store! Can you imagine getting an individual offer for that sweater you liked a week ago? "Hi, Susie, especially for you, the dress you tried last week with 20% discount!" and this update will blink when Susie is passing by the store.
It is critical to choose and implement the right pricing enhancement model correctly. No company wants the clients to feel unequal when it comes to price or quality of the product. At the same time, each of them desires the special treatment. Implementing any model always important to stay ethical and fair, as in the connected society is hard to maintain the information confidentially. Better be as transparent as possible, like Uber and Amazon, offering the best-personalised solution possible.
The Big Data analysis allows firms to created personalized products and offers. Individual pricing is what will come together with the tailored goods. Customers will start manipulating the mechanisms of dynamic pricing increasing the personal value while decreasing the costs. Therefore, the personalised pricing will take the important place in companies' strategies.