A number of famous Business Schools in the UK and US such as MIT Sloan, NYU Stern and Imperial College have launched new programmes in business analytics. These courses have been nicknamed ‘Big Data finishing school’. Why might qualifications in this area be highly valued by firms?
Employees who have the skills to collect and process Big Data might help firms to successfully implement a pricing strategy that approaches first-degree price discrimination.
First-degree price discrimination is where the seller of a product is able to charge each consumer the maximum price he or she is prepared to pay for each unit of the product. Successfully implementing this type of pricing strategy could enable a firm to make more revenue. It might also lead to an increase in economic efficiency. However, the strategy might be opposed on equity grounds.
In reality, perfect price discrimination is more of a theoretical benchmark than a viable pricing strategy. Discovering the maximum amount each of its customers is willing to pay is an impossible task for a firm.
It may be possible for some sellers to implement a person-specific pricing strategy that approaches first-degree price discrimination. Firms may not be able to charge each customer the maximum amount they are willing to pay but they may be able to charge different prices that reflect customers’ different valuations of the product.
How could a firm go about predicting how much each of its customers is willing to pay? Traditionally smaller sellers might try to ‘size up’ a customer through individual observation and negotiation. The clothes people wear, the cars they drive and their ethnicity/nationality might indicate something about their income. Second-hand car dealers and stall-holders often haggle with customers in an attempt to personalise pricing. The starting point of these negotiations will often be influenced by the visual observations made by the seller.
The problem with this approach is that observation and negotiation is a time-consuming process. The extra costs involved might be greater than the extra revenue generated. This might be especially true for firms that sell a large volume of products. Just imagine how long it would take to shop at a supermarket if each customer had to haggle with a member of staff over each item in their supermarket trolley!! There is also the problem of designing compensation contracts for sales staff that provide appropriate incentives.
However the rise of e-commerce may lead to a very different trading environment. Whenever people use their smart phones, laptops and tablets to purchase goods, they are providing huge amounts of information (perhaps unconsciously) to the seller. This is known as Big Data. If this information can be effectively collected and processed then it could be used by the seller to predict different customers’ willingness to pay.
Some of this Big Data provides information similar to that observed by sellers in traditional off-line transactions. However, instead of visual clues observed by a salesperson, the firm is able to collect and process far greater quantities of information from the devices that people use.
For example, the Internet Protocol (IP) address could be used to identify the geographical location of the customer: i.e. do they live in a relatively affluent or socially deprived area? The operating system and browser might also indicate something about a buyer’s income and willingness to pay. The travel website, Orbitz, found that Apple users were 40 per cent more likely to book four or five star hotel rooms than customers who used Windows.
Perhaps the most controversial element to Big Data is the large amount of individual-level information that exists about the behaviour of customers. In particular, browsing histories can be used to find out (a) what types of goods people have viewed (b) how long they typically spend on-line and (c) their previous purchase history. This behavioural information might accurately predict price sensitivity and was never available in off-line transactions.
Interestingly, there has been very little evidence to date that firms are implementing personalised pricing on the internet. One possible explanation is that effective techniques to process the mass of available information have not been fully developed. This would help to explain the growth in business analytics courses offered by universities. PricewaterhouseCoopers recently announced its aim to recruit one thousand more data scientists over the next two years.
Another possible explanation is that firms fear a backlash from customers who are deeply opposed to this type of pricing. In a widely cited survey of consumers, 91% of the respondents believed that first-degree price discrimination was unfair.
Articles
Big data is coming for your purchase history – to charge you more money The Guardian, Anna Bernasek and DT Mongan (29/5/15)
Big data is an economic justice issue, not just a Privacy Problem The Huffington Post, Nathan Newman (16/5/15)
MIT’s $75,000 Big Data finishing school (and its many rivals) Financial Times, Adam Jones (20/3/16)
The Government’s consumer data watchdog New York Times, Natasha Singer (23/5/2015)
The economics of big data and differential pricing The Whitehouse blog, Jason Furman, Tim Simcoe (6/2/2015)
Questions
- Explain the difference between first- and third-degree price discrimination.
- Using an appropriate diagram, explain why perfect price discrimination might result in an economically more efficient outcome than uniform pricing.
- Draw a diagram to illustrate how a policy of first-degree price discrimination could lead to greater revenue but lower profits for a firm.
- Why would it be so difficult for a firm to discover the maximum amount each of its customers was willing to pay?
- Explain how the large amount of information on the individual behaviour of customers (so-called Big Data) could be used to predict differences in their willingness to pay.
- What factors might prevent a firm from successfully implementing a policy of personalised pricing?
Merlin Entertainments PLC is one of the largest operator of visitor attractions in the world and owns over a third of the most popular theme parks in Europe. It runs the four most visited parks in England – Alton Towers, Legoland Windsor, Thorpe Park and Chessington World of Adventures as well as the most popular theme park in Italy – Gardaland. Alton Towers alone had 2.5 million visitors in 2013. Anybody thinking of going to one of these attractions is faced with a wide range of different entry fees .
Theme parks and tourist attractions have market power so their owners have to make some interesting pricing decisions. They have to tackle the same dilemma that confronts any seller that faces a downward sloping demand curve for its goods/services.
One option for the firm would be to increase the entry fee. This would produce higher profits per visitor as some of the surplus from the transaction previously enjoyed by the consumer will be extracted by the seller and converted into producer surplus. Unfortunately for the business the higher price, all other things equal, will also result in fewer visitors. Some people will be deterred from visiting because of the higher price and the seller will lose out on potential revenue.
An alternative strategy would be for the theme park to reduce its entry fee. All other things equal, this will increase the number of visitors. However, it would also mean that the profit per customer would fall. The frustrating issue for the seller is that some of its customers, who would still have visited the attraction at the higher price, are now able to get a better deal.
This dilemma exists if the seller has to charge all of its different customers the same entry fee. If it could charge a higher entry fee to those customers who would be willing to pay more and a lower entry fee to those who would be willing to pay less then it could make more money. Extra revenue could be obtained from those additional sales that take place at the lower price while more consumer surplus could be extracted from those still paying the higher price.
Is it possible for a firm to charge different prices to different customers for the same or a similar good or service? Table 1 below shows the entry fees for Warwick Castle, another tourist attraction owned by Merlin Entertainments PLC.
It can immediately be seen from this table that some groups of customers pay a different entry fee from others. For example adults have to pay £24 to enter on the day while people aged 60 and over pay a lower price £16.80. The entry fee for children aged between 4 and 11 is £21.00 while those aged 3 and under go for free. Students aged 16-18 can gain entry for a price of £13.50 if they can provide valid ID and purchase the tickets from the visitbritainshop website.
In this example, the company has allocated people into different categories by age (i.e. senior, adult, student, older children and younger children) and has set the entry fee that customers in each group have to pay.
The table also shows that if customers purchase on- line then they can get the tickets more cheaply. The entry fee for each category is 25% lower if the ticket is booked seven days in advance i.e. the prices shown in the last column in the table. If the booking is made between 2-6 days in advance then the discount is only 10% i.e. an adult ticket would cost £21.60. The on-line discounts are open to everyone. People are given the choice to either book on-line in advance or pay on the day. This is different from a situation where you are placed into a category by the firm. For example the customer cannot choose whether they are over 60!
If people are prepared to spend more time searching on the internet then other cheaper prices can also be obtained. Once again these offers are open to anyone willing to spend the time and effort in order to find them.
All the ticket prices above give people access to exactly the same attractions on the day. They do not give the visitor access to two of the attractions at the castle – the Dragon Tower and Castle Dungeon. Entry to the Dragon Tower would cost an adult on the day an extra £1.80 while entry to the Castle Dungeon would cost an extra £5.40.
Warwick Castle Ticket Prices Warwick Castle (accessed on 04/09/14)
Alton Towers Alton Towers (accessed on 08/09/14)
Warwick Castle Tickets visitbritainshop (accessed on 02/09/14)
Global Attractions Attendance Report teaconnect (accessed on 05/09/14)
Merlin Entertainments Merlin Entertainments (accessed on 08/09/14)
Questions
- What pricing decisions do firms have to make if they operate in a perfectly competitive market?
- Explain why an individual tourist attraction will have a downward sloping demand curve
- Paying an entry fee and an extra payment per attraction is known as what type of pricing? What advantages does this type of price strategy have for the seller?
- How would you calculate the profit per customer? What factors other than the entrance fee would determine the profit made per customer in a theme park or tourist attractions?
- Paying a different price depending on which category you have been assigned to by the seller is known as what type of pricing strategy? Can this type of pricing strategy ever be in the interests of society?
- In the example used in the case, customers are assigned to different categories by age. Can you think of any other ways that firms could categorise their customers?
- Given the category customers have been assigned to they can pay different prices depending on whether they buy the tickets on line. What is the price strategy called when customers can choose from a variety of pricing options for the same or similar product? Can you think of any different methods that could be used by the seller to carry out this type of pricing strategy?
As students, many of you probably have a student identification card, which you might use when you go to the cinema or when you buy something in a shop offering student discounts. Your parents or grandparents, if they are 60 or over, may get similar discounts, and your younger siblings or nieces and nephews may pay nothing for certain services.
It doesn’t cost a cinema more to provide a seat for an adult than it does for a child, a student or a senior citizen. So, why is it that firms can charge different groups of consumers different prices, even though they are consuming the same good or service? We are, of course, referring to the ability of a firm to price discriminate. The following short cases look at the concept in action.
Price discrimination: Russians get a discount Daily Markets, Mark Perry (12/10/10)
Theme park tickets and passes for Florida residents Walt Disney World 2010
Price discrimination: India and Disney World Daily Markets, Mark Perry (10/10/10)
Freedom’s just another word for getting a state subsidy The Economist (18/10/10)
Questions
- What are the different types of price discrimination?
- In the cases in the articles above, what type of price discrimination is being used?
- Illustrate this concept on a diagram and explain why a firm would use price discrimination. How will it affect revenue and profits?
- What are the key conditions needed for price discrimination to take place? In the cases above, why is it that British consumers are charged a higher price? What does this tell us about their price elasticity of demand?
- What forms of price discrimination (a) are being practised by US private universities and (b) being proposed in the Browne report for students at English universities?
- What other examples of price discrimination can you think of? Try and think of examples that fit into the different types of price discrimination.
A number of famous Business Schools in the UK and US such as MIT Sloan, NYU Stern and Imperial College have launched new programmes in business analytics. These courses have been nicknamed ‘Big Data finishing school’. Why might qualifications in this area be highly valued by firms? 
How could a firm go about predicting how much each of its customers is willing to pay? Traditionally smaller sellers might try to ‘size up’ a customer through individual observation and negotiation. The clothes people wear, the cars they drive and their ethnicity/nationality might indicate something about their income. Second-hand car dealers and stall-holders often haggle with customers in an attempt to personalise pricing. The starting point of these negotiations will often be influenced by the visual observations made by the seller.