Price discrimination online
Last week, I used an example from agri-business to argue that start-ups can revolutionize online markets by using computer algorithms that allow for the real-time aggregation of both demand and supply, combined with perishability of the goods or services being traded. I pointed out that this could disrupt not only Uber and other firms in the ride-hailing business, but also other marketplaces for a variety of goods and services that are perishable.
Today’s online marketplaces focus on demand, and when demand peaks, use a mechanism called ‘surge pricing’ to price-discriminate among potential customers. The new algorithm I spoke of last week would also consider the supply-side of the equation, as well as how perishable the traded items are, and allow suppliers to bid against each other when trading in perishable commodities, for instance, rush hour rides, or phone models that are facing imminent obsolescence. A portion of the savings would then pass on to the consumer.
This week, I shall try to present the rationale that Bill Gurley, an investor in and board member of Uber, came up with some years ago, which he published on his blog abovethecrowd.
This post was written when Uber first began to use the surge pricing mechanism. At the time, Gurley raised several points to defend the strategy Uber had moved to with this pricing model, since the strategy had caused angst among customers and traditional competitors such as licensed cab drivers, and had led to increased governmental scrutiny around the globe.
In my opinion, Gurley’s analysis deviates from current experience, and hence helps build the case that I started last week—that a firm with the algorithms to upend dynamic pricing by online marketplaces might be the next ‘disruptor’.
While I will be using Gurley’s blog about Uber as a prime source for this analysis, its conclusions apply to all online marketplaces that have garnered significant market power over the last few years through internet-based platforms.
They use this newfound market power to dynamically adjust their prices based on demand. Using online tracking technology such as website cookies, they are able to price not just according to the time of day, popularity and season, but also on an individual basis according to how interested someone seems to be in the particular product.
Let’s consider a mundane example to make this clear. let’s assume you check the price of a flight from say, Bengaluru to Coimbatore, several times this week. This means that the online marketplace you are using has registered that you, as an individual, are very interested in that flight sector, and proceeds to dynamically adjust the price upward when you finally push the button to book your flight.
The first argument Gurley makes is that Uber is a marketplace and its drivers are all independent agents. This ignores the fact that experience across the globe has shown that drivers’ independence is only notional—ride hailing firms are rumoured to have the ability to place drivers in a penalty box and hence deny them access to the marketplace.
The second argument he makes is that his is a low-margin business, since the majority of the fare goes to the driver, and that the company only holds on to a minimum of the amount in order to run its infrastructure. This too is open to debate, since other ride-hailing companies such as Blacklane allow drivers to bid on rides and keep the difference between the fixed price that the customer pays for the ride, and what the driver bids for it.
Blacklane’s drivers recognize that the rides themselves are perishable commodities since riders want the car only at a specified time, not several hours before or after, and so vary their bids according to how badly they want the business.
He then makes the claim that the firm’s surge pricing affects a tiny minority of all Uber rides—less than 10% of trips—and that the firm is transparent about its dynamic rates. One will never know the true figure here, so let’s just accept that claim at face value. He ends by saying that the only real alternative to dynamic pricing is a ton of customers (yes, even 10% is a ton, by Gurley’s own admission) staring at screens that read “no cars available”, since the availability and reliability for all forms of transportation are under stress at that same moment in time.
He says that drivers ‘are people too’ and so it is too much to expect an individual to be excited about working precisely when the rest of us all want to travel. He asks, rather incredulously, whether the independent drivers should be more concerned about your needs, or those of their own family and friends. This defies common sense—it is precisely because the travelling public is not willing to drive (unlike public transport drivers who are) that the market even exists in the first place!
I know that by extending Gurley’s ‘ton and ten’ statistics to other businesses I am reaching out on a limb. However, if you would allow me the latitude to do so, it would seem as if new network orchestrators, who are bringing together isolated and fragmented participants with the use of the appropriate algorithms, have at least 10% of the existing market to play with. Even 10% of customers being price-discriminated against by online marketplaces in goods and services is a sufficient opening to allow new and scrappy competitors plenty of room to manoeuver.
These arguments hold true for a variety of businesses, and not just for Uber or other ride-hailing companies, that are based on online marketplaces that have disrupted traditional businesses and now use their new market power to alter prices dynamically as demand shifts up or down for their product or service.
It would seem that the problem with being a disruptor is that you, yourself, are open to being disrupted.
Siddharth Pai is a world-renowned technology consultant who has personally led over $20 billion in complex, first-of-a-kind outsourcing transactions.