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Towards Uberization: Balancing demand, supply and trust

“You get what you pay for.” But like many an oft repeated phrase we already know that there are exceptions to the rule. Why else would we hunt out bargains? Or wait for the sales to begin? We already know that the person sitting next to us on the flight almost certainly paid a different price to us.

Variable pricing isn’t new, but it is now becoming much more data-driven. You might expect a flight to get more expensive as the number of seats fill up, and cheaper if there are still seats left as departure approaches, but you might be surprised that you’re paying a different price in the middle of the week compared to the weekend.

Balancing supply and demand

We expect prices to fluctuate as a principle of free markets. Higher demand drives up prices which can incentivize, although doesn’t always deliver, an increase a supply. Likewise, oversupply drives prices down. Trust is a fundamental enabler in this balance, and is a value very much integral to how Thomson Reuters does business and the role that we play in enabling transparent markets.

Data, or to be more specific the increase in readily available, frequently refreshed data means that the price, and the balance of supply and demand can adjust much more rapidly than before. And like the example of the variable price of flights, dynamic pricing is driven by both the principles of enabling a free market, and the commercial opportunities that come from better understanding what we are willing to pay at any given moment. This might be driven by the weather, what a competitor is charging, how your sports team is performing or any number of other drivers. Behavioural insights can drive choices, spending and, ultimately, loyalty.

Nobody likes paying more than they think they should and, in the press at least, nothing sparks debate and opinion more than “Uber’s mysterious surge pricing algorithm.” In spite of the algorithmic approach to pricing, Uber is also not averse to intervening to mitigate in unusual situations, such as limiting price hikes during New York’s recent snowstorm, or offering free rides after surge pricing stayed in place in the midst of a hostage situation in Sydney.

Transparent pricing and Uber

Uber’s surge pricing is not a unique approach. And as they explain, they take great pain to be transparent about when it is in effect and what its impact will be, and to give their users alternatives such as being alerted when pricing returns to normal. This approach is being noticed and alongside those that complain about surge pricing, there are others who acknowledge that you are always made perfectly aware what price you are going to pay. But if the objective of the differential pricing is to get more drivers on the road, then this article by the Washington Post reports a different effect, shifting drivers from adjacent areas and leading to longer waiting times in those areas.

Uber does not surge prices to make money, according to Garrett van Ryzin, Head of Dynamic Pricing Research at Uber, and Professor at Columbia Business School. Speaking as part of the Data Science Insights series at Imperial College, he also sees the potential for the same model to change pricing strategies in other industries. With Uber having sought patent protection for its pricing algorithms, that opens up ways in which they might look to benefit from the growing trend of “Uberization.”

Platforms and the Uberization phenomenon

One way in which Uber is different to others implementing dynamic pricing is that they are a platform company – the means to connect supply and demand without any direct means of controlling supply. They don’t own any cars! It’s an attractive approach, particularly for tech start-ups who see an opportunity for the “Uberization of everything.” But it does make it difficult to build that trusted brand when you are reliant on the incentives you give to those using your platform, both as customers and suppliers. In a balanced approach, an open platform can see offerings from suppliers sitting alongside those from the platform provider. App Studio in Thomson Reuters Eikon is one example of that. Fulfilling a customer’s expectations is not solely achieved by others building on the platform but rather enhances what is already there.

Since we are pre-disposed to expect to “get what we pay for,” those businesses hoping to “Uberize” will need to think carefully about how trust is built in that value equation.


Learn more

Visit Innovation @ ThomsonReuters.com to learn more about how we are pairing smart data with human expertise and how you can get involved.

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