This is the third of a four-part series on Uber’s past and future. Today’s article focuses short-term tactics to improve Uber’s profitability.
- Why Uber May Never Be Profitable — June 2, 2019
- Are There Quick Fixes To Improve Uber’s Profitability? – June 3, 2019
- What Can Uber Do In The Short-Term To Reverse Its Steep Losses? – June 4, 2019
- Can Uber Ever Deliver The Transformative, Profitable Future That Its CEO Has Promised? – June 5, 2019
The previous article in this series concluded that quick fixes such as raising prices or lowering driver pay can not reverse Uber’s deep operating losses. However, there are
four business opportunities in the short- to medium-term where Uber’s superior scale could convey profit-enhancing competitive advantage: pooled ride services, loyalty programs, data monetization, and price discrimination.
1. Pooled ride services
In theory, pooled ridesharing should be a win-win proposition for riders, drivers, Uber, and the communities served because higher vehicle and labor productivity (measured by riders and revenue per trip) creates more value to share amongst stakeholders. As such, pooled ridesharing should yield lower fares for passengers (20-25% lower than UberX), higher pay for drivers, increased Uber profitability and reduced congestion and emissions per rider.
Moreover, Uber should have a competitive advantage in delivering its UberPOOL services, because the likelihood of finding matching routes for pooled ridesharing increases in direct proportion to the number of requested rides.
But in practice, UberPOOL has been a disappointment for Uber and other rideshare providers. A majority of passengers dislike pooled ridesharing because of the variability of service. Some passengers luck out, getting a solo ride at reduced UberPOOL prices. But it’s more likely that riders will be paired, with uncertain added time for passenger pickup and detoured routing. On top of that, conflicts amongst passengers can arise over loud phone calls, music or unwanted conversation.
Most drivers also hate pooled ridesharing because it adds considerable stress and travel time for little upside pay. Each UberPOOL ride is 2-3 times as likely as an UberX trip to involve miscommunication about desired pickup locations, inability to find parking to safely load passengers, and the possibility of circuitous routing. To add insult to injury, drivers are more likely to get low ratings from passengers on UberPOOL trips, which may lower their future ride assignments or bonuses. As a result, many drivers are inclined to simply refuse to accept UberPOOL trips.
There are downsides for Uber as well, since the company is on the hook to compensate drivers at the normal UberX pay rate, even if a solo passenger remains unmatched at the reduced UberPOOL fare. Nonetheless, Uber has tried valiantly, if unsuccessfully to leverage its scale to increase pooled rideshare demand. For example, Uber recently introduced a lower-priced Express POOL service, where passengers are asked to walk a few blocks to a designated location to speed up pickup times. While the company does not release official data on its pooled ride volume, it is believed to be below 20% in most major metro areas and not available in smaller locales.
Given the inherent logistical complexities and rider/driver resistance, it appears unlikely that Uber can leverage its scale advantage to significantly increase pooled ride demand.
2. Loyalty programs
Airlines learned a long time ago that frequent flyer reward programs can be a valuable (but expensive) way to build customer loyalty. Uber recently rolled out its own loyalty program, Uber Rewards, to all US customers. For every dollar spent on Uber, enrolled users earn points to ascend to different benefit tiers of the loyalty program. All passengers receive a $5 ride credit after accumulating 500 reward points. Higher spending yields additional perks, including ride cancellation penalty waivers, surge price protection, vehicle upgrades, free Uber Eats deliveries, phone support, and coming soon, ride credits for ebikes and scooters.
Lyft’s loyalty program is still under development, but Uber’s program should be more appealing, since it operates more services in more cities on which to accumulate and use ride or meal delivery credits. Moreover, Uber’s head start may help it lock in some early power users before Lyft can roll out its competing initiative.
Nonetheless, Uber should not expect a major profit improvement from its loyalty program. From a consumer perspective, earning a few free Uber rides every six months or so isn’t as enticing as the prospect of earning a free airline ticket to Hawaii over a similar time frame on an airline. The loyalty reward for UberX provides only a 1%-2% credit on future fares. At that level, for many consumers, the primary choice consideration will likely remain the speed and price between competing rideshare providers for any given trip – the very behavior Uber hopes to modify.
Uber’s loyalty program is also relatively expensive. Unlike airlines where the marginal cost of providing an otherwise empty seat to a reward passenger is close to $0, Uber is required to cover the full driver cost for every reward trip.
So while Uber Rewards is a logical and somewhat advantaged addition to Uber’s value proposition, it is unlikely to drive game-changing economics.
3. Data monetization
Uber collects a vast amount of data on its riders’ and drivers’ movements, and more recently, on customers’ restaurant orders as well. Lest there be any doubt about the value of such data, consider how Uber has deviously used this information for its own benefit in the past. Using one feature dubbed “God View,” Uber employees were able to track the movements of passengers (for all kinds of inappropriate reasons) without rider consent, resulting in an FTC privacy violation settlement. In another instance, Uber used a platform feature dubbed “Hell” to track the movements of drivers who also worked for Lyft. Armed with this insight, Uber was able to order and cancel trip requests from bogus Lyft accounts, and then quickly send real Uber ride requests to the aggrieved drivers, in the hope of gaining greater loyalty.
Fortunately, neither of these unethical practices is still in effect, and CEO Khosrowshahi has promised to “do the right thing” going forward. Nonetheless, there are more legitimate opportunities to exploit or monetize user data for Uber’s benefit. For example, Uber Eats has been able to recommend menu additions to its participating restaurant owners based on detailed analyses of customer food choices (albeit, so too have competitors).
Uber might also consider selling data insights from its massive database on customer travel patterns. The New York Times
reported that a growing number of companies sell, use or analyze locational data to cater to advertisers, retail outlets and even hedge funds seeking insights into consumer behavior. In one example, an advertising agency bought location data from a mobile phone tracking app to sell ad campaigns to personal injury lawyers targeting patients who recently visited hospital emergency rooms (without, of course, the patient’s knowledge or consent). There are undoubtedly other ways Uber could monetize its vast global locational database, in a market where sales of location-targeted advertising in the US reached $21 billion in 2018.
But with Uber’s fraught history of misusing customer and driver data, and the growing tech backlash against the unauthorized commercial sale of personal data, Uber is unlikely to risk further reputational harm pursuing this potentially lucrative, but legally and ethically murky business opportunity.
4. Price discrimination.
Rather than raising all prices uniformly, Uber could utilize price discrimination, i.e. charge each customer the price he or she is willing to pay for each trip.
Here’s a hypothetical example. Suppose two separate customers request an Uber ride from point A to point B at precisely the same time. Both are frequent Uber users, having taken hundreds of rides with the company in the past.
- Customer #1 has never turned down a requested Uber trip, even during peak periods, when surge pricing was in effect, from which it can be inferred that she is relatively price-insensitive.
- Customer #2 has frequently canceled ride requests, both in surge and non-surge conditions, suggesting he is a non-loyal price shopper, willing to switch to a better (cheaper and/or faster) offer on Lyft.
Suppose the “normal” price for this trip is $18, based on Uber’s pricing algorithm that factors in distance, congestion conditions, and driver supply and demand. But instead of charging both customers the same price, based on known past behavior, Uber charges Customer #1 $29 and Customer #2 $17.50. As expected, both customers accept their identical rides despite a 66% price differential.
For companies that charge all customers the same price for a given product, including Uber, consumer surplus – defined as the difference between the standard price and a customer’s willingness to pay − can be quite large.
For example, a recent study published in the National Bureau of Economic Research found that in 2015, Uber’s US consumer surplus was $6.8 billion. To put that figure in perspective, Uber’s global bookings that year were $10.8 billion, 50%-60% of which were in the US. So in essence, Uber has been leaving more money on the table (in terms of what consumers would be willing to pay for rides) than what they earn from their current uniform pricing policy.
For most companies, consumer surplus is an interesting construct, but irrelevant, because they simply don’t know each customer’s willingness to pay for every purchase.
But Uber has amassed billions of data points on customer behavior regarding under what circumstances (origin, destination, time of day, day of week, weather, etc.) and at what price ride requests were accepted or rejected. Data analytics and AI algorithms could be used to assign a price sensitivity score to each customer, giving Uber the opportunity to apply price discrimination in numerous situations. For example:
- Customer #3 has a track record of low price sensitivity. For the first time ever, he requests a ride from an airport in a city he’s never used Uber before. It’s a good bet that the customer is a visitor, and relatively unknowledgeable about local taxi/rideshare fares for this unusual trip. Price high.
- Customer #4 orders an Uber from home every Tuesday morning to the airport and again back on Thursday night. She has never canceled a ride request, regardless of price. It’s a good bet she is traveling on a business travel account, and so might be particularly price-insensitive. Price high.
The beauty of price discrimination is that for relatively loyal customers, Uber would have an asymmetric information advantage, not only over customers, but over Lyft as well. Uber could therefore quietly experiment with different pricing algorithms to find the optimal “break points” for premium price opportunities.
Uber’s rideshare bookings have grown fourfold since the 2015 study, suggesting that its US consumer surplus exceeded $25 billion in 2018. If Uber were able to capture just 20% of its consumer surplus through price discrimination, it would have earned profits of $2 billion in 2018, rather than losing roughly $3 billion.
It sounds almost too good to be true, and for a number of reasons, it probably is. For starters, there’s something particularly creepy about basing corporate strategy on systematically gouging the company’s best customers, even if they never found out. But they would
find out. All it would take is for a few customers to notice creeping price escalation, and verify their suspicions by cross-checking Lyft pricing on selected trips.
Word-of-mouth would undoubtedly spread virally through social media on suspected price discrimination and gouging, with consequent reputational harm and increased defection rates of the very customers Uber desperately hopes to retain. Uber could possibly mitigate its reputational risk by sweetening the perks for its most loyal customers (so in essence, they would be getting a better product at a higher price). Nonetheless, although potentially highly rewarding, price discrimination, would undoubtedly be perceived as inconsistent with Dara Khosrowshahi’s pledge that Uber is committed to “do the right thing” under his leadership.
In summary, none of the quick fixes or short-term profit improvement opportunities identified so far in this series are likely to reverse Uber’s unsustainable economics, for one of three reasons.
- The initiatives are infeasible or ineffective, given the realities of Uber’s business model (raise consumer prices, cut driver pay)
- The initiatives are legally or ethically inadvisable (acquire competitors to gain market power, monetize customer data, price discrimination)
- The initiatives should be pursued, particularly since Uber enjoys some competitive advantages, but the likely impacts are too small to materially reduce Uber’s operating losses (Uber Rewards, pooled ride services).
The final article in this series, to be published on June 5, 2019, explores the prospects for Uber to fundamentally change its business model and financial performance by realizing Dara Khosrowshahi’s long-term vision to become the “Amazon of transportation.”