I first found out about Luxe, an on-demand valet parking service, this summer in San Francisco as I attempted to figure out parking options for my daily ~20 mile commute into the city. Luxe is a mobile app which does exactly what it sounds like: you specify where you want your car picked up within specific city bounds, and a Luxe valet will meet you there to pick up and park your car on your behalf. The app will show you a picture of your valet with their estimated arrival time and their location. The trick is to request the valet before you get to your final destination, since Luxe will use your GPS location to try and match the valet’s arrival with yours, limiting the user’s wait time at their destination. After exchanging keys with the valet, s/he will drive your car to a secure lot. You can then request the car once you need it at the same or different location, or can pre-book your pick-up ahead of time. A valet will return the car to you, hand you your keys, and you’ll be on your way, with payment handled through the app. Pricing runs at $5/hour with a maximum of $15/day (40-50% cheaper than a traditional garage!), though prices can surge if demand is high (similar to Uber and Lyft).

Source: App Store description

Luxe’s low pricing scheme was the reason I tried it initially, but within a couple of weeks I noticed that my prices started surging regularly. That’s when I found Zirx, the second big player in this market, which provides essentially the exact same service as Luxe with a tweaked pricing model. Their pricing on average seemed a bit higher from Luxe’s base rate, but there was no surging. I began a pattern of checking both apps in the morning and selecting the cheaper option. It felt very similar to my normal interactions with Uber and Lyft, until I received a promotional offer from Zirx for a monthly pass at $250 (cheaper than my daily rate), which included unlimited valet requests and free overnight parking (normally an additional charge). I bought the pass and ended up staying with Zirx for the rest of the summer.

 $15 a day… do the numbers make sense?

While there are a handful of smaller players in the market, Luxe and Zirx have established themselves as the largest two players, both beginning operations in 2014. Both have raised significant amounts of funding from VCs; Luxe at $25.5M(1) and Zirx at $36.4M(2). Since launching in San Francisco in 2014, Luxe has found its way into U.S. nine cities and Zirx in seven cities, many of which overlap with. Additionally, both offer pricing in very similar ranges based on location. But one fundamental question remains: how do the economics of these companies work? Sure, $15 a day for a parking spot isn’t unthinkable in a garage at a monthly rate, but with additional costs of valets and insurance, the numbers seem suspect.

Luxe mentions they are often able to negotiate down the average $300 parking spot to roughly $250(3) by utilizing less popular garages, with monthly turnover per spot reaching up to 40-60x, resulting in a cost of ~$5 per park. Assuming the average valet makes about $20 an hour picking up and dropping off cars, and can turn two cars per hour based on my wait times in San Francisco, that’s another $10 in costs. We’ve already hit $15 per park, excluding the additional cost of car insurance covering the valets. It’s possible that valets can turn more cars per hour than I’ve assumed based on the density of requests in the area they are in and how far they are from a garage. It’s also possible that spots can turn more often. But, it’s probably safe to assume that most parks are currently making a loss (funded by venture capital), though negotiating power and better placement of valets in the future could help bring costs down and make the unit economics profitable at a later point.

At present, however, both Luxe and Zirx have offered add-on services to their valet offerings at slightly higher-than-market prices to supplement their valet income—oil changes, fuel-ups, overnight parking, and even a new “drive home” feature launched by Luxe to drive both you AND your car home, say, after a night of drinking. It’s a step up from Uber, where you’ll get home but your car won’t, though it’ll also cost you a good deal more ($25 plus $3/mile). A year after launch, Luxe’s CEO states that there had been 3.6K customer fuel-ups and 2.7K customer car washes(4) in total. But putting that in perspective, he also says there are “thousands of parks” per day(4), suggesting that almost 100% of parks are currently completed at questionable levels of (un)profitability based solely on the valet service.

 Even if the numbers eventually work, will there be a clear winner?

So here we have two companies with very similar business models, both fighting for nickel and dime, differentiating slightly through branding, pricing schemes including monthly passes, and a few different add-on services. Sounds an awful lot like something familiar: Uber vs. Lyft. With scale as a driving force behind success, can both Luxe and Zirx exist successfully in the same markets, or is this a winner-take-all opportunity? Let’s evaluate the marketplace.

  • Where is value being created? Luxe and Zirx create value for three primary parties: consumers, valets, and parking lot owners. Consumers are benefited from saved time, and Luxe cites that in the past year alone they have saved drivers 10 years(4). Valets are benefited by earning extra income via hourly shifts (similar to Uber drivers). Parking lot owners are benefited by being able to rent out spaces that were often underutilized.
  • Are there positive network effects? Indirectly between the three parties mentioned above, yes. With more users on the app, the service becomes more appealing for valets to join, and the higher the upside for a parking lot owner who is willing to rent out spots. But, higher volumes of individuals in each party don’t necessarily help others in that party. Additional consumers don’t really contribute value to existing consumers unless more valets join to keep service levels high, but more valets means fewer car turns and tips for other valets. And more parking spaces doesn’t help an individual parking lot owner, it just means more price competition. This is different from Uber, which only deals with riders and drivers.
  • Is this an undifferentiated offering? Yes. These companies are essentially providing the same service to meet the basic pain points of frustration and high costs around parking. Unless either company can truly evolve into a holistic car management operation with a significantly improved value proposition over the other, there’s not much else to compete on besides price and quality (e.g. low wait times).
  • Are there high multihoming costs? For the occasional user, I’d say no. I checked both apps regularly until I committed to a monthly pass with Zirx, and that too because I was using the service almost every day. For the average user who may only use the service a couple times a week, it won’t make a difference which provider they use as long as their car is safely parked. A strategic switch to targeting regular commuters with monthly passes is a path to improving stickiness, but it’ll be a race as to who can lock in consumers at the best price first.
  • How important is scale? As discussed above, indirect network effects are important and strengthened by scale. Unlike Uber of Lyft, however, the on-demand valet model doesn’t extend beyond city borders. Uber’s benefit is that it provides a consistent service across the globe with the same functional app. But Luxe and Zirx operate to help manage car ownership problems, and the average person owns a car in one city, not multiple. So at a city level, scale is important for profitability and operations and a first-mover advantage to capture limited parking spots is very important. But it’s entirely possible that Luxe could dominate one city and Zirx another, which questions why they currently overlap operations in many cities.

Overall, I don’t think this is a winner-take-all market, but I do think there will be a race to a clear market leader, and utilizing price will likely be a strong driver in getting there. Uber and Lyft have already been battling it out for several years, so Luxe and Zirx likely have a few more years of fight left in them. But, given the latest trends toward decreased car ownership (thanks to ridesharing) and autonomous vehicles, it’s unclear how relevant the parking problem will even be in upcoming years. Until that time though, Luxe and Zirx serve as an intermittent business model handling car problems of today, and I’m curious as to who will end up on top.


(1) https://www.crunchbase.com/organization/luxe-valet#/entity

(2) https://www.crunchbase.com/organization/zirx#/entity

(3) http://www.forbes.com/sites/forbestreptalks/2015/10/23/valets-on-demand-can-this-app-solve-our-parking-mess/

(4) https://medium.com/@curtisylee/luxe-a-year-later-241fbfed67c7

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By: Anju Somani

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Uber for X is all the rage. But can (and should) we try to apply Uber’s model to one of the world’s most stagnant institutions?


10 seconds. Maybe a little longer if you mistype your password.

That’s how long it takes to call an Uber. Through the app, you can see your driver’s name and rating; you can see the make and model of the car and track its approach; and you can even call if one of you gets lost. After the ride, payment is handled automatically and you can leave a review that helps decide whether the driver gets to continue working with Uber. All this at a fraction of the cost of taking a taxi.

If you’re reading this blog, you’ve probably already used Uber. Since 2009, Uber has grown into a $50B behemoth that offers its services in 300 cities in 57 countries.

Given its tremendous valuation, it’s no surprise that entrepreneurs and investors alike have rushed to support Uber-like models in other industries. Need an on-demand dog walker? Meet Wag. How about a mover? Try Lugg. Left your plane at home? There’s even an Uber for private jets.


For now, many of the above services are only relevant for narrow segments of the population. Sorry, Glamsquad, but the average American doesn’t need on-demand hair styling. But could an “Uber for X” startup work in a different type of business, perhaps one that could affect nearly every individual in the world?

As an education entrepreneur, I’m excited about the potential impact that Uber-like services (often labeled “on-demand mobile services” or ODMS) can have on the way we learn, from early childhood education to professional development.


How education has already changed

First, some context.


Don’t listen to the naysayers – education certainly has changed over the last century. In the 1950s, US classrooms focused almost exclusively on rote memorization. By the 1970s, they had begun flirting with the Open Classroom model. By the 2000s, schools were beginning to emphasize softer skills like the 4C’s: communication, collaboration, critical thinking, and creativity. Policies like No Child Left Behind have encouraged more standardized testing, and things like cursive, arts, and recess are mostly absent in today’s schools. Charter schools have transformed the public school landscape by allowing administrators to adapt organization, culture, and curricula to community needs. From a technology standpoint, educators are increasingly using online video libraries like Khan Academy to “flip the classroom” and software like Google Classroom to promote collaboration. Interactive whiteboards have replaced chalkboards in over 2.8 million K-12 classrooms globally. From a pedagogy perspective, 46 states have adopted national Common Core standards which emphasize a quicker path to literacy and deeper mathematical understanding.

Despite progress, in other ways education has been slower to adopt changes seen in other industries. Students don’t have individual learner profiles which follow them around from school to school and capture their strengths, weaknesses, and learning preferences (like electronic medical records in healthcare). We don’t really have a great sense of how to collect, analyze, and interpret student data (like we do for consumer data in e-commerce). Most learning management systems don’t have robust predictive algorithms to truly personalize learning (like the ones powering Netflix or Amazon’s recommendation engine).

So while education has changed somewhat, the pace of this change is remarkably slow compared to other sectors. Can we change education as swiftly and extensively as Uber is changing the taxi industry?

To figure this out, let’s:

  1. Break down Uber into its component parts
  2. Imagine what these components would look like when applied to education
  3. Identify education-specific challenges and way to overcome them


Component 1 – Two-sided platform which matches latent supply with unmet demand


A two-sided platform in education would connect educators who have excess capacity, with students who have unmet demand. Here, educators aren’t teachers in the traditional sense. Uber educators are anyone with the ability to help others learn a specific skillset. They may themselves be experts in the particular area they are teaching, or they may simply know how to help others become expertsin that area.

This looser definition of a teacher is relevant because the US is facing a nationwide teacher shortage, so latent supply for an educational Uber would need to come from other professions (e.g., engineers, writers, musicians). For starters, we could focus on the areas of education with the greatest supply/demand mismatch. Given the increased emphasis on STEM in schools and the increasing number of workers moving to the tech industry, matching experienced  tech professionals with students interested in technology could be one option.


Non-traditional teachers may not know how to teach – You could be the world’s foremost biologist, but that doesn’t necessarily make you more qualified to teach middle school biology. Teaching requires more than just subject knowledge – it requires an ability to connect with students, an understanding of pedagogy, and unbelievable patience, among other skills. Any two-sided platform in education needs to either properly train the supply side in effective teaching methods, or pair non-teachers with teachers to give students a solution that combines content expertise with teaching expertise.

Unions would fight back – Teacher unions are notoriously resistant to outside influences in the education system, which they fear could erode their power. And given teachers’ immense political clout, an Uber-like business in education would be prudent to figure out how to deal with unions before they are overburdened with regulations that stymie its growth. It could potentially position itself as a supplement, not competitor, to teachers, or perhaps employ the Uber approach of lobbying for regulations that fight against incumbents.


Component 2 – On-demand, mobile service

This actually has a few sub-components, so let’s examine each individually.


  1. Exactly what you need – Just like Uber gets you from point A to point B and does little else, an Uber for education should deliver exactly the educational content you need in bite-sized chunks. The best way to do this is to tie content to action-oriented outcomes. In other words, you want to learn how to do X? Let’s match you with someone who can teach you how to X. No more, no less.
  2. When you need it – In order for Uber to match every rider with a driver within minutes of opening the app, and to keep drivers close to full utilization, it needs to carefully connect supply to demand and ensure neither side outgrows the other. Students find that instruction is most effective when it is delivered when they need it most. Perhaps you can expand the capacity of individual educators by making it easier for them to serve multiple students at the same time, without sacrificing quality. And if we assume the teacher-student interactions can take place online, a supply of teachers located across multiple time zones can support 24/7 coverage.
  3. Where and how you need it – True on-demand learning means that students are taught wherever they are most comfortable, whether that’s at the library, in the classroom, or from home. They also need to be able to choose from multiple teaching styles (e.g., video lectures, problem sets, group projects) in order to learn in a way that best suits them. A service could either match specific teaching styles (e.g., expert video lectures) with specific learning preferences (e.g., student wants watch videos on the subway), or make it easy for an educator to convert a lesson into multiple formats.


Students may not be able to outline specific learning needs – What if a student is falling behind in algebra and wants general math help, instead of help with a specific algebra problem? Well just like you wouldn’t order an Uber without having a single, imminent destination in mind, Uber for education may not be right for students who can’t modularize their needs. Any viable service would most likely need to focus on specific, manageable chunks of education, either in the form of specific homework questions, learning objectives, or even tasks at hand (i.e., professional development). If students can’t break their needs up into chunks themselves, the service should be able to help.


Component 3 – High-quality, community-rated suppliers

Just like with Uber drivers, any teacher on the platform should be continuously rated and dismissed if their rating falls below a predetermined threshold.



It’s difficult for a student to gauge a teacher’s quality –It is arguably easier to assess the quality of an Uber experience than an educational experience, partly because preferred learning styles and speeds vary vastly among individuals. Instead of giving a rating on a single dimension, an educational Uber could ask for teacher ratings on multiple dimensions like content knowledge, patience, enthusiasm, etc., like AirBnB does by asking guests to rate accuracy, cleanliness, location, etc. The service could also periodically match teachers with “master teachers” and have them be rated more formally, much like they would be rated by an observer in a school.

Digital lessons aren’t as effective as in-person sessions– As anyone who has taken an online course can confirm, learning over your computer or phone isn’t always as engaging, and thus less effective, than learning in an actual classroom. An Uber-like service can mitigate this decrease in quality by focusing on subjects which can be augmented with technology, not ones where technology is just a medium for the interaction. For example, a physics teacher can easily send over simulations to students to help them understand tough concepts, or a programming teacher can do a quick code review with any number of digital tools – activities which wouldn’t be as seamless in-person.


Component 4 – Low cost

Uber keeps its prices to consumers low by paying drivers as contractors, not employees, circumventing a taxi monopoly which requires taxicabs to own highly-priced medallions, and using scalable technology in place of overhead like a central dispatcher.

An Uber in education may to keep costs low by having younger, more inexperienced employees (e.g., college students) work as teachers, or by hiring lower-cost teachers from overseas like some online tutoring services do.


Maybe we can Uber-ize education, but should we?


In summary, there is definitely opportunity in creating low-cost, on-demand learning experiences, especially in disciplines where there is a growing demand for teachers and flexible supply (e.g., technology professionals can  supplement the  learn-to-code movement).

However, it is important to consider the effect such a disruption would have on the broader education system. Many students would not benefit from an educational Uber, from reasons ranging from being unable to pay for a premium educational service, to not being engaged by a digital teacher (and perhaps no in-person teachers are nearby).  As a result, the service may miss the students who need it the most, entrenching inequity issues we have been fighting for decades. And just like the success of Uber may leave the lowest-quality drivers left in the traditional taxi industry, we should worry if on-demand education gives wealthier students a monopoly on the best teachers.

Furthermore, the analysis above assumes that the goal of education is to learn a specific, well-defined skill. That premise is itself controversial. When Governor Scott Walker of Wisconsin tried replacing the words “search for truth” with “meet the state’s workforce needs” in the state code for universities, it was met with backlash from academics and educators alike. They argue that an education should provide a sense of social responsibility, encourage discovery, and instill wonderment about the world. Any service that claims to educate should serve this dual purpose of preparing students for work and life.


What next?

Several well-positioned players are already moving into on-demand education. Online course provider Udacity has recently pivoted from offering full-scale university courses to bite-sized “nanodegrees” which are proctored by their global network of 300 code reviewers. They claim their best code reviewer can earn more than 8x the monthly salary of a part-time teacher in the US. Startups like MathCrunch provide Uber-like math tutoring services at a fraction of the cost of incumbent Tutor.com. Maybe even Uber, who partnered with Levo League in early 2015 to offer brief “mentoring rides” with influential businesswomen, can themselves make a play in the market.

As for myself, I’m excited about exploring whether an “Uber for Education” has any merit given the immense social value it could create. If you have thoughts on the topic, please share them below!



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By: Vibin Kundukulam

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