Unbundling news and advertising

I’ve written earlier about how once news media became dependent on subscriptions, it started becoming partisan. Thinking about it, it is not particularly correct.

If we think of the traditional (physical) newspaper, it was seldom given away for free (when I lived in London I would pick up free copies of the Evening Standard on days when I needed to line my compost bin). Traditional newspapers relied (and still do) on a combination of subscription and advertising for their revenues.

In that sense, what the New York Times does now (read this nice interview with its outgoing CEO) is basically a digital transformation of what it has been doing for over a hundred years – make money off a combination of subscription and advertising.

So if the business model was the same, why did the online New York Times differ from its previous avatar and become politically partisan? Because the nature of advertising changed.

Nowadays I have this favourite theory that everything is a bundle (maybe I should write my next book about this?).

You can consider this post to belong to this meme.

The traditional newspaper, if you think about it, was a collection of news and advertisements all bundled together. While you could choose what part of the paper you wanted to consume, when you went to a page you would inevitably scan all the headlines. And whether you liked them or not, you would actually eyeball all the advertisements.

The important thing to note is that the paper was a physical product and what advertisement the reader was shown did not depend on that person at all. Whether you were a raving communist or a slaveholder, you would be shown the same set of advertisements.

This meant that physical newspaper advertisements were (and still are) dominated by mass products that were aimed at everyone. And since these advertisements were usually paid for based on an estimate (sometimes highly inaccurate) of how many people saw them, the newspapers wanted to maximise the eyeballs. This meant not taking any extreme political stances, and keeping all parts of the political spectrum onside.

What changed with the move to digital was that this bundle containing the news and the advertisements broke down.

With advertising being sold through data-driven ad exchanges, it was now possible to show different advertisements to different people. And with advertisements now dependent on your search and browsing history (apart from your political preferences), it was effectively personalised. The New York Times did not need to directly sell advertising any more. All they needed to do was to sign a contract with Google or Facebook or both. Job done.

Digital advertising doesn’t make sense for mass brands. Rather, it is highly likely that the availability of data will mean that they will frequently get outbid by highly targeted brands. So whether mass brands wanted to advertise in the New York Times became a less important decision. The paper had no compulsion to be politically neutral any more.

And once their early set of subscribers showed a marked preference for one kind of politics, it made sense to them to go after the subscription dollars of this audience rather than the already uncertain dollars of potential subscribers that preferred another kind of politics. And then there as a self-reinforcement cycle.

Media can crib as much as they want about the likes of Google and Facebook taking away their money. They can lobby, like they have done in Australia, to “levy a google tax“. People can crib about media having become biased.

However, we need to remember that all this mess started with the unmaking of a bundle – once news and advertising had been separated, there was no turning back.

Amazon and brand-building

Sometimes shopping on Amazon feels like shopping in Burma Bazaar or National Market or any of those (literally) underground “shopping malls” where you get cheap imported stuff of uncertain quality. This is especially true when shopping for things like children’s toys and some electronics, where you don’t have too many established brands.

The only times I feel completely comfortable shopping on Amazon is when I’m buying known brands – like last month when I bought a LG monitor or Logitech keyboard and mouse. LG and Logitech have built their brands sufficiently outside of the Amazon ecosystem that I trust their quality even while buying on Amazon.

This is not the case when it comes to other categories, though. One day I was browsing for toys on Amazon and was simply unable to decide what to buy – it all looked so “cheap”. Finally, my wife noticed one brand of which we already had a toy (that we liked), and we ended up buying that (that was a sound decision). Once again, we had used our knowledge of brands that had build their brands outside of Amazon to make our decision.

The thing with Amazon is that it is an “everything store” – one store to serve all markets. That’s not how offline markets work. In offline markets, stores fairly easily differentiate themselves based on the markets that they serve – by their locations, by their price points, by the overall “look and feel” and so on. That way, when you go to a store that you know serves your segment, you can be confident that what the store sells you is what you’re looking for.

This is not the case with Amazon. Since one store serves all, it is very difficult to know upon seeing a product whether it is “made for you”. Well, Amazon has information about your previous purchases on the platform, which should give them a good idea of the “segment” you belong to, but I guess making money from advertisers on the platform trumps making your choice easier?

From this perspective, if you are a hitherto unknown brand trying to sell on Amazon, it makes sense for you to build your brand elsewhere. Here, we run into the “double cost problem” (that I had used to describe long ago why Grofers is not a sustainable business). Essentially, building a brand is expensive and once you’ve spend your dollars on (let’s say) the Facebook ecosystem to build your brand, does it make sense to also pay Amazon to push up your product when it comes to search?

It seems like brands are now choosing one way or the other. Mass market brands (it appears) are sticking to the Amazon ecosystem. Some premium brands are using Instagram to acquire customers, and then using the Shopify-Razorpay-Delhivery ecosystem to deliver. Some other premium brands are using a combination of Instagram and Amazon, but only using the latter as a fulfilment mechanism – not spending money to advertise there.

In any case, it seems to me that building brands on Amazon is not a viable business. Now I’m reminded of my other old post where I talk about how platforms are useful only if they aggregate unreliable supply. And this is a path that Amazon seems to have firmly taken.

And the moment you focus on branding, you are trying to send out the message that you are not “unreliable supply”. And this means that getting mixed up with other unreliable suppliers is not good for your business. Which is why you find that the direct to consumer brands that advertise on Instagram (have I told you I love instagram ads?) usually stay away from Amazon.

(you might think I’m going round and round in circles in this post. This is because it’s been about a month since I thought of writing this but only got down to it today. It’s also funny that I’m writing  this less than an hour after talking to someone who builds her brand on Instagram and then sells through Amazon (and offline shops) ).

PS: I got reminded of when I initially thought of this post. I bought a yoga mat from Amazon a couple of months ago. Quality turned out to be pathetic. And there was no way for me to know that when I was buying.

Open and closed platforms

This is a blogpost that I had planned a very long time (4-5 weeks) ago, and I’m only getting down to write it now. So my apologies if the quality is not as good as my blogposts usually are. 

Many of you would have looked at the title of this blogpost and assumed that the trigger for this was the “acquisition” of Joe Rogan’s podcast by Spotify. For a large sum of money, Spotify is “taking his podcast private”, making it exclusive to Spotify subscribers.

However, this is only an “immediate trigger” for writing this post. I’d planned this post way back in April when I’d written one of my Covid-19 related blogposts – maybe it was this one.

I had joked the post needed to be on Medium for it to be taken seriously (a lot of covid related analysis was appearing on Medium around that time). Someone suggested I actually put it on Medium. I copied and pasted it there. Medium promptly took down my post.

I got pissed off and swore to never post on Medium again. I got reminded of the time last year when Youtube randomly pulled down one of my cricket videos when someone (an IP troll, I later learnt) wrongly claimed that I’d used copyrighted sounds in my video (the only sound in that video was my own voice).  I had lodged a complaint with Youtube, and my video was resurrected, but it was off air for a month (I think).

Medium and Youtube are both examples of closed platforms. All content posted on these platforms are “native to the platform”. These platforms provide a means of distributing (and sometimes even marketing) the content, and all content posted there essentially belongs to the platform. Yes, you get paid a cut of the ad fee (in case your Youtube channel becomes super powerful, for example), but Youtube decides whether your video deserves to be there at all, and whose homepages to put it on.

The main feature of a closed platform is that any content created on the platform needs to be consumed on the same platform. A video I’ve uploaded on Youtube is only accessible on Youtube. A medium post can only be read on medium. A tweet can only be read on twitter. A Facebook post only on Facebook.

The advantage with closed platforms is that by submitting your content to the platform, you are hoping to leverage some benefits the platform might offer, like additional marketing and distribution, and discovery.

This blog doesn’t work that way. Blogposts work through this technology called “RSS”, and to read what I’m writing here you don’t need to necessarily visit noenthuda.com. You can read it on the feed reader of your choice (Feedly is what I use). Of course there is the danger that one feed reader can have overwhelming marketshare, and the destruction of that feed reader can kill the ecosystem itself (like it happened with Google Reader in 2013). Yet, RSS being an open platform means that this blog still exists, and you can continue to receive it on the RSS reader of your choice. If Medium were to shut down tomorrow, all Medium posts might be lost.

Another example of an open platform is email – it doesn’t matter what email service or app you use, my email and yours is interoperable. India’s Universal Payment Interface (UPI) is another open platform – the sender and receiver can use apps of their choice and still transact.

And yet another open platform (which a lot of people didn’t really realise is an open platform) is podcasting. Podcasts run on the RSS protocol. So when you subscribe to a podcast using Apple Podcasts, it is similar to adding a blog to your Feedly. This thread by Ben Thompson of Stratechery (that I just stumbled upon when I started writing this post) sums it up well:

What Spotify is trying to do (with the Joe Rogan and Ringer deals) is to take these contents off open platforms and put it on its own closed platform. Some people (like Rogan) will take the bait since they’re getting paid for it. However, this comes at the cost of control – like I’m not sure if we’ll have another episode of Rogan’s podcast where host and guest light up a joint.

Following my experiences with Medium and Youtube, when my content was yanked off for no reason (or for flimsy reasons), I’m not sure I like closed platforms any more. Rather, someone needs to pay me a lot of money to take my content to a closed platform (speaking of which, do you know that all my writing for Mint (written in 2013-18) is behind their newly erected paywall now?).

In closing I must mention that platforms being “open” and platforms being “free” are orthogonal. A paid podcast or newsletter is still on an open platform (see Ben Thompson tweetstorm above), since it can be consumed on a medium independent of the one where it was produced – essentially a different feed is generated depending on what the customer has paid for.

Now that I’ve written this post, I don’t know what the point of this is. Maybe it’s just for collecting and crystallising my own thoughts, which is the point behind most of my blogposts anyway.

PS: We have RSS feeds for text and podcasts for audio. I wonder why we don’t have a popular and open protocol for video.

Footage

So after a fifteen year gap, I was in the Times of India yesterday, writing about the joys of working from home (I’d shared the clipping yesterday, sharing it again). The interesting thing is that this piece got me the kind of attention that I very rarely got with my six  years with the HT Media family (Mint and Hindustan Times).

The main reason, I guess, that this got far more footage, was that it came in a newspaper with a really high circulation. ToI is by far the number one English newspaper in India. While HT may be number two, we don’t even know how much of a number two it is, since it seemingly didn’t participate in the last Indian Readership Survey.

Moreover, ToI is read widely by people in my network. While the same might be true of Mint (at least until its distribution in Bangalore went kaput), it was surely not the case with HT. I didn’t know anyone who read the paper, and since my articles mostly never appeared online, they seemed to go into a black hole.

Another reason why my article got noticed so widely was the positioning in the paper – it was part of ToI’s massively extended “page one” (it came on the back of the front page, which was full of advertisements). So anyone who picked up the paper would have seen this in the first “real page of news” (though this page was filled with analysis of working from home).

On top of all this, I think my mugshot accompanying the article made a lot of difference. While the title of the article itself might have been missed by a few, my photo popping out of there (it helps I have the same photo on my Twitter, Facebook, LinkedIn and WhatsApp – thanks Anuroop) ensured that anyone who paid remote attention to my face would end up reading the article, and that helped me get further reach among my existing network.

ToI is going to pay me a nominal amount for this article, far less than what Mint or HT used to pay me per piece (then again, this one is completely non-technical), but I don’t seem to mind it at all. That it’s given me much more reach among my network means that I’m satisfied with ToI’s nominal payment.

Thinking about it, if we think of newspapers as three-sided markets connecting writers, readers and advertisers, it is possible that others who write for ToI do so for below market prices as well, for it has an incredibly large reach among “people like us”. And that sets the size-related network effects (“flywheel” as silicon valley types like to call it) in action among the writer side as well -you don’t write for money along, and if it can be sort of guaranteed that a larger number of people will read what you write, you will be willing to take lower payment.

In any case, this ToI thingy was a one-off (the last time I’d written for them was way back in 2005, when I was a student – it’s incredible I’ve given this post the same title as that one. I guess I haven’t grown up). But I may not mind doing more of such stuff for them. The more obscure the paper, though, the higher I’ll be inclined to charge! Oh, and henceforth, I’ll insist my mugshot goes with everything I write, even if that lowers my monetary fees.

 

Active aggression and passive aggression

For the record I’m most often actively aggressive. I believe passive aggression is a waste of energy since not only do you end up fighting but you also end up trying to second guess the other party, which leads to suboptimal outcomes. This post is a justification of that.

Let’s say you and I are trying to decide the price of something I want to sell you. There are two ways we can go about it. One way is for us to have a negotiation. I can name my asking price. You call your bid. And if the two meet, well and good. Most often they won’t meet. So one of us will have to budge. We start budging slowly, in steps, until a time when the bid and ask are close together. And then we have a deal.

In most situations (except exceptional cases where there are very few buyers and sellers – read the first chapter of my book. This is within the Kindle sample), this will lead to an efficient outcome. Even if the final price were a little too close to the bid or to the ask, both parties know that under the circumstances they couldn’t get better. And the transaction takes place and the parties move on.

The other situation is where one party publicly states that they are unwilling to negotiate and will do the deal if and only if the counterparty comes up with a good enough offer. If the offer is not good enough, there is no deal. This is similar to the ultimatum game popular in behavioural economics. In this case you are also required to guess (and you have exactly one guess) what the counterparty’s hurdle rate is.

When there is a liquid market, there is no issue with this kind of a game – you simply have your own hurdle rate and you bid that. And irrespective of whether it gets accepted or not, you get the optimal outcome – since the market is liquid, it is likely that your quote will get accepted somewhere.

In a highly illiquid market, with only one buyer and one seller, the ultimatum setup can lead to highly suboptimal outcomes. I mean if you’re desperate to do the sale, you might bring your price “all the way to zero” to ensure you do the deal, but the thing is that irrespective of whether you get a deal or not, you are bound to feel disappointed.

If your ask got accepted, you start wondering if you could’ve charged more. If you didn’t get your deal, you start wondering if reducing a price “just a little” would have gotten the deal done. It is endless headache, something that’s not there when there is an active negotiation process.

Now to build the analogy – instead of a sale, think of the situation when you have a disagreement with someone and need to resolve it. You can either confront them about it and solve it “using negotiation” or you can be passive aggressive, letting them know you’re “not happy”. Notice that in this case the disagreement is with one specific party, the market is as illiquid as it can get – no negotiations with any third party will have any impact (ignore snitching here).

When you express your disagreement and you talk/fight it out, you know that irrespective of the outcome (whether it was resolved or not), you have done what you could. Either it has been resolved, which has happened with you telling what exactly your position is, or you have given it all to explain yourself and things remain bad (in this case, whatever happened there would have been “no deal” or an “unhappy deal”).

And that is why active aggression is always better than passive aggression. By expressing your disagreement, even if that means you’re being aggressive, you are stating the exact extent of the problem and the solution will be to your satisfaction. When you’re passive aggressive, nobody is the winner.

PS: I realise that by writing this post I’m violating this own advice, since this post itself can be seen as a form of passive aggression! Mea culpa.

The market for gay relationships

The market for homosexual relationships is an interesting one from the analysis perspective. Like the market for heterosexual relationships, it is a matching market (we are in a relationship if and only if I like you AND you like me). Unlike heterosexual relationships, it is not a “bipartite” market, since both the nominal “buyer” and the “seller” in a transaction will come out (no pun intended) of the same pool (gay people of a particular sex).

The other factor that makes this market interesting (purely from an analysis perspective – it’s bad for the participants) is that there is disapproval at various levels for homosexual relationships. Until today, for example, it was downright criminal to indulge in gay sex in India. Even where it is legal, there is massive social and religious opposition to such relationships (think of the shootout at the gay bar in Florida, for example).

Social disapproval has meant that gays sometimes try to keep their sexuality under wraps. Historically, it has been a common practice for gays to enter into heterosexual marriages, and pursue relationships outside. In fact, there is nothing historical about this – read this excellent piece by Srinath Perur on gays in contemporary hinterland Karnataka, for whom Mohanaswamy, a collection of short stories with a gay protagonist, was a kind of life changer.

Organising a market for an item that is illegal, or otherwise frowned upon, is difficult, since people don’t want to be found participating in it. If I were a gay man looking for a partner, for example, I couldn’t go around openly looking for one if I didn’t want my family to know that I’m gay. So the first task would have been discovery – “safe spaces” where I would be happy to expose my sexuality, and where I could also meet potential partners.

When demand and supply exist, buyers and sellers will find a way to meet each other, though often at high cost. One such “way” for homosexual people has been the gay bar. Though not explicitly advertised, such bars act as focal points (I have a chapter on focal points in my book) for gay people.

They also act as an “anti focal point” (a topic I HAVEN’T covered in the book, for a change!) for heterosexual people who want to stay away because they don’t want to be hit on by gay people (thus reducing market congestion – another topic I cover in my book). Similarly other cultural activities have acted as focal points for gay people to get together and meet each other.

Like in heterosexual relationship markets (this is the link to a sample chapter from the book), the advent of dating apps has revolutionised gay dating, as apps such as Tinder and Grindr have provided safe spaces where gays can look for relationships “from the comfort of their homes”. There are studies that show that Grindr has changed the nature of relationships among gay men, and how these apps have “saved lives” in places such as India where homosexuality was criminal until today.

Today’s Indian Supreme Court ruling will have a massive positive impact on gay relationships in India. For starters, there are still millions of people in the closet – while apps such as Tinder and Grindr allowed more people to participate in these markets (since this could be done without really “coming out”), that gay sex was a criminal act would have led to some people to err on the side of caution (and deprive themselves of the chance of a relationship). Gay people who were worried about criminality, but not that much about social sanctions, will now be more willing to come out, leading to an increase in the market size.

Barring congestion (when “bad counterparties” prevent you from finding “good counterparties”),  the likelihood of finding a match in a market is generally proportional to the number of possible counterparties. Since gay relationship markets are not bipartite, we can say that the likelihood of finding a good match varies by the square of the number of market participants (and this brings in the Indian Prime Minister’s infamous 2ab term). In other words, it not only allows the people now coming into the market to find relationships, but it also allows existing players to find better relationships.

Then, there is the second order effect. Decriminalisation will mean that more people will come out of the closet, which will mean more people will find homosexuality to  be “normal” leading to better social mores (to take a personal example, I used to use the word “gay” as a pejorative (to mean “uncool”) until I encountered my first openly gay acquaintance – someone with whom I share on online mailing list). And as social attitudes towards homosexuality change, it will lead to more people coming out of the closet, setting off a virtuous cycle of acceptance of homosexuality.

In other words, today’s decision by the Indian Supreme Court is likely to set off a massive virtuous cycle in the liquidity of the market for homosexual relationships in India!

PS: It is a year since my first book was published, so we are running a promotional offer where you can buy the Kindle version for one dollar (or Rs. 70).

 

Information Technology and Large Cities

In my book Between the buyer and the seller, officially released exactly a year ago, I have a chapter on cities. In that I explain why industry clusters form, and certain cities or regions become hubs for certain types of industries.

In that, I spoke about the software industry in California’s Silicon Valley, and in Bangalore. I also mentioned how the Industrial Revolution wasn’t evenly distributed around England, and how it was clustered around textile hubs such as Birmingham and Manchester. I also used that chapter to talk about the problem with government-mandated special economic zones (this podcast with Amit Varma can help you understand the last point).

Back when Silicon Valley was still silicon valley (basically a semiconductor and hardware hub), it wasn’t as concentrated a hub as it is today. It was still fairly common for semiconductor companies to base themselves away from the valley. With the “new silicon valley” and the tech startup scene, though, there is no escaping the valley. It is almost an unwritten rule in US Tech startup circles that if you want to be successful with a tech startup, you better be in the valley.

And this is for good reason, as I explain in the book – Silicon Valley is where the ecosystem for successfully running a tech startup already exists, including access to skilled employees, subcontractors and investors, not to speak of a captive market. This, however, has meant that Silicon Valley is now overcrowded in many respects, with rents being sky high (reflected in high salaries), freeways jammed and other infrastructure under stress.

In fact, it is not just the silicon valley that has got crushed under the weight of being a tech hub – other “secondary hubs” such as Seattle (which also have a few tech majors, and where startups put off by the cost of the valley set up) are seeing their quality of life go down. The traffic and infrastructure woes in Bangalore are also rather similar.

So why is it that information technology has led to hubs that are much larger than historical hubs (based on other industries)? The simple answer lies in investment, or the lack of it.

Setting up an information technology company is “cheap” in terms of the investment in capital expenditure. No land needs to be bought, no plants need to be constructed and no machinery needs to be bought. All one needs is an office space (for which rent is paid monthly), and a set of employees (who again get paid a monthly salary). Even IT infrastructure (such as computing power and storage and communication) can be leased, and paid for periodically.

This implies that there is nothing that stops a startup company from locating itself in one of the existing hubs. This way, the company can avail all the benefits of being in the hub (supplier and customer infrastructure, employee pool, quality of life for employees and investors) without a high upfront cost.

Contrast this to “hard” industries that require manufacturing, where the benefits of being located in hubs is similar but the costs are far higher. As a hub develops, land gets expensive, which puts off further investors from locating themselves in the hub. This puts a natural limit on the size of the hubs, and if you think about it, large cities from earlier era were all “multi-purpose cities”, serving as hubs for several unrelated industries.

With information technology, though, the only impediment to the growth of a hub is the decreasing quality of life, information regarding which gets transmitted in indirect means such as higher rentals and commute times, and poor health. This indirect transmission of costs to investors results in friction, which means information technology hubs will grow larger before they stop growing. And as they go through this process, the quality of life of the hub’s residents suffers!

Ratings revisited

Sometimes I get a bit narcissistic, and check how my book is doing. I log on to the seller portal to see how many copies have been sold. I go to the Amazon page and see what are the other books that people who have bought my book are buying (on the US store it’s Ray Dalio’s Principles, as of now. On the UK and India stores, Sidin’s Bombay Fever is the beer to my book’s diapers).

And then I check if there are new reviews of my book. When friends write them, they notify me, so it’s easy to track. What I discover when I visit my Amazon page are the reviews written by people I don’t know. And so far, most of them have been good.

So today was one of those narcissistic days, and I was initially a bit disappointed to see a new four-star review. I started wondering what this person found wrong with my book. And then I read through the review and found it to be wholly positive.

A quick conversation with the wife followed, and she pointed out that this reviewer perhaps reserves five stars for the exceptional. And then my mind went back to this topic that I’d blogged about way back in 2015 – about rating systems.

The “4.8” score that Amazon gives as an average of all the ratings on my book so far is a rather crude measure – since one reviewer’s 4* rating might differ significantly from another reviewer’s.

For example, my “default rating” for a book might be 5/5, with 4/5 reserved for books I don’t like and 3/5 for atrocious books. On the other hand, you might use the “full scale” and use 3/5 as your average rating, giving 4 for books you really like and very rarely giving a 5.

By simply taking an arithmetic average of ratings, it is possible to overstate the quality of a product that has for whatever reason been rated mostly by people with high default ratings (such a correlation is plausible). Similarly a low average rating for a product might mask the fact that it was rated by people who inherently give low ratings.

As I argue in the penultimate chapter of my book (or maybe the chapter before that – it’s been a while since I finished it), one way that platforms foster transactions is by increasing information flow between the buyer and the seller (this is one thing I’ve gotten good at – plugging my book’s name in random sentences), and one way to do this is by sharing reviews and ratings.

From this perspective, for a platform’s judgment on a product or seller (usually it’s the seller, but for products such as AirBnb, information about buyers also matters) to be credible, it is important that they be aggregated in the right manner.

One way to do this is to use some kind of a Z-score (relative to other ratings that the rater has given) and then come up with a normalised rating. But then this needs to be readjusted for the quality of the other items that this rater has rated. So you can think of some kind of a Singular Value Decomposition you can perform on ratings to find out the “true value” of a product (ok this is an achievement – using a linear algebra reference given how badly I suck in the topic).

I mean – it need not be THAT complicated, but the basic point is that it is important that platforms aggregate ratings in the right manner in order to convey accurate information about counterparties.

Platform as a platform

This afternoon, as I was getting off the tube, I looked at the railway platform, and wondered how it compared to “platforms” as we now know in the context of “platform economics“. For those of you under a rock, platform economics talks about the economics of “platforms” that bring together two sides of a market to interact.

In that sense, Uber is a platform connecting drivers to passengers. Ebay is a platform connecting buyers and sellers of used goods. Paypal is a platform connecting people who want to pay and those who want to receive payment. And so forth (these are all textbook examples nowadays).

So is the railway platform a platform? And if not, is it correct that we refer to entities that run two-sided markets as platforms (arguably, the most intuitive meaning of the word “platform” in the last hundred or so years has been in the railway context)? These were some of the questions I grappled with as I walked along the length of the platform at Ealing Broadway.

For those of you who’re not in the know, I’ve written a book on market design. The Takshashila Institution is publishing it, and the book should be out fairly soon (manuscript is complete, but there’s still plenty to do). In that book, I have a chapter on taxi marketplaces such as Uber/Lyft/Ola, and how they’ve transformed the efficiency of the taxi market. Before I introduce these characters, though, I draw the history of the taxi market.

In that, I talk about taxi stands. Taxi stands work in the way of Thomas Schelling’s focal points. Passengers go there because they know empty taxis will go there. Taxi drivers looking for passengers go there because they know passengers looking for taxis will go there. This way, rather than waiting at a random place looking for either a passenger or a ride, going to the taxi stand is rational. And in that sense, taxi stands are a platforms.

In a way, railway platforms are platform in the same sense. Think of a train that wants to pick up passengers, and passengers who want to travel on a train. If there were no designated pick up points, trains would stop at random places, which passengers would have to guess. While engine drivers could see passengers waiting by the side, stopping at random places might have meant that the train would have had to go empty.

From this perspective, railway platforms act as platforms – they are focal points where trains and passengers come together. Passengers wait there because they know trains stop there, and vice versa. And helpfully, there is an actual physical platform that elevates passengers to the height of the train door so they can get on and off easily!

Isn’t this a wonderful way to have complicated a rather simple concept?

Market depth, pricing and subsidies

A few days back I had written about how startups should determine how much to subsidise their customers during the growth phase – subsidise to the extent of the long-term price. If you subsidise too much initially, elasticity might hit you when you eventually have to raise prices, and that can set you back.

The problem is in determining what this long-term sustainable price will be. In “one-sided markets” where the company manufactures or assembles stuff and sells it on, it is relatively easy, since the costs are well known. The problem lies in two-sided markets, where the long-term sustainable price is a function of the long-term sustainable volume.

A “bug” of any market is transaction costs, and this is especially the case in a two-sided market. If you are a taxi driver on Ola or Uber platform, the time you need to wait for the next ride or distance you travel to pick up your next customer are transaction costs. And the more “liquid” the market (more customers and more drivers), the lesser these transaction costs, and the more the money you make.

In other words, the denser a market, the lower the price required to match demand and supply, with the savings coming out of savings in transaction costs.

So if you are a two-sided market, the long-term sustainable price on your platform is a function of how big your market will be, and so in order to determine how much to subsidise (which is a function of long-term sustainable price), you need to be able to forecast how big the market will be. And subsidise accordingly.

It is well possible that overly optimistic founders might be too bullish about the eventual size of their platform, and this can lead to subsidising to an extent greater than the extent dictated by the long term market size. And some data points from the Indian “marketplace industry” show that this has possibly happened in India.

Having remained credit card only for a long time now, Uber has started accepting cash payments – in order to attract customers who are not comfortable transacting money online. This belated opening shows that Uber perhaps didn’t hit the numbers they had hoped to, using their traditional credit card / wallet model.

Uber has problems on the driver side, too, with an increasing number of its drivers turning out to be rather rude (this is anecdata from several sources, I must confess), refusing rides, fighting with passengers, etc. Competitor Ola has started buying cars and loaning them to drivers, perhaps indicating that the driver side of the market hasn’t grown to their expectations. They are all indicative of overestimation of market size, and an attempt to somehow hit that size rather than operating at the lower equilibrium.

So an additional risk in running marketplaces is that if you overestimate market size, you might end up overdoing the subsidies that you provide to build up the market. And at some point in time you have to roll back those subsidies, which might lead to shrinkage of the market and a possible death spiral.

Now apply this model to your favourite marketplace, and tell me what you think of them.