Revenue management and transaction costs

So I just sent off a letter to India. To be precise, it is a document I had to sign and send to my accountant there – who sends regular “letters” any more?

The process at the post office (which, in my suburb, is located inside a large bookstore) was simple. In the first screen of the touch screen kiosk, there was an option for “worldwide < 20 grams”. A conveniently placed scale told me my letter weighed 18 grams, and one touch and one touch of my debit card later, I had my stamp. Within a minute, my letter was in the letterbox.

The story of how we pay the same amount for sending mail over large areas (“worldwide” in my case today) is interesting. Earlier, mail rates were based on distance, but as new roads kept being built in the 19th century America, and distances kept changing, figuring out how much to charge for a letter became “expensive”. A bright fellow figured out that the cost (in terms of time) of figuring out how much to charge for mail was of the same order of magnitude as the cost of the mail itself. And so the flat rate scheme for mail, that is prevalent worldwide today, was born.

Putting it in technical terms, transaction costs trumped price discrimination in this case. Price discrimination is the art (yes, it’s an art) of charging different amounts to different people based on their differential willingness to pay. Uber surge pricing is one example (I have a chapter in my book on this). Airline fares are another common example.

Until the late 18th century (well after mail prices had gone “flat”), price discrimination was rather common everywhere, a concept I have devoted a chapter to in the book. In fact, the initial motivation for fixed price retail was religious – Quakers, who owned many departmental stores in the US North-East, thought “all men are created equal before God” and so it was incorrect to charge different amounts to different people.

Soon other benefits of fixed prices became apparent (faster billing; less training for staff; in fact it was fixed prices that permitted the now prevalent supermarket format), and it took off. The concept is the same as stamps – the transaction cost of figuring out how much to charge whom is higher than the additional revenue you can make with such price differentiation (not counting possible loss of reputation, and fairness issues). Price discrimination at the shop is now confined to high value high margin businesses such as cars.

And it works in other high gross margin businesses such as airlines, hotels and telecom. These are all businesses with high fixed costs and low marginal costs for the suppliers. Low marginal costs has meant that price discrimination ha been termed as “revenue management” in the airline industry.

During the launch function of my book last year, I got asked if Uber’s practice of personalising fares for passengers is fair (I had given a long lecture on how Uber’s surge pricing is a necessary component of keeping average prices low and boosting liquidity in the taxi market). I had answered that a marketplace needs to ensure that its pricing is perceived as being “fair”, else they might lose customers to competitors. But what if all players in a market practice extreme price discrimination?

Thinking about it, transaction costs will take care of price discrimination before businesses and marketplaces start thinking of fairness. Beyond a point (the point varies by industry), the marginal revenues from price discrimination will fall below the transaction cost of executing this discrimination. And that poses a natural limit to how much price discrimination a business can practice.

British retail strategy

Right under where I currently live, there’s a Waitrose. Next door, there’s a Tesco Express. And a little down the road, there’s a Sainsbury Local. The day I got here, a week ago, I drove myself nuts trying to figure out which of these stores is the cheapest.

And after one week of random primary research, I think I have the classic economist’s answer – it depends. On what I’m looking to buy that is.

Each of these chains has built a reputation of sourcing excellent products and selling them to customers at a cheap price. The only thing is that each of them does it on a different kind of products. So there is a set of products that Tesco is easily the cheapest at, but the chain compensates for this by selling other products for a higher rate. It is similar with the other chains.

Some research I read a year or two back showed that while Amazon was easily the cheapest retailer in the US for big-ticket purchases, their prices for other less price-sensitive items was not as competitive. In other words, Amazon let go of the margin on high-publicity goods, and made up for it on goods where customers didn’t notice as much.

It’s the same with British retailers – each of their claims of being the cheapest is true, but that applies only to a section of the products. And by sacrificing the margin on these products, they manage to attract a sufficient number of customers to their stores, who also buy other stuff that is not as competitively priced!

Now, it is possible for an intelligent customer to conduct deep research and figure out the cheapest shop for each stock keeping unit. The lack of quick patterns of who is cheap for what, however, means that the cost of such research and visiting multiple shops usually far exceeds the benefits of buying everything from the cheapest source.

I must mention that this approach may not apply in online retail where at the point of browsing a customer is not “stuck” to any particular shop (unlike in offline where a customer is at a physical store location while browsing).

Variable pricing need not be boring at all!

Who do you subsidise?

One basic rule of pricing is that it is impossible for all buyers to have the same consumer surplus (the difference between what a buyer values the item at and what he paid). This is because each buyer values the item differently, and is thus willing to pay a different price for it. People who value the item more end up having a higher consumer surplus than those who value it less (and are still able to afford it).

Dynamic pricing systems (such as what we commonly see for air travel and hotels) try to price such that such a surplus is the same for all consumers, and equal to zero, but they never reach this ideal. While the variation in consumer surplus under such systems is lower, it is impossible for it to come to zero for all, or even a reasonable share of, customers.

So what effectively happens is that customers with a lower consumer surplus end up subsidising those with a higher consumer surplus. If the former customers didn’t exist, for example, the clearing price would’ve been higher, resulting in a lower consumer surplus for those who currently have a higher consumer surplus.

Sometimes the high surplus customer and the low surplus customer need not be different people – it could be the same person at different times. When I’m pressed for time, for example, my willingness to pay for a taxi is really high, and I’m highly likely to gain a significant consumer surplus by taking a standard taxi or ride-hailing marketplace ride then. At a more leisurely time, travelling on a route with plenty of bus service, I’d be willing to pay less, resulting in a lower consumer surplus. It is important to note, however, that my low surplus journey resulted in a further subsidy to my higher surplus journey.

When it comes to markets with network effects (whether direct, such as telecommunications, or indirect, like any two-sided marketplace), this surplus transfer effect is further exacerbated – not only do low-surplus customers subsidise high-surplus customers by keeping clearing price low, but network effects mean that by becoming customers they also add direct value to the high surplus customers.

So when you are pleasantly surprised to find that Uber is priced low, the low price is partly because of other customers who are paying close to their willingness to pay for the service. When you pay an amount close to the value you place on the service, you are in turn subsidising another customer whose willingness to pay is much higher.

This transfer of consumer surplus can be seen as an instance of bundling, but from the seller’s side. Since a seller cannot discriminate effectively among customers (even with dynamic pricing algorithms such as Uber’s surge pricing), the high-surplus customers come bundled with the low-surplus customers. And from the seller’s perspective, this bundling is optimal (see this post by Chris Dixon on why bundling works, and invert it).

So the reason I thought up this post is that there has been some uncertainty about ride-hailing marketplaces in Bangalore recently. First, drivers went on strike alleging that they weren’t being paid fairly by the marketplaces. Then, a regulator decided to take the rulebook too literally and banned pooled rides. As i write this, a bunch of young women I know are having a party, and it’s likely that they’ll need these ride-hailing services for getting home.

Given late night transport options in Bangalore, and the fact that the city sleeps early, their willingness to pay for a safe ride home will be high. If markets work normally, they’re guaranteed a high consumer surplus. And this will be made possible by someone, somewhere else, who stretched their budget to be able to afford an Uber ride.

Think about it!

Cross-posted at RQ

More football structuring

I’ve commented earlier on innovative structuring of football player contracts, with call options and put options and all other exotic options being involved. Now I see another interesting transfer structure, this time in the contract of Juventus (and Spain) striker Alvaro Morata.

In 2014, Real Madrid sold Morata to Juventus for a transfer fee of €20 million, but the sale had a “buy back clause”. Embedded in the sale was an option for Real Madrid to buy back Morata at any time for €30 million, and now it seems like they’re exercising it!

While this might be based on Morata’s performances (both for Juventus and Spain) in the last couple of years, the interesting thing about the buyback is that Real Madrid are unlikely to keep hold of Morata. Instead, talk is that they plan to sell him on, with PSG and Manchester United being interested in the forward.

Effectively the deal is something like “as long as Morata’s perceived market value is  < €30M, Juventus can keep him, but once his perceived market value goes up, all the upside goes to Real Madrid”. The downside (in case Morata regressed as a player and his market value went below €20M), of course, remained with Juventus. To put it simply, Madrid is exercising its call option on the player.

While loan agreements have earlier had clauses such as “right but obligation to make deal permanent” or “obligation but not right to make deal permanent”, this is the first time I’m seeing an actual transfer deal with this kind of a clause, which is being exercised. So why did Juventus and Real Madrid hammer out such a complicated-looking structure?

For Juventus, the simple answer is that the option they wrote reduced the cost of buying the player. While they have given up on significant upside in writing this call option, this is what perhaps made the purchase possible for them, and in some ways, it’s worked out by giving them two more Scudetti.

The answer is less clear from Real Madrid’s perspective. Clearly, the fact that they got a call option meant that they believed there was a significant chance of Morata improving significantly. At the point of time of sale (2014), however, he was surplus to their requirements and they believed sending him elsewhere would help in this significant improvement.

It is possible that the market in 2014 wasn’t willing to bear the price implied by Real Madrid’s expectation of Morata’s improvement, but was only willing to pay based on his then abilities and form. In other words, while Morata’s current abilities were fairly valued, his future abilities were grossly undervalued.

And Madrid did the smart thing by unbundling the current and future values, by structuring a deal that included a call option!

Again, this is only my speculation of how it would have turned out, but it’s indeed fascinating. Given how global financial markets are performing nowadays, it seems like structuring of football deals is now far more interesting than structuring financial derivatives! But then the market is illiquid!

Valuing Global Fashion Group

Yesterday, in Mint, I wrote about ratchets in option valuation (a pet topic of mine), and gave alternate valuations of different Indian “unicorns” by accounting for the downside protection clauses that come with startup investment.

Money quote:

This implies that a share of the company held by [investors] includes a long put option, while a share of the company held by earlier investors includes a short put option (since they have implicitly written this option). In other words, a share held by the new investors is worth much more than a share held by earlier investors.

Now comes news that Global Fashion Group (that includes Jabong and a few other fashion houses started by Rocket Internet) has raised money at a “down round”. This gives me a good opportunity to put my theory to practice.

GFG has now raised $339M for a headline valuation of $1.13 billion. In its earlier round, it had raised $169M for a headline valuation of $3.5 billion. Let us look at a hypothetical employee of GFG who owned 0.1% of the company before the previous round of investment, and see what these shares are worth now.

Absence of ratchets

GFG had a “pre-money” valuation of $3.33 billion, and 0.1% of that would have been worth $3.33 million. As of that round of investment, existing investors had 95% stake in the company, so our friend’s share of the company would have come down to 0.095% (95% of 0.1%).

The new round shows a pre-money valuation of $791 million, and so our friend’s stock would be worth $750,000 after the latest round of valuation. This is a comedown from the previous valuation, but is still significant enough.

Presence of ratchets

Let’s assume that the previous round of investment into GFG came with a full ratchet (we’ll look at other downside protection instruments later). This would mean that its investors in that round would have to be compensated for the drop in valuation.

Investors in the previous round put in $169M for a headline valuation of $3.33Bn. The condition of the full ratchet is that is that if this round’s pre-money valuation were to be less than last round’s post-money valuation, the monetary value of last round’s investors has to be the same.

So despite this round showing a pre-money valuation of only $791M, last round’s investors would claim that $169M of that belongs to them (the way this is achieved in an accounting context is that the ratio in which their preferred shares convert to common shares changes). So the earlier investors (who came before last round) see the value of their shares go down to a paltry $622M. From owning 95% of the company, the down-round means they only own 79% now. And that is before the new round has come in.

Investors in the new round have put in $339M for a headline valuation of $1.13Bn, giving them a round 30% stake. Earlier investors have a 70% stake, of which investors who came before the previous round (which includes employees like our friend) have a 79% stake, giving them a net stake of 55%.

Coming back to our friend, remember that he owned 0.1% of the shares before the last round of investment. The ratchet means that he owns 0.1% of 55% of the company’s current headline valuation. This values his shares at $622,000.

But not so fast – since this assumes that the latest round of investment has no ratchets. If we need to take into consideration that this round has a full ratchet as well, the option formula I used in the Mint piece says that GFG is now worth $760M, far lower than the $1.13Bn headline valuation.

This implies that the stock held by investors prior to this round is now worth only $421M ($760M – $339M). Investors prior to the last round held 79% of these shares, so their stake is worth $331M now. Our friend held 0.1% of that, so his stake is only worth $331,000.

In other words, if both the previous and current rounds of investment in GFG came with a full ratchet protection, the shares held by ordinary investors such as our friend would have lost 56% of its value on account of optionality alone! Notwithstanding the fact that the remaining shares are held in a company whose value is on the downswing!

Then again, downside protection for investors could have come by other means, which were less harsh than full ratchet. Nevertheless, this can help illustrate how much of founders’ and employees’ shareholder value can be destroyed using ratchets!

InMails and the LinkedIn backfire

A few months back I cleaned up my connections list on LinkedIn. Basically I removed people who I don’t “know”. I defined “know” as knowing someone well enough to connect them to someone else on my network (the trigger for a cleanup was when someone asked me to connect them to someone else on my network who I hardly knew).

The interesting thing about the cleanup was that a lot of the spurious connections I had on LinkedIn were headhunters. Thinking back at how they got in touch with me, in most cases it was with respect to a specific opportunity for which they were finding candidates. Once the specific opportunity had been discussed there was no value of us being connected on LinkedIn, and were effectively deadweight on each other’s networks.

Over the last couple of days, ever since I wrote this piece for Mint on valuation of startup ratchets, I’ve got several connection requests, all from people I don’t know. Normally I wouldn’t accept these invitations, but what is different is that most requests have come with non-standard messages attached. Most have mentioned that they liked my Mint piece and so want to either connect or discuss it.

When you want to simply exchange messages with someone, there is no need to really add them as a “friend”. Except that LinkedIn’s pricing policy makes this kind of behaviour rational.

LinkedIn offers a small number of “InMails” which you can send to people who you aren’t directly connected to. Beyond this number, each InMail costs you money. So if you want to have a discussion with someone you’re not connected with, there’s an element on friction.

There’s a loophole, however. You can send messages for free as long as they go along with a connection request. And if that request is accepted, then you can have a “free” conversation with that person.

So given the current price structure, if you want to have a conversation with someone, you simply send your initial message as part of a friend request. If the person wants to continue the conversation, the request will get accepted. If not you haven’t lost anything!

Then again, there are mitigating features – an InMail won’t get charged unless there is a reply, and LinkedIn’s UI is so bad that it takes effort to read messages attached to connection requests. So this method is not foolproof.

Still, it appears that LinkedIn’s pricing practice (of charging for InMails) is destroying the quality of the network by including spurious links. I guess they’ve done a cost-benefit analysis and believe that the cost of spurious connections is far lower than the revenue they make from InMails!

 

The problem with premium ad-free television

I watched snippets of the just-concluded ICC WorldT20 final using an illegal streaming service, which streamed content drawn from SkySports2.  The horrible quality of the streaming aside (the server seemed to have terrible bandwidth issues), the interesting thing to note was that it was completely devoid of advertisements.

With the quality of cricket coverage in India currently being abysmal due to the frequent cutting for advertisements (I remember getting thoroughly pissed off with the cuts for advertisements before the replay of a wicket was shown during the India-Australia series earlier this year), it made me think about the economics of a separate premium service that is ad-free.

The infrastructure for delivery is in place, given that internet-based legal streaming services are fairly common now (the likes of HotStar). Internet-based delivery also makes it easy to charge pay per view, so payment is also not a problem. This raises the question of whether it is a good idea for channels to monetise the demand for ad-free cricket by providing the service through online streaming, leaving the mainstream broadcast to be monetised via advertisements.

While in theory this appears like a good idea, the problem is with the kind of people who will migrate to the new service – they will be people who have the ability and willingness to pay for a higher quality broadcast. Such people are likely to belong to two overlapping categories – loyal fans of the game and people who can afford to pay a premium.

It is unlikely that the union of these two sets will comprise of too high a proportion of the overall viewership of the game, but the point is that these are the two groups who are likely to be most lucrative to advertisers – the loyal fans watch regularly and the people who are able to pay have more disposable income.

Moving such customers to an ad-free online channel might reduce the supply of advertisements which can be used to reach them, and this might not make advertisers happy. And given that television channels have cosy relationships with advertisers (or at least media buyers), they are unlikely to piss them off by moving the most lucrative customers to a premium platform.

Of course if this segmentation (between ad-free and free broadcasts) is implemented, it will also impact the price of advertisements in the free broadcast. That will need to be taken as an input while setting prices for the ad-free service. In other words, pricing is going to be a challenge!

If some television channel wants to work on this, I’m available for hire as a consultant. I’ve done a fair amount of prior work on pricing and dynamic pricing, am pretty good at quantitative methods and am in the course of writing a popular economics book.