Making Zero Rating work without disruption

The Net Neutrality debate in India has seen a large number of analogies being raised, in order to help people understand and frame the debate. Internet services have been variously compared to television, postal services, highways, markets and what not. Things got so bad that that at some point in time people had to collectively denounce all analogies, for they were simply taking away from the debate.

One of the analogies that were being drawn in an argument in favour of Zero Rating was to compare it to e-commerce companies that provide free shipping, for example, or the deep discounts provided by services such as Uber or Ola. If you ban zero rating, other legitimate activities such as free shipping will be next, critics of net neutrality argued, arguing that there would be no end to this. The counter-argument is that free shipping doesn’t disrupt the basic structure of the market while zero rating does. Here is a way in which zero rating can be made to work without disrupting the market.

And it is a rather simple one – cash transfers. Rather than an e-commerce company subsidising your browsing of their website directly (by paying the telecom provider to make your access free), they can instead refund your costs of browsing their sites in terms of a discount. Going back into the analogy space, this is similar to malls that charge you heavily for parking but then offset your parking fees against any purchase you make in the mall.

So Flipkart, for example, can estimate the amount of bandwidth a particular user would have spent in browsing their app (not hard to track at all, especially if the user uses the app), and any purchase on their site can be appropriately discounted to that extent (and maybe a little more to cover for browsing that didn’t lead to a purchase).

This works in several ways. In the current proposed model of Zero Rating, the e-commerce company doesn’t know how many users will access it, using each ISP, so there is uncertainty in the amount that they have to pay the ISPs for such access. By moving to a user-wise subsidy model, they know exactly what users are using how much, and this enables them to target the subsidies much better. Another way in which it helps the retailer is that it doesn’t waste money spending on bandwidth for people who only browse the website without buying (of course, if they wish to, they can subsidise such usage also, but since it can be so obviously gamed, they won’t do it).

More importantly, what such a system ensures is that the internet is not broken. You might recall my earlier post on this topic that zero rating results in “walled gardens” that leads to a broken internet which reduces the overall value of the internet. With a cash transfer scheme (rather than direct subsidy), such distortions are avoided, and the internet remains “free” (of any barriers, not free of cost) and maximum value of the internetwork is realised.

So as described above it is well possible for e-commerce players to subsidise users’ browsing of their apps without distorting the internet, and without using zero rating. And as shown above, doing so is in their interest.

PS: This post also came out of the same discussions from which my earlier post on 2ab had come out.

How Long Tail affects pricing

My late mother never shopped for fruits and vegetables in the Gandhi Bazaar market. She found that the market was in general consistently overpriced, and if we look at the items that she would buy, it is still the case. For “normal” stuff, you are better off going to nearby “downmarkets” like the one at NR Colony, or even Jayanagar Fourth Block.

So why is the Gandhi Bazaar market overpriced? The answer lies in the long tail. In the book of the same name, Chris Anderson talks about products that are not the most popular, but which has a niche demand. In that he talks about companies such as Amazon or Netflix which are successful not because they do a better job of selling the “bestsellers” but because they are able to service well the “long tail” – items that are not found elsewhere thanks to the high cost of selling.

In other words, it is a liquidity story. If the neighbourhood kirana, for example, wants to sell olives, his costs are going to be high as the rate at which he sells olive bottles is going to be so low that his inventory costs are going to increase, and the risks of ageing and spoilage of inventory also goes up. And he has to spend that much more manpower and effort in managing this extra item, so he decides to not sell this item at all (he will have to charge such a high premium to sell such goods that it doesn’t make sense for the customer to buy it).

Yesterday I bought an “imam pasand” mango in Gandhi Bazaar. Now, this is not one of the “standard” mango varieties that are available in Bangalore. In fact, I had never in my life eaten this variety of mango until yesterday, for the simple reason that it is not generally available in Bangalore. The fruit stall in Gandhi Bazaar, however, stocked it. A neighbouring fruit stall was where I used to source the Dashehri mangoes (common in North India but rare in Bangalore) a couple of mango seasons back. Avocados, which are generally hard to find in “traditional” retailers in Bangalore were also available in every fruit stall in Gandhi Bazaar, as were other not-so-common fruits.

So why did my mother find Gandhi Bazaar expensive? The answer is that the fruit sellers at Gandhi Bazaar stock the “long tail” because of which their general costs of inventory are high compared to competitors who don’t. Thanks to the range, they will have a large number of customers who come to them to buy specifically these “long tail” items. And while they are at it (buying the long tail items), they also end up buying some “normal” items. Customers who come seeking the long tail are usually those that are willing to pay a premium, and thus the shops in Gandhi Bazaar are able to charge a premium for the non long tail items also.

 

Thus, if you purely look at rates of “common” items, Gandhi Bazaar, a market which offers the “long tail” will always be more expensive than other markets. Anecdotally, along with the Imam Pasand yesterday, I also bought a kilo of “vanilla” Raspuri mangoes, at the rate of Rs. 100 per kg. At the shop down the road, Raspuri was available for Rs. 90 per kg. The shop down the road, however, doesn’t stock Imam Pasand, which means that the price of Imam Pasand in that shop is infinity.

So if you are only looking to buy Raspuri, you are better off going to the shop down the road. If you either want only Imam Pasand, or both Imam Pasand and Raspuri, though, you should go to Gandhi Bazaar! In other words, the “range” that the fruit seller in Gandhi Bazaar offers implies that he can get away without discounting. Theoretically speaking, though, we can say that the fruit seller in Gandhi Bazaar actually discounts on the long tail items by the sheer act of stocking them (thus dropping their price from infinity to a finite number), and he is using this discount to sell his “normal” goods at “full price”. Ruminate on it, while I go off to devour a mango!

 

Startup equity and the ultimatum game

The Ultimatum Game is a fairly commonly used game to study people’s behaviour, cooperation, social capital, etc. Participants are divided into pairs, and one half of the pair is given a sum of money, say Rs. 100. The objective of this player (let’s call her A) is to divide this money between herself and her partner for the game (whom we shall call B). There are no rules in terms of how A can divide the money, except that both sums need to be non-negative and add up to the total (Rs. 100 here).

After A has decided the division, B has an option to either accept or reject it. If B accepts the division, then both players get the amounts as per the division. If B rejects the division, both players get nothing.

Now, classical economics dictates that as long as B gets any amount that is strictly greater than zero, she should accept it, for she is strictly better off in such a circumstance than if she rejects it (by the amount that A has offered her). Yet, several studies have found that B often rejects the offer. This is to do with a sense of “unfairness”, that A has been unfair to her. Sociologists have found that certain societies are much more likely to accept an “unfair division” than others. And so forth.

The analogy isn’t perfect, but the way co-foundes of a startup split equity can be likened to a kind of an ultimatum game. Let’s say that there are two people with complementary and reasonably unique skills (the latter condition implies that such people are not easily replaceable), who are looking to get together to start a business. Right up front, there is the issue of who gets how much equity in the venture.

The thing with equity divisions between co-founders is that there is usually not much room for negotiation – if you end up negotiating too hard, it creates unnecessary bad blood up front between the founders which can affect the performance of the company, so you would want to get done with the negotiations as soon as possible. It should also be kept in mind that if one of the two parties is unhappy about his ownership, it can affect company performance later on.

So how do the founders decide the equity split in this light? Initially there will be feelers they send to each other on how much they are expecting. After that let us say that one of the founders (call him the proposer) proposes an equity division. Now it is up to the other founder (call him the acceptor) to either accept or reject this division. Considering that too much negotiation is not ideal, and that the proposer’s offer is an indication of his approximate demand, we can assume that there will be no further negotiation. If the acceptor doesn’t accept the division that the proposer has proposed, based on the above (wholly reasonable) conditions we can assume that the deal has fallen through.

So now it is clear how this is like an ultimatum game. We have a total sum of equity (100% – this is the very founding of the company, so we can assume that equity for venture investors, ESOPs, etc. will come later), which the proposer needs to split between himself and the acceptor, and in a way that the acceptor is happy with the offer that he has got. If the acceptor accepts, the company gets formed and the respective parties get their respective equity shares (of course both parties will then have to put in significant work to make that equity share worth something – this is where this “game” differs from the ultimatum game). If the acceptor rejects, however, the company doesn’t get formed (we had assumed that neither founder is perfectly replaceable, so whatever either of them starts is something completely different).

Some pairs of founders simply decide to split equally (the “fairest”) to avoid the deal falling through. The more replaceable a founder or commoditised his skill set is, the less he can be offered (demand-supply). But there are not too many such rules in place. Finally it all boils down to a rather hard behavioural problem!

Thinking about it, can we model pre-nuptial agreements also as ultimatum games? Think about it!

The Box: A review

So over the weekend I started and finished reading “The Box: How the shipping container made the world smaller and the world economy bigger” by Mark Levinson. It’s a fascinating book, and one that I had been intending to read for a very long time. Somehow it always kept slipping my mind whenever I wondered what book to buy next, and I’d pushed buying it for a long time now.

Finally, a few days back, when “unknown twitter celebrityKrish Ashok asked his followers to send him reading recommendations, and when he published the list, and I saw this book on the list, and I saw that the book was available on Kindle for Rs. 175, I just bought it. This is the first book in a very long time that I’ve bought “straight” off the Kindle Store, not bothering with a sample.

It’s a fascinating book, as it takes us through the 50-odd years of history of the shipping box. And on the way, it gives us insights into the development of the world economy through the 50s and 60s, and factors that led to the logistic revolution ushered in by the box.

We think of post world war America as this capitalist haven, where markets were free, and you could get jailed for communist leanings. We tend to think about this time as one of innovation and freedom of business, leading to high economic growth.

This wasn’t the case, though. While the US was nominally capitalist and markets were supposedly free, this was a time of heavy regulations, and the presence of cartels. International shipping rates, for example, till the mid-1970s, were set by “conferences” (basically cartels), after which the cartels broke down. It was not possible for a carrier to quote an integrated source-to-destination rate, and rates had to be quoted by leg. Someone who wanted to start a new train route had to prove to the regulators that it would not harm existing players!

And then there were the unions. Levinson devotes an entire chapter to how the unions were managed. Basically containerisation meant greater mechanisation and a reduction in demand for labour. And this was obviously not acceptable to the dockworker unions, and led to protracted battles which needed to be resolved before containerisation could take off. The most interesting story came from the UK, where unions in most established ports (primarily London and Liverpool) blocked containerisation, and went on strike in the specially developed container port at Tilbury. Felixstowe, which had hitherto been too obscure a port to attract unions’ attention, now unencumbered by unions, jumped on to the container business and is now by far the UK’s biggest port.

Levinson also pays much attention to how the container shaped economies in general. Prior to containerisation, the cost of changing mode of transport was very high, since individual items needed to be unloaded from one means of transport and loaded to another. Industries were usually located based on access to port, and ports came up to service nearby industries. Containerisation changed all that. Now that it was easy to transport using a series of different means of transport, the location advantage of being close to port was lost. And this had massive effects on the economy of regions.

Massive effects on economies also happened due to the scale factor that containerisation brought in. Small ports didn’t make any sense any more, since the transaction cost of berthing was too high. And so small ports started dying, with business being soncolidated into a few larger ports. The game changed into a winner take all mechanism.

In the 1950s and 60s, before the coming of the container, shipping was a low-capex high-opex (operational expenditure) business. Most ships were old and cheap, but costs in terms of labour and other things was high. With the coming of the containership, the cost structure inverted, with the capital expenditure now being extremely high, but opex being quite low. This led to “revenue management”, and a drop in prices, and ultimately the breaking of the cartels.

The book is full of insights, and chapters are organised by subject rather than in chronological order. It gets a little repetitive at times, but is mostly crisp (I read it in a weekend), and the insights mentioned above are only a sample. And it tells us not only the story of the box (which it does) but also the story of the world economy, and regulation, and competition, and unionisation and economies of scale. Highly recommended.

 

Why Google, Facebook, etc. are against Net Neutrality in India

I’ve been out of country for close to a month now, so haven’t really been following India news too closely (apart from via social media). But from my (biased :) ) sources I understand that TRAI has put out a discussion paper in which they want to permit telecom companies to charge you based on the service that you use, thus violating Net Neutrality.

Now I’m yet to take a stand on this (this argument by Tim Harford against Net Neutrality is rather compelling, making me believe that well implemented competition regulations can mean we can make do without Net Neutrality, but I haven’t given it too much thought yet), but I have an idea as to why the likes of Google and Facebook, which in the past and in other geographies have come out strongly in favour of Net Neutrality, are okay with Net Neutrality violation in India.

The basic issue in India is with “over the top” services such as WhatsApp and Viber which the likes of Airtel and Vodafone see as a threat for it competes with their rather lucrative voice and SMS business. I’ve mentioned in the past that there’s a quality issue here which the telecom companies can differentiate on (packet switching doesn’t work that well for voice), but given costs it is hard to make a compelling case for using circuit switching for international calls.

So the likes of Airtel and Vodafone are threatened by such services and want to charge users more for using WhatsApp and Viber compared to other applications. Net Neutrality supporters, who argue that internet infrastructure should just be a set of neutral pipes (rather than a “two-sided platform”, as Harford argues), argue that this is unfair, and that Airtel and Vodafone are exploiting their positions as gatekeepers (literally) to defend their own related business.

Coming to the point of this post, entities such as Google and Facebook are coming out on the “wrong” side of the net neutrality debate here in India, arguing that internet companies should be looked at as two-sided platform markets rather than neutral pipes (resisted the urge to use the phrase “information superhighway” there!). Considering that they’re proponents of Net Neutrality elsewhere, why are they taking this stance in India?

Assuming that final regulations come out in favour of net neutrality (treating internet as infrastructure, and not a platform), how should the likes of Airtel and Vodafone react? Clearly their data business is cannibalising their voice business, so they should logically increase their prices for data plans (no brainer). Given that they will not be allowed (in this situation) to charge differential rates based on the service, they will have to uniformly jack up data rates.

This can be troublesome for Google and Facebook on two counts. Firstly, the telecom providers may not get their pricing right, and rather than having a ramp (charging heavy users heavily, since only such people will be using WhatsApp or Viber), they might increase data rates across the board. This will result in a drop in mobile internet penetration (one reason it’s so high now is that it’s cheap), and considering that Google and Facebook are services that pretty much every who uses the internet in India uses, it will result in loss of user base, traffic and revenue (possibly) for them.

The second problem is that even if telecom operators get their pricing right (maintain current pricing for basic plans, but jack up rates for high data usage) it spells trouble for Google and Facebook. One of Google’s widely used services is the video streaming application Youtube, and Youtube consumes high bandwidth. Facebook is getting into native video in a big way, and it is estimated that it might be more successful than Youtube in terms of advertising. And with correct internet pricing under net neutrality, demand for services such as Youtube and Facebook Video will go down significantly, which is not good for those services.

So the simple answer is that the reason Google and Facebook are coming out against Net Neutrality is that they are coming out on the right side of the new proposed (anti neutrality) regulations. Like WhatsApp and Viber, they too are high bandwidth applications, but unlike WhatsApp or Viber they don’t compete directly with the owners of the pipes. Thus, they want providers to have the ability to impose differential pricing, since that will mean that subscribers can access their content for cheaper, and this allows them to make more advertising revenues.

In my view (again note that I’m yet to take a stand on this net neutrality business), this move by Google and Facebook to support the anti-neutrality regulations is extremely short-sighted since it can hit them back at a later point in time. There is no guarantee that in the long term their services will not compete with that of telecom providers (Hangouts? Facebook voice calling?) and the regulations that they are currently supporting can come back to hit them at a later point in time.

It seems that Google and Facebook are working on an assumption that there will not be other high-bandwidth applications that will compete less with pipe-owners (telecom operators) than them (Google & Facebook). They are very likely to be in for a surprise, and end up as the cranes in this Panchatantra story.

Useless LinkedIn

I’m not a big fan of LinkedIn. I mean, I use it, and fairly regularly at that (check it at least once a day), and I think conceptually it’s quite useful. However, in practice, I think there are a number of sticking points about the service, which makes it quite useless.

For starters its apps (iPad and Android) are quite lousy, and offer nowhere close to the kind of experience that the web interface offers. Things are extremely unintuitive (down to the tabbing order – you compose message, hit tab and enter, and you don’t send the message. It takes you to the profile of the person you’re messaging instead) on the website. Sometimes the apps show notifications even after you’ve checked them on the web, and so on.

In other words it’s an extremely poorly engineered product, but which is surviving (and thriving) thanks to network effects!

I might have commented on this in the past but there is this thing on endorsements. This was something that coincided with the time when LinkedIn went public (if I’m not wrong), and you could endorse people for their “skills” on LinkedIn. For a while I played along with the game. But then I completely lost it when a distant uncle who I’m sure has never traded derivatives endorsed me for “derivatives”. I quickly deleted my skills.

Then there are the LinkedIn recommendations, which has inherent selection bias and hence adds no value. And then you have the “say goncrats” feature, where LinkedIn prompts you to “say congrats” on people changing jobs or hitting job anniversaries. I’ve found this mildly useful (dropping a note when someone switches jobs is a good way to stay in touch), but there are the bugs in terms ofjob downgrades and people getting fired.

And of late, there has been serious spam in terms of people’s status updates. I don’t know when it became popular to post silly puzzles on professional networking sites, yet I find several of them popping up on my timeline every day, and the number of people who have shared each is not funny. Then you have these cartoons (Dilbert and the copycats), and “guru quotes” that appear in the form of images that further spam your timelines! The only way I can think of these being useful is that they act as a negative indicator when you’re checking out the profile of someone you are looking to hire or do business with!

To summarise, LinkedIn seems to be an extremely badly engineered product on several counts, but thanks to network effects (so many people are already on it that entry barriers for competitors are really high) the site still manages to do well! I wonder what it will take to disrupt it. Facebook for business is not the answer for sure – the potential havoc caused by a breach in chinese walls there will scare people enough to not sign up.

What do you think? Here is their stock price movement for reference:

 

 

Uber’s new pricing structure

So Uber has changed its pricing structure in Bangalore. Earlier they nominally charged Rs. 50 fixed, Rs. 15 per kilometer and Rs. 1 per minute, and then slapped a 35% discount on the whole amount. From today onwards the new fare structure is Rs. 30 fixed, Rs. 8 per kilometer and Rs. 1 per minute, without any further discounts. They’re marketing it using the Rs. 8 per kilometre number.

I took a ride this afternoon under the new fare structure, and the bill was Rs. 152, about the same as it would have been under the old fare structure. In that sense, I guess this was an “average ride”, in terms of the distance by time covered. This was the kind of ride where their assumption on distance travelled per unit time (in coming up with their new formula) was exactly obeyed!

So how do we compare the old and new formulae? We can start by applying the discount on the nominal numbers of the old formula. That gives us a fixed cost of Rs. 32.5, a per kilometer cost of Rs. 9.75 and a per minute cost per 65 paise. We can neglect the difference in fixed cost. Comparing this to the new cost structure, we find that the passenger now gets charged a lesser amount per kilometre, but a higher amount per minute.

In face, taking the “slope” between the old and new rates, the per kilometre cost has come down by Rs. 1.75 while the per minute cost has risen by 35 paise. Taking slope, this implies that Uber has assumed a pace of a kilometre per five minutes, or twelve kilometre per hour.

So if your journey is going to go slower than twelve kilometres per hour, on average, you will end up paying more than you used to earlier. If your journey is faster than twelve kilometres per hour, then you pay less than you did under the previous regime.

A few implications of the new fare structure are:

1. Peak hour journeys are going to cost more, for they are definitely going to go slower than twelve kilometres an hour
2. Your trips back from the pub should now be cheaper, for late nights when the roads are empty you’ll travel significantly faster than twelve kilometres an hour
3. What does this imply for the surge pricing in the above two cases? I think the odds of a surge during peak office hours will come down (since the “base price” of such a trip goes up, which will push down demand), and  the odds of a surge late on a Friday or Saturday night might go up (since base fare has been pushed down for that).
4. The Rs. 30 fixed cost implies that if a driver travels at 12 km/hr when looking for a new ride, the gap between rides for a driver is 11.5 minutes (if the driver spends X minutes, he will travel X * 12/ 60 kilometres in that time. The compensation for this combination is X + X*12/60 * 8, which we can equate to 30. This gives us X = 11.54).
5. Trips to/from the airport will now be cheaper, for you can travel much faster than 12 km/hr on that route. So Uber will become even more competitive for airport runs. Again this might increase probability of a surge at peak flight times.

I continue to maintain that Uber has the most rational price structure among all on-demand taxi companies, since the fare structure fairly accurately mirrors drivers’ opportunity costs. Ola doesn’t charge for the easily measurable time, and instead charges for “waiting time”, which is not well defined. Ola also has a very high minimum fare (Rs. 150). I wonder how they’ll play it if their planned acquisition of TaxiForSure goes through, since TaxiForSure was playing on the short trip model (with minimum fares going as low as Rs. 49). Given the driver approval before a ride, though, I doubt if anyone actually manages to get a Rs. 49 ride from TaxiForSure.

Times continue to be interesting in the on-demand taxi market. We need to see how Ola responds to this pricing challenge by Uber!