India – Platform Business Firms

App-in-app?

I recently got an email from my airline app that I could book my car ride within the same app. It was a way of providing end-to-end services. Much like the home pickup and drop service provided for business class customers by the Emirates. What are the implications of these for the customer, the airline, and the cab-hailing firm? Let’s explore.

It is an app-redirect

First, read the terms of how it works in the case of Jet Airways and Uber here. The substantive part of the T&C is hidden in the paragraphs quoted below:

“PLEASE NOTE, YOU ARE MAKING THE PAYMENT TO UBER DIRECTLY. JET AIRWAYS IS NOT RESPONSIBLE / INVOLVED IN THIS FULFILMENT PROCESS. JET AIRWAYS WILL NOT BE LIABLE AND/OR RESPONSIBLE FOR REFUNDS, DELAYS, REJECTIONS, PAYMENT AND FULFILLMENT OR OTHERWISE OF THE SERVICES OR IN RESPECT OF ANY DISPUTES IN RELATION THERETO, IN ANY MANNER WHATSOEVER.” (emphasis original)

Then, what is the value of this app-in-app integration?

Customer perspective

For the customer, it has the potential to work as a seamless end-to-end service. I imagine a future, where you would find a partner using Tinder or TrulyMadly, plan your evening to a game/ movie using BookMyShow, find a restaurant & book your table using Zomato, and take Uber whenever you are ready to move on, or better still, have an Ola Rentals car waiting for you through the evening. All in one app. Wouldn’t you love it, if all of it were integrated in one App? Just imagine the convenience if your restaurant-finder knew that you are in a particular concert at a specific place and you are likely to head out for dinner at a particular time. This specific knowledge could immensely help your restaurant-finder app to customize the experience for you – for instance, it could not only provide you those restaurant options that are open late in the evening after the concert was over, in a location that is close to the venue; it could possibly alert the restaurant that you were arriving in 15 minutes, based on your Uber location. And through the evening, post your pictures on Instagram and SnapChat, check-in to all those locations in Facebook, and Tweet the experience live.

Yes, you would leave a perfect trail for the entire evening in a single place, and if you were to be involved in an investigation, it would be so easy for the officer to trace you! No need for Sherlock Holmes and Watson here – the integrator app would take care of all the snooping for you!

Convenience or scary? What are the safeguards related to such data sharing across different entities? How will the data be regulated?

The Integrator perspective

Why would a Jet Airways provide an Uber link inside its App? Surely cab-hailing and air travel are complementary services. Plus, Jet Airways believes that its customers would find it convenient to book an Uber ride from within the Jet Airways app, as they trust the app to provide Uber with all the relevant details – like the estimated landing/ boarding time of the flight, drop/ pickup addresses, etc. Jet Airways also needs to believe that its customers would rather choose an Uber cab, rather than its competitor OLA Cabs, or any other airport taxi service. The brands should have compatible positioning. Given that Jet Airways is a full service carrier, and differentiates based on its service quality, Uber might be a good fit. But the same might not hold good for a low-cost/ regional carrier like TruJet connecting cities like Tirupati, where Uber does not operate.

Does integrating complementary services affect customer satisfaction, brand loyalty, customer switching costs, and/or multi-homing costs? In contexts where these services and brands are compatible, and there is a convenience involved in sharing of data between these services, there is likely to be some value added. Like airlines and hotels (hotels would like to know your travel schedule); currency exchanges and international travel (the currency exchange would love to know which countries you are visiting); or international mobile services. If there was no data to be shared between the complementary services, the user would rather have them unbundled. Think travel and stock brokerage.

That said, platforms find innovative complementarities. For instance, airlines (primarily the full-service carriers) have launched co-branded credit cards. In a recent visit to Chennai, there were more American Express staff at the Jet Airways lounge than the airline or lounge staff! And they were obviously signing up customers. What are the complementarities between credit cards and air travel, apart from paying from that card? A lot of business travellers have their business travel desks do the payments; consultants have their clients booking the tickets; and even for individuals and entrepreneurs, the credit card market is so fragmented that everyone holds multiple cards. And the payment gateways accept all possible payment options, including “paying cash at the airport counter”. They why co-brand credit cards – sharing of reward points/ airline miles. Either customers do not earn sufficient airline miles and using these co-branded credit cards help them earn more miles and retain/ upgrade their airline status (remember the 2009 movie, Up in the Air?); or they do not earn enough reward points in using their credit cards that they can redeem their airline miles as credit card reward points. Either ways, each one is covering up for the other.

In this covering up, or more diplomatically consolidation of rewards, the partners increase customer switching and multi-homing costs. Surely, redeemable airline miles might be more valuable to a frequent traveller than credit card reward points that have limited redemption/ cash back opportunities. But for loyalty to increase, it is imperative that both brands stand on their own – providing compatible services.

Mother of all apps

All this looks futuristic to you? A lot of you have been using an ubiquitous desktop app known as the browser for a long time, which has been doing exactly this! In a subtle form, though. However, there are firms that own multiple such apps, and they use a single sign-on – like all of Google services. Plus, even third-party sites like Quora allow for using your Google credentials to sign-in. The trade-offs are not always explicitly specified – it is always the case of caveat emptor – consumer beware.

So, the next time you experience some cross-marketing across platforms/ apps, think what data might be shared across both the apps; and if you would really value the integration.

Cheers!

FirstCry.com: Leveraging the power of offline

In my blog post last week, I wrote about how a hybrid online and offline strategy is useful for collecting small data. As a couple of my readers pointed out, what marketers and strategists call small data, ethnographers and sociologists call as thick data. Honestly, I had not heard of thick data. @fernandogaldino introduced thick data to me. I dug through the online references on thick data, and realized we are talking the same thing. Exactly the same thing. Thank you Fernando! So, I am going to continue using the term small data (that is what I have read academic articles about) with the caveat that small data is also thick data. Last week, I promised to delve deep into FirstCry.com and its online-offline strategy. Here it goes.

FirstCry.com

The firm was founded by Supam Maheshwari and Amitava Saha in 2010 as a pure online venture. By 2011, FirstCry.com opened its first offline stores. In an interview to TechCircle, co-founder Supam Maheshwari elucidated how a vertically focused ecommerce firm could survive and make money in a market dominated by horizontally spread competitors (you can read the interview here). He talked about replicating Quidsi’s business model in the Indian market, by owning a set of vertical markets like diapers.com and soap.com. In replication, firstcry.com has a sister website goodlife.com. The key difference, he said, between the Indian and the US market for baby care products was that, more than 95% of the products were imported. In fact, that was the seed for the enterprise – his own difficulty in finding good quality products for his child in India, whereas he could buy a lot of them during his international travels. That effectively makes this business inherently inventory-heavy. One needs to leverage economies of scale and scope in sourcing, hold inventory and invest in logistics to be able to service customers across the length and breadth of the country (read about firstcry.com inventory model here).

Omni-channel strategy

Here is where the omni-channel strategy helps. Instead of keeping inventory in dark warehouses, ready to be shipped, it was possible for firstcry.com to open retail outlets in tier II and tier III cities (where real estate was also likely to be cheaper), where ecommerce penetration was not as much as the tier I cities and the metros like Mumbai, Delhi, or Bangalore. The inventory holding was thus distributed across the various franchised retail outlets. The outlets also provided customers with the look and feel of the products before they bought them – you need to appreciate that baby apparel and shoes dominate the market, only to be followed by toys and diapers. Clothes and shoes … when was the last time you bought your own shoe purely online? Inventory provided increased footfalls to the store, created brand awareness, and inventory off-take. The decision to have the same prices between online and offline stores, coupled with large touch screen interfaces to shop online from within the offline store could have provided exponential growth in traffic and sales.

Promotion: The FirstCry Box

Firstcry.com began promoting using traditional mass media – television and online ads. They invested in Bollywood’s longest serving (possibly) celebrity, Mr. Amitabh Bachchan as their brand ambassador and launched a few television advertisements (see some of their ads on YouTube here). However, they soon realized that mass media advertising was highly expensive and yielded low returns for a niche range like baby care products. That is when the idea of the FirstCry Box was born. The FirstCry Box is a bundle of some essential products that the mother would need during the first few days of the baby and mother reaching home from the hospital. Firstcry.com has agreements with over 6000 hospitals, through which these FirstCry Boxes are gifted to the new mothers, congratulating them on the birth. These boxes also contained gift and discount coupons from major brands of baby products, that the parents could redeem at either online at firstcry.com or any of their retail outlets. This ‘welcome kit’ to parenting provided firstcry.com a significant opportunity to build brand equity and recall amongst the over 70000 mothers receiving these kits every month. Some marketers call this permission marketing (read about it here), or direct-to-parents strategy. For me, it is a wonderful platform, a two-sided platform mediated by firstcry.com. Parents, especially first-time mothers, are initiated into parenting with the help of these grooming products (basic diapers and lotions) and the gift coupons for free. The new mothers as a subsidy side is being financed by the brands that provide the products and coupons to be included in the box and act as the money side in the platform. For the brands, this is highly targeted sampling of their products, and most mothers would stay loyal to quality brands/ retail stores in baby products. In the entire transaction between the mothers and the brands, firstcry.com benefits significantly in three ways: (a) store loyalty resulting in increased sales, (b) small data about how these mothers use these products, the basket, frequency of purchase, and willingness-to-pay for quality; and (c) good quality prediction of demand in specific geographies, leading to efficiencies in inventory and supply chain management practices.

By the way, such welcome kits are not entirely new – a lot of employers have been on-boarding their employees with such welcome kits. I first heard/ saw such welcome kits when I was part of a team that delivered a customized training programme for the ITES service provider ADP India, a few years back. It was fascinating to see how the entire family was on-boarded into the firm! Not just ADP, a variety of other new age firms, I see have adopted this practice (read this article on how some Indian organizations welcome their employees). I wish I was welcomed like this by my employers!

Are hybrid models here to stay?

I would say, yes. We saw how Amazon was opening stores in our blog last week. We also discussed how Amazon.in was using firms like StoreKing to reach the Indian retail hinterland. I read last week that their Indian competitor, Flipkart.com was also opening offline store to reach users in small cities (Flipkart to open offline stores as well). And in vertical markets like baby products, it has become all the more important to target your promotion very narrowly, and focus on the backend (inventory, supply chain, and logistics) efficiencies, while at the same time achieve scale.

Is vertical ecommerce a winner-takes-all market?

Three industry conditions define a platform market as a winner-takes-all market: presence of strong cross-side network effects, high multi-homing costs for the users, and the absence of special requirements. The baby products retail market is dominated by imported brands, is a highly fragmented industry, and the brand owners are dependent on their retail partners to promote their brands. The demand for these products are relative price inelastic, and consumers would be willing to pay premiums for sustained quality and reliability. An aggregator platform like firstcry.com would significantly aid in establishing and reinforcing the cross-side network effects between the brands and consumers. Second condition – the quality and reliability concerns of the parents would ensure significant store loyalty and brand loyalty. As long as there are no serious concerns, consumers would be loath to switch; and when the fill rates are high (there are no stock-outs of items that they want to buy) in their preferred stores, would not multi-home. In other words, consumer switching costs for brands are high, and as long as these brands are available with their favorite retailer, they would not shop from multiple outlets. And most infants have the same needs – diapers, creams, lotions, oils, and basic toys. Special preferences begin showing up only when they ‘grow up’. Some of them don’t ever grow up, but that is a different matter!

Firstcry.com and BabyOye merger and further consolidation

Given the industry conditions of geographically distributed year-round demand, operational efficiency and leveraging economies of scale and scope become key success factors. Consolidation is inevitable to achieve both backend (sourcing, inventory, and supply chain/ logistics) efficiencies as well as frontend scale (online and offline stores distributed across the country). That is why we would see waves of consolidation in such strong vertical markets. Like how firstcry.com and BabyOye merged their operations, I agree with Supam that this market will see more and more such mergers (read his interview here).

Lessons for enterprises focused on vertical markets

Based on what we have discussed over the past few weeks, I would urge enterprises focused on vertical markets (like firstcry.com) to (a) seriously consider your business model to include online and offline consumer touchpoints … for instance, online furniture store, Urban ladder is ‘pivoting’ to offline stores (read the news here) and are positioning their offline stores as customer experience centers; (b) invest in collecting and analyzing small (or thick) data through these omni-channel (or hybrid) business models; and (c) critically evaluate if the market conditions favour winner-takes-all dynamics.

Hope my readers from India and the diaspora had a great deepavali festival! Greetings from Bangalore.

Disclaimer: I am in no way related to FirstCry.com, Goodlife.com, its investors, or its founders.

Startups out there: What instant gratification do you offer to your customers?

Last week, Tim Romero of ContractBeast published an article on LinkedIn on why he turned down $500K, pissed off his investors, and shut down his startup (read here). Easily one of the best articles I have read in the recent past. A quick summary on the story – Tim and his co-founders had set up the enterprise, done beta testing and received good reviews from their customers. However, what was bothering Tim was that his customers were using their product only for a small proportion of their total requirements. Deeper analysis of early adopters of the product revealed that they did not get any value from the product that provided them with something of an “instant gratification”. In the absence of a short-term value add, it was difficult to turn these free users into paying users, once the trial was over. And they decided to pull the plug on the product and the enterprise.

Scaling your startup

A lot of entrepreneurs and founders keep discussing about how to ‘scale’ their business, either to achieve traditional economies of scale or to kick-in network effects. In their attempt at scaling, a recurring theme is the provision of subsidies, at least for one set of users. Some of them provide these subsidies for a limited time period; some offer differentiated products/ services under a ‘freemium’ model; and some others provide their services ‘cheaper than free’.

Providing subsidies is a time-tested model of scaling up a business. Traditionally such subsidies were provided as a trial period, during which the customer experienced the product as the product provided the customers with some functionalities, if not all of the full version. When the trial period ended, the product reminded the customer to pay and upgrade/ renew, but pretty much stopped there. Some smart products could have collected valuable data on how and what the customers used the product for; and therefore provided them with partially customized offers. Take the example of Dropbox. It began providing me with free storage space and allowed me with more and more storage as I invited friends; and began collaborating with others (sharing files and folders). It allowed me enough storage on the cloud so that I could store files that I needed to access from ‘anywhere’, allowing me to work seamlessly from home/ during my travels (on my MacBook). The upgrade reminder kept popping up whenever I came close to using up my storage space, but it was always easy to move out those files that belonged to finished projects off the cloud and free-up space for newer projects. Eventually, it took a long time to convince me to pay up for the upgrade (I paid up when I had to share large number of files with a variety of collaborators across the globe). What Dropbox provided me was the seamless integration of my desktop folder with cloud storage without the hassle of actively uploading a document using a browser. I saved it in ‘the folder’ on my office desktop, and it was available in ‘a folder’ on my home desktop/ MacBook.

Some products provide customers with so much subsidies that it could become ‘cheaper than free’. For instance, Indian taxi aggregation market has become so competitive between Uber and OlaCabs that they are raising large sums of capital, and pumping them into the market as lower fares for riders and subsidies for drivers. These drivers get their incentives once they complete a certain number of rides per day, get to keep pretty much what they earn, and have the flexibility to sign up with other operators (or in platform-business terminology, multi-home with other operators). The story is wonderful and sustainable until the incentives last and keeps the drivers motivated. However, a caveat in the Indian market is that driver is not ‘the entrepreneur’ as what Uber and OlaCabs would like to believe. The company refers to them as driver-partners, and treats them as if they were independent. The truth in many cases is that, most of these drivers are paid employees of car-owners and their incentives are not the same as that of the car-owners. So when we introduce a third party in the transaction, a lot of traditional incentive schemes fail – does ride incentives benefit the car-owner or the driver? That depends on the terms of employment of the driver with the car-owner. Some owners lease the car for a fixed fee per day, some others pay monthly compensations to the drivers, and some others a combination of a fee and revenue/ profit shares. In this context, it would be difficult for Uber and OlaCabs to design an incentive system to shift these driver-partners from enjoying these freebies to a more (economically) sustainable model of revenue/ profit sharing. However, Uber’s ability to lock-in the driver by secularly increasing the number of rides required to earn incentives has increased the switching costs of these partners (car-driver-owner combine).

Instant gratification

In order to scale (either linearly or through network effects), firms would need to provide some form of instant gratification to its customers/ partners. However, it is imperative that the value provided should lead to increasing the switching and multi-homing costs for the customers. Take the case of Romero’s product, ContractBeast. What Tim observed during the trial period was that the customers were indeed multi-homing with other competing products and services to manage their contracts, and were not using ContractBeast for managing a majority (if not all) of their contracts. Had ContractBeast provided a value that did not allow for its SMB customers to multi-home, the story could have been different.

Increasing multi-homing costs

I perceive three levers for increasing the multi-homing costs of customers in a platform business model – asset specificity, not absorbing sunk costs, and integration with other systems and processes. Asset specificity refers to the requirements of the customers to invest in certain specific assets to adopt your product/ service. For instance, the B2B supplier platform IndiaMART requires SMB sellers to invest time and energy in uploading their product details, photographs, technical specifications, contact information and all details about their firm as part of the registration process. Such an intensive registration process ensures that the seller will focus all his energies on a single platform rather than multi-home. Quick reference, see the registration process in the dating platform eHarmony (the relationship questionnaire)! If you have filled that long a questionnaire once, you do not want to do that again and again in multiple platforms, right?

The second and the easiest lever for increasing multi-homing costs is the absorption of partner sunk costs. For instance, OlaCabs subsidizes/ absorbs the cost of the phone that is used by the drivers. This subsidy ensures that the drivers are free to multi-home with other taxi aggregators, as they have incurred no or little sunk costs. On the other hand, firms like Tally require you to invest in the license (albeit very inexpensive) to be able to use the full functionalities of the product/ service offerings.

The third lever for increasing multi-homing costs is to integrate your product/ service with other systems and processes of the customers. Take the example of Practo. Practo has ensured that clinics need to invest in Practo Ray, the practice management software that manages a lot of processes in the clinics, including managing electronic medical records and integration with pathological laboratories. Such tight integration with the processes ensures that their customers – the clinics – do not multi-home, and increasingly use Practo.com (the doctor-patient discovery platform) exclusively for all their appointments.

Startups out there: Can you tell me how you do it?

That thing Tim Romero missed with his product! High multi-homing costs. So my dear entrepreneur friends, define (a) what is that instant gratification you offer for your customers? (b) does that value-add require temporary or permanent subsidizing, and (c) what is your strategy for increasing your customers’ multi-homing costs – increasing asset specificity? Not subsidizing their sunk costs? Or tight integration with their processes? Or a combination of these?

Would love to hear from my startup friends and followers.

StoreKing: Taking ecommerce to rural India

Each of my visits to Europe has taught me something new over the past few years. My recent visit in April-May, I had to travel through three countries – Switzerland, Germany, and Italy. What struck me this time was how much the local language was used in a lot of business and commerce, with English being the common language. While looking for similarities between India and the European continent, I was amazed at how much they value their local languages. For instance, my colleagues in Germany did my hotel bookings for Nuremberg and Rome through Booking.com and HRS.com, and the entire communication cycle was in German language. Not surprising. But it triggered the thought about “why don’t we have websites and mobile apps in India’s languages?” What would be the impact of an ecommerce site in a local language like Kannada on a rural consumer in say, the Dakshin Kannada district?

I began my exploration and in a recent road trip to Tiruchchirappalli (Trichy for the phonetically challenged) in Tamil Nadu, I experienced the power of StoreKing. StoreKing is not a traditional retailer or an ecommerce firm. It leverages the power of ecommerce and solves the three major problems faced in rural penetration of ecommerce – language barriers, non-specific addresses, and trust. A detailed description of the StoreKing business model is available in a write-up on YourStory.in (read here), but for the sake of explanation, let me briefly introduce the same.

StoreKing approaches rural retailers (brick and mortar) and convinces them to install the StoreKing kiosk/ buy a StoreKing tablet in their shops. These kiosks or tablets are powered in the local language, and has a large variety of SKUs, ranging from electronics, appliances to digital goods like mobile/ DTH recharges. Customers walk in to the store, and with the help of their trusted retailer, browse and shop on the StoreKing kiosk. Once they have placed an order, they pay the retailer in full, StoreKing communicates with the customer through their mobile phones in their local language. The problem of poor (ill-specified) addresses is taken care of by dispatching the goods to the local retail shop (from their central warehouse in Bangalore) within 48 hours. The retailers receive a 6-10% commission on the sale proceeds. Though I am not sure how StoreKing sources the goods, it uses the standard FMCG distribution network to ship the products to the retailers.

StoreKing’s last-mile connectivity to its rural consumers addresses the three main problems faced by traditional ecommerce firms – lack of scale in rural markets to justify investments in delivery infrastructure, lack of sufficient data about rural consumer habits and preferences, and their (misplaced) perceptions about rural buying power. An older YourStory.in report talks about how StoreKing’s customers bought dishwashers (not one, but two for the same household) and iPhone 6s (read here). The lack of scale has been overcome by adopting a hub-and-spoke distribution system that piggy backs on the FMCG distribution network.

I am not sure this happens, but would it be possible for the customer to change the default language of communication? I appreciate that rural India would not have enough linguistic diversity to justify this, but if StoreKing were to penetrate into border towns like in Belagavi (nèe Belgaum) district, where multiple languages are used, it would definitely need customization.

StoreKing has partnered with Indian Oil petrol bunks (gas stations) as retailers (see here); as well as Amazon.in, presumably for expanding their breadth of products. The recent media reports talk about Amazon.in’s Udaan initiative to reach rural customers with limited internet connectivity, and the synergies Amazon.in will have through this partnership with StoreKing, but not the perspective of StoreKing. Amazon.in would leverage their deep local presence and established distribution network; and I would guess StoreKing would significantly benefit from Amazon.in’s breadth of products list.

StoreKing claims to be neither a discounter nor a premium seller of goods. The primary value proposition is the trust its customers have on the local retailer; and that has enabled them to even collect cash in advance, rather than cash-on-delivery that has become the dominant mode of ecommerce transactions in India. This trust placed by the retailers on StoreKing provides it with a significant first mover advantage. At over Rs.10,000 investment and significant local knowledge of the customers, the switching costs and multi-homing costs for the retailers are very high. Even when a competitor enters the market directly, it would be difficult to convince a retailer to shift out of the StoreKing kiosk/ tablet to another competing solution. It is here, that I believe StoreKing should follow the classic Wal-Mart strategy of “regional rural saturation”, and convince every retail shop/ kirana store in a particular geography to host a StoreKing kiosk.

Four questions pop up in my mind, for which I have no answers right now.

Should StoreKing open its own exclusive stores, as they grow big? What are the costs of signing up with competing retail stores in the same village? Can these costs be overcome by stand-alone StoreKing kiosks?
At the other extreme, should StoreKing allow for a tight integration of the brick-and-mortar retailers’ inventory and their inventory? For instance, if a customer ordered a Micromax mobile phone through the StoreKing kiosk, which was already available with the retail store in his physical inventory, should he fulfill it from his store (and forego the StoreKing sales commission) or block those items that he sells in his store?
If these brick and mortar stores who are trusted by the local customers offer discounts and credit for their offline sales, how does that affect StoreKing operations and business model? Should StoreKing allow a retailer to extend the same credit terms he offers to his customers for ordering good through StoreKing?
As StoreKing expands into more and more geographies (as of June 2016, they operate in the five South Indian States, plus Goa, Maharashtra, Gujarat, and Odisha), is this model scalable? What challenges would a market like Eastern Uttar Pradesh pose?

I am watching this firm and its growth trajectory from the outside. Any answers?

PS: I am nor in any way related to StoreKing or its investors/ founders.

Surge Pricing: The importance of focusing on the supply side

The Delhi Government, Karnataka Government, and even the Union Transport Ministry in India has been sieged with this issue of surge pricing by taxi aggregators. While there has been a lot written about surge pricing (see my earlier post, more than a month back), a lot of what I read is incomplete, misleading, and sometimes even biased. Here is adding to the debate, by clarifying what surge pricing and how it differs from other models of price setting. And I draw policy implications for dealing with the phenomenon by focusing on the supply side, rather than focus on just the price.

What is surge pricing?

Surge pricing is an economic incentive provided to the suppliers of goods and services to enhance the supply of products/ services available in times of higher demand in the market by (a) incentivising those suppliers who provide them, (b) ensuring that these suppliers do not go off the market in such times, and (c) rationalise demand through fulfilling only price inelastic demand. As a driver in a taxi aggregator system, it makes economic sense for the driver not to take his breaks during the peak demand times, and ensuring that only those riders who desperately need the service, and are price inelastic avail the service. A price sensitive customer should ideally move off the aggregator to a road-side hailing service (if available, as in Mumbai) or simply take public transport.

Who is a typical surge pricing customer?

A recent study talked about riders being more willing to accept surge pricing when their phone batteries are about to die, and they need to conserve the same (read here) before they reach home. A city with good public transportation infrastructure that is designed for peak hour loads should ideally witness the least surge pricing (please don’t ask me about Bangalore, or should I say Bengaluru?). In most Indian cities, the typical cab aggregator rider is someone who is a regular user of cabs and autorikshaws (three wheel vehicles) to commute short and medium distances. Typically either the origin or destination of the ride is in the city centre or a high-traffic area (like a train station or airport). It is when the public transportation infrastructure fails that these riders are forced to use cabs for their regular (predictable) transport needs.

Let us take an example of an entrepreneur (call her Lakshmi, named after the Hindu Goddess of Wealth) whose work place is in the city centre and she commutes about 15km every day. She should ideally use public transport, or if her route is not well connected she should have her own SUV or a sedan (remember her name!). She would possibly have a driver if her work involves driving around the city to meet customers/ partners, or her daily work start and close time are not predictable. The only time she would use a cab aggregator is when she is riding to places with poor parking infrastructure, for leisure, or say a place of worship. She is price inelastic.

Take another example of a front office executive at a hotel. Let us call him Shravan. His work times are predictable, he works on a fixed remuneration, and is most likely struggling to make ends meet. He is most often taking public transport to work, or self-driving his own budget car/ 2-wheeler. He would only take a cab aggregator for his leisure trips with his young family during the weekends; and when the entire weekend out with family is an experience in itself, he is unlikely to be price sensitive to a limit. However, when surge pricing kicks in beyond a limit, he would baulk out of the market, and take public transport or other options.

As a policy maker, the demand side (riders’) welfare should be higher on priority than that of the supply side (drivers and aggregators). The demand side is large in numbers, is fragmented, and has very few options (especially in times of high demand). Price ceilings are justified when riders who are desperate to reach are price elastic. In other words, those who need the safety, security and comfort of the taxi services cannot afford it. Like the sick desperate to reach a hospital or children reaching school/ back home on time. These are segments best served by other modes of transport, rather than taxi aggregators – the Governments of the day should invest in and/ or ensure availability of good quality healthcare transport services (ambulances) and public/ private school related transport infrastructure.

Surge pricing is dynamic pricing

Dynamic pricing is not new to the Indian economy. Almost the entire informal economy or the unorganized sector works with dynamic pricing. What the rate per hour of plumbing work in your city? Depending on the criticality of the issue, the ability of the customer to pay (as defined by the location/ quality of construction and fixtures), and the availability of plumbers, the price varies. So is the case with domestic helps, and every other service provided by the informal sector. Why even professional service firms like lawyers and accountants use dynamic pricing based on ability to pay and criticality of the issue.

What surge pricing by taxi aggregators do is to take the entire control of dynamic pricing out of the suppliers’ hands and places it with the platform. The drivers may be beneficiaries of the surge price, but they do not determine the time as well as the multiple. Plus, given that the surge price is announced at the time of cab booking, the riders have a choice to wait, change the class of service (micro, sedans, or luxury cars in the system), choose an alternative aggregator, or choose another mode of transport. A fallout of the transparency and choice argument is that the “bargaining” for price is done before the service provision, and not after the ride. This transparency and choice empowers the riders, and as long as the multiple is “reasonable”, we could trust the riders with rational economic decisions. What is reasonable may vary across riders and the criticality of the context. While Lakshmi may be willing to pay a 4x multiple on her way back from work at 9pm in Hyderabad, Shravan may only a 4x multiple at 9pm when he has to reach the hospital on time to visit his ailing mother.

Data is king

The amount of data collected by the cab companies about individual behaviour and choices can enable the aggregator design appropriate pricing structures, customised to each customer, a segment of one. For instance, Uber can run micro-experiments with surge pricing and tease Shravan with different multiples at different points of time/ origin-destination combinations, and learn about Shravan’s willingness to pay, far more than what he can articulate it himself. Powered with the data, Uber should be able to define something like ‘Shravan will accept a surge price of at most 2.2x, as he is trying to return home from his workplace at 10.30pm on a Friday evening.’ Over long periods of time and large number of transactions, this prediction should mature and get close to accurate.

Given that the aggregator platform would be armed with this data, it is for the policy maker to ensure that such data is not abused to further its own gains. How does policy ensure this? By capping the multiple through a policy decree, no! Rather ensuring a market mechanism that caps the surge pricing multiple would generate significant welfare to all the parties. In order to ensure a market mechanism that makes profiteering out of surge pricing unviable, the Governments must focus on developing robust public transportation infrastructure. As attributed to a variety of leaders on the Internet/ social media, ‘a rich economy is where the rich use public transport’. These investments would provide significant alternatives to attack supply shortages in the market, and make them more efficient. This supply side intervention would do the market a lot of sustainable good, by ensuring that the Shravans of the city need not use the taxi aggregators more frequently, and thereby increasing the price inelasticity.

Policy recommendation

In conclusion, the entire analysis of the demand-supply situation leads me to recommend one simple thing to the policy makers – focus on the supply side. Get more and more public transport (greener the better) on the road; provide better and efficient alternatives to all segments; and in the short run, just ensure that there are enough ‘vehicles available for hire’ on the road.

Comments welcome.

Building a platform business is hard work, not for lazy people: A response to Prof. Ajay Shah’s column in the Business Standard

I read with interest what Professor Ajay Shah had to say about young men and women entrepreneurs of today wanting to become rich quick, with dreams of laziness in the Business Standard (see here). This note is a response to his observations/ allusions that businesses that run on network effects (a) are not-so-innovative, (b) operate in monopolies, and (c) are built around inferior products.

Building a platform is hard work, not for lazy people

Let me begin with the title – lazy businesses. The implication of laziness is that while there is opportunity and capability to do the hard work, these businesses (and by implication, its founders) are unwilling to work hard. I disagree to the notion that anything develops fast is not hard work. The implication that a business that grows slow is “steady” and the one that grows fast is cutting corners. True capitalism favours entrepreneurs who chase and capitalise on big opportunities, and that too pretty fast. Building network effects is not as easy as he alludes. He quotes the example of Google monopolising cloud-based email due to the network effects it has generated. Google was not the first entrant in the cloud-based email space, there were two large competitors operating when it entered – Hotmail and Yahoo Mail. Gmail entered with a disruption – it offered almost unlimited storage on the cloud, and two, it began with invitation only. It took a while for Gmail before it became open for signup, but given that innovative positioning of “never having to delete your email”, it was quick enough. Behind this innovation at the customer end was the hard work, the painstaking task of building server farms across the world with sufficient security and redundancy built into them. This is exactly the hard work Prof. Shah talks about, innovating around products – the Google innovation was riding on the falling storage costs and leveraging the power of global network connectivity to build a network of server farms, thus driving costs down. The fact that Gmail was able to unseat Hotmail and Yahoo Mail from their leadership positions is sufficient evidence that competition is working, and capitalism is safe too.

Platforms are innovative

One of the key tenets of capitalism is that factor endowments (like capital) flow freely from inefficient uses to the most efficient uses. The fact that the venture capital market is amply fragmented is the first signal that capitalism is working there. Let us turn to the platform business firms that seek these capital resources. As capitalism would have it, money should only flow to the most efficient uses of capital – ask any entrepreneur about raising money, and you would hear enough of how difficult it has been. Raising money has never been so difficult, as each of the business models have been unique. Yes, there have been replication business models that get funded, like I want to be build the Uber of Indian hospitals, but they are few and far between. Each of the business models that are flush with funds from the venture capital firms and angel investors are indeed innovative. May not be in the traditional sense of the product innovation like Google’s server farms, but a lot of them offer unparalleled service innovations. Take the example of Quickr, the C2C used goods marketplace. Though such used goods marketplaces had existed in the past, Quickr has managed to bridge the information asymetry between buyers and sellers in a variety of ways (photographs of products, contact details of sellers, premium services, and enabling within-platform communication through QuickrChat) as an insurance against the platform becoming a “market for lemons.” These innovations have not happened in one day, it has taken them years of competing with similar and local marketplaces and keenly listening to their customers on both sides – buyers and sellers.

Not all platform businesses operate in winner-takes-all markets

Prof. Shah alludes to the suggestion that most, if not all, platforms create and operate as monopolies, once they reach a threshold of network effects. Research in economics shows that there are three conditions for a platform market to become a winner-takes-all market – network effects are strong and positive, multi-homing costs are high for the users, and there are no special preferences for users. He has clearly defined the network effects in his article, and I would skip that part. Let me turn to multi-homing costs. Unlike switching costs which measure user costs of switching from one competing product/ brand to another; multi-homing costs measure the user costs of staying affiliated to multiple product/ brands. A good example of multi-homing costs is the number of emails accounts a user can efficiently own and operate. Even though most of cloud-based email is free to use, and a user can create any number of email ids for herself, what restricts her choices to a few is the costs of logging in to each email id, and making sure you do not miss out on important communication. This multi-homing costs ensure that the market has one social networking site, where people connect with friends, family, co-workers, as well as their business partners. However, not all markets have high multi-homing costs. Users (bargain hunters) do shop on multiple ecommerce sites and maintain their login/ passwords for each of these sites. The third condition for a market to demonstrate winner-takes-all economies is the absence of special preferences amongst the users. In the peer-to-peer networking space, where Facebook dominates the social networking market, professional networking (finding jobs and customers for one’s skills as a special need) has another player, LinkedIn. Passive job seekers would populate LinkedIn, while active job seekers would register with one of the many job sites like Naukri.com. The point I want to drive home here is that having network effects by itself does not guarantee a winner-takes-all economy. Firms expend time and effort in building multi-homing costs and enveloping any special needs to create a winner-takes-all market.

Successful platforms have a superior product/ service core

Though network effects make switching costs high, the history of platform business evolution is strewn with a lot of products/ services that have fallen by the wayside due to poor quality of its core product/ service. We did talk about Hotmail and Yahoo Mail, that did not innovate at the right time and lost out to Gmail. On the other hand, Friendster and MySpace failed due to Facebook’s superior quality and constant innovation. Google+ with the backing of the Internet giant, is an also ran in the peer-to-peer social networking space. Yes, switching costs exists and are non-zero, but given the right kind of strategy adopted by the challenger, that is apart from the superior product/ service, users can, and will shift.

Network effects are hard to build

Prof. Shah’s piece asserts that network effects are easy to build and can be done quickly too. Building cross-side network effects are difficult. How would Prof. Shah like to be the first contributor of a new newspaper, not as established as the Business Standard? He writes a column for the BS because of the existence of network effects – he knows that his columns would be read by the “right audience.” Traditional businesses like newspapers have long known to subsidize one side of its user base, its readers, while making money from advertisers (and in some cases, even benefactors and sponsors). So is the case with the media industry. This is a classic “chicken-ane-egg” problem that network industries have to resolve. There are many ways to solve them, and subsidising one side is just one of them. For instance, Practo has invested heavily in building its practice management software, Practo Ray for its clinics side of the business, so that it could build cross-side network effects. Now that the clinics use Practo Ray, Practo can afford to subsidise patients discovering doctors/ clinics through Practo.com. Tough, hard work buidling and selling practice management solutions to clinics, before the subsidising began. Subsidising one side of users to build network effects is not in itself any bad, but such subsidising should not be at the cost of overall economic well-being. Founders/ VC investors (shareholders) and managers make money because the customers, at least one side of the platform, are willing to pay. And they are willing to pay in return for the value they receive.

In sum, building a platform business with network effects is not lazy work, it takes a lot of patience, investments, and creative solutions to succeed. Yes, they are unlike traditional “pipeline” businesses where value flows from one direction to another linearly. They are different, and in some kinds of ways, fun. They have multiple sides of customers to deal with, and are on the toes all the time to keep the fine balance intact. These are exciting times when traditional pipeline businesses compete with platform businesses.

Comments welcome.

Measuring E-commerce firms’ performance

The week began with the news of the online grocer PepperTap closing its grocery business to become a pureplay logistics firm (see here). And we just read that SnapDeal is recalliberating its performance metrics (read here). So, what exactly is the problem and what can we do about it?

The investor obsession with GMV

Throughout the world, venture capitalists and other investors have used the metric of Gross Merchandise Value (GMV) to measure the performance of E-commerce firms. Everyone manages what they are measured on. So, all E-commerce firms focused on increasing their GMV, that is increasing the gross value of their sales. What this obsession with gross sales does to firms is that there is significant incentive to pursue what I call as “profitless growth”, where only the topline matters, with no attention whatsoever on all other parameters. Especially so, when the entire industry thrived on deep discounting and low customer switching and multi-homing costs. Focus on just one parameter like the GMV might be valuable when the business just sets up to measure the initial traction amongst the target customer groups, but continued focus on the single parameter can lead to misplaced strategies.

Evolving other measures

After all, E-commerce is also a business that needs to provide sustained returns to its shareholders. As with all for-profit businesses, good measurement of performance should include a variety of metrics that reflect the organization’s priorities and strategies. For a consumer focused multi-category retail business, it would be prudent to measure performance on the following four parameters – (a) gross and net (of returns) revenues; (b) gross and net margins; (c) customer addition, loyalty, and attrition; and (d) distribution of sales across categories in line with the firm strategy/ priorities (merchandising mix).

The bane of COD

The boom of Indian Ecommerce industry and its reach to tier II and tier III towns in India could be attributed to the industry adopting “cash on delivery” as a means of payment. With the proliferation of mobile phones and 3G/ 4G coverage across the country, customers with smartphones, and with no access to any digital transaction platform (like a credit card/ debit card/ wallet) can easily buy goods online. And pay for them when they actually receive them through cash. The impact of this on Ecommerce companies is three-fold: adding more number of customers, providing time for customers to actually make up their mind – they could actually return the goods when they arrive with no liability at all (see the recent Flipkart ads), and larger investments in working capital for the industry (either the platform or its suppliers, or both). Therefore, it is imperative that the E-commerce firms measure not just their gross merchandise value, but include the GMV net of returns, or Net Merchandise Value (to account for returns).

E-commerce = discounts

The primary selling proposition of E-commerce firms in India have been around deep discounts. While the idea of a zero-inventory marketplace model (that Amazon pioneered over a decade and half ago) does provide sufficient economies of scale and cost advantages, competitive discounting in the Indian E-commerce industry has over the years shaped customer expectations to the extent of equating online buying to deep discounting. Therefore, measuring gross and net margins of the entire firm is imperative.

Spreading Commerce to the “hinterlands”

The first line of defense Ecommerce firms take umbrage to when someone accuses them of being focused on a single parameter is that “the industry is in its infancy, and we need to broaden our net”. True that the low penetration of E-commerce in India provides a big opportunity for growth, we need to define appropriate metrics to measure the firm’s performance on that front. It is therefore important that firms measure the total number of transactions (as a proxy for volume sales in the offline world), number of active customers (as a measure of customer concentration – or an ABC analysis of customers), number of new customers added (not registrations but at least on transaction), average GMV per customer (as a measure for identifying high-value customers), average contribution per customer (gross profitability), and the proportion of customers whose GMV increased over the past period. In addition to this, we need to also factor in the cost of acquiring customers (CAC), and derive the long term value (LTV) of customers to evaluate performance. As the firm matures, it should strive to bring the CAC lower than the LTV.

PepperTap’s source of worry (read the article on YourStory.com here) was its rapid expansion to new towns where the costs of servicing was far higher than the LTV of the customers in those geographies. As they cut down on the number of cities, their performance improved. Therefore, it is imperative that Ecommerce firms measure and report their CAC and LTV of their customers as a key performance metric.

Alignment with strategic priorities

For a multi-category retailer, the distribution of its sales, costs and margins across categories is a critical parameter to monitor. Firms may prioritize certain categories over others as per their market position and strategic priorities. Successful firms therefore need to measure and monitor their performance across categories, and benchmark against their intent and priorities.

Creating a holistic dashboard

In sum, E-commerce firms would do well to measure, monitor, and report their performance on the four categories of parameters including (a) the traditional GMV, and a GMV net of returns; (b) overall gross margins and net margins for the firm; (c) total number of transactions, number of active customers, new customers added, average GMV per customer, average contribution per customer, proportion of customers registering increase in contribution over the past period, and the cost of acquiring customers; and (d) distribution of GMV, GMV net of sales, gross margins, net margins, number of (net of returns) sales, and CAC & LTV numbers in each category.

Interesting times lie ahead for the industry, as the golden tap of venture capital finance dries up, leading to reduction in discounts and possibly consolidation of firms to leverage the traditional scale economies of a zero-inventory marketplace model.

How to build a platform business?

In his recent convocation address at our institute (Indian Institute of Management Bangalore), Mr. Nandan Nilekani stressed on how platform firms have come to dominate the Indian (and global) markets, and the need for our graduating students to understand them well (see http://www.iimb.ernet.in/convocation-2016). In this post, I would focus on categorizing different types of platforms, and some key issues in building a platform business.

Platforms are firms that operate in multi-sided markets. Unlike firms where products and services flow in one direction (remember, Porter’s value chain?) in a pipeline fashion, and money flows in the opposite direction, platform business models connect multiple sets of users. In the traditional sense of the word, a railway platform helps passengers find their trains and vice versa. The train station manager sets the rules, provides the infrastructure, and enables a smooth discovery and transaction between the different sides (trains and passengers). Imagine trying to find and board trains like you would board a taxi in the streets of Mumbai or New York! Generalizing this, the firm that provides the infrastructure is the “platform provider” and the one that sets the rules and norms is called the “platform sponsor”. In some cases, the platform provider and sponsor could be the same firm (like in the case of a railway platform); and in some other contexts, the platform provider could be different than the sponsor (like in the case of Uber or OYO rooms, where the cabs/ rooms are owned by independent entrepreneurs and the rules of the exchange/ transaction is set by the aggregator).

Platforms match different sides of users. In their role as matchmakers, they provide different value propositions – discovery, quality assessment, norms for interaction, setting expectations, and provide feedback – for each of the sides. Let me discuss how to build each of these value propositions (when you are setting up a platform business model) in detail, with examples from established platforms.

Discovery

This is in fact the first thing to focus on when you set up the platform. Setting up the infrastructure to facilitate interactions is the easiest thing to do. The most difficult part of process is the populating the sides with users. Here is where new platforms encounter the classic “penguin” problem, where users on one side postpone adoption till such time there are enough users on the other side. How would you like to be the “first” person to be listed on a dating site, seeking to find a date? You would affiliate with a dating site only when you are sure that there are already enough members on the other side. Platforms need to overcome this inertia by incentivizing one side to affiliate, in anticipation of affiliation by a large number of right kind of members on the other side. Various platforms have solved the penguin problem differently. For instance, Facebook solved the penguin problem by starting small and being focused on Harvard University students and alumni. Practo solved it by building and selling their practice management software (Practo Ray) to clinics before opening the patient interaction platform.

Having solved the penguin problem, i.e., having built enough members on both sides, platforms have to ensure that the discovery engine is powered to ensure quality, current, and relevant results. For an interesting take on how Indian ecommerce firms stack up on search results, see this post by Aditya Malik.

Quality

In a platform where products/ services/ information are provided by independent parties on one side, it is imperative that the platform ensures quality. It would require verifying the genuineness of the information provider as well as the veracity of the information. For instance, Quickr.com (an Indian C2C marketplace for used goods) positively discriminates posts with pictures of the items being offered for sale than those posts without pictures while sorting the search results. IndiaMART (the B2B marketplace for industrial goods) certifies the sellers with a TrustSEAL, by verifying the antecedents of the seller’s businesses, including their legal compliance, manufacturing facilities, and product range. Verification of quality comes with a cost, and provides the platform with high credibility and enables loyalty of users.

Some platforms use user-ratings and reviews as indicators of quality (like zomato.com, the restaurant discovery platform). Crowd-sourcing of ratings and reviews might provide higher credibility to the platform, but has to be used cautiously. These could be gamed by users. More on this later.

Norms and rules

As a platform sponsor, it is important to set the norms for communication and interaction among users across the different sides. These norms should set the boundary conditions for interactions, like the terms of sale (delivery charges, delivery times, returns policy) in ecommerce marketplaces.

In pure discovery platforms like JustDIal.com (an online yellow pages) or Quickr.com (marketplace for used goods), indiscrimately providing mobile numbers could be abused. Quickr.com has in the past few months introduced a secure chat service whereby sellers and buyers could chat with each other within the platform without having to provide each other’s mobile number. Even when the agreement is reached and the transaction has to be completed, Quickr allows for an anonymous delivery service (Quickr doorstep), where the users need not know each others’ personal contact details.

BharatMatrimony (the online matrimony match maker) allows only paid members to initiate communication with others. What this does is to ensure that brides and grooms who are actively seeking matrimony to become paid members, as the other side is unlikely to respect someone who is “not even willing” to pay for discovering his potential partner!

Setting expectations

The platform should allow for users on both sides to clearly set expectations apriori, to ensure that there are no surprises during the transaction. More the information sought and shared during the discovery phase ensures smooth transition to the transaction and fulfilment phases in the platform. Here is where the platform should ensure that there is a mimimum amount of high quality information available about the entity/ prodcut/ service being matched. Imagine trying to book a hotel room on a travel website without information on the hotel location, types of rooms available on that particular night(s), and the rates! It is therefore an important consideration that platform designers need to keep in mind when designing the infrastructure and rules. For instance, dating sites like trulymadly.com ensure that users provide their facebook pages during the registration process. While actual verification of each users claims on the dating sites might be difficult, linking their facebook account to the trulymadly account ensures that they do not lie (too much!) with respect to critical information about themselves (like marital status). Now you know why the job search portal you just signed in wanted you fill in pages of information, and links to your LinkedIN profile.

Providing feedback

Even after ensuring quality, defining the norms, and setting expectations, there could be some errors. The platform architecture should therefore provide for immediate feedback on all four parameters – quality of the entity/ product/ service/ information; relevance/ adequacy of information; currency of information; and the quality of the discovery, transaction, and fulfilment processes. Cab aggregators like OLACabs request for feedback on the quality of the cab and driver as soon as the ride is completed. However, there is no provision (not that I could find) to provide feedback on all the discovery stage of the platform – the time it took for the app to find me a cab/ auto, or the accuracy of the location services within the app.

Surge pricing: Implications for India

Last weekend, I was in Chennai and I keep using taxi-hailing apps a lot when I am outside Bangalore. About half the time, I was offered rides with surge pricing, ranging from 1.4x through 2.5x of the base fare. And in some cases, for rides in the middle of a hot afternoon, I was offered an upgrade from a “mini” to “sedan”. Riding through the upgraded sedan, I was flipping through the news article, and found an article on Uber’s surge pricing lawsuit (see http://www.bloomberg.com/news/articles/2016-03-31/uber-antitrust-lawsuit-over-pricing-green-lighted-by-judge).

On Monday, 4th April 2016, the Economic Times, Bangalore Edition carried this piece about the Karnataka Government regulation of ride-hailing service (see http://economictimes.indiatimes.com/small-biz/startups/karnataka-nixes-surge-pricing-by-taxi-hailing-apps-like-ola-uber/articleshow/51678792.cms). In a nutshell, this regulation caps surge prices, encourages drivers to operate for multiple services (multi-home), and relaxes norms for drivers to affiliate with a ride-sharing platform.

I was left wondering, what would be the implications for the lawsuit in a duopoly market like India, where OLA and Uber compete. Would the economics be any different? In this post, we will understand surge pricing and its economics, in conditions of a duopoly, and the implications of the lawsuit in India.

What is surge pricing? How does Uber justify it?

The Uber website explains surge pricing thus: (https://help.uber.com/h/6c8065cf-5535-4a8b-9940-d292ffdce119).

“Uber rates increase to ensure reliability when demand cannot be met by the number of drivers on the road.

Our goal is to be as reliable as possible in connecting you with a driver whenever you need one. At times of high demand, the number of drivers we can connect you with becomes limited. As a result, prices increase to encourage more drivers to become available.

We take notifying you of the current pricing seriously. To that end, you’ll see a notification screen in your app whenever there is surge pricing. You’ll have to accept those higher rates before we connect you to a driver.”

The core argument is that surge pricing incentivises more drivers to be available during times of high demand. At the core of this argument is that Uber cannot “mandate” drivers to be available when the demand is likely to be higher, and therefore has to “incentivise” them. Just like tipping the driver to be available. The difference is that the amount of the tip is pre-defined. The effects of surge pricing are well documented in the case study by Chicago Booth School faculty here.

There are two challenges: who pays for the incentive – is the charge on the riders justified? Do drivers like this?

Riders’ perspective on surge pricing

A lot of riders (at least in India) do not like the haggling and negotiating with taxis and autorikshaws for a ride both on price and whether they do want to go to your destination. Most of us using public transport in India are familiar with the famous rant “I have to come back from there empty”. Uber and OLA implicitly promised to eliminate it with its fixed and transparent pricing. Add to that, the ease of hailing a cab to your doorstep/ boarding point, thanks to the mobile app and navigation tools available for both the driver and the rider. In that sense, cab-hailing apps should have their loyalist converts. However, when surge pricing is applied, a typical rider would think twice before confirming the same – she is confronted with the same behaviour the autorikshaw driver on the street would have told her – “this is my price, take it or leave it.” In a sense, it brings out the haggler in the rider, just that now the firm is haggling, and the rider is not even sure the driver benefits out of it (more on the drivers’ perspective later).

The second thing that puts off the rider requesting the ride is the number of cabs available on the map before the surge pricing announcement is made. If surge pricing was indeed designed to get more drivers available, what is happening to all these cabs stationed around my pickup point? Here is where customers begin their multi-homing behaviour (having/ using multiple apps at the same time). She would immediately try the other app – OLA or Uber to see if there is surge pricing there.

It hurts when there is an emergency or a discomfort, like having small children/ elders waiting with you; a flight/ train to take; having to reach for a meeting on time; making another person wait on the other side; or a combination of the above. In effect she is made to negotiate, haggle, bargain for a ride. She does feel she is being taken for a ride, literally.

What does all this result in – a poor experience to begin with, resulting in lower driver ratings. Poor driver, he is being penalised because sufficient number of other drivers were not available. Yes, he may make more money, but at the end of the day, the overall economics may not make sense. Surge pricing acts as a “moment of truth” for the rider, and she resets her expectations. When I am paying 2.1x times the normal fare, I expect the driver to be extra courteous, cab to be clean, and even the traffic to be lighter. On the contrary – surge pricing happens mostly during peak hours when everyone is either getting to work or back home, and on the road; and traffic is likely to be very heavy. All this plays on the riders’ minds and they are lowering the drivers’ ratings.

Drivers’ perspective on surge pricing

A typical driver joined the Uber system (Uber or UberX) with the intention of leveraging her/ his car for monetary gains. Compared to a taxi license, which is highly regulated (check out how to get a cabbie license in London, or what the dominant political parties think of cabbies in Mumbai), or a company employment that can be highly restrictive in terms of business, driving your car for Uber or OLA provides a combination of independence and profitability. At the core of the decision is the value of economic choice the driver has – he can choose when to “switch on”, or become available for a ride, and therefore, how many number of rides and how many hours of the day he wants to ride. This economic choice is also guided by the incentives provided by the cab-hailing firms to the drivers on the number of rides they take per day. Given the very low market penetration in India, most drivers multi-home, i.e., they sign up for both Uber and OLA. And make consolidated economic choices, viz., distributing the amount of time/ number of rides for the two firms so that they can maximise the incentives.

Surge pricing for drivers mimics the pre-disruption world. When there is high demand, I charge more. In fact, OLA (in India) has mandated that drivers should be available through the peak period to be able to earn incentives. While the peak period varies across cities, it is still such a large window that drivers could balance the demand across both the firms (Uber and OLA). And drivers make the choice of going online to that system where surge pricing is high. Even though they do not know in real time when and how much surge pricing is applicable, once the rider has accepted the ride, they would know. And with experience (and a little experimentation), it is easy to estimate. So, if it is likely that OLA would have higher surge pricing rates than Uber, the drivers would shift to OLA, thereby decreasing the supply available for Uber, triggering surge pricing in Uber. While the increased number of cabs for OLA should eventually bring down the surge pricing, it is not quick enough, as multi-homing riders (with both their apps running) are choosing the ride with the lower surge price.

Elasticity of demand and supply in a duopoly

This brings us to the question of how truly “elastic” is the supply, give the duopoly in India? Unlike in markets where there is just Uber and competition is poor, India suffers from a duopoly where the drivers’ multi-homing artificially increases/ decreases supply in one system. And when the riders are also multi-homing, the system stabilises and behaves like a monopoly, albeit with some time lags (than a monopoly market).

Would a flat peak-time pricing work? It may, but given the technology and its ability to discover real-time demand and supply, surge pricing is any day superior algorithm to peak-time pricing. Fixed peak-times are things of the past, when people went to work at the same time in the morning and returned back home around the same time in the evening. Flexible working hours, working from home, working for overseas customers in different time-zones … peak-times are stretched throughout the day in urban metropolises like Bangalore and Mumbai.

The law-suit [Meyer v. Kalanick, 1:15-cv-09796, U.S. District Court, Southern District of New York (Manhattan)]

The law suit against Uber’s CEO, Mr. Kalanick (note, the suit is against the CEO, and not the firm Uber) claims three things:

Uber is not just a technology company, selling apps, but a transportation company
Drivers are employees and not independent contractors
Price fixing by the CEO of Uber, while using fixed prices despite using non-competing independent contractors as drivers

The arguments against these charges by Uber and its CEO are that Uber is just an aggregator, and the drivers as independent service providers have wilfully entered into an economic arrangement to agree to the policies set by Uber to find good quality and quantity of riders. Implying that without a platform like Uber, drivers would find it difficult to discover good quantity and quality of riders. And vice versa for riders. The transportation contract is between the rider and the driver. If this were to be entirely true, then the rider should have absolute choice of drivers/ cabs, as well as drivers to have absolute choice of which rider to take. Given that Uber make the match, and provide you “one” driver-rider combination, this true contract is questionable.

Drivers as independent contractors may be defensible with the argument that drivers have the choice when to login to the service. They may choose to switch off when they want, after fulfilling some minimum conditions. If they were employees, the firm would mandate more than a set of minimum conditions and behaviours; and would not provide the driver with the absolute economic choice provided in the current arrangement. It is to Uber’s economic policies that they have signed up to, and that explains why drivers with different economic expectations can co-exist in a single platform.

The price fixing charge is defensible with the argument that since drivers are independent contractors, it is important to “incentivise” them rather than “mandate” them to be available in peak demand times. To argue that these drivers do not compete is flawed, as the extent of surge pricing is determined by the supply of drivers in relation to the demand. In order to be available on Uber, each driver must maintain certain service quality, and do a certain number of rides. There is definitely competition amongst the drivers – they would want to be available where demand is likely to be higher than supply; and be there before other drivers. For accusing Uber of price fixing under anti-trust laws, Meyer should establish that in spite of varying demand and supply, Uber maintains the same price, coordinating with independent contractors (drivers) who do not compete.

Here is where surge pricing comes to Uber’s rescue – it is their most effective defence against price fixing charge.

Implications in India

The Indian law is uncertain, to say the least, on the regulation of platforms. The (in)famous case of a Uber male driver raping a female rider in Delhi is a case in point. Uber was first banned by the Delhi Government, the ban revoked by the High Court, only for the Delhi Government to subsequently not approve its application. Uber and OLA then went back to court and the courts agreed to revoke the ban when they promised to replace diesel cars with CNG vehicles. What this means in terms of legality is that Uber and OLA are in fact, undertaking on behalf its independent contractors.

The courts and everyone else in India would be waiting for the judgment of the class action suit in the USA on how this market pans out. Given the size of the Indian market, classifying drivers as employees, and Uber and OLA as transportation companies would kill the platform business model. While I do not believe that it would not go that extreme, interesting times lie ahead on how the courts and regulators interpret the developments.

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