Category: E-commerce

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.

Ratings, reviews, and recommendations in platforms

In my post last week, I talked about crowdsourcing ratings and reviews to create and sustain credibility of the platform. Almost every platform that operates in a multi-sided market has a mechanism for the users of one side to rate the other side. In this post, I will talk about how to design an appropriate system of measuring the quality of the entity/ product/ service.

Ratings

The dictionary definition of rating reads “classification or ranking of someone or something based on a comparative assessment of their quality, standard, or performance.”

At the end of every ride, OLA Cabs requests riders to rate the driver/ cab, and the driver ratings are available to the riders when they book the ride. Similarly, Uber has a two-way rating system, where riders rate the drivers and the drivers rate the riders. And the average ratings matter for the driver and the riders to continue using the platform.

The primary (definitional) issue with rating is that it is a comparative score. As a rider takes more and more rides in the OLA system, she is able to compare that particular ride with reference to the other rides in the same system. However, when a Uber loyalist (say for example, my colleagues from USA) takes an OLA ride while in India, he is rating his ride with reference to his Uber in San Francisco benchmark. And when someone who rarely takes an OLA (and otherwise relies on public transport like suburban trains/ buses) would rate his ride with reference to his bus ride. As the references change, the meaning of the same rating changes. Which brings us to the next concern with ratings. That it is always an overall score. The riders may penalize the driver with a lower rating for whatever reason: not able to find your destination, taking a longer route, not having the cab clean enough, or even for this things outside his control like a temporarily blocked road. And the same could be true of a superlative rating – depending on the rider’s benchmark, he could rate the driver a five-star rating in comparison to the crowded Chennai-Chengalpet suburban train, that he takes daily.

This is not to say that ratings are not useful. Over long periods, with sufficient data points, ratings do bring out the true quality and standard of performance. Underlined here is the “long periods of time” and “large number of data points”. Long periods of time provide sufficient opportunities for services with low ratings to improve their performance and sufficient data points provide for cushion against freak low (or high) ratings provided by irrational customers.

One insurance against inclinations to rate a service at either of the extremes (no central tendencies work here) is to decompose the ratings into various service touch points. For instance, the Jet Airways’ service tracker seeks feedback on every aspect of the flying, making the entire responding to the online questionnaire a drudgery. Such long questionnaires would therefore only attract people who have a reason to provide you feedback – who really had a bad experience and want to express their distress, or those who had a superlatively (and unexpected) great experience that they take the effort to fill-in the forms. When the service is as expected (good or bad), one wouldn’t expect customers to fill in long forms (unless mandated). Isn’t this why most of us teachers’ feedback scores have high standard deviations?

Reviews

As a service aggregation platform, one would want to supplement rating scores with a descriptive assessment (justification) of the rating. For instance, the OLA cabs app would request you to provide the reasons for a low rating by choosing one of predefined set of options. One could not choose multiple options – for instance, it is possible that the driver was late, as well as had his car dirty. This is where open ended responses add value. Again, like long itemised rating forms, open ended questions attract respondents with extreme experiences.

Restaurant aggregators like zomato, ecommerce firms like Amazon.in, and travel sites like Booking.com have implemented reviews along with ratings. Zomato’s review forms require reviewers to provide details of their visit to the restaurant, and the food they ate. In the absence of such information, such reviews may not be relevant to the readers, who intend to use these as the basis for their decision making.

Reviews add value by highlighting specific peculiarities in the product/ service offerings that could not be captured by the ratings. For instance, a sensitive Uber driver who would play appropriate music that is appreciated by the rider would not be a standard data point that Uber wants to capture for all its drivers. However, such an information would be a great input to subsequent riders of that particular driver, who may choose to engage with him about the music. When this becomes a sufficient enough point of discussion in the reviews (enough people write about it about sufficient number of drivers, positively or negatively), Uber might take cogniscance of this to add this to the standard rating form. This is where detailed analytics of the reviews is required.

The dictionary definition of review is very insightful to our discussion: “a formal assessment of something with the intention of instituting change if necessary.” Good analysis of reviews should lead to change, if necessary.

Like the different benchmarks issue with ratings, reviews suffer from an assessment of credibility of the reviewer. It is important that the reviewer is an expert/ has demonstrated that he has used that particular product or service. Amazon.in certifies reviews with a tag “verfied purchase”; and provides the readers of the review an option of rating the review, if that was useful at all or not. Travel sites like booking.com ensure that reviewers have actually booked their stay on that particular hotel and provide the exact details of the reviewers’ credentials to provide the review. In the absence of such credibility, reviews could be abused and gamed in various ways.

Recommendations

Ratings and reviews are good apriori inputs to customers making product/ service selection choices. However, in the case of platforms like Practo, where one chooses physicians (doctors), I am not sure ratings and reviews are sufficient. When the client-service provider relationship is being evaluated (where the service provider is more knowledgeable than the service consumer; unlike a customer, where the customer is more knowledgeable than the service provider), ratings and reviews fall flat. Would you choose your dermatologist based on ratings by other patients, or by the recommendation of your trusted general physician?

The dictionary meaning of recommendation is revealing: “a suggestion or proposal as to the best course of action, especially one put forward by an authoritative body.” Notice the phrase – authoritative body. Credibility not just by consuming the product/ service, but other certifications would be required for a recommendation to be taken seriously. Most popular doctors might not be most efficient. And mind you, the ratings are reviews might just be about the quality of the infrastructure, waiting time to meet the doctor, friendliness of the staff and the doctor, as well as other clinical processes followed by the doctor and her staff. However, while seeking a recommendation for a serious illness, there could be clients who trade-off these against doctor’s effectiveness in curing the illness. Here is why platforms like Practo would require doctors to add their certifications and academic credentials, and mandate that they update them every six months, apart from the ratings and reviews by patients.

So, when you design you platform’s user experience and feedback system, choose carefully – is a rating sufficient, or would you also want a review and a recommendation?

100% FDI in e-commerce – will prices fall?

On the 29th March 2016, the Government of India allowed 100% FDI in Indian e-commerce firms. While there is reason to cheer about the fast-growing sector getting more access to much needed funds for fuelling growth, there are three interesting developments in the notification.

  1. The Government has explicitly defined what is a marketplace model, as different from an inventory model.
  2. The consequence of this definition means that marketplace ecommerce firms cannot have a single retailer selling more than 25% of the retailer’s sales.
  3. The definition also means that the retailer cannot provide discounts and promotional offers on their own, directly or indirectly.

The impact of these three definitional changes would in the short run, require marketplace e-commerce firms to discontinue price discounts they offer directly or indirectly. Amazon’s promotional funding to sellers, PayTM’s cash back offers, or Flipkart’s big billion sale have to end. Will this mean they would stop offering discounts? I do not believe they will. They will find other ingenious ways of providing the customer with discounts, given that they would have access to larger source of funding through the FDI investments. More on that below.

It’s the sellers that matter

This definition of the marketplace model would clearly lead to interesting dynamics on the seller side. For instance, an SMB seller who would otherwise be listing his goods across multiple e-commerce companies would now be wooed by more and more marketplaces, as they seek to expand their base of sellers. Do you realize that the firm that owns the site www.amazon.in is actually called Amazon Seller Services India Pvt. Ltd.? In order to expand and sustain their broad base of sellers, these marketplaces would now have to offer discounts and freebies to the seller side, rather than the buyer side as it was apparent in all these years of growth. These seller-side offers would eventually translate into lower prices for buyers in two ways.

One, in the traditional sense of the word, the seller bargaining power would go up; sellers’ multi-homing costs (costs of simultaneously offering their products and services across multiple marketplaces) would come down; and the volumes would go up. Larger sellers therefore, would invest in technology to manage their multi-homing costs, automate a lot of processes, outsource specialised functions like last-mile delivery to focused service providers, and would grow their own sourcing networks. Smaller sellers on these marketplaces would have no incentive to be remain small, and would either get gobbled up in a consolidation game or become second-tier sellers to the larger sellers operating on the marketplace e-commerce retail. This consolidation and growth of sellers on the marketplace would result in lower costs through economies of scale and scope, which the seller would eventually pass on to the buyers.

Two, the consolidation of the seller market would lead to fierce competition across sellers; and the basis of competition between the sellers is likely to be only price. Other differentiators like product variety/ features and brand are likely to be owned by manufacturers/ marketers (like Samsung), whereas service differentiators like distribution network, logistics and related customer service are likely to be managed by the marketplace. The only bases of competition for the sellers to compete would be (a) optimisation of inventory to reap appropriate economies of scale and scope, (b) managing distributed inventory through accurate prediction and forecasting of demand and supply, and (c) reducing costs through faster inventory turns as well as leveraging their bargaining power with manufacturers as well as retailers/ ecommerce firms.

Good times are here to stay (for the consumers)!

So, in effect these regulations do not necessarily mean that the prices in the ecommerce retail would rise and match the offline prices. There may be small adjustments; but in the long run, the discounting would shift from the retailer to the supplier. And the consumer would continue to enjoy lower prices (offered by the sellers) along with superior customer service (provided by the retailer, as this would be the only basis of competition across  marketplace e-commerce competitors).

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