Alibaba And JD.com Business Model Analysis: Which Is Better?

Summary

• The “platform” business model usually generates higher margins than the “direct retailing” model.
• Alibaba’s platform business model has drawbacks such as lower control of product quality and weak logistic services.
• The demonstrated customer adherence to Taobao and Tmall marketplace plus the strong executive force in solving problems with its platforms will make Alibaba a more attractive investment opportunity than JD.

Alibaba (NYSE:BABA) and JD.com (NASDAQ:JD) are the two largest online retailers in China. In the first half of 2014, Alibaba's Tmall platform commended 57.4% of the B2C market, ranking No. 1 in market share followed by JD with 21.1% of market share. Both companies have been growing their businesses very fast. In third quarter 2014, Alibaba's GMV increased 49% and active buyers increased 52% year-over-year. JD grew even faster with GMV and active buyers picking up 111% and 109%, respectively, for the quarter. Although both companies are riding the trend of accelerated e-commerce in China, I believe Alibaba provides a better investment opportunity primarily because of its "platform" business model.

Alibaba adopted a "platform" model. It derives the revenue from online marketing services and earns commissions on merchandises sold on its platforms, whereas JD is an online direct seller and earns the mark-up from products sold to customers. Although JD has also developed the marketplace for third-party sellers, it represented only 6% of total net revenues. As the cost of acquiring products constituting a large part of the cost base, JD has pretty thin margins. In addition, the fulfilment expense as a result of establishing its own national fulfilment infrastructures also squeezed the margins. To the contrary, Alibaba carries an asset-light business and earns hefty profit margins because it doesn't procure, store and deliver the products itself, but offers a marketplace to sellers, buyers and logistic service providers. The below table summarizes the major differences between the two companies.

Table 1 Comparison between Alibaba and JD

	Alibaba	JD
Business model	Online platform for retailers	Online direct sales
Means of making money	Earn from merchants through online marketing services, commissions on transactions. etc.	Directly procuring, storing and delivering goods to earn a margin
logistics	Partnership with third-party logistic companies to provide logistic services	Own nationwide dispatch and fulfilment centers, and delivery networks
After sale services	Almost none	Well established customer services, fast response to after sales queries
Assortment of goods	Greater assortment	40.2 million SKUs (Electronic products and home appliances account for 63.6%)
Merchandises' price in general	Relatively low due to vast number of sellers that increase the competition and beat down the selling price	Relatively high as selling price has to at least cover the cost of sales
Profit margins(3Q14) Gross margin Operating margin	71% 34%	9.9% -0.8%

The fact that the "platform" model generates higher margins is not unique in e-commence market in China, but also appears in mature markets, such as the US. Take eBay (NASDAQ:EBAY) and Amazon (NASDAQ:AMZN) for example. The former is a pure platform operator whereas the latter is a dual player in online direct sales and marketplace operating, but online direct sales take greater weight in Amazon's total net sales. Table 2 compares the profit margins of the two companies. We see from the table that eBay has much higher gross margins and operating margins than Amazon. Admittedly, there are other factors, including the management's strategic decision that lead to Amazon's near-zero operating margins. For instance, in the prime membership program, Amazon offers members unlimited free shipping, which resulted in the shipping cost exceeding the shipping revenue. Nevertheless, the comparison between eBay and Amazon did illustrate the difference of profitability between the two business models.

Table 2 Comparison between eBay and Amazon

	eBay	Amazon
Business model	"platform" model	Mix of "platform" and direct retailing model
Gross margin(NYSE:TTM)	68%	28.6%
Operating margin(TTM)	19.8%(37.3% for Marketplace segment only)	0.1%

Back to Table 1, we see there is a negative side in Alibaba's platform model, which is primarily its weakness in controlling counterfeit products. Many people think of Alibaba's Taobao marketplace as a chaotic bazaar. The prevailing counterfeit products have resulted in the loss of trust from many online shoppers. In contrast, as JD sells its own merchandise, it takes product quality seriously, placing strict quality check from sourcing the products. Hence, JD has been gradually establishing credibility among customers.

In addition, JD provides better delivery and after sale services. For example, relying on its own fulfilment infrastructure and delivery network, JD promises the "same day" delivery in some major cities. JD also promises home pick-up of the defected product if a quality problem is identified within 15 days from the sale and promises to replace the defected product with a new order or refund within 100 minutes. Moreover, JD provides the home repair services if a quality problem arises within one year from the sale for their direct selling products. None of these are achieved from Alibaba's marketplaces at present.

Considering both the pros and cons of the two business models, I believe the "platform" model is more attractive for an e-commerce business. As we can see, both Amazon and JD originated from direct retailing and are scaling up the third-party business. Having that in mind, I still prefer Alibaba over JD for the following two reasons:

1. Alibaba's marketplaces displayed strong customer adherence.

First, price and product assortment are still the most important factors for Chinese shoppers. The development of the online retailing industry usually has to experience three stages. The first stage is the competition on products' availability and price, where retailers or platforms that sell products with a lower price and greater assortment will stand out. The second stage is the competition on products' quality and delivery services. Passing through the first two stages, successful online retailers or marketplace operators will be able to establish their brand and gradually accumulate their brand value. In the third stage, the market competition will hinge on consumers' shopping experience and their brand loyalty, i.e. consumers will choose their favorite shopping site. Platform operators or retailers with a brand reputation and that give consumers a better shopping experience will be the winner of the market.

In China, as e-commerce is still in the early stage of development, I think the industry is transitioning from the first stage to the second stage, i.e. products' availability and price are still paramount, though more and more shoppers, particularly those in the first and second-tier cities, started to care more about the services. From this prospective, though JD leads Taobao marketplace and Tmall in after sale services, low price and a variety of choices remain the primary concern for the majority of Chinese online shoppers. Therefore, Taobao and Tmall are still the No. 1 shopping sites in China.

Second, if breaking down the market share by product categories, we find that the only category of products of which JD has taken away the market share from Tmall in the B2C market is the computers, communication and consumer electronics products (3C-products). In 2012, JD had 38.1% of the market share in 3C-products as compared with Tmall's 25.6%. In all the rest of the product categories, Tmall still possesses the largest market share. This is understandable as 3C-products are the kind of products that consumers care about the quality the most.

2. Alibaba will be able to conquer the problems and bridge the gap with JD in the near future.

In my opinion, JD's advantages are not enduring. Alibaba has the capacity to catch it up. The top priority for Alibaba is to crack down on counterfeit goods and rebuild credibility among consumers. Once Alibaba can guarantee the quality of the merchandise sold from its platforms, it will be able to defend the attack from competitors and strengthen its market leading position. In fact, Alibaba has adopted a number of measures, including launching the rating system for sellers, adopting more stringent admission standards for sellers who intend to open stores in Alibaba's platforms, shortening the time for investigation of the vendors who are suspected to be involved in selling fake products and more severe punishment for vendors selling counterfeits. We have seen the Taobao marketplace and Tmall becoming more and more regulated.

The second is to improve the logistic services. China's logistics industry is highly fragmented, featuring intense competition, low profitability and poor services. It's said that complaints towards dispatch and delivery services from online shoppers in China accounted for 80% of total complaints. To combat this problem, JD invested heavily to develop its own logistic network - an integrated logistic system that JD controls every stage of the logistic process, which leads JD to an asset-heavy business. Alibaba has chosen a different way- it partnered with selected logistic companies through equity investment. Although at the current stage the delivery services from Alibaba's marketplaces are not as satisfactory as that from JD due to lack of direct control over the fulfilment, dispatch and delivery process from Alibaba, it has the potential for significant improvement in the future - Alibaba has established a logistic information system operated by China Smart Logistics in which Alibaba committed RMB2400 million for a 48% stake. The system provides useful information to buyers, sellers and logistic partners to improve the efficiency of logistic services, such as real-time tracking, self-service pick-up, performance analytics, customer satisfaction rating, route planning and order volume forecasts, etc. This information allows Alibaba's logistics partners to operate more efficiently by optimizing their warehouse, transport and people resources to effectively meet consumer demand. Its goal is to enable the delivery of over 100 million packages per day anywhere in China within 24 hours of an order being placed. Though it looks ambitious, it demonstrates that Alibaba is on the right track to improve the logistic services.

Conclusion

For an e-commerce business, a "platform" business model is superior to a direct sales model. Although Alibaba's marketplace has its drawbacks, such as prevailing counterfeit products and inferior logistic services, such problems will not substantially undermine the attractiveness of its platform model. We believe Alibaba will have the capacity to combat these problems in the foreseeable future, making BABA a valuable investment.

Mobile Advertising

Ad inventory is typically broken down into four buckets: sponsorships, premium guaranteed, audience targeted, and remnant. Each of these buckets can be sold through a variety of sales channels.

image: http://www.imediaconnection.com/images/content/1208_Picard_image_1.jpg

Revenue distribution across this "layer-cake" inventory model flows downward -- with the vast majority of inventory coming from premium and a significantly lower amount of revenue coming from the remainder:

image: http://www.imediaconnection.com/images/content/1208_Picard_image_2.jpg

The process of an advertising sale begins with the media buyer, who sends a request for proposal (RFP) document to numerous publishers. These RFPs typically are written in prose and define the overall goals of the advertiser in question, and of the specific campaign being executed. A typical RFP has between 50 and 100 elements that are laid before the publisher as acceptable or desirable outcomes, and these elements (attributes or attributes of the buy) are generally descriptors of the audience, of the media the advertiser is looking to run on, of the acceptable (and unacceptable) content to be associated with, etc.

Advertising inventory is the base unit sold by a publisher to an advertiser. It is measured in "impressions," which are defined as an opportunity to show an advertisement to a person. Impressions at their most basic are blank vessels made up of opportunity. Inventory is generally defined in advance by the seller based on a variety of factors, and it is these predefined impressions that are contractually agreed up on between buyer and seller.

Nearly all impressions sold are made up initially of one or two media attributes based on content association (e.g., MSN>Entertainment or MSN>Entertainment>Celebrities; Yahoo>Autos, or Yahoo>Autos>News). Or they're sold just based on category -- in some cases blind, meaning without the knowledge of which publisher the impression ran on. Further refinement of the inventory is based on other attributes such as above the fold, rich media units, or a variety of quality scores. Additional media attributes included in the definition of a piece of sold inventory include various types of targeting and other types of intelligence and filtering such as inventory quality scores and contextual targeting.

Beyond media attributes, there are numerous audience-based targeting attributes available for the buyer to request, or for the seller to offer. These include such attributes as geographic, demographic, psychographic, behavioral, etc.

It is the combination of these various attributes that define the inventory that is sold. Inventory is sold in a number of ways, including on a guaranteed basis (a buyer contracts with a seller for a fixed volume of inventory between specific dates) and on a non-guaranteed basis (if inventory is available that matches, it will be sold, but the seller doesn't make any guarantees on volume).

In order to predict how much inventory will be available, publisher ad platforms need to look at historical data with seasonality and apply some very sophisticated algorithms to make a guess as to how much inventory will be available during specific date ranges. These "avails," as they are called, become the basis for how all guaranteed ad sales are done.

But ad inventory has many very complex and difficult-to-predict issues that are endemic to the problem -- the problem of predicting how many impressions will exist in a specific month is sort of like imagining how many cars will cross the Golden Gate Bridge in a given week. Predicting this based on historical data isn't too hard. And predicting the color of the various cars that might cross the bridge is probably feasible with some degree of accuracy. Maybe even predicting the general destinations of the cars crossing the bridge is possible. But trying to predict how many red Toyotas driven by women with an infant in the car who have red hair and who make more than $125,000 annually is probably not a solvable problem.

This is akin to the requests given on a daily basis regarding ad targeting. This type of prediction is extremely technically challenging; nobody has been able to accurately predict how much ad inventory will be available in advance for more than three to four targeting attributes in advance. Therefore, publishers rarely will sell inventory that contains more than three to four attributes because this causes an immense amount of work during the live ad campaign for the publisher's ad operations team. (They must monitor ad delivery carefully and adjust numerous settings in order to ensure delivery of the campaign.)

Inventory is sold within a contract called an insertion order (I/O), and each sold element is typically called a "line item" on the I/O. Line items correspond to a variety of attributes within the publisher's inventory management systems. A simple example would be MSN>Entertainment. But a more complex example would be MSN>Entertainment>Women>18-34.

Beyond a typical guaranteed media buy, there are several other mechanisms for selling ads. Some ads are re-sold by a third party such as an ad network (examples include Collective Media, ValueClick, Advertising.com, etc.). Some ads are sold through an automated channel such as a supply-side platform, or SSP (examples include Rubicon, Admeld, PubMatic, etc.). There are also ad exchanges that can sit in the middle of all the transactions, and as the industry has matured, the difference between an exchange and an SSP has become less clear. These exchanges and SSPs then create a marketplace that allows ad networks and various demand-side platforms (DSPs) to compete for the inventory in real time. We'll refer to this as real-time bidding (RTB) even though in some cases this term doesn't apply exactly. 

The management systems for buying RTB inventory are generally called demand-side platforms (DSPs). In RTB media buys, it is extremely rare to have more than three to four targeting attributes (just like in guaranteed media buys), not because of prediction but because inventory that exists for each campaign or line item that contains more than three to four attributes delivers with extremely low volume. In fact, the amount of inventory available on a per-impression basis as you layer on more targeting attributes generally drops significantly with each new attribute.  This means that a typical line item for an RTB campaign would look very much like the one for a guaranteed buy: Entertainment>Women>18-34.

For a DSP to spend an entire media buy at more than four targeting attributes, the buyer would have to manually create hundreds or thousands of ad campaigns that each would then be manually optimized and managed. It isn't actually feasible to do this at scale manually.

In summary In a perfect world, advertisers would be able to find all available ad inventory that matches their goals, with as many attributes as exist on all impressions. The problem is that existing inventory management and ad serving systems are not designed to deal well with more than two to three concurrent targeting attributes, whether for guaranteed media buys or RTB.

So why do advertisers and publishers prefer to sell ads on a guaranteed basis?

Inventory guarantees serve several purposes. The most critical is predictability; media buyers have agreed with the advertiser on a set advertising budget to be spent on a monthly basis throughout the year. They are contractually obligated to spend that budget, and it is one of their primary key performance indicators. Publishers like to have revenue predictability as well, which is solved by selling a guarantee on volumes for a fixed budget.

For all the innovation in the ad-tech space over the last decade, it's fairly impressive that very few of the core problems of a publisher have been solved. At the end of the day, 60-80 percent of the revenue that publishers bring in comes from their premium inventory, sold on a guaranteed basis -- which represents generally less than half of all their available inventory. Nearly all the ad technology innovation in the last decade has focused on what to do with that other half in order to raise the median price of that revenue from nearly zero to a bit more than zero.

It seems to me that there is an opportunity to focus on something else. (And you might imagine that I'm doing just that.)

Source: http://www.imediaconnection.com/content/32420.asp

E-commerce Companies : Ad Revenues vs Spends

Amazon collected $1 billion in 2014 from its online Ad sales. the same year Google Inc. too home more than $55 billion from advertising.

Nearer home, Indian E-commerce companies are realizing the potential to tap this pot. Flipkart is improving its ad platform by buying mobile advertising technology firm AdIQuity Technologies and the company plans to compete with the likes of Google and Facebook in India for a share of online ad spending.AdIQuity’s technology will help Flipkart tap its fast-growing user base and analyse consumer data and shopping patterns for generating ad revenue.

Flipkart and Snapdeal generate ad revenue mostly in three ways: by selling so-called banner ads; by getting brand partners such as Xiaomi to spend on marketing on their sites; and by charging extra fees for promoting third-party sellers. For instance, a third-party seller can pay extra to have its products shown first when a shopper uses certain keywords to search for goods on the two sites; if a user searches for “casual shoes”, a seller can ensure its products are shown prominently by paying extra.

As Flipkart and Snapdeal add thousands of sellers this year, these marketplaces are hoping that competition among sellers will prompt some of them to pay lucrative rates for prominent positioning. Flipkart has set itself a target of drawing 100,000 sellers this year to its site from 12,000-13,000 currently. And with a large user base that is growing fast, Flipkart and Snapdeal are also betting that retail brands, consumer goods makers and electronics brands will increasingly use their platforms to place advertisements. In India, a majority of online ad spending goes to Google and Facebook currently as there are few other sites with large traffic numbers.If successful, these moves can provide a much-needed boost to margins at Flipkart and Snapdeal and create an additional, large revenue stream for them. Both Flipkart and Snapdeal are trying to model themselves on Alibaba, which listed in the US last year in a record initial public offering. Alibaba generates more than 55% of its sales from ads. Though Flipkart generates less than 5% of its sales from ads, it is aggressively building the ads business. Making ads work is important enough for Flipkart that chief executive officer Sachin Bansal is spearheading this business. Flipkart generates about 75% of its traffic from its mobile app, while that number is 90% for Myntra. Both companies are betting that by becoming app-only, they will reduce costs, get more exclusive customers and reduce dependence on the likes of Google Inc. and Facebook Inc. for marketing.

Flipkart is readying its mobile ad platform and will start serving ads on its mobile app within the next three months, two people familiar with the matter said. As soon as it starts publishing ads on its app, the company will encourage its ad clients to shift their marketing efforts on the mobile.