E-commerce startups

Very few successful e-commerce companies were started in the 2000s. Since then, e-commerce startups have enjoyed a revival. Dozens of companies have gotten traction and venture dollars have followed. Phrases like flash sales, social commerce, and subscription commerce have entered the startup lexicon.

As Josh Kopelman points out, the list of the top 15 e-commerce companies has barely changed over the past decade, in sharp contrast to the list of overall top internet companies. This can be interpreted in one of two ways.

The bull case is that startups neglected e-commerce and are now waking up to the opportunity. The key equation driving e-commerce is: profit = lifetime customer value minus customer acquisition costs. New marketing strategies (“content plus commerce”, social commerce, etc) lower acquisition costs enough to make startups competitive with incumbents.

The bear case is that scale and brand effects make e-commerce incumbents nearly unbeatable. As one entrepreneur said, “If it has a UPC code, Amazon will beat you.” A lower price is just one search away. The only way to compete is to sell used stuff or make your own products (or provide a marketplace for those things). The fat head (large incumbents) and the long tail (artisanal shops) will thrive, but the middle of the distribution will suffer. (The public markets seem to agree with this assessment, e.g. Overstock trades at 0.2x revenues.)

What most people agree on is that e-commerce as a whole will continue to grow rapidly and eat into offline commerce. In the steady state, offline commerce will serve only two purposes: immediacy (stuff you need right away), and experiences (showroom, fun venues). All other commerce will happen online.

Pricing to the demand curve

Many college microeconomics courses include the following exercise. The teacher offers the students an imaginary trip to Hawaii, and asks them to write down on notecards how much they are willing to pay for the trip. The teacher takes the notecards and graphs the bids. Here’s how the graph might look:

The y-axis is the students’ “willingness-to-pay” and the x-axis is the students sorted from highest to lowest bids. The line is known as the demand curve.

Now imagine you’re the company selling these trips. For simplicity, suppose you’ve already bought the trips, so your marginal cost is zero. What’s the optimal price you should charge? If you set the price at, say, $500, then the students who are willing to pay above $500 would buy the trip, and the rest wouldn’t:

Your total revenue and (assuming zero marginal cost) profit will be the area of the green square (revenue times quantity).

Notice the sections under the curve to the right and above the green box. To the right are students who were willing to pay but were priced out. Those are missed sales opportunities. Above the green box are students who were willing to pay more than you charged. That is lost revenue. (Since the underpricing benefits customers, the area above the green box is called the consumer surplus).

After you have chosen the right price, the only way to make the area under the curve greener is to charge different customers different prices. The theoretically optimal way to do this is to look at each notecard and offer to charge each student, say, 10% less than the prices he or she bid. In real life you can’t do this (although Priceline has gotten close by asking customers to enter their willingness to pay). Some companies – most famously Amazon – have attempted outright price discrimination, but this tends to anger customers and can even run afoul of the law.

So the goal of pricing is to capture as much area under the demand curve as possible. In practice, the best way to do this is to find proxies for willingness-to-pay that are easy to observe and that customers will accept.

For example, airlines know that business customers will pay more than vacation travelers. They therefore look for acceptable proxies to segment business and vacation travelers and capture more of the area under the demand curve.

This is why flights are cheaper when you book early, stay over on weekends etc. The airline pricing models assume you are a vacation traveller.

Book publishers would like to price their books according to customer enthusiasm. Hardcore fans will pay more for books when they are first published, and casual readers will wait. If publishers offer the same book at different prices at different times, their price discrimination will be too obvious (interestingly, time windowing for movies doesn’t provoke much outrage). So book publishers offer modestly better goods – hardcovers – to early buyers.

Enterprise software companies price using proxies for the customer’s budget. Oracle databases are priced by the number of processors. Salesforce is priced by the number of end users (“seats”). Many enterprise software companies obfuscate the highest tier of pricing, telling sales prospects at that level to “call us.” What this really means is: “Call us, so our sales people can attempt to estimate your budget and price discriminate accordingly.”

Sometimes, the search for pricing proxies can lead to absurdity. I once heard someone from a prominent hardware company tell a story about how his company had offered two versions of a printer. The cheaper model was identical to the more expensive one, except the cheaper one printed fewer pages per minute. To accomplish this, the cheaper printer had the same hardware as the expensive one, except the cheaper one had an additional chip that forced it to slow down. This made the cheaper printer more expensive to produce. Situations where cost and price have zero or negative correlation are far more common than most people assume.

eBay vs Amazon: decentralized vs centralized e-commerce

Note: The company I cofounded, Hunch, was acquired by eBay in November 2011. I am now an eBay employee. But all the opinions expressed below are my own, and were developed prior to the Hunch acquisition, through my own research on e-commerce.

Amazon and eBay are the two largest e-commerce companies. As of this writing, Amazon has a market cap of about $87B, trading at a trailing twelve-month P/E of about 139. eBay has a market cap of about $42B, trading at a trailing P/E of about 13. Each company competes with many other companies in many different areas. For example, Amazon competes with Apple on tablets (Kindle vs iPad) and digital media (Amazon’s media store vs iTunes). Ebay’s Paypal unit competes with multiple payment companies, and its marketplaces division competes with other “peer-to-peer” e-commerce sites like Craigslist. But given the potential size of the e-commerce market (not to mention the online-to-offline commerce market), Amazon and eBay’s main competitors are each other. And to understand their large strategic moves (e.g. large acquisitions like GSI and Zappos), it is important to understand their fundamentally opposing strategic outlooks: eBay wants commerce to be more decentralized (around its GSI/Magento partners and eBay marketplaces sellers) and Amazon wants it to be more centralized (around itself).

First, some background. During the dot-com boom, many largest offline brands debated how to best move their businesses online. Some tried to build their own websites from scratch. Others partnered with commerce technology providers. Toys ‘R’ Us took a novel approach and signed a “strategic alliance” to outsource all of their e-commerce operations to Amazon. Over the next few years this relationship soured – apparently Toys ‘R’ Us felt Amazon was competing too directly with them and successfully sued to end the relationship.

The end of the Toys ‘R’ Us – Amazon relationship marked a turning point for a company called GSI Commerce. GSI took an aggressively neutral approach to providing technology and marketing solutions to retailers. Their main appeal over Amazon is that they didn’t compete with their partners (but of course their partners competed with each other). This approach paid off: GSI now powers over 500 large commerce sites, including Toys ‘R’ Us, Adidas, Ralph Lauren, and the commerce sites of all the large sports leagues like the NFL, MLB and NBA.

Last year, eBay paid $2.4B to acquire GSI Commerce. They also acquired a smaller company called Magento that provides e-commerce technologies to smaller retailers. You can think of GSI as the leading commerce platform for the “fat head” of retailers, and Magento as the leader for the long tail.

The key difference between eBay and Amazon isn’t auctions vs. fixed price sales (the majority of eBay sales aren’t auctions anymore). It is that eBay doesn’t take inventory, and prefers to be an intermediary that facilitates peer-to-peer commerce. This strategy wins if e-commerce becomes more decentralized, with the majority of commerce continuing flow through small to medium retailers. In this world, eBay makes money by sending traffic from eBay.com, from fees collected by GSI and Magento, and Paypal transaction fees. In a centralized world, Amazon grows its current 9% e-commerce market share to a much larger percentage, taking advantage of its scale, efficiency, advanced technology, and the convenience of shopping in one place.

One way to view this battle is to think of eBay as a platform a la Windows or Android and Amazon as an end-to-end solution a la Apple computers in the 90s or iOS devices today. Platforms tend to provide greater diversity. In the case of e-commerce, the platform approach could also have a price advantage. As the CEO of TrialPay, Alex Rampell, argues: “Who can beat Amazon on price? The companies whose products are sold on Amazon”. End-to-end solutions like Amazon’s tend to provide greater convenience and a better user experience.

I’m not arguing that one approach is superior to the other. My point is simply that when you understand that the battle is between centralized and decentralized commerce, the strategic moves of the two companies make a lot more sense.

 

Experiment: blog in Kindle book form

There is an amazing amount of useful, free information available on tech blogs for fledgling tech entrepreneurs (this list is a great place to start). I think sometimes we techies forget that this wealth of content is unknown to the non-startup world. I was reminded of this recently when I met a first-time entrepreneur who said when he was first starting out he tried finding books on Amazon, Googling for stuff etc. He described it as an epiphany the first time he stumbled upon Fred Wilson’s blog, which then led him to Brad Feld, Mark Suster, Eric Ries, Venture Hacks, etc.

So this weekend I thought I’d try an experiment. I took about 100 of my blog posts (the ones that I thought were most “evergreen”), bundled them as a PDF and submitted them to the Kindle Store. The Kindle submission process was surprisingly easy. You give your book a name and upload the PDF and then choose pricing.  They force you to charge a minimum of $0.99.  Also, strangely, if you charge less than $2.99, Amazon takes 70% of the revenue, but if you charge between $2.99-$10 they only keep 30%.

I decided to price my book at $2.99 and donate all of the proceeds (~$2 book) to HackNY, a non-profit that “keeps the kids off the Street” (encourages college students to join/start tech startups instead of working on Wall Street). All of the content in the book is available for free on cdixon.org. The only reason to buy the book is to get this blog in a different format and to support a good charity. It is available in the Kindle Store here.

I don’t expect many people to buy the book but maybe some first-time entrepreneurs will stumble on it and from there discover more tech blogs. Think of it as “Kindle SEO” for tech blogs.

Finally, I am having trouble getting the links to work on the Kindle version. I’m not sure if this is an Amazon policy or if I am just doing something wrong (the links work fine in the PDF I uploaded to Amazon). So here is an alternative version on Scribd that has working links.

While Google fights on the edges, Amazon is attacking their core

Google is fighting battles on almost every front:  social networking, mobile operating systems, web browsers, office apps, and so on.  Much of this makes sense, inasmuch as it is strategic for them to dominate or commoditize each layer that stands between human beings and online ads.  But while they are doing this, they are leaving their core business vulnerable, particularly to Amazon.

When legendary VC John Doerr quit Amazon’s board a few months ago, savvy industry observers like TechCrunch speculated that Google might begin directly competing with Amazon:

[Google] competes with Amazon in a number of areas, particularly web services and big data. And down the road, Google may compete directly in other ways as well. Froogle was a flop, but don’t think Google doesn’t want a bigger chunk of ecommerce revenue from people who begin their product searches on their search engine.*

In fact, Google and Amazon’s are already direct competitors in their core businesses. Like Amazon, Google makes the vast majority of its revenue from users who are looking to make an online purchase. Other query types – searches related to news, blog posts, funny videos, etc. – are mostly a loss leaders for Google.

The key risk for Google is that they are heavily dependent on online purchasing being a two-stage process:  the user does a search on Google, and then clicks on an ad to buy something on another site. As long as the e-commerce world is sufficiently fragmented, users will prefer an intermediary like Google to help them find the right product or merchant. But as Amazon increasingly dominates the e-commerce market, this fragmentation could go away along with users’ need for an intermediary.**

Moreover, Google’s algorithmic results for product searches are generally poor. (Try using Google to decide what dishwasher to buy). These poor results might actually lead to short term revenue increases since the sponsored links are superior to the unsponsored ones.  But long term if Google continues producing poor product search results and Amazon continues consolidating the e-commerce market, Google’s core business is at serious risk.

* Froogle (and Google Products) have been unsuccessful most likely because Google has had no incentive to make them better: they make plenty of money on these queries already on a CPC basis, and would likely make less if they moved to a CPA model.

** Most Amazon Prime customers probably already do skip Google and go directly to Amazon.  I know I do.