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Monthly Archives: September 2008

Comment Spammers Gone Bad

I guess I should take it as a compliment that this blog is increasingly being hit by comment spammers looking for “link juice” by writing a lame comment followed by a link to an equally lame Web site.

Over the last few days, I’ve gotten some pretty bad attempts at comment spam. First, my recent article about Kayak.com – the travel Web site – received a comment with instructions on how to properly use a paddle in a kayak, followed by a link to an Internet marketing Web site. I guess if you build a semantic search comment spam tool, you run into this sort of problem.

Then today I received two comments in a row from an anonymous spammer. He gave a link to a safe search Web site, which basically sanitizes the Web for young kids. Apparently, however, the first time he attempt to spam me, it didn’t work. He then added this nice comment: “what the hell happened to the message i typed? shit!” Maybe he needs to start using that safe search site a little more to learn what is and is not appropriate language for a comment!

 
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Posted by on September 29, 2008 in comment spam

 

Good Profits and Bad Profits: Kayak Rowing in the Wrong Direction

One of my favorite travel Web sites for many years has been Kayak.com, the AJAX-based travel aggregator that scours multiple Web sites to find you the lowest prices on airfare and hotels. I liked Kayak because I could trust the site to find me the lowest fares, unlike many travel sites that tack on “service charges” or try to push their “recommended choices” first because these happen to give them a bigger commission.

I assumed that Kayak made their money from users choosing to purchase their ticket from a Kayak partner, like Orbitz or CheapTickets, and the fact that you could go straight to the airline was just a nice, user-friendly feature that drove “eyeballs” and customer loyalty. Good interface, user-friendly options – its just the sort of thing that makes an online company successful.

Over the last few months, however, Kayak has slowly been changing, and not for the better. First, I noticed that when you did a search there were several text boxes auto-checked at the bottom of the page. If you didn’t uncheck these you got new browser windows full of offers from Priceline or Expedia. Pretty much glorified pop-ups, not what any user likes to see.

More recently, I noticed that Kayak has removed the option of going straight to the airline booking site altogether. In other words, the low price you now see on Kayak includes a service charge from another travel Web site.

I’m sure that both the advertiser pop-up and the link to a service-charge based booking site increase Kayak’s revenue per visit, but the long-term impact of this short-term profit gain will likely be quite negative. In Fred Reichheld’s latest (and very awesome) book The Ultimate Question: Driving Good Profits and True Growth he draws a stark contrast between “good profits” and “bad profits.” First, here’s what he says about “bad profits”:

Whenever a customer feels misled, mistreated, ignored, or coerced, then profits from that customer are bad. Bad profits come from unfair or misleading pricing. Bad profits arise when companies save money by delivering a lousy customer experience. Bad profits are about extracting value from customers, not creative value. . . When complex pricing schemes dupe customers into paying more than necessary to meet their needs, those pricing schemes are contributing to bad profits. (emphasis added).

Now compare bad profits to good profits:

If bad profits are earned at the expense of the customers, good profits are earned with customers’ enthusiastic cooperation. A company earns good profits when it so delights its customers that they willingly come back for more – and not only that, they tell their friends and colleagues to do business with the company.

As I see it, Kayak started out as a “good profits” company and is rapidly descending into a “bad profits” company. As you might expect, companies that live on bad profits eventually lose customers, market share, and employee morale. Companies that thrive on good profits go the exact opposite direction. It’s never too late to become a “good profits” company and I hope Kayak will see the light and turn the boat in the right direction again!

 

Google’s Political Donations Over the Last Three Years

Google has a lot of reasons to care about national politics: potential Department of Justice anti-trust litigation, net neutrality, H1-B visas for foreign workers, corporate tax rates, and so on. So it makes sense that Google would want to use their influence to push the election toward the candidates that will bolster their business objectives.

In the last three years, Google has contributed over $185,000 to political candidates through their political action committee (PAC) called NetPac.

The top ten fund recipients were:

  1. Nancy Pelosi (D-CA) – Speaker of the House and California Representative – $12,000;
  2. Anna Eshoo (D-CA) – Representative of Google’s district in Mountain View and member of the Energy & Commerce Committee which works on Internet-related issues – $8,500;
  3. Barbara Boxer (D-CA) – California Senator – $8,500;
  4. John Dingell (D-MI) – Ranking member on the Energy & Commerce Committee, and also the representative for Ann Arbor Michigan, where Google has a large call center – $8,000;
  5. Arlen Specter (R-PA) – Ranking member of the Senate Judiciary Committee which includes Subcommittee on Antitrust, Competition Policy and Consumer Rights – $8,000;
  6. Frederick Boucher (D-VA) – Member of the Energy & Commerce Committee – $6,500;
  7. John Boehner (R-OH) – Member of Energy and Commerce Committee – $6,000;
  8. Zoe Lofgren (D-CA) – Representative for San Jose and parts of Silicon Valley – $6,000;
  9. Harry Reid (D-NV) – Senate Majority Leader – $6,000;
  10. Gordon Harold Smith (R-OR) – Serves on Committee on Commerce, Science & Transportation – $6,000

The top ten contributors to this PAC are not that shocking:

  1. Sergey Brin – $15,000;
  2. Vinton Cerf – $15,000;
  3. David Drummond – $15,000;
  4. Urs Hoelzle – $15,000;
  5. Jeffrey Huber – $15,000;
  6. Lawrence Page – $15,000;
  7. Jonathan Rosenberg – $15,000;
  8. Shona Brown – $10,000;
  9. William Coughran – $10,000;
  10. Robert Eustace – $10,000.

So now the question: based on this information – who (if anyone) will Google contribute money toward in the 2008 presidential election? Well, despite the fact that the seven out of Google’s top ten donations went to democrats, I think the truth is that Google is playing a very apolitical game here and will likely avoid contributions to either campaign.

Google’s past contributions basically fall into two categories: local politicians who can help Google out in Silicon Valley, and members of powerful Senate and House committees that directly impact Google’s business. The fact that many of these people are democrats makes sense considering the democratic control of the Congress and the resulting control of important committees.

In other words, Google waits to see who is in charge, and then contributes generously to the winner. In a close presidential election, the risk of backing the wrong candidate is too great considering the minimal return on an investment of a few thousand dollars.

 
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Posted by on September 17, 2008 in Uncategorized

 

Best . . . Spam . . . Ever

Just read this spam message and reflect on it for a minute – this is brilliant!

If this email is not spam, click here to submit the signatures to [Name Changed] – AntiSpam Service.


 
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Posted by on September 9, 2008 in spam poetry

 

Does Google Not Want Mortgage, Credit Card, Pay Day Loans, and Insurance Ads on AdSense?

Google has been very aggressive over the last year at promoting the content network (AdSense) to advertisers. One of the best innovations they’ve developed as a result is “placement targeting“, which enables advertisers to bid on a specific site (or a specific section of a site), rather than just buying the keyword “widget” and hoping that Google’s algorithm places their ads on the right sites.

Google’s placement targeting tool is very good at helping advertisers discover sites on which to advertise – they even have a mini-directory of top categories like “beauty” and “games” where you can immediately get a list of hundreds of category-specific sites.

But here’s the really weird thing about this category directory – there’s no category (or sub-category) for consumer finance. The very advertisers who practically power AdWords – insurance, credit cards, mortgages, pay day loans, debt consolidation, credit reports, banking, stock trading, etc, etc – you can’t find them in Google’s placement-targeting directory.

I cannot think of any reason of the top of my head why Google would want to hide this category from potential advertisers? Considering the billions they make off these advertisers on AdWords, it seems logical that they’d want to drive a lot of revenue through AdSense from these same advertisers.

I am certain, however, that this is not just an accidental omission – there is a good reason that Google has left these off the list, but what it is I don’t know. If anyone has any ideas, please post a comment with your theory!

 
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Posted by on September 8, 2008 in adsense, placement targeting

 

Best Practices in Bid Management: Part IV of The 7 Habits of Highly Effective SEM

Bid management is probably the most difficult and least understood aspect of search engine marketing. Indeed, it is so complex that I am confident that I won’t be able to truly do it justice in one short article. So consider this article an introduction to the basics of bid management, not the be-all, end-all document. In a coming print issue of the magazine, I’ll go into more detail about some of the more advanced bid management techniques (rules-based bidding versus positional profit optimization, for example).

It All Begins with Tracking. Whether you are Walmart.com or selling out of your garage, your bid management is only as good as your tracking. There is simply no excuse not to have keyword-level tracking for all of your paid search campaigns – without it, you might as well consider your spend on the search engines a charitable donation to the Larry and Sergei private jet foundation.

The simplest way to quickly get keyword-level tracking is to install the search engines’ conversion pixels. These are small bits of code that have virtually no impact on your site’s load time and can be implemented by anyone with a basic knowledge of HTML. Install these tracking pixels and you’ll be able to see which keyword and often which ad text, search query, and referring site drove your conversions. You can then immediately start reducing or pausing keywords/ad text/referrers that aren’t bringing in the appropriate return.

Rules-Based Bidding: The Industry Standard. The easiest and most popular mode of bidding is “rules-based bidding.” Rules-based bidding means that you establish the value of a click to you, then bid a portion of that value based on a business objective. I realize that the preceding sentence makes it sound pretty complicated, but trust me it isn’t. There are three parts to rules-based bidding: A) determine your business objective; B) set minimum data thresholds; C) calculate the appropriate bids.

A. I have generally seen three business objectives occur over and over again in SEM campaigns:

1) Maximize revenue within a given budget. If you are start-up trying to grab market share, you may look at SEM as a means to grab as many customers as you can as quickly as possible, without regard to profit dollars. In such a case, your objective is to drive maximum revenue/leads/sign-ups/whatever within the constraints of your marketing budget.

2) Maximize profit. Most lead generation companies and many mature businesses are concerned with profit and profit alone. In such a case, a business would rather drive $5 of revenue with profit of $4 then drive $1,000,000 of revenue with profit of $1. Of course that’s a bit of an extreme example, but the point here is that a profit maximization strategy does not look at revenue or margin as a goal but rather as a means to drive the most profit.

3) Maximize revenue with a margin constraint. This is probably the most popular business objective. The goal here is to get as much revenue as you can, provided that you don’t go below the company’s margin objective. This enables a business to grow revenue/customers/market share while at the same time ensuring that this growth is not coming at a rate that will bankrupt the company. Basically it’s a hybrid of the aggressive growth approach of revenue maximization and the aggressive profit approach of profit maximization.

B. The next step in rules-based bidding is to determine your minimum data thresholds. The concept here is that you don’t want to bid adjust every keyword every day, simply because most of your keywords don’t have enough statistical data to make an informed bid. For example, if you have a keyword with one click and zero conversions, you wouldn’t want to reduce the bid to zero, nor would you want to make a dramatic increase in bid price on a keyword that received one click and one conversion.

I recommend a two-part approach to establishing minimum data thresholds – one based on time and the other based on your historical keyword performance. The time-based threshold basically suggests that you run data over multiple time periods – for example, you could run a 7 day report, a 14 day report, and a 28 day report. By doing this, you’ll quickly see that some keywords that didn’t get many clicks over a 7 day period are suddenly very significant over a 28 day period. You may also find the opposite to be true, where a sudden spike in clicks over a short-time period suggests that something has changed in the bid landscape that requires your attention.

For your historical keyword threshold, I recommend looking at three factors: clicks, cost, and conversions. Determine your historical conversion rate and revenue per conversion for your keywords, and then use this as a benchmark to determine when it is time to make a bid adjustment. For example, let’s say that you expect a 2% conversion rate and each conversion is worth $50 of revenue to you. Using this data, a simply threshold rule of thumb would be to say that you are going to bid-adjust any keyword that has gotten 30% more clicks than your average number of clicks required for a conversion (2% would mean 50 clicks to a conversion, 30% more would mean 65 clicks) or has cost you 30% more than the average revenue without a conversion ($65 – 30% more than $50). To account for opportunity keywords, you also want to identify keywords that may not have reached your minimum click or cost threshold, but have already gotten a certain number of conversions.

C. Now that you’ve got your business objectives and data thresholds established, it’s finally time to begin bidding (you thought it would never come, didn’t you?). A rules-based approach is defined by the following formula: Bid = RPC(1-MG) where RPC means “revenue per click” and MG means “margin goal.” Let’s put this into action. Say that you have a keyword that has received 100 clicks and $25 of revenue. Your goal is achieve a 20% margin. First, calculate your revenue per click. In this case $25/100 = $.25 RPC. Our margin goal is 20% which we express in the calculation as .2. Thus Bid = $.25(1-.2) or .25X.8 or a bid of $.20. Note that revenue per click doesn’t have to just be revenue, it can be “cost per conversion” or “cost per lead” or whatever your business metric is.

Combine Filtering with Your Bidding. If you’ve installed a conversion tracker, or better yet installed an analytics package (like Google Analytics, Omniture, or CoreMetrics), you can combine your rules-based system with additional data about your users to get even better results. I’ll be writing a separate column on filtering, so I am not going into a lot of detail on it here, but suffice to say, understanding day-parting, geo-targeting, match-type, and referrer conversion rates can have a huge impact on your bidding strategy.

Just to show this in practice, I’ve found that for some of my clients, conversions spike substantially between 7 and 9 AM and then around lunch time. Between 9am and noon, however, conversions plummet. Why is this? I suspect that people browse for products before work, then get into the office and work hard for a few hours, then go back online and start shopping during their lunch break. By increasing bids during peak shopping hours and reducing them when people aren’t serious about buying, I can achieve huge profit increases. The same is true for understanding all other elements of your user behavior.

Cluster. If you’ve built out a list of thousands of keywords, the odds are that there are many keywords in your mix that get a few clicks here and there but never get enough clicks to make it on to your 7 day, 14 day, or 28 day reports. This can often be a real problem for you, since these little keywords can collectively cost you a lot of money and margin. Consider, for example, if you had 1000 keywords that each cost you $5 a month and never converted – on an annual basis you’d end up spending $60,000 on these seemingly harmless keywords!

A good solution to stop these losses (on keywords I call ‘slow bleeders’) is to cluster groups of similar keywords together and bid en masse. If you’ve organized your Ad Groups into tightly knit groups of related keywords, the easiest way to do this is to simply create an Ad Group level default bid. For example, if you have five keywords in the Ad Group that have met your minimum data thresholds, but 200 that have not, you bid individually for the five keywords, but then aggregate click, cost, and revenue data for the remaining 200 and bid these together. If you want to get even more sophisticated, you can try to cluster keywords based on semantic similarity (words that are like each other) or behavioral similarity (users interact with the keywords in the same manner), but frankly I think creating very basic clustering rules is the best strategy to save your sanity.

Keywords are Zeros and Ones. It’s easy to fall in love with keywords. I know I sound like an uber-nerd just for saying that, but it’s hard not to get excited when you find that ‘secret’ keyword that your competitors haven’t discovered, or to just see a keyword drive in revenue day after day.

At the end of the day, however, to perfectly execute your bid strategy, you must remain impartial to all keywords. Although it sometimes hurts to bid reduce, pause or even delete one of your favorite keywords, numbers speak louder than your keyword affection. I tell my clients that I consider all keywords to basically be binary code – zeros and ones. If the keyword “coffee cake” sells diamond rings, I’m going to buy it, and if the keyword “diamond rings” doesn’t sell diamond rings, we’re going to cut it. Sometimes keyword bidding seems illogical – it can be hard to believe which keywords work and which ones don’t – but you have to listen to the numbers and not to your heart!

 
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Posted by on September 8, 2008 in 7 Habits, bid management

 

Geographic Performance Reporting from Google: Don’t Take This Feature Lightly!

Google recently launched a new report in AdWords: the geographic performance report. This is going to be a fairly brief post, so let me tell you exactly what I think about this report: if you have the Google Conversion Tracker installed, you are an absolute idiot not to check this report on a regular basis.

Could I make that point any more forcefully? Geographic performance will show you – down to the suburb if you want it to – the relative performance of different geographic regions. Let me give you an example of the power of this report. I have a client that has a service business in Arizona. They were buying keywords on a national level and appending the keyword with their location name (for example: “Tucson Chiropractor”). We bid lower nationally because the conversion rate was lower than a local campaign.

I ran the geographic performance report last night and did an analysis of performance by state and then rolled up the data to regions (i.e., West, East, Midwest, South). The south and the west were performing well, the midwest was slightly above average, and the east was absolutely horrendous. In fact, the east was 4oo% over the amount we were willing to pay for a lead. By pausing these eastern states, we’ll be able to raise our bids in the south and west. In other words, we’re no longer paying for bad traffic, but we’ll get more market share of the good traffic.

This geographic performance report is an absolute must. Congrats Google, you are once again light years ahead of your competitors. Now here’s two suggestions for the next iteration of this tool – first, enable geo-parting – allow us to vary our bid by state, city, or metro area. You could even offer a “radial bidding” tool, which would allow me to bid more for clicks coming from a short distance from my location, and less and the radius expands. Second, why am I only able to run a report on a daily basis and not summarize data up to the month or even all time? Someone at Google owes me a t-shirt for this suggestion!

 
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Posted by on September 5, 2008 in google geographic performance report

 

Google Chrome: Trust Us, We Aren’t Really Lizards from Outerspace Who Have Come to Harvest You for Food

Is it just me, or is the sudden flurry of Matt Cutts posts explaining the goodness of Google Chrome cause for concern?

Here’s a guy who posted a total of six times throughout all of August, and then suddenly launches five extensive posts in three days about Chrome. Just look at the titles of a few of these posts and tell me that this isn’t part of a major “We’re not evil like Microsoft and Internet Explorer” campaign:

“Preventing Paranoia: When Does Google Chrome Talk to Google.com”
“Answers to Common Google Chrome Objections”
“Google Does Not Want Rights to Things You Do Using Chrome”

Touchy, touchy!

 
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Posted by on September 4, 2008 in google chrome

 

eTail 2.0: It’s Not What You Think

There’s been a lot of talk in ecommerce circles about what the next generation of Internet retailing will look like. The trendy predictions you’ll hear involve things like “social shopping” (customer reviews, Wikis, user generated content, etc), and impressive user interfaces that weave together AJAX, video, and 360 degree product reviews. These are all worthwhile endeavors that will increase conversion rate for merchants who implement them, but eTail 2.0 isn’t just about conversion rate, and therein lies the secret to the next generation of successful online merchants. eTail 2.0, simply put, is customer retention.

eTail 1.0 Circa 2001 – If You Build It, They Will Buy
To date, the Internet has enabled easy growth via customer acquisition (and it may turn out, too easy). By simply paying the right cost per click, or buying the right banner ad, or even having the right domain name, your ecommerce store can show up front in center on Google, MSN, Yahoo, Shopping.com, and so on. Consumers, it seems, have been easily wowed by a nicely designed site, tax-free prices, and the increased selection that online stores offer. As a result, thousands of companies have created incredibly successful online retail businesses.

But lurking beneath this success is an ugly secret – many etailers do not have the means (and in some cases, the desire) to provide even a modicum of customer service. After all, when the concept of selling online first started, the idea was that ecommerce would eschew traditional offline costs (inventory, customer service, a brick and mortar store, etc) and pass the savings onto the customer.

Problem is, the early days of online shopping ended a few years ago. Today, consumers expect that an order placed online will come with the same level of service they would get from their local retailer. This creates quite a problem for etailers who have based their model on the ‘low prices, no infrastructure’ approach. These etailers – having refined their marketing strategy and user experience – are still adept at acquiring new customers. But these new customers now have different expectations than the early adopter customers of 2003. The customers of 2008 expect the same level of service and infrastructure online as they expect offline.

eTail 1.0 Circa 2008 – Death By A Thousand Cuts
The collision between eTail 1.0 retailers and eTail 2.0 customers is often not pretty. It often involves angry phone calls, complaints to the Better Business Bureau, negative feedback on shopping engines, multiple recitations of the bad shopping story to friends and relatives, and of course a vow never to shop at the specific store again.

This is a problem for etailers for three reasons. First, a pattern of bad customer service results in “negative customer retention” – instead of gaining new customers for life, the negative reviews drive away the specific customer at issue and any potential customer who hears/reads the tail of bad service. Second, bad customer service results in negative ratings on comparison shopping engines and anywhere else a consumer can post a review. These negative ratings can and are used by shopping engines, eBay, Amazon, and Google to ban bad service advertisers from advertising in the future, thereby cutting off any future growth.

Third – and perhaps most importantly – is that a lack of customer retention ultimately leads to non-competitive back-end economics. As I wrote in a prior post:

If you can get the customer to return five times and spend $100 each time, that’s $500 more you could spend profitably acquiring this customer. Moreover, it turns out that repeat customers tend to spend more than new customers, require less customer service, and are more likely to recommend your business to others. LTV can be a real cash cow for businesses that can crack it.

Inevitably, bad customer service catches up to an etailer. Publishers ban you from advertising, consumers spread the bad word to other consumers, and competitors out-spend you with superior back-end economics.

eTail 2.0 – Price, Select, Convenience AND Service
The emerging kings of ecommerce are companies that get customer service. They understand that in a Google Quality Score world, your customer acquisition channels can disappear overnight, and that the most valuable advertising comes from your brand advocates or net promoters.

I recently took a tour of Zappos.com headquarters in Las Vegas. The tour is open to anyone – indeed, you could probably be a direct competitor, identify yourself as such, and be welcomed with open arms. I think this tour should probably be a required activity for anyone involved in ecommerce, simply because the overall mantra you walk away with is “service, service, service.” Here’s a few examples of what I mean:

  • The Zappos motto is proudly displayed on the front door of the building: “We’re a service company that happens to sell shoes.”
  • Each and every employee of Zappos – regardless of position – must spend four weeks in customer fulfillment and customer service.
  • It takes an average of six seconds for any call into Zappos to be answered – 24 hours a day.
  • You can call Zappos and ask them to order a pizza for you . . . and they’ll do it!
  • In the front lobby, there’s a library of more than 100 business best-sellers – free to whoever wants to take them. All are focused on customer service.
  • If a customer orders a shoe on Zappos and it is out of stock, Zappos will order it from another retailer and get it delivered.
  • The Zappos fulfillment center in Kentucky is right next to UPS, resulting in rapid delivery of any product ordered.

Zappos doesn’t claim to be the cheapest place to order shoes online, but customers come back again and again. The Zappos Web site doesn’t have all the Web 2.0 bells and whistles, but consumers buy over a billion dollars of products annually.

Think of two of the biggest retailers online – Zappos and Amazon. What’s the one thing people say about these two companies again and again – “The package arrived much earlier than I thought.” Underpromise and overdeliver.

In 1999, you can differentiate etailers based on selection, price, or information. Today, these differentiations are disappearing quickly. Prices are usually no more than 5% different between retailers, selection is virtually identical, and Web design and technology have improved to the point that the difference between an A+ and an A- Web design aren’t that great.

In short, the process of buying online is becoming commoditized. The only differentiator left is customer service and fulfillment. Build a company that converts customer acquisitions into long term business through service and fulfillment and you will survive and grow. Build a company that acquires customers without regard for orders #2 through 100 from that customer, and you face extinction.

A Final Note from Zappos

I’ll end this post by quoting at length from the Zappos “About Us” page on their site. If you are a retailer and you read Zappos‘ credo, ask yourself how your business compares. If you can’t hold a candle to their customer service approach, what do you think will happen when Zappos expands beyond shoes to your vertical? If you aren’t scared, you aren’t paying attention.

So here is our vision:

  • One day, 30% of all retail transactions in the US will be online.
  • People will buy from the company with the best service and the best selection.
  • Zappos will be that company.

We believe that the speed at which a customer receives an online purchase plays a very important role in how that customer thinks about shopping online again in the future, so at Zappos, we have put a lot of focus on making sure the shoes get delivered to our customers as quickly as possible. In order to do that, we warehouse everything that we sell, and unlike most other online retailers, we don’t make an item available for sale unless it is physically present in our warehouse.

Our goal is to position Zappos as the online service leader. If we can get customers to associate the Zappos brand with the absolute best service, then we can expand into other product categories beyond shoes. And, we’re doing just that.

Internally, we have a saying:
We are a service company that happens to sell ________.

  • shoes
  • and handbags
  • and clothing
  • and eyewear
  • and watches
  • and accessories
  • (and eventually anything and everything)

We view shoes as just our foundation. We believe that as long as we are known for our service, then expanding into almost any category is possible.

So a little bit of information about shoes: It’s a $40 billion market in the US, and in 1999, $2 billion of that was sold by mail order catalogs. In surveying our first customers in 1999, we found that only 1 out of 3 customers had purchased shoes by mail order before, implying that the e-commerce market would be much bigger than $2 billion.

In brick and mortar stores, about 1 in 3 sales are lost due to the customer’s size not being in stock. Brick and mortar stores are limited in how much inventory they can carry, and therefore they are limited in the number of brands, number of styles per brand, and number of sizes and widths they can carry.

Zappos.com currently stocks more than 3 million shoes, handbags, clothing items and accessories from over 1,100 brands. We offer the absolute best selection of shoes available anywhere, but much more important to us is offering the absolute best service.

We staff our call center 24/7, and currently have a staff of over 1,300 people. The vast majority of our employees work on the front lines taking care of our customers or shipping shoes out of our warehouse. We believe that the most important key to our success will be our service-oriented culture, and we spend a lot of time and effort working on ways to constantly improve our culture.

As one example, every new employee that we hire in our corporate office is required to go through 4 weeks of Customer Loyalty training (answering phones in our call center) before starting the actual job that he/she was actually hired for. To us, customer service isn’t just a department — it is the entire company.

 
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Posted by on September 3, 2008 in customer service, etailers, zappos, zuberance

 

Google Chrome: A Few Quick Thoughts

News has leaked that Google is launching an open-source Web browser, called Google Chrome. My five second summary of the browser’s benefits is as follows:

  1. It operates like a multi-processor operating system, meaning that each tab on your browser runs by itself, and if one crashes, the entire browser will not crash (cool);
  2. It visually shows you nine Web sites in your cache when you start to type a URL into the browser bar (also cool);
  3. It has a lot of security features to prevent hackers from stealing your data (not sure how useful this is versus everything else out there);

Google has released a very long comic describing the application. My initial thought is that it sounds like this browser has some cool applications, but I also wonder what the folks at both Mozilla (FireFox) and Microsoft (Internet Explorer) think about this. Mozilla makes over $100 million a year from Google ads appearing on searches through the Mozilla browser; and Microsoft knows all too well how the world reacted to the bundling of IE with computers.

Which brings me to my favorite page in the comic – this one:

Ah yes, for the sake of competition! Too bad Microsoft didn’t think of this approach ten years ago.

 
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Posted by on September 2, 2008 in google chrome

 
 
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