Best Business Books of the Year

With the holiday season upon us, I thought I would write about my favorite business books of the year to provide some gift giving ideas for you and your teams. Here, in no particular order, are my favorites among the books I read this year. (Note: These books were not all published this year, but since I read them this year I’m including them in my list.)

Six Pixels of Separation: Everyone is Connected. Connect Your Business to Everyone.
by Mitch Joel

Six Pixels of Separation begins as a primer for any business leader with limited knowledge of the Internet’s capabilities and quickly turns into an indispensable set of guidelines and advice for any business person who plans to make use of the web (which should be any business person). Mitch Joel offers excellent insight and plenty of simple, direct, digestible advice. This is a must read.

The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty
by Sam L. Savage

Every business person should read this book. We are so often looking for precise numbers when precise numbers are unrealistic. The reality is, we would actually be much more accurate to use probabilities and ranges when referencing uncertain number such as sales forecasts or project timelines. Savage takes us through the dangers of using averages to describe distributions and offers solid solutions that can be used to better manage our business.
Preview Flaw of Averages

Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets
by Nassim Nicholas Taleb

This book made me think more than any book in recent memory. That may be partly because it’s pretty dense and I had to read it more slowly than I normally read. However, I’ll give a lot more credit to the fact that Taleb’s makes some very interesting points about the amount of randomness in our lives and how that randomness is all too often mistaken for something more substantive.
Preview Fooled by Randomness

How We Decide
by Jonah Lehrer
I loved this book. Jonah Lehrer takes us through some fairly common behavior economics principles and experiments, but the very interesting twist he takes is to explain the brain mechanics that drive our thinking and decisions. He really uncovers why we’re “predictably irrational” and provides great insight into how we make decisions and how we can use that knowledge to improve our decision making.

The Drunkard’s Walk: How Randomness Rules Our Lives
by Leonard Mlodinow

I’m on a randomness kick lately, and this is the book that got me started on it. Mlodinow does a nice job of illustrating some of the finer statistical points in a pretty accessible manner. While this book isn’t as deep at the book I’m currently reading, “Fooled by Randomness,” it’s definitely an easier read and does a nice job of covering the basics.
Preview The Drunkard’s Walk

Sway: The Irresistible Pull of Irrational Behavior
by Ori Brafman, Rom Brafman

Another one of the behavior economics books I so love. This one has some pretty interesting stories and anecdotes, and its insights benefit from one of the writers being a psychologist and the other a businessman.
Preview Sway

More Than a Motorcycle: The Leadership Journey at Harley-Davidson
By Rich Teerlink and Lee Ozley

This is a very interesting book about culture change at Harley-Davidson during the ’90s written by the CEO and lead consultant who initiated the change. It can be a bit dry at times, but the details behind the thinking and the execution are excellent. I learned a lot by reading it.
Preview More than a Motorcycle


And here are some great books that I re-read this year:

The OPEN Brand: When Push Comes to Pull in a Web-Made World
by Kelly Mooney, Nita Rollins
The world is changing rapidly, and those who fail to realize it will be left in the dust. However, those who open their brand and see the value of allowing their best customers to participate in the brand will not only reap the benefits of those customers ideas, but they will also benefit from those customers becoming the largest and more credible Marketing department a company could have. Kelly Mooney and Nita Rollins explore these themes in an extremely insightful book that comes with lots of examples that help the reader visualize how these ideas could apply to his or her own business. The writing style and formatting is fun and extremely easy to read. This is a great handbook for any marketer in the 21st century.

Moneyball: The Art of Winning an Unfair Game
by Michael Lewis

While this is ostensibly a baseball book about the success of Oakland A’s GM Billy Beane, I actually found this to be an excellent business book. Michael Lewis tells the story of Beane defying the conventional wisdom of longtime baseball scouts about what good baseball players look like. Rather than trust scouts who literally would determine a baseball player’s prospects by how he physically looked, Beane went to the data as a disciple of Bill James’ Sabermetrics theories. Lewis describes how James took a new look at traditional baseball statistics and created new statistics that were actually more causally related to winning games. By following the James’ approach, Beane was able to put together consistently winning teams while working with one of the lowest payrolls in the Major Leagues. How can the same principles of trusting data over tradition and “gut” play in the business world? That is a thought I constantly ponder thanks to reading this book.
Preview Moneyball

The Culture Code: An Ingenious Way to Understand Why People Around the World Live and Buy as They Do
by Clotaire Rapaille

I picked this book up on a whim one day because the title was interesting. I was quickly engrossed by reading the story in the introduction of Clotaire Rapaille’s work with Chrysler on Jeep Wrangler. He describes the “code” word for Jeep in America is HORSE and advises executives to design round headlights instead of square headlights because horses have round eyes. They think he’s nuts, of course, but when it turns out round headlights are cheaper they go with them — and they’re a hit. They also then position the Wrangler as a “horse” in their ads and have great success. Rapaille goes on to describe what he means by “culture code” and details some of the hidden cultural patterns that affect most all of us. Some samples of other codes within the book are:
– The American Culture Code for love is FALSE EXPECTATION
– The female code for sex is VIOLENCE (Whoa! You’ve got to read the book to understand)
– The code for hospital in America is PROCESSING PLANT

There are tons more of these interesting observations embedded in short, easy-to-read chapters. Whether or not you buy into everything he says, it’s very interesting to see how he developed each code and certainly will expand your understanding of how and why people behave as they do under the powerful forces of culture
Preview The Culture Code

Predictably Irrational: The Hidden Forces That Shape Our Decisions
by Dan Ariely

This is the book that first turned me on to the fascinating world of behavioral economics. Ariely does an excellent job of explaining many of the core principles of behavioral economics with stories and experiments. Every retailer should read this book to better understand how people (customers) think and behave. It will absolutely open your eyes.

Those are some of my favorites. I’m always looking for a new read. What books fired you up this year?



Amazon is hunting for you this holiday season

The holidays are hunting season for Amazon, and they’ve got your business in their sights. Over the years, Amazon has consistently proven to be extremely adept at
maximizing their competitive advantages and creating innovations to
shore up their disadvantages. And the holiday season is the time they most leverage their advantages to grab more market share.

But here’s the thing: many of Amazon’s advantages are shared by e-commerce operations of all
types, but Amazon seems to be quicker to recognize and capitalize on
those advantages than everyone else.

This morning, I pulled up the Amazon home page and was greeted by yet
another letter from Jeff Bezos announcing Amazon’s latest brilliant
innovation. This time, it’s “Frustration Free Packaging” – just in time
for the holiday season when those of us who are parents still haven’t healed the scars from last year’s unbelievable frustration with trying to release our kids’ new toys from wicked constraints that would have defied Houdini (all while the kids are jumping up and down with excitement to play with the new toys).

The secure packaging we’ve been fighting with is designed for physical stores to allow for attractive displays while at the the same time preventing theft. You can see all gory details in this patent filing for toy packaging. But the need for that type of packing in an e-commerce warehouse is moot. So, why not push manufacturers for “e-commerce packaging” that is designed to protect items in shipping but allows for easy removal from the package? Amazon’s size probably gives them an advantage in pushing for this type of action from manufacturers, but many of today’s biggest multi-channel retailers certainly have massive pull with manufacturers and probably could have pulled this type of thing off either individually or collectively — had they thought of it.

And, of course, Amazon has been the trailblazer for many of today’s e-commerce innovations, including customer reviews, affiliate programs and recommendations. So, you might say, let them bear the costs of the innovations and we’ll just capitalize on them after Amazon has proven the way.

While that strategy may work sometimes, it’s fraught with risk because Amazon doesn’t often relinquish market share once they’ve gained it (particularly if they hook customers into Amazon Prime), and they tend to gain that market share during the holiday season. Check out their quarterly results in the “North American Media” category over the last 22 quarters in comparison to Barnes and Noble and Borders:

You can see it’s the fourth quarter where they gain market share. They don’t gain much in the other three quarters, but they certainly hold on to a lot of the share they gained the prior holiday season.

So, what can the rest of us do about it?

For starters, we might want to put innovation on the front burner. Yes, there are costs and risks associated with innovation. But the costs of doing nothing or simply following the crowd might be greater. And successful innovations don’t always have to be earth-shatteringly new, whiz bang technology. They simply need to solve problems better than current solutions.

I believe the most successful innovations have at least one of the following characteristics:

  1. They create convenience for consumers
    We love convenience, and we’ll sacrifice quality and spend more money to get it. I’ve talked about this previously in my post “Predicting the Future of Retail.”
  2. They create efficiencies for businesses
    Efficiencies allow us to make more money faster, and we love that. Given the unusual shapes some toy packaging can take, I wouldn’t be the least bit surprised if Amazon’s Frustration Free Packaging is also alleviating frustrations in their warehouse and giving Amazon added efficiency in the supply chain.

It’s important to carefully examine our businesses to truly understand where we have advantages and disadvantages. As is the case with packaging, these advantages might not always be immediately obvious. We really need to dig deep to understand the problems our customers and businesses are facing and then carefully look for ways to solve those problems by leveraging our inherent strengths. In this process, we need to listen hard to our customers to understand their needs. Steve Jobs once famously said, “You can’t just ask customers what they want and then try to give that to them. By the time you get it built, they’ll want something new.” He’s right. Customers often can’t give us the specific solution, but if we listen properly they can describe their problems well enough to give us the basis for developing effective solutions.

Innovation usually takes time and money. What can we do this holiday season?

There are lots of little things we can do to improve the experience for customers who come to our sites this holiday season.

  1. Truly look at our sites from our customers’ perspective.
    Go to Google and click on one of your search terms. Is the experience what a customer should expect? Try taking a different path on your site to a product than you normally do. How is the experience?
  2. Get more product front and center
    Physical stores pack the front of store and end caps with gift ideas. How well does your site parallel this sort of technique?
  3. Review your error messages
    A poorly written error message is a shameful way to lose a sale. Go through your site and intentionally generate errors. Put yourself in your customers’ seat. Are those error messages clear and easy-to-understand?

While it may be too late to implement huge changes for this holiday season, it’s certainly not too late to pay attention to customers’ needs and start thinking about what can be done for next holiday season. We can carefully consider our advantages and think about how we could better leverage them next year. And we can carefully consider our disadvantages and think about how we can better mitigate them next year. I’m confident Amazon’s already actively considering their next moves.

What do you think? What tips do you have for retailers for this holiday season? What types of innovations do you see coming?



The Prizes and Perils of Free Shipping

Shipping charges. As customers, we HATE paying for them, and we LOVE getting them free. In fact, our feelings about shipping charges are so strong that we highly overvalue free shipping. We’ll spend money we didn’t plan to spend on products we don’t need in order to avoid dumping cash into those awful shipping fees, even when that incremental spending is much more than the shipping charge.

So, free shipping promotions are a powerful tool for retailers. But, if we’re not careful, overuse of free shipping offers could lead us down a path where free shipping becomes more an expectation than an attractive benefit. At that point, we’ll be left with the huge costs of subsidized shipping without incremental sales to support those costs. And that ain’t a pretty equation.

That said, strategic use of free shipping incentives can lead to incremental sales and greater brand loyalty. We’re probably all familiar with the various “free shipping when you spend $X” offers that are out there, so let’s consider some of the more innovative strategies in use today for free shipping:

Free shipping as part of the business model

Zappos really uses free shipping on purchases and returns as a key component of their business model. They encourage people to order multiple sizes of the same pair of shoes and return those that didn’t fit (or those they just didn’t like, for that matter). Free shipping removes a key disadvantage Zappos has to physical retailers, and in fact even provides an advantage for customers who can try on shoes in the comfort of their own homes.

Zappos’ CEO Tony Hseih has said Zappos is a customer service company not an e-commerce retailer, and free shipping is a big part of their customer service strategy. He’s also said Zappos looks at customer service as a marketing expense, which I think is an interesting perspective that might help the cost make business sense.

But free shipping both way at all times is not a sustainable business strategy without trade-offs. Zappos is not the low price leader in their category by any means. Even with their higher prices, public filings from the recent Amazon acquisition of Zappos exposed their relatively low profits as a percentage of sales. Zappos has certainly built a powerful brand with a loyal following so it looks to me like they’ve made the trade-offs work, but theirs could be a tough model for others to follow. I’ll be curious to see if the model continues to work within the Amazon business model.

Speaking of which…

Free shipping as a loyalty program

Amazon Prime is one of the more brilliant loyalty program innovations to come along over the last several years. For an annual fee of $79, customers can get free 2-day shipping on many key items and free standard shipping on many more. Again, this is a case of a pure-play e-commerce retailer looking to mitigate one of its disadvantages to physical retail. Amazon sunk some money into this program by giving away a lot of free trials, but they’ve since hooked people in to the fee. A recent Piper Jaffray analysis estimates Amazon Prime’s membership at 2 million people and growing at 24% annually. And once you pay $79 to get free shipping, you’re going to make the most out of it. Piper Jaffray found member spend growing from $400 annually to $900 annually!

But this again is an expensive proposition that wouldn’t be sustainable for most businesses. The $79 will help to defray some of the free shipping costs, but as with most paid loyalty programs that I’ve studied, customers don’t renew their memberships unless they’re getting a positive return on their investments. And Amazon, as a general merchandiser, can provide customers with enough product choices that they can visualize making enough purchases to get their money back and then some. Specialty retailers may not be able to offer a similar program on their own; although, I keep thinking there might be an opportunity for some third party to aggregate a bunch of retailers into a program in a way that might work. (Maybe that’s a future post.)

Free shipping as a store traffic driver

The previous two examples were pure-play retailers using free shipping as a way to mitigate a major disadvantage they have to physical retailers. So how can multi-channel retailers leverage the advantages they have with their multiple channels? Free shipping to stores is one way. When I was at Borders, we offered unrestricted free shipping to our stores as a cross-channel strategy in order to leverage the selection and experience of Borders.com combined with the convenience of picking up the order in our stores. Originally, we thought it would appeal mostly to urban dwellers who didn’t want packages left on their doorsteps, but it turned out to be a hit all around for people who just didn’t want to pay for shipping. Wal-Mart does something similar with their Site-to-Store program. And Borders just took it a step further with their recently announced “in stock guarantee” for their stores that offers free shipping to home for customers if the Borders store is out-of-stock on the item the customer came in to purchase.

But businesses offering free shipping without purchase hurdles often depend on additional future purchases to make the offering profitable. For example, we ran a lot of analysis at Borders on the free shipping to stores offer. We determined we needed X% of people to buy $X more in-store when they picked up their orders for the offer to make financial sense. With the new offering, it appears Borders is counting on pulling some market share from Amazon with the promise of books available right now in their stores.

There can be little doubt that free shipping is a powerful offer, but we have to be careful how we wield it. Someone recently told me that effectiveness of fire lies in prudence and intention. Used in a positive manner, it can provide great warmth and light but when used in a negative manner it can cause great destruction. Since I like overly dramatic metaphors, I’m going to compare free shipping to fire. Let’s be careful out there. 🙂

What do you think? Should we be concerned about free shipping becoming an expectation? How do you use free shipping strategically?



Wanna be better with metrics? Watch more poker and less baseball.

Both baseball and poker have been televising their World Series championships, and announcers for both frequently describe strategies and tactics based on the statistics of the games. Poker announcers base their commentary and discussion on the probabilities associated with a small number of key metrics, while baseball announcers barrage us with numbers that sound meaningful but that are often pure nonsense.

Similarly, today’s web analytics give us the capability to track and report data on just about anything, but just because we can generate a number doesn’t mean that number is meaningful to our business. In fact, reading meaning into meaningless numbers can cause us to make very bad decisions.

Don’t get me wrong, I am a huge believer in making data-based decisions, in baseball, poker, and on our websites. But making good decisions is heavily dependent on using the right data and seeing the data in the right light. I sometimes worry that constant exposure to sports announcers’ misreading and misappropriation of numbers is actually contributing to a misreading and misunderstanding of numbers in our business settings.

Let’s consider a couple of examples of misreading and misappropriating numbers that have occurred in baseball over the last couple of weeks:

  1. Selection bias
    This one is incredibly common in the world of sports and nearly as common in business. Recently, headlines here in Detroit focused on the Tigers “choking” and blowing a seven-game lead with only 16 games to go. In a recent email exchange on this topic, my friend Chris Eagle pointed out the problems with the sports announcers’ hyperbole:

    “They’re picking the high-water mark for the Tigers in order to make their statement look good.  If you pick any other random time frame (say end-of-August, which I selected simply because it’s a logical break point), the Tigers were up 3.5 games.  But it doesn’t look like much of a choke if you say the Tigers lost a 3.5 game lead with a month and change to go.”

    Unfortunately, this type of analysis error occurs far too often in business. We might find that our weekend promotions are driving huge sales over the last six months, which sounds really impressive until we notice that non-sale days have dropped significantly as we’ve just shifted our business to days when we are running promotions (which may ultimately mean we’ve reduced our margins overall by selling more discounted product and less full-price merchandise).

    In a different way, Dennis Mortensen addressed the topic in his excellent blog post “The Recency Bias in Web Analytics,” where he points out the tendency to give undue weight to more recent numbers. He included a strong example about the problems of dashboards that lack context. Dashboards with gauges look really cool but are potentially dangerous as they are only showing metrics from a very short period of time. Which leads me to…

  2. Inconsistency of averages over short terms
    Baseball announcers and reporters can’t get enough of this one. Consider this article on the Phillies’ Ryan Howard after Game 3 of the World Series that includes, “Ryan Howard‘s home run trot has been replaced by a trudge back to the dugout.The Phillies’ big bopper has gone down swinging more than he’s gone deep…He’s still 13 for 44 overall in the postseason (.295) but only 2 for 13 (.154) in the World Series.” Actually, during the length of the season, he had three times as many strike outs as home runs, so his trudges back to the dugout seem pretty normal. And the problem with the World Series batting average stat is the low sample size. A sample of thirteen at bats is simply too small to match against his season long average of .279. Do different pitchers or the pressures of the situation have an effect? Maybe, but there’s nothing in the data to support such a conclusion. Segmenting by pitcher or “postseason” suffers from the same small sample size problems, where the margin of error expands significantly. Furthermore, and this is really key, knowing an average without knowing the variability of the original data set is incomplete and often misleading.

    This problems with variability and sample sizes arise frequently in retail analysis when we either run a test with too small a sample size and assume we can project it to the rest of the business, or we run a properly sized test but assume we’ll automatically see those same results in the first day of a full application of the promotion. Essentially, the latter point is what is happening with Ryan Howard in the postseason. We often hear the former as well when a player is all of the sudden crowned a star when he outperforms his season averages over a few games in the postseason.

    In retail, we frequently see this type of issue when we’re comparing something like average order value of two different promotions or two variations in an A/B test. Say we’ve run an A/B test of two promotions. Over 3,100 iterations of test A, we have an average order size of $31.68. And over 3,000 iterations of Test B, we have an average order size of $32.15. So, test B is the clear winner, right? Wrong. It turns our there is a lot more variability in test B, which has a standard deviation of 11.37 compared with test A’s standard deviation of 7.29. As a result the margin of error on the comparison expands to +/- 48 cents, which means both averages are within the margin of error and we can say with 95% confidence that there really is no difference between the tests. Therefore, it would be a mistake to project an increase in transaction size if we went with test B.

    Check out that example using this simple calculator created by my fine colleagues at ForeSee Results and play around with your own scenarios.  Download Test difference between two averages.

Poker announcers don’t seem to fall into all these statistical traps. Instead, they focus on a few key metrics like the number of outs and the size of the pot to discuss strategies for each player based largely on the probability of success in light of the risks and rewards of a particular tactic. Sure, there are intangibles like “poker tells” that occur, but even those are considered in light of the statistical probabilities of a particular situation.

Retail is certainly more complicated than poker, and the number of potential variables to deal with is immense. However, we can be much more prepared to deal with the complexities of our situations if we take a little more time to view our metrics in the right light. Our data-driven decisions can be far more accurate if we ensure we’re looking at the full data set, not a carefully selected subset, and we take the extra few minutes to understand the effects of variability on averages we report. A little extra critical thinking can go a long way.

What do you think? Are there better ways to analyze key metrics at your company? Do you consider variability in your analyses? Do you find the file to test two averages useful?



Related posts:

How retail sales forecasts are like baby due dates

Are web analytics like 24-hour news networks

True conversion – the on-base percentage of web analytics

How the US Open was like a retail promotion analysis

The Right Metrics: Why keeping it simple may not work for measuring e-retail performance (Internet Retailer article)

Retail: Shaken Not Stirred by Kevin Ertell


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