And Tom isn’t alone in considering Michael Lewis’s sports writing to be a hidden treasure; just look at this marketing-based analysis of his book,  Money Ball.  But Tom Peters has been alone in recognizing the business applications of Michael Lewis’s astonishing article on the surprising innovation and success of Texas Tech Football, written no less than three years ago.

Click here to view the embedded video.

Action & Tempo:

“…[Coach Leach] had been harping on tempo all week: he thinks the team that wins is the team that moves fastest, and the team that moves fastest is the team that wants to. He believes that both failure and success slow players down, unless they will themselves not to slow down. ‘When they fail, they become frustrated,’ he says. ‘When they have success, they want to become the thinking-man’s football team. They start having these quilting bees, these little bridge parties at the line of scrimmage.’”

You have to learn by implementing, and it’s incredibly advantageous if you work hard to keep your testing tempo as fast and continuous as possible.  Theory and intuition are great at helping you figure out what to test, what to look for in your analytics, and how to interpret your data, but untested assumptions can kill you.  If you think that customers would respond well to X, figure out an easy-to-implement test to confirm or disprove that.  The last thing you want to do is let your website sit static for months while you plan a major change based off of faulty assumptions about the market and/or customer motivations.

Plus, even if you have a brilliant plan to improve your website, it won’t help you until you’ve actually implemented the changes.  So a fast cycle of smaller tests and changes not only keeps you safer by verifying assumptions and improving learning, but successful tests implemented early can pay off during the time you would have wasted staging a larger “batch” of changes.

In a similar manner, Texas Tech is well aware of the “opportunity costs” involved in not keeping their offensive op-tempo as high as possible:

“An idea about the use of football time was being challenged. The typical football offense seeks to eat up as much of it as it can. The Texas Tech offense, which at that point in the season had passed for more touchdowns than any team in the country, uses just a shade over two minutes on each drive. But speeding everything up has a curious effect on game time. A typical college football team runs 65 to 75 offensive plays a game. Texas Tech tries to run 90 – and sometimes does. A college team with a robust passing game might throw the football 35 times a game; at this point, 8 games into an 11-game regular season, the Red Raiders were averaging 53 passes a game.”

Preferring batch implementation of changes and tests is kind of luck holding onto the football to control the clock – you’re wasting opportunities to move the ball down the field and score.  Yet most companies, like most traditional football offensive teams, don’t have Texas Tech’s sense of urgency; they don’t understand the often substantial opportunity costs involved.  Here’s a real life example:

I presented a client with a lead generation website for a considered purchase with a Persuasive Scenario Analysis towards the end of August.   As part of that report, I also presented a prioritized list of “most likely to generate dramatic improvement” changes/tests.  And among those suggested tests, I predicted that the easiest to implement change that was also most likely to produce immediate results was to prominently display the company’s phone number within their banner.

About 1.5 weeks ago they finally made that change (along with several others) and went from getting 0 calls from their website each week to 20 calls in the first full week they had stats for the revised website.  One of those 20 calls converted into a sale.  Most sales average in at $20,000 to $30,000.

Now, I’m hesitant to put too much weight on only one week’s worth of results, but even conservatively downgrading those figures still results in a significant opportunity cost for NOT implementing that change right away.

Orientation

“Leach made his way to the sideline and from his back pocket pulled a crumpled piece of paper with the notations for dozens of plays typed on it, along with a red pen. When a play doesn’t work, he puts an X next to it. When a play works well, he draws a circle beside it – “to remind myself to run it again.” But at the start of a game, he’s unsure what’s going to work…

The Red Raiders trotted off the field at halftime with a lead, but not a large one: 14-10. A disappointing half, yet with hidden value. For 40 plays Leach’s offense had groped – digressing, probing to learn something new – and it had been useful to see how the empty spaces on the field shifted. Coach and quarterback now knew what they wanted to know about the A.&M. defense.  They had paid for the knowledge with time, but time means less to them than it does to any other offense in the land. A half to the Texas Tech offense is as good as a full game to most. The game within the game was about to begin…

In the five full years Leach has coached Texas Tech, four or five times each season the team has flopped around ineffectually for the first third or so of a game before racing off to score touchdowns at a rate unheard of in organized tackle football. It’s as if his opponent’s defense has some deep dark secret that takes time for his offense to extract.”

Action isn’t good enough if you’re just throwing stuff against the wall and not learning from it by reinforcing your successes and killing your failures.  Coach Leach doesn’t just know that this play worked and this play didn’t, he also seeks to understand why, so that he and his quarterback can adjust their overall strategy accordingly.  Once the Raiders have correctly sized up their opponents, that’s when the real scoring opportunities begin to appear.  Here’s what that looks like in the game Michael Lewis was describing:

“Leach had just a few minutes with Hodges, but he told him what he had noticed. First, the A.&M. cornerbacks were disguising their intentions. They were lining up as if to cover the fade routes – that is, before the play began, they stood between the receiver and the sidelines – but then, just as the ball was snapped, they were scampering back into the middle of the field. To Hodges it looked as if fade routes would be covered, so he had been sending his receivers on slants into the middle of the field. ‘Throw the fade,’ Leach said. ‘It doesn’t look like it’s there, but it is.’

The other glaring opportunity, to Leach’s mind, was A.&M.’s response to Tech’s formations. On the few occasions when Texas Tech lined up in a formation that suggested a running play, with two running backs, the Aggies ’put their ears back and stop the run.’ But when Tech was, as it preferred, in its passing formation, A.&M.’s fear of the pass caused them to leave huge empty spaces to run in. In the second half, the Tech running backs would be charging into pass coverage, and the Tech receivers would be running toward the sidelines.

There was one other thing Leach had noticed – and Hodges had noticed it, too. The A.&M. front line appeared tired. ‘The minute you see the defensive line bent over and their hands on their hips,’ Hodges told me, ‘that’s when you know you have them.’ The A.&M. linemen were a lot bigger than the Texas Tech linemen. They may or may not have been fatter – Leach insists they were – but their bodies were clearly designed for a different sort of football game than this frenetic one. ‘That’s the risk of playing 330-pound guys,’ Leach said later. ‘You get good push, but if you got to run around a lot, you get tired.’”

The problem with most companies is that even when they do run A/B and multivariate tests, they’re often just testing random variables or best practices, which means they have no basis for interpreting the results in terms of a larger ‘game strategy.’ If you only know that headline “A” outperformed headline “B” without understanding WHY headline “A” worked best, it would be like Coach Leach only knowing that play X worked and play Y didn’t without seeing the larger patterns or flaws in his opponents defense and without being able to exploit that during the second half.

Here’s a practical web example of this principle taken from Microsoft’s Experimentation Platform blog.  The post in question features three separate A/B tests and the second test of two different site search bars is a perfect example of how the WHY is so crucial.  But first, here are the two search bar designs:

Which one worked better?  Neither: the results were statistically negligible.  Now, if that’s all that you took away from that test, you’d have lost out.  But if you started the tests with some hypothesis about why one design might work better, you could follow up with goal scoring, revised search bar.

For instance, most people would find the search area of Option A much more inviting because it’s more spacious.  Plus, the “Popular Searches” is labeled as such in Option A whereas it’s something of a disconcerting mystery in Option B.

On the other hand, Option B does one very important thing right, that Option A doesn’t: it labels with strong verbs!  Rather than guessing that the magnifying glass means “search,” I can look at the big green button and instantly know that clicking on it will start my search.  That one is kind of a no-brainer, actually, especially since Steve Krug has rather famously taught that search buttons should either say “Search” or “Go.”

If you started with those assumptions, you might have actually created an Option C that combined the best elements of both features.  Something like this:

And then I’d be willing to bet rather heavily that you’d come up with a very clear winner. But if you simply threw Options A and B up in a simple split test and accepted the results without thinking about them, you’d never get to an improved search bar.

So how can you more consistently move past a “best practices” or a “let’s test everything” approach to Website optimization?  What kind of methodology will let you advance beyond page-level optimization to Website-wide conversion improvement?

Well, while that subject definitely builds on what we’ve just discussed, it’s also worthy of a post in itself, so make sure to subscribe to get Part II as soon as it comes out.