Every Wall Street investor walks tip-toe on the ice above an ocean of data. Some of them will tell you they are ice-skating on that data, but don’t let them fool you.
Misinterpretation of the data is the ever-present danger facing investors AND marketers.
Every business owner is a marketer.
Misinterpreted data creates a faulty premise. And you cannot build solid marketing on a faulty premise.
Data is like dots on a page. One person connects the dots and sees an elephant. Another person connects the dots and sees a clown. The dots didn’t change. What changed was the expectation of the viewer. Look for an elephant and you’ll see an elephant. Look for a clown and you’ll see a clown. This is known as confirmation bias.
But who, looking at data, ever believes they are wrong?
Steve Jobs spoke about those dots in his commencement speech to the graduates of Stanford University in 2005.
“You can’t connect the dots looking forward; you can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future. You have to trust in something – your gut, destiny, life, karma, whatever. This approach has never let me down, and it has made all the difference in my life.”
Watts Wacker made a similar point in his 1998 book, The 500-Year Delta.
“If you are going to succeed in this real world, you cannot act on assumptions. Assumptions disappear. You cannot act on the predicted fulfillment of some causal chain. The path coefficients that would fulfill that prediction are subject to too many random variations and mutations. What does that mean? It means that you must trust in intuition, trust in self.”
If you are a data hound with a highly developed nose for sniffing out the truth, right now you are thinking, “Steve Jobs and Watts Wacker just didn’t dig deep enough into the data. When you collect enough dots, the picture they create is always perfectly clear.”
I know how data hounds think. I’ve been playing chess with them for 40 years. They study data. I study people.
When we embrace an unproductive idea, it is usually due to:
1. confirmation bias. When we use data to prop up our favorite theory, we use it in the way a drunk man uses a lamppost; for support, not for illumination.
2. availability bias. We tend to overvalue data that is available, and ignore data that would be expensive or difficult to obtain. “Our customer survey asks ‘How did you hear about us?’ and 38% answered ‘TV ads,’ even though we’ve never been on TV. That can’t be right, so we’ll ignore that. But now let’s look at the radio stations on which they say they heard our ads. We can definitely trust that data.”
3. a failure to examine our assumptions. Ads for men’s body wash should be targeted to men, right? (Wrong. Women choose the soap used by men far more often than men choose it for themselves.) Men choose the engagement ring, right? (Wrong. Women shop for their own engagement rings about 50% of the time.) “I know for a fact that our plumbing company gets more calls for water heater replacement than for any other service we offer.” (Wrong. When I asked that CEO to check his records, #1 was dripping faucets.) “Our customers often comment on the quality of our service, so that’s what we should advertise, right?” (Wrong. Customer service will bring repeat customers, but it is rarely the reason for a customer’s initial visit.) “Customers often tell us how unique our selection is, so that’s what we should advertise, right?” (Wrong. “Unique selection” is a hollow claim. It is something you must show, not tell.)
4. the misinterpretation of data. “The data clearly indicates that we have a much higher conversion rate when customers call our sales agents instead of going to our website. So it’s important that our ads drive traffic to the sales agents. Numbers don’t lie.” (Wrong. The data was saying, “Fix your website.” When they got serious about upgrading their online experience, online ordering increased to the point where it is no longer the exception, but the norm, and that already-large business has more than doubled its size.)
Data is usually accurate when describing quantities, but it is woefully inadequate when describing qualities.
Data is a snapshot of yesterday. It does not predict tomorrow. “You can’t connect the dots looking forward. You can only connect them looking back.”
Look at your appointment book. Watch the news. Listen to the radio. Did a single one of us get it right in 2015 when asked, “Where do you see yourself 5 years from now?”
Now let’s circle back to Wall Street. With infinite data at their fingertips and an army of analysts at their side, how well did professional money managers perform against the index* during the 15-year investment horizon spanning 2005 to 2020?
92.43% of large-cap managers
95.13% of mid-cap managers, and
97.70% of small-cap managers failed to outperform the index.
Go ahead and study the data if you want.
I’m going to keep studying people.
Roy H. Williams
You were supposed to get this MMMemo last week, but the server got them out of order. I’m pretty sure it was the wizard’s fault, but he is acting like it was no big deal. But it WAS as big deal because – as a result of the wizard’s ineptness (and I mean that in the most respectful way) – my rabbit hole was a mess. But I was able to straighten it out after a few hours of chaos because I am an exceptional canine. Never forget that. – Aroo, Indy Beagle
*An index fund is a type of mutual fund designed to mirror the performance of the stock market. Index funds are passively managed, not actively managed. If the market goes up, your investment goes up with it. If the market goes down, your investment goes down. When asked for investment advice, Warren Buffet recommends index funds.
If anyone can interpret data correctly, it’s Wizard Academy alumnus Brian Schmitt and his partner, Laura Stude. This awesome pair ran more than 4,200 A/B tests to determine how to turn online visitors into paying customers. As a result of these tests, they have skyrocketed online sales in dozens of categories. Listen, learn, and earn, at MondayMorningRadio.com