June 30, 2017 | Written by: Bryan Eisenberg
Categorized: Augmented Intelligence
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Data is a great resource, especially when it’s correct. But, it can’t replace good judgement. I’m going to provide a brief history of how we got here and how we get ourselves back on track with using data to drive good decision making.
How It All Started
In the 1980s, Robert Crandall the CEO of American Airlines made the decision to remove the olive from in-flight salads. It turned out that the airline paid its caterers based on the number of ingredients in the salad: sixty cents for four items and eighty cents for five. The olive was the fifth item. This move saved more than $40,000 a year. Today some of us would be thrilled if they even served us an olive. The data showed most people were not eating it anyway. This was the beginning of the airlines continuous efforts in cost cutting at the expense of the customer experience. Maybe the olive was not a big deal, but we know how far that cost cutting has gone.
There’s a value to doing the right thing with people. How did airlines become so generic that we no longer care? They cut the warm nuts, and then the peanuts, then the pretzels and then all the other comforts. They made the seats less comfortable and keep trying to find more ways to squeeze extra seats in. They kept cutting things because it didn’t affect the bottom line but it affected customers. Because now we don’t care who we fly with. That’s a problem. Today they are making billions in profits from these cuts and all the additional fees from their calculated misery. We recently saw how dangerous this type of thinking is for both the brand and the customer.
There’s too much data and not enough behavioral understanding.
In our latest book, Be Like Amazon: Even a Lemonade Stand Can Do It, we share the story about the time that General Motors sold two-thirds of all the cars in the United States. It was the bluest of all blue-chip stocks. Chevrolet, Pontiac, Buick, Oldsmobile, and Cadillac were five distinctly different brands, and the car you drove said a lot about you. In the mid-1970s, GM decided to boost profits by eliminating the design costs and retooling costs of maintaining five separate product lines. They figured they’d just build one car, hang some different chrome and change the headlights and taillights a little and cover the seats with a different fabric and you’ve got yourself five different brands. GM was selling five different versions of the same car at five different prices by calling the first one a Chevrolet, the second one a Pontiac, the third one a Buick, and so on. GM immediately began making record profits, of course, because brand loyalties ran deep, and loyal customers aren’t quick to abandon their brand.
In 1980, GM still had a 62.9% market share in the US. Then he started sticking Chevy motors in Oldsmobiles, Pontiacs, and Buicks because he had surplus capacity in his Chevrolet motor factories. Keep in mind this was when the Olds Cutlass was the top-selling car in America. He then decided that GM would abandon its traditional once-a-year price increase when the new models were released and replace it with random price increases multiple times a year. Sometimes the price increases would be double-digits. This is when the term ‘sticker shock’ was born. The end result of all this blurring of the brands was that GM had to shut down Oldsmobile in 2004 and Pontiac in 2009. GM’s total market share had fallen to just 19.8%.
Both the airlines and the car companies got to where they are based on data. The challenge is they failed to use empathy to understand the importance of the customer experience. I find it ironic, that the next battle for the automobile companies will be the AI’s used in their cars.
Rise of the bots!
We are seeing AI helping us in many settings today, from IBM Watson, Apple Siri, Microsoft Cortana and Amazon Alexa. AI, what most people call Artificial Intelligence would be much better if it was thought of as Augmented Intelligence with heart. There is a certain amount of “ethics” we can add to the software algorithms but it will never replace the ability of human empathy.
Data driven decision making is taking over everywhere from business to baseball and even personal health. AI is stepping in to help us make decisions. As we become overwhelmed with the exponential growth of data available in our lives we need systems that can collect, filter, and analyze that data in real time so we can make the best decisions. You see this now in some of the work that companies such as IBM and others are doing. Facebook also made announcements recently: the bots are coming. You are not going to solve all the problems with these AIs, but at least they can process some of the data for us and alert us. Organizations still need to be qualified to act on the alerts. But you still need human intelligence and empathy. It will balance out things better.
How to Reinforce Empathy in Data-Driven Decisions
To some degree, I am seeing marketing teams increasingly making efforts to use data to make decisions. However, what’s important here is not just the fact you are using data to make a decision. Rather, it’s what decisions marketers choose to use data for, and how that data plays a role in shaping marketing choices. For instance, big data has been around a long time and people have tried to process and analyze it. But the issue with using data has been the fact that aligning the customer journey with the marketer’s vision by having an analyst look at the numbers is not an empathetic approach. In order for this to make a real difference, those metrics need to be tied into customer stories and journeys (what we call Buyer Legends) that help the marketer develop and embrace empathy for the customer mindset. And that is what is changing about the way marketing teams make data-centric decisions – dealing with data isn’t just about numbers, but using those numbers to derive real-life empathy and understanding for the buyer journey.
The biggest difference between selling and helping people buy is the degree of empathy the marketer feels for the customer. Empathy demands that you think about how the customer goes about the process of buying and that you find ways to make it easier. Empathy begs you to help them make a more confident decision, remove their fears, and ultimately to allow them to make the decision that is best for them, not just for you. It doesn’t matter if you sell books, cars, diamonds, or a complex B2B enterprise solution when you become an advocate for your customers you win hard earned trust, and even if they don’t buy from you today that trust becomes currency in this increasingly transparent word-of-mouth marketplace. It’s hard to find a downside to this approach.