Six Tips for Turning Customer Feedback into a Powerful Business Tool
Tesla is basically a car company built on Steve Jobs’ Apple company model. They both have design-first concepts, they both dominate their chosen segments (electric cars for Tesla), they both sell premium products, and they both wrap those products with powerful services. However, where the companies differ is that Apple tends to aggressively work to not discover problems with products that are shipped and certainly not talk about them, while Tesla has implemented one of the most aggressive analytics-based systems to find, report and correct problems, even before they occur.
The end result is that Apple’s products are seen as the best in the market and Tesla was just dropped as a recommended product by Consumer Reports. This doesn’t speak to the relative quality of the offerings, but the effort to be transparent and aggressively look for problems before they occur. It should be pointed out that both companies enjoy some of the highest customer satisfaction and Net Promoter Scores in any industry.
Arguably, Tesla builds a better product than Apple does, but now Tesla is under a quality cloud and Apple isn’t. This is more about understanding reputation and image than it is about analytics and product quality, but it showcases how analytics can bite you in the butt.
Skill Sets: Elon Musk vs. Steve Jobs
I see two big differences between Tesla Motors CEO Elon Musk and Jobs. One is that Musk is much better educated (a degree in physics, another in economics, and a PhD in physics) and Jobs dropped out of college. The other is that Jobs understood the importance of appearance and Musk clearly does not. I expect many, if not most, believe that, of the two men, Jobs was the smarter. He certainly was wealthier and more powerful.
Jobs spent an incredible amount of time and effort on marketing. Musk spends much more time coming up with new product ideas and inventing incredible things, but when was the last time you actually saw a Tesla commercial?
So the end result is that Jobs created products that folks thought were “magical,” but that mostly were just repackaged ideas that hadn’t done well in market (mp3 players, screen phones and tablets weren’t selling well at all until Jobs brought his versions to market, and then they took over their respective segments). Even though the Tesla is so good that it literally broke some of the Consumer Reports testing machines before it failed, the Tesla is mostly popular in and around Silicon Valley and has had a great deal of difficulty selling anywhere else. All that, even though it truly is innovative and magical: In its performance version, it is an electric car that’ll carry seven, go nearly 300 miles on a charge, and outperform any supercar short of a Bugatti in a straight line race. Oh, and it is the first car on the road that can almost drive itself.
This kind of makes you wonder what Jobs’ marketing skills could have done for Tesla, or what amazing product Musk could have created at Apple, doesn’t it?
Analytics and Perception
Analytics are most often used by marketing organizations to help them understand and manipulate perceptions and, I expect, that is how they are mostly used at Apple. However, at Tesla, they are mostly used to analyze the cars and alert about problems that have not yet become visible to the driver. For any other car, most of the problems either get caught when the car fails or they are quietly fixed when the car goes in for a service. Now, in a service, the car owner has to take the car to the dealer and wait or be without the car while it is fixed. With Tesla, someone comes to you, gives you another Tesla like the one you bought to drive, and takes your car for repair related to a problem you likely haven’t even seen yet. But, because Tesla is proactive, you see every problem they fix, and Tesla promotes forums where folks talk about their problems, partially so the company can make sure it is capturing all of them.
Apple doesn’t want folks talking about problems. Often, when it fixes something, it requires the user to sign a non-disclosure agreement preventing them from talking about an issue. Apple doesn’t proactively fix anything and goes to great lengths to make sure problems don’t become common knowledge.
The analytics that Apple does aggressively maintains the perception that the products are high quality, while the analytics that Tesla does actually assures the quality of the product. But, because the user is more aware of the problems with the Tesla approach, they are more likely to showcase them, damaging the perceptions surrounding the Tesla car.
Wrapping Up: Perception Is Important
This comparison between Tesla and Apple showcases that Apple is by far the more powerful company, with what is arguably a lower-quality offering. From that, you should conclude that analytics focused on perceptions are the more powerful and that, if you are going to choose one analytics focus over the other, perception should come first. This isn’t to say that a focus on analyzing actual quality isn’t important. It certainly is. But if you don’t have an equal focus on assuring perceptions, then those surrounding your product will likely degrade.
In the end, you want to both have a high-quality product and one that is highly popular. But if you have a choice, popularity does a better job paying the bills than quality does.
I’ll leave you with one final story. Years ago, while working for IBM, I did an in-depth review of why our products weren’t selling. My report was leaked to a competitor and not only did it do a lot of damage, it almost got me fired (the VP of sales who leaked it did depart). A sister group created a similar report that focused on how wonderful our products were. That report, while largely fictional, was incredibly useful in selling products, and that group continued to get funded, while mine did not. Perception is not only 100 percent of reality, it is often more important. Something to noodle on this week.
Rob Enderle is President and Principal Analyst of the Enderle Group, a forward-looking emerging technology advisory firm. With over 30 years’ experience in emerging technologies, he has provided regional and global companies with guidance in how to better target customer needs; create new business opportunities; anticipate technology changes; select vendors and products; and present their products in the best possible light. Rob covers the technology industry broadly. Before founding the Enderle Group, Rob was the Senior Research Fellow for Forrester Research and the Giga Information Group, and held senior positions at IBM and ROLM. Follow Rob on Twitter @enderle, on Facebook and on Google+
