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I’m pretty sure if I sneeze near a bank today I’ll soon get a text message asking me to rate the bank for sneezeworthyness; or if I take out money from an ATM, I’ll soon receive an email asking me how my ATM experience was.
We are near constantly being asked how the coffee was, what the checkout was like, how well the comb met our satisfaction. If hotels were as keen to actually meet my needs as get me to rate my experience with them, I’d be in heaven.
The price we pay for any form of interaction with a brand today is a satisfaction survey twatishly sent on Twitter. And brands hit the most valuable people hardest. The more you fly with an airline the more they ask you how it was and the happier they are to waste your time on their admin. I get cheery emails asking about my vacation in Denver when I fly there each month for work meetings. Is this really that hard? We’ve fallen out of love with empathy because we want the data.
I am the biggest fan of listening to customers, observing how they behave and asking them for feedback. Yet precisely 100% of feedback surveys come from noreply@ emails; they also actively spell out “if you have a complaint, please visit XXX to tell us”.
What they want is measurement, not feedback. Actually, telling an airline or hotel how you feel – unprompted, qualitative, context-rich, honest feedback – is near impossible. It’s something that gets in their way, takes time, needs a reply. What if these companies had the audacity to hold focus groups, or to observe behaviour? Yet these things fit very badly in spreadsheets.
Brands’ data illiteracy
We talk a lot about big data these days but we talk little about data literacy or our ability to extract meaning or make decisions from it. Spurious claims are digested readily in our industry because to challenge it takes guts and what data really allows us to do is to pass blame onto something that can’t be fired.
We also want to understand new things so much we rarely challenge the intentions of those behind it. We need to remind ourselves daily of Twyman’s law: If a statistic looks interesting or unusual it is probably wrong.
Let’s learn to torture data, question routines, understand bias and most of all examine the intentions behind what’s shared.
We repeat “facts” like ‘41% of adults use voice search on a daily basis’, or ‘a Facebook like is worth $174’ or ‘Nike’s sales have gone up by 31% thanks to a TV ad’. The modern media environment needs the remarkable to make headlines that pull in the reader.
But we must remember that the ability to parrot these facts does not make for data analysis. We must not let success come to those who practice poor methodology, frame data irresponsibly and tell good old fashioned lies. Instead, let’s learn to torture data, question routines, understand bias and most of all examine the intentions behind what’s shared. With virtually endless data there is always a way to cut it to make a point.
Data is leading to the end of marketing
Before we called it digital, which is a crap name, and after we called it new media, which was worse, we called online stuff “interactive”. It was a great name that described – slightly – what the technology actually meant. Lots of people assumed this was the era of people having conversations with brands or playing crappy flash games with them, but they were morons for thinking that. What interactive really meant was a two-way street, you could see how people were behaving.
This lead to the dawn of ultra-cheap (or free), real-time, objective, data-rich measurement. And thus the end of marketing began. We fell in love with the hardness and robustness of data. We could see click rates, likes, shares, comments. We could measure so easily, so precisely and so quickly things we felt important because they could be assessed, aggregated, and trends lines established for almost anything, every day, in real-time.
These metrics were the best (and only) easy metrics we’d ever had, and we could play with them. Social media posts with boobs, babies and pets did well, so banks became publishers of clickable content, not news about interest rates or products, but alas it was “success”.
Let’s use data to establish progress, but see it as a friend in a pub, not an idol to pray to.
Customer happiness scores are going the same way and so should be judged as basically useless. The people who reply are atypical people behaving abnormally. They are likely a reflection on a person’s current state of mind, not reality, and they (like all reviews on Yelp) measure the person, not the event.
Within the tonnage of the data is hidden the beauty of the lesson. Yet our culture is in love with things that we can use to show progress, or show where to refocus efforts. It’s more important to be seen to be hitting KPIs than it is to make a real difference in a way we can only feel.
The things in our personal lives that matter are indescribably ethereal. How much love you receive and give, how much joy you experience, how meaningful your lives are. All things very hard to measure, to know, to change. So we find proxies, we compare salaries, friends on Facebook, the value of your home, the speed of your car, the job title. We know it’s nonsense but it helps gauge where we are in life. We know how we really feel is in our gut.
In marketing, what really matters is the ability to charge a premium, the sales we can attribute to something we’ve done and brand awareness. These things are literally impossible to really track, to really see change in, but we can probably feel when we’re doing things right.
Let’s fall in love with our hearts again, let’s use data to establish progress, but see it as a friend in a pub, not an idol to pray to. And don’t piss people off in the process.
Tom Goodwin is executive vice-president and head of innovation at Zenith USA. He is also the author of Digital Dawinism.