When I was a kid, we used to go trout fishing up in mountain rivers. I used to put artificial and fleeting faith in the type of bait I was using. I would vary my bait rapidly in search of the magic fishy elixir. This fake cheese stuff, some scented “marshmallows”, salmon eggs, and even the fancy plastic worms that I think I liked more than the fish did.
Fish bait catches fish, so click bait catches clicks. Not groundbreaking, but why is there so much of it? Do we honestly not believe that there are ways to repurpose bread ties and toilet paper tubes? I feel like that’s something we’ve been doing since arts and crafts time in elementary school.
We know click bait isn’t designed for the reader. It does not care if you save money on your insurance, organize your life, or identify that celebrities are people too. In fact, it generates more traffic by the reader never learning. It becomes Pavlov’s Buzzfeed, where the reader salivates at the sound of a bell and not the presence of food.
People are craving authentic connections. With their loved ones, with their companies, with their world. See here, here, here and here. And yet clickbait pushes a different narrative.
These 12 calls-to-action will make you jump! Number 7 will make you ask “How high?”
Let’s stop. We don’t have to stop with the listicles, the lifehacks, or even the quizzes to find out which pizza topping gives you life. But let’s start turning those into something. Something that gives you a great starting place but encourages you to add to the list. Something that teaches you how to solve problems in unconventional ways. Something that helps you understand yourself and how you think. Let’s use our powers for awesome.
Let’s start making engage bait, or learn bait. Even better… change bait. Let’s start making things that draw readers into a worthwhile experience that leaves them better off. As Scott Stratten says in his book Unmarketing:
“What is stopping you from calling yourself one of the experts in your field? Being an expert is not an official designation. You don’t get a certificate in the mail, nor do you get a cookie.”
We’re all experts in something. If you have experience, a special skill, or training in something, you can be an expert in that thing. Maybe not THE expert, but definitely AN expert. So be an expert and train someone. Channel your inner Splinter. The mutagen turned the teenage turtles into mutants, Splinter made them ninjas.
We already know how to make people click, now let’s lead them to something better.
Growing up, I was a fan of the San Diego Padres baseball team. Well, specifically Tony Gwynn, but the Padres came with him. There have been years where I watched them trade away quality top talent, in hopes of landing a large quantity of moderate talent. Why have one 5-star player, when you can have three 2-stars? So when a team I loved had replaced every player at every position with new players, were they still “my team”?
This is the crux of the thought experiment raised by Plutarch. Not Hunger Games Plutarch; I’m talking about ancient Greek Plutarch. He wanted to know when the Ship of Theseus stopped being the Ship of Theseus, if it was replaced with replica parts, one by one. You can check out a discussion at Brain Pickings.
At least make sure you watch the video in the Brain Pickings article, which can also be found here: Who Am I?
Humankind asks “Who am I?” At least since we’ve been able to think these types of thoughts. There may be some earlier humans who never really contemplated their place in the universe, or if Oog and Thag talk about them when they’re not in the cave… I digress.
Both the video and article are fantastic for explaining what is at the heart of the conundrum. However, I want to know what’s at the heart of the human. This leads me to a different question.
Why do we ask “Who am I”?
“Who am I?” gets at identity. I want to understand why we question it. I am going to spoil the end of this post and tell you right now, I don’t know. But it does generate interesting questions that need to be explored. Surely, some folks have explored one or more of these. I want to to talk to these folks. If you are one of these folks, let me know! I want to talk to you.
Is who we are different from time to time? From place to place? From situation to situation?
Is “Who am I?” even what we want to know?
Should it be “Am I being who I want to be?”
Should it be “What’s my place in the universe?”
Should it be “Who do others think I am?”
Do people with extreme levels of self-confidence ask “Who am I?” (extreme = really high AND really low)
Does “wearing many hats” fragment our identity?
Why can’t we be the same person and keep our identity whole?
Are the forces on the need for “many hats” external or internal?
Does finding an answer to “Who am I?” solve anything?
One Last Thing Before You Go
This search for identity generates a new-to-me connection. Our inability to satisfyingly answer “Who am I?” leads to a void that “things” have been able to fill. If I buy a cat, I open the door to becoming a cat person. If I buy activewear from Nike, I showcase my athletic identity. Heck, you can’t even properly root for the Padres without buying some team gear. Maybe that’s part of how we cement part of our identity answer.
“Who am I? Well, I got all these Padres hats and shirts, so clearly I’m a Padres fan.”
It feels like those are the easy answers to what is supposed to be a deep and soul-searching question. “Who am I?” sounds like a status report on the path to the ideal you want to achieve.
My great friend, Joseph Greaser, posted an excellent write up about understanding your audience. Especially when it comes to innovation. You can read all about his case study and data that illustrate this point clearly. Read his post, follow his blog, and then come right back.
The next time you are stuck needing some small talk, here’s a little trivia for you. The average elevation for the state of Arizona is roughly 4,100 feet. Yet that fact covers up a big hole in the data. Actually, one of the biggest holes. The Grand Canyon is also in Arizona. Its elevation bottoms out at only 70 feet in the canyon. Now you’re saying “Of course it glosses over the Grand Canyon. That’s what an average does. It smoothes over the really high peaks and really low valleys.”
So then why do we use the average when trying to understand your customer?
The whole point of understanding your customer is to understand their pain points, their usage, and what innovations they would gain from. But if we keep just looking at average data to “get a feel” for how the whole group is using your prototype, then you could be missing grand canyons of opportunity.
Let’s change the lens for this. Imagine you are a teacher and you are looking at the grades for your students at the end of the year. Half of your class ended with a grade of 100%, the other half ended with a grade of 50%. Would you just average them out and say that your class earned a 75%? You wouldn’t unless you wanted to be looking for a different line of work in the fall. No, you would see two distinct “user-groups” in your classroom. Regardless of grade, both user-groups need your attention.
You would work hard to understand why it wasn’t working for your 50-percenters. You would try new things, different strategies, and observe to identify their pain points. Even your 100-percenters need you. You need to observe them as well to find what is working, try to push them to new territory, and give them some challenges. You would be doing so much to understand your students.
Similarly in innovation, we must journey to the bottom of data canyon to understand our customers.
Let’s look at what the average leads us to. Based on analytics, a website was tracking an average of 5 minutes per session duration. Remembering what we can about averages from freshman year, we imagine the graph to look like this beauty.
Yet, through the magic of mathematics, this graph is also equally likely and just as valid.
Whoa! Talk about two completely different use cases for this website. Let’s put the graphs together to get the whole picture.
Only in some cases would innovating for the average actually provide some benefit to our customers. There are other valid cases where innovating for the average wouldn’t benefit the customers at all. Talk about wasted time, development, and effort.
Another great example of this is to look at the Diffusion of Innovations curve. Ignore the extremes for now and look at what aiming for the average would get you. You would be nestled between the Early Majority and the Late Majority of customers. Your innovation would be targeting a user-group that is torn between being scared and skeptical of change. They would be wanting to get something out of your innovation, but at the same time they just don’t want to get left behind.
So what is a good innovator to do? One thing that we are always fond of is looking for micro-patterns instead of macro-solutions. Macro-solutions are the golden bullet, “this will work for everyone” type of product. These have their benefit in some instances but not when you are trying to understand your customers. Remember that averages smooth out the mountains and canyons that customers experience. Macro-solutions need averages to survive.
Micro-patterns help shed light on your customer personas. Go back to the classroom scenario, even though it is simplistic. Just looking at the grade data beyond the average shows us that their are at least two distinct customer personas in the class. It is ok to have multiple personas as long as you understand that they have different needs and desires from your product. The students with 100% grades have different demands from the classroom than the students with 50% grades. Your job as the innovator is to decide which group to innovate for.
The more complex your data is, the more micro-patterns there may be… and this is ok. Complex is neither good nor bad, it just is. As an innovator you aren’t here to judge numbers, you’re here to listen to their stories. And stories can be as deep as the Grand Canyon sometimes, but you have to make the trek to the bottom via mule to truly understand the customers there. Don’t let the shiny averages distract you with their homogenous targets for innovation.
Challenge: Take a look at some data for your innovation.
What are some of the shiny, yet deceiving, averages that exist?
Dive deeper into your data. Are your averages glossing over some of the customer stories?
Try to identify the different, distinct user-groups for your innovation. List their pain points.