Mental models are frameworks we use to make decisions, explain things, or think about the world. We use them subconsciously and many have become reflexive to our everyday lives. If you’ve ever made a pros/cons list, considered the opportunity cost of a situation or taken an action based on FOMO, you’ve applied a mental model.
We’ve written about confirmation bias, an important one for product managers to keep watch for, yet there are hundreds of less commonly applied mental models we can use to deliberately frame our thought processes. When you apply mental models as a deliberate thought tool, not just a reflex, they can help you explore illuminating paths to better decisions.
Growth has come to dominate all conversations that concern developing new products. Marketers, engineers, and product managers are under great pressure to deliver growth. Many have found that the best way to achieve it is to combine skills from all three areas. Enter the Growth Marketer.
No matter whether you see yourself as someone who’s main goal is to deliver growth, or a marketing generalist who’s looking to develop their skill set in order to stay competitive, developing technical skills is important to everyone who wants to grow a product in the Digital Age.
But where do you start? Being able to code and run regression analysis sound great, but developing those skills takes many years to master.
To help you on the journey of becoming more tech savvy, we’ve identified five essential technical skills growth managers need and how you can apply them to deliver on your growth strategies.
Establishing a monopoly — near-total domination of a market — may seem like the ultimate marker of success. You’ve edged out your competitors, and have the ubiquitous product in your sector. But having a wildly successful product can be dangerous.
It can take your focus away from product development, and shift time and attention towards beating competitors and securing your business with sales and marketing. This can seem like the right decision in the short-term, as ramping down on R&D decreases your operating expenses and exposes some fat profit margins.
However, that shift in focus can cripple you down the line. It can take behemoth companies and bring them to their knees.
Confirmation bias is one of the most pervasive tendencies in human nature.
Bestselling author and professor, Michael Shermer sums up the reason why we are so susceptible to confirmation bias: “Smart people believe weird things because they are skilled at defending beliefs they arrived at for non-smart reasons.”
Confirmation bias is the human tendency to interpret new information as a confirmation of our existing beliefs and ignore it if it challenges our existing beliefs. For example, if you see a glowing object in the night sky and you’re a firm believer in UFOs, you might be convinced you’ve just spotted an alien spacecraft.
The presence of confirmation bias has been well-documented in everything from the 2016 U.S. election to scientific research. And product managing, growth hacking and analytics are definitely not immune to it. Here are some important examples of confirmation bias in product management and analytics and suggestions for how to avoid it.
Remember the days when online gaming consisted of terrible design and graphics with heavily pixelated characters? Thankfully, technology has improved and those days are behind us.
Launched in 2012, Tinybop is part of a growing market of educational apps for kids. In an age where tech rules, they’ve adapted to the changing landscape to accommodate how children learn and play. Their slogan says it all: Toys for Tomorrow. Continue reading
Solving problems with data is appealing because it’s effective. It builds on measurable standards of success that help take the guesswork about which path to take. So why doesn’t everyone in every company make decisions with data all the time?
Exponential growth is one of the most powerful forces in nature. Here are three quick stories to prove it:
- In 1859, an English farmer named Thomas Austin brought 24 rabbits with him to his new home in Australia. As it turns out, they took quite well to the environment down under. Six years later, there were 22 million rabbits all across the continent.
- In 1945, a group of physicists split an atom in the New Mexico desert. When they did, two new atoms split. After that, four atoms split—and eight, and sixteen, and thirty-two, and so on, eventually producing the largest explosion then recorded.
- In 2004, a social network invented at Harvard was so popular that everyone who joined invited several of their friends. Not wanting to be alone, they all invited their friends too—and so on. Now there’s more than a billion people using it.
Facebook, the Manhattan Project, and Australia’s rabbit infestation were all driven by this one force. Alternately cute (rabbits!) and terrifying (the nuclear bomb), exponential growth can start from what seems like nothing to create huge explosions and worldwide phenomena.