For those who prefer video–
For those of you who like to read (talking to you, Lars)–
Have you ever wondered why there is a delay between a change initiated by you and when that change registers? This is known as adoption latency. It’s the time gap between action and outcome. Defection latency is the evil twin.
To understand adoption latency let’s look at a phenomenon from the eCommerce world. Looking at your Google Analytics data you will
likely definitely notice desktop conversions rates are 2x mobile conversion rates. This trend has held steady for years.
Initially, we speculated mobile visitors were in a different state of mind, constantly multitasking, making their attention fragmented. This, coupled with the idea that mobile users are in “research” mode and not “buying” mode should explain why desktop conversions are higher, right? Not necessarily.
Photo credit: Photo by Bruce Mars from Pexels
Know the biggest reason for mass shoppers not to buy on their phone? Habit. I myself almost always prefer to “investigate” on my phone but place orders on my desktop. Also, to me, the idea of placing an order somehow seems unsafe; it’s a public network. It’s an irrational fear, but I can’t seem to shake it (thanks, System 1!).
It’s taken a long time but the shift is happening. If you look at the numbers, younger shoppers convert much more on mobile devices because that psychological friction isn’t there. However, most marketers are not prepared for the long run, they see the numbers now and think sales will continue to be primarily from the desktop. At their own peril, they’re ignoring adoption latency.
What about defection latency? There are plenty of examples for this too. Have you ever heard of the company Kodak? Do you know Kodak pioneered digital photography?
They made a crucial mistake when evaluating the market. They told themselves that people are still buying a ton of traditional film cameras, so clearly there is a lot of demand for it. Wrong. They were ignoring defection latency.
Consumers wanted the new technology. But were paralyzed by habit and terrified of change. Their behavior didn’t reflect their intent. So Kodak continued on their course. And then, one day, it was too late.
Let’s look at an example from the world of email marketing. The scenario: A marketing executive knows that emails drive 20% of overall sales and wants to grow that. They increase email frequency, sending an email every 10 days vs. every 14 days (what they were doing previously). What happens? An increase in revenue. That correlation signals to the team that the strategy is working. The manager keeps increasing the frequency each quarter until eventually, an email is being sent every 2 days. While this happening, revenue continues to go up.
The company even surveys their customers and they say they want fewer emails, but they are obviously wrong because the numbers tell a different story.
The company continues harvesting their email channel until one day, they have a 45% unsubscription rate. That’s almost half their customers.
The main point to take away from adoption and defection latency is that we need to always look under the surface.