The Smile Graph
I came across the term, Smile Graph whilst reading Nir Eyal’s book, Hooked. I thought it would be a good idea to share my understanding here.
Nir Eyal suggests that when users interact and/or input data in a service, they are essentially “investing” in the service as they create “stored value”. The service doesn’t necessarily have to solve any burning desires but over time as users routinely use the product they continue to “invest” in the service they think less about walking away from it.
Evernote’s Smile Graph demonstrates how over time users increased engagement with the service the more they used it over time. [2]
So basically, the theory is that the more stuff you put in the service, the more important the service is to you. In Evernote’s case, their bet was if their customers would be unhappy to pay $5 a month to a company that was storing their memories and helping retrieve them? [3]
The former CEO of Evernote, Phil Libin in a presentation to investors [3] showed two interesting patterns:
- Upgrade Behaviour
- Within a month of signing up Evernote users were upgrading to the paid version was 0.5%.
- For those users who had been using Evernote for a year, the upgrade rate was an impressive 8%.
- Evernote users became more likely to upgrade over time.
2. Activity rates — how often an average user was actually using Evernote over time
- The curve was a smile — there was a slight drop-off in usage after first few months, then it went up.
Phil Libin argued that not only were active users finding the service more and more useful, but also because customers who had stopped using the service were returning to it. People who left Evernote missed it.
This was counter-intuitive to industry understanding at the time, because:
- For user upgrade behaviour. In companies with freemium models, users who upgrade tend to do so pretty quickly.
They sample the free version, and if they like it, they upgrade right away to get all the features; if they don’t like it enough to upgrade, they tend to abandon the service altogether or use it lightly.
- For many software companies, activity rate curve runs relentlessly downward.
Most people who try an app abandon it pretty quickly or use it less frequently as time goes on.
Since I published this post, a colleague of mine, Rohan Swami, pointed me to another interesting interpretation of user behaviour in products/services called the Power User Curve [4].
Related links
- [1] Hooked: How to Build Habit-Forming Products https://www.amazon.com.au/Hooked-How-Build-Habit-Forming-Products-ebook/dp/B00LMGLXTS
- [2] User Investment: Make Your Users Do the Work https://www.nirandfar.com/2012/07/makeyourusersdothework.html
- [3] Evernote: 2011 Company of the Year https://www.inc.com/magazine/201112/evernote-2011-company-of-the-year.html
- [4] Power User Curve: https://andrewchen.co/power-user-curve/
Hi, I’m Saidur Rahman — a Software Engineer at Atlassian Growth Team.
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