The a-ha moment is the moment when a user experiences your product’s core value proposition (i.e. “This is the best way to solve a problem I have”), and decides to keep coming back to use your product.
A-ha moments are defined by taking a good hard look at the data collected about user behavior. For example, Facebook realized that users kept coming back when they added at least 7 friends in 10 days. So as soon as a user logged into Facebook, every interaction was designed to achieve that goal.
What if you are just starting out building a product?
Building a product is a mixture of both art and science — art is the intuition which leads you to form creative hypotheses on how to solve a problem, and science measures the user behaviour to see if your hypotheses are valid. Finding your product’s a-ha moment is also a mixture of both these — hypothesize when users will experience core product value, and run experiments to see if you are right.
Here are some examples of products along with hypotheses on their a-ha moments.
I also talk about the metric to track to see if the hypothesis is valid i.e. do a large percentage of the customers who experience the hypothesized a-ha moment come back to use the application?
Uber is everyone’s favourite startup, and with an e-commerce product, the opportunity to provide core value presents itself again and again.
- A-ha moment: For the an Uber user, the sensation of booking a cab while not being on the road, and walking outside and straight into the cab is a novel experience that can’t be replicated.
- Metric to track: Repeat transactions in a particular time period.
The team chat application is taking over the world, and recently raised a fresh round of funding. Slack was not the first player in this space (Yammer and Hipchat were already around), but has quickly moved to become a powerhouse with numbers that are off the charts.
- A-ha moment: What differentiates it from other products is its interaction with Slackbot during the onboarding. It’s a great way to set up your profile on the application as well as get familiar with the interface and what your primary action in the app is going to be — chatting! This way, even if your team is not on the app yet, you quickly experience the core product value by chatting with Slackbot.
- Metric to track: Number of messages sent by people who complete on-boarding with Slackbot and are still active daily vs those who skip the on-boarding (although this might be slightly off since some teams might force you to use Slack whether you like it or not)
- A-ha moment: The first time you search for a particular topic, and the results are displayed to you in an infinite scroll. “Woah this is never ending!”. Of course Pinterest had to get people to discover content and add it to the platform, but that was a whole another battle.
- Metric to track: Number of pins viewed vs usage of the platform.
- A-ha moment: The problem it solves is two fold — aggregation of news, and summarization i.e. it gives information to busy people. However, consumption of news itself does not satisfy me as a user — the true a-ha moment for me was when I read something on the in shorts app (which I was unlikely to read elsewhere) and was able to use it in a conversation.
- Metric to track: Correlation between number of articles read in the app and the frequency of usage 1 day, 1 week, 1 month and so on after installation. Objective is to find if there is a number of articles read after which a user becomes active.
Snapchat started out as everyone’s favourite app for shady stuff, but now has become quite the entertainment powerhouse.
- A-ha moment: Core product value is pretty evident here — messaging with the twist of being ephemeral. Sending your first snap to “Team Snapchat” is forced in the onboarding and immediately tells you everything you need to know about “Snapping”. This also creates the first connection in your network, and essentially gives you your “first friend” to make the notion of the private network more evident.
- Metric to track: Snaps sent vs Retention OR Friends added vs retention.
- A-ha moment: The difference with Splitwise is that users have to invest a lot in the application by way of inputting expenses before getting a return. You might be sharing expenses in your apartment, but you have to key in 10 spends before settling at the end of the month.
- Metric to track: Number of expense entries per user vs activity/retention.
- A-ha moment: The first time a spam call is identified by the application and saves you the headache of talking to yet another telemarketer.
- Metric to track: Objective is to determine whether number of incoming calls tracked daily affects how long users have the app on their phone.
- A-ha moment: The first time you open your social media account and see engagement on a tweet you scheduled when you were supposed to be asleep. “Hey this is magic!”
- Metric to track: Whether the number of scheduled posts, and engagement on those posts affects service usage.
Or any other task management application
- A-ha moment: The feeling I get when I tick off tasks assigned to me (“Mark as Complete”) is unmatched. There is a strong psychological force at work here as well — people need gratification for stuff they do, and the act of completing a task and seeing it vanish from your bucket replicates the emotion well.
- Metric to track: Number of tasks marked complete vs activity on the platform.
The sentiment from some of my friends who have used Twitter is that they “don’t get it”. More often than not the first experience of people who use Twitter is that it’s a big noisy room and just too much information to follow. But people who have mastered Twitter swear by it as the fastest way to keep up to date on trends around the world. This includes a judicious use of lists, favourites, hashtags, and finding exactly the right people to follow.
- A-ha moment: For the first users, it probably was just a toy to send short messages to each other, and the ability to send tweets possibly mimicked the real time experience that chat is now taking over. For me however, the a-ha moment was when Marc Andreessen retweeted me i.e. having a conversation or interaction with someone you would probably not have the chance to meet in real life.
- Metric to track: At a broad level, how many accounts you follow in the first few hours seems to be the activation/a-ha metric for Twitter, which is why the on boarding suggests people to follow. However as the service becomes more crowded and noisy, maybe the way to kick up engagement is push users to start conversations with people they admire.