If you don’t have questions, you won’t get answers. Remember, you explore the data in search for answers to specific questions. Ask yourself (and your team) questions about the users and their behaviour, even if those questions are hypothetical - like “What is the most used feature by the users who stay active for over 1 year?” Or “What should be number of sessions an user does per month before converting into a premium/paying user?” - Those questions are your path of exploring your data. Define an initial path of data exploration.Start by stating/reporting/observing the metrics and KPI’s that you are comfortable identifying and then ask questions to which you don’t have answers yet. When searching for insights, you start with what you know about your product, and work your way through the unknown.
So, I thought to mention this upfront: if you feel a bit confused in the beginning, keep on reading this was how I actually felt during the process, and things got progressively very, very clear… eventually. It dawned on me that I’ve written this article in a way that actually shared the states I went through while on the search for iqraaly’s aha moment. And this would be a shame because it all got clear to this reader in the end. When this article was still in review, it was pointed out to me by that from a reader’s point of view, the journey starts in a bit confusing mood, which might turn further readers away. Searching through an unknown path for something rather unknown is quite the ride. This has shown us that a lot of pretty simple insights can be explained in a couple of sentences while disguising a heap of work to reach them especially when you have a pool of 500,000 app downloads and 4,000,000+ monthly listened minutes to trawl through (back then). It took us about 10 weeks of work ( Mahmoud Salaheldin iqraaly’s Technical Manager back then and myself, the co-founder and General Manager) to figure out the path towards analyzing the aha-moment, in addition to trying to do the analysis itself. However, nobody usually tells you the methodology to identify a product’s aha-moment, which is what I’m trying to compensate for with this article. They also might state the identified aha-moments of large products like Facebook, Dropbox, Zynga, Twitter and perhaps others ( here). How do you run an aha-moment analysis?Ī lot of blogs state the importance of identifying the aha-moment of a product. The aha-moment sits at the very core of identifying the user retention pattern of a mobile/web product, specifically mid- to long-term retention and user retention is the defining success factor of any consumer app/tech-product, as it is the main component in calculating an app’s ARPU (Average Recurring Revenue Per User) and ARPPU (Average Recurring Revenue Per Paying User). The aha-moment is the set of events or certain experience a user has with a product that transforms him/her from a casual user trying out the app into an avid, hardcore, loyal user that will stick with the app until “forever”.
Mischief, learning, value, pain and pleasureĪmong the progressive and relatively avant-garde activities I’m proud we did in iqraaly is trying to analyze the reasons why people continue using iqraaly (our app for narrated Arabic audiobooks, audio articles and podcasts) for longer times, commonly known as the aha-moment or magic-moment of a tech-product.
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