People switch their way of getting a job done when they find a product that does this better than the existing alternatives. But just creating a more effective solution isn’t enough. Teams have to learn how to articulate and deliver this value to target users.

This involves analyzing how successful users go from learning about the product for the first time to realizing that this is the best way they know for getting the job done.

One of the most important tools for structuring and describing how users realize value is to define the “aha moment” and conditions necessary for that moment to happen. In this article, we’ll discuss the mistakes that teams tend to make when trying to define and work with “aha moments”.

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Typical mistakes involving the “aha moment”

Most mistakes occur when teams take the “aha moment” concept too literally.

The world around us is always more complicated than the concepts we use to describe it. That doesn’t mean these concepts are useless. We just need to understand when it makes sense to apply them, as well as their limitations.

Typical mistakes that teams make with the “aha moment” include:

  • Reusing the same “aha moment” for multiple jobs-to-be-done
  • Defining the “aha moment” based on when payment is made
  • Assuming the “aha moment” for a given JTBD is always identical for all users
  • Defining the “aha moment” based on your own understanding of the product
  • Defining the “aha moment” based on product features or properties
  • Conflating the “aha moment” with the metric used to measure it
  • Selecting the wrong metric to describe the “aha moment”

Reusing the same “aha moment” for multiple jobs-to-be-done

Many teams try to set a single “aha moment” for the entire product. But if there are multiple jobs-to-be-done for the product, the “aha moment” will almost certainly be different for each JTBD.

Remember that an “aha moment” arises from a particular combination of product and JTBD that the user wants to solve. That’s why added value in the context of that JTBD will be the key factor driving change in user habits.

Defining the “aha moment” based on when payment is made

The moment of payment is very rarely the moment when the user realizes the product’s value. It’s more likely that payment merely reflects that the user has already realized the product’s value.

However, for some products, payment serves as a sort of marker of trust. The user can then evaluate all the product’s features and decide whether to keep using it.

For example, the Calm meditation app requires users to pay almost immediately after downloading. At that point, users haven’t yet had a chance to experience value or understand the situations in which the product might be useful for them. To answer these questions, they’ll need to buy the premium version of the product.

Assuming the “aha moment” for a given JTBD is always identical for all users

The “aha moment” can vary within a single JTBD

Whenever we define a certain event as an “aha moment”, we are making a simplification that is useful for keeping the team’s efforts coordinated and focused.

But reality is always more complex. Even for the same JTBD, different users may experience an “aha moment” at different times. The “aha moment” can depend on how the user previously solved their JTBD, personal preferences, and other aspects of their situation.

Here’s one example of this complexity.

Educational product X is aimed at professional development and advancement. Students realize its value when they obtain their first deep insight with a major impact on their professional views and methodologies.

Even though the essence of the “aha moment” is the same for all these users, the moment itself happens at different times for different people. Everything will depend on the student’s existing knowledge as well as current responsibilities at their job.

Another example.

Previously, John used a mobile app from HSBC bank, which charges a large commission for exchanging currencies. He then tried out Revolut, which led to an “aha moment” when John could exchange currencies at market rate at any time of day. This “aha moment” is specific to those users who previously used HSBC. Users new to Revolut who have already been enjoying market exchange rates from a different neobank will experience a different “aha moment”.

Users can have different “aha moments” even within the same JTBD

If you interview users and ask them to describe their journey from learning about the product to realizing its value, you might notice that people experience different situations that shape their perception of the product’s value.

For instance, for educational product X, a key “aha moment” might be linked to a deep professional insight. But students might also have other “aha moments” that are more local or unique: passing a test and getting admitted to a selective program, for example, or meeting leaders in their industry.

For the sake of convenience and keeping the team focused, we select one specific “aha moment” that maximally correlates with future user success. This doesn’t mean we can ignore all the other factors that impact value delivery, however.

Events will differ in their effect and importance for perceived value, but they all impact activation rates.

This is why we examine mechanisms for delivering value by performing qualitative interviews to try and identify all potential “aha moments”.

Defining the “aha moment” based on your own understanding of the product

Another frequent mistake is to define the “aha moment” based not on the user’s experience, but on yours, as the creator. This can lead you to false assumptions about where users see value.

We want to know how users perceive product value. And the thing is that their judgments and decisions are not always fully rational. Perceived value will often differ from objective value.

That’s why when you’re defining “aha moments”, be sure to start with qualitative research. We also recommend using quotes from user interviews to describe “aha moments”. This approach will enable you to zero in on how users perceive value, as opposed to your insider perspective. You get a very specific and detailed description of where people find value.

Here is how that might look in action.

Your product team is building a next-generation bank. Its main added value compared to classic banks is cashback on card transactions. Based on the team’s understanding of the product’s value, you define the “aha moment” as the moment when cashback is credited to the user’s account.

But users might actually value things other than cashback—like seeing all their transactions in a sleek and up-to-date mobile app, or the ability to open an account and send transfers more quickly and with less hassle.

Defining the “aha moment” based on product features or properties

Another common mistake is to define an “aha moment” in terms of a product’s features, instead of a specific event.

For example, it would be wrong to say your users have an “aha moment” simply because of your great UX and clean interface. For a banking product, it would similarly be incorrect to say your product’s “aha moment” comes from the fact that you offer a high cashback percentage.

An “aha moment” is a specific event that enables the user to experience value personally for themselves. So if users see value in your product’s cashback, then a possible “aha moment” might be when they actually receive that cashback. The mere existence of cashback is not enough.

This mistake is often the byproduct of another mistake we’ve looked at already, when teams define the “aha moment” based on their own understanding of the product’s value.

The best way to minimize the likelihood of this mistake is to perform in-depth qualitative interviews with users and use verbatim quotes to describe potential “aha moments”.

Conflating the “aha moment” with the metric used to measure it

An “aha moment” is an event that happens to a user when they personally experience and realize the value of a product.

Only after we define this event do we select a metric indicating whether this event has occurred for a user.

For certain products and JTBDs, you won’t be able to formulate a JTBD to perfectly capture that “aha moment”. But that doesn’t mean you shouldn’t try to define the “aha moment” yourself and use it for making decisions.

Let’s think back to our example with educational product X. The user’s “aha moment” occurs when they get their first insight with a major impact on their professional views and methodologies.

This event occurs inside the user’s head, of course. Therefore, it will occur in different ways for different students. We won’t be able to find a metric that will tell us when that “aha moment” has happened.

But if you understand how users find value in the product, you can build out activation in a more thoughtful way. For example, we could arrange the curriculum to stack the most intensive and insight-heavy materials near the start.

Selecting the wrong metric to describe the “aha moment”

Last but not least, poorly chosen metrics may fail to describe the target experience you want for a user’s “aha moment”.

Let’s say that the team for an online marketplace has decided, after qualitative research, that the key “aha moment” for users occurs when they receive their first order and are satisfied with it.

Accordingly, the team decides on the following “aha moment” metric: users who have made their first purchase on the marketplace. Although this metric correlates with the “aha moment”, it doesn’t fully describe what the team actually wants. There are three issues:

  • First, someone who places an order may not receive it.
  • Second, they might receive it late or encounter delivery issues.
  • Third, the merchandise may be damaged or unsuitable for other reasons.

In none of those cases does the user have the target experience originally intended by the team for the “aha moment”.

Our job is to carefully define a metric that captures the product’s added value and the “aha moment”. For the marketplace, we could define that moment more precisely: users who received their order on time, did not leave a negative review, and did not reach out for support during or after the order process.