You Can’t Just Listen to Customers: the Intention-Behavior Gap

In this article, Co.Lab PM Alum Adeyinka talks about leveraging empathy and Jobs to be Done (JTBD) when conducting user research.

Adeyinka Adedoja
March 22, 2024

As a product manager, you've likely been advised to "empathise with your customers" countless times.

Or hold on sec, tap your nose if you’ve never heard ‘empathise with your customers’ before. Gasp, you haven’t??? Tell me, under what rock have you been living???

It Is true though, we can never underestimate the importance of understanding user needs, motivations, and behaviours in creating products that truly resonate with them. But what does that even mean to empathise with users?

How do you unpack insight from talking to your users when most of the time you can’t even trust what they say, especially when there's a well-documented gap between what people say they will do and what they actually do.

Do you think it’s about asking the right questions? I think not.

Let me paint you a scenario.

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Imagine you work in a hospital and you want to avoid the unnecessary spread of infection. You know that Increasing handwashing is a proven solution, so  you ask people to report their past handwashing behaviour, can you trust what they say?

Okay let’s try this: Did you remember to wash your hands the last time you went to the bathroom? Haha, got you.

There’s a gap between what people say they'll do and what they actually do. Psychologists call this gap intention-behaviour gap. And for this reason, talking to users to reveal what they want is mostly ineffective. You still don’t believe me? Let me paint you another scenario

You’re the product manager for a recipe sharing app. You noticed that while the product’s new feature is attracting tons of new signups, data shows 90% of users abandon it after one use.

To understand why,  you would  engage users. Typically, your questions would  be designed around the 3 traditional questions to understand users:

• Past- You would want to know what features users interacted with.

• Future- How users envision incorporating the app in their cooking routine.

• Why- why the app didn’t meet user expectations. But can we trust the answer to this question?  Maybe less than we think.

Responses to these questions are often unreliable due to several biases:

1. Social desirability bias: People express intentions that they believe are socially acceptable or desirable, even if they don’t plan to act on them.

2. Predicting Future Behavior:  When asking people about their future behaviour, they are imagining their ideal self. In the future, I’m a perfect person. In the future, of course, I’ll use the app to cook. I want to make delicious meals for my babies.

3. Changing Circumstances: We often  assume responses represent strong preferences.” Yes, I see myself using your app regularly in the future! I love the idea of discovering new recipes and sharing my own creations with others." However, a few weeks later, User A's work schedule becomes more demanding, leaving them with less free time for cooking

4. Lack of Actionable Insights:  User Interviews and Surveys are often asked in Vacuum as if the environment decision making has no effect on our decision making. Unless we can replicate the environment of decision making, you cannot trust people to tell us what they will or won’t do

5. Overconfidence and Procrastination: Customers might overestimate their likelihood of taking action. User B answered "I wanted to explore new culinary ideas and improve my cooking skills."  Meanwhile they downloaded the app impulsively while browsing through app stores, without a clear intention to actively engage with it. 

To truly grasp why users behave as they do, simply asking them isn't enough. We must instead dive into their actions and underlying motivations through behavioural diagnosis. This approach involves analysing user behaviour to identify patterns and understand the motivations driving those behaviours.

A powerful tool of Behavioural diagnosis is the Jobs-to-be-Done (JTBD) Framework, which allows us to dissect the tasks users aim to accomplish, delineate the steps they take, ascertain their needs, and identify the variables influencing their decisions.

While product analytics tools are invaluable for identifying patterns, JTBD offers a more nuanced insight into user preferences and behaviour, enabling the development of targeted strategies to enhance user engagement.

To effectively leverage the JTBD framework for our recipe sharing app, and thereby tackle user retention, we can follow a structured approach:

Step 1: Identify the JTBD - Start by defining the core task or goal your users are trying to achieve with your app. This could be as straightforward as "Finding and sharing exciting recipes."

Step 2: Break Down into Job Steps - Detail the individual actions or tasks users undertake to accomplish the job. Understanding these steps offers insight into the user's workflow and the sequence of actions they prefer, revealing potential friction points.

Step 3: Identify Job Needs - These encompass the functional and emotional requirements users seek to fulfil when engaging with your product. Functional needs might include finding recipes that fit dietary restrictions, while emotional needs could involve the joy of discovering new cuisines.

Step 4: Identify Job Variables - These are contextual factors that impact how users perform their job and the outcomes they achieve. Variables could range from time constraints affecting recipe selection to the availability of cooking tools.

Step 5: Develop Solutions Based on Insights - Use the insights gained from the previous steps to ideate and develop solutions that directly address the identified needs and variables. This might involve creating features for quicker recipe discovery or tools for sharing cooking experiences with the community

By analysing the job steps, needs, and variables, we can uncover where the new feature may be falling short. if for instance, users abandon after the first use, the feature might be too complex or not intuitive, suggesting a need for simplification and improved UX design.

Or perhaps, there's a critical step missing - lack of relevant recipe recommendations could indicate that the feature doesn't adequately filter recipes based on users' dietary preferences or skill levels.

Bringing it all together, there are 2 takeaways.

By understanding that what people want to do remains constant, the JTBD framework offers a stable foundation for innovation. It encourages product managers to look beyond the superficial aspects of user interviews and surveys to the underlying jobs users are trying to get done.

This approach not only fosters deeper empathy with users but also drives the creation of products and features that are more likely to stand the test of time, as they are rooted in the perennial needs and desires of humans

Secondly, When we focus on what people actually do rather than what they wish they did, it expands possibilities. Looking for discrepancies exposes opportunities. Understand the job steps and variables really well in-depth because variables and needs always change

Today, users might prioritise speed, dietary customization, or the ability to share experiences with a community. Recognizing these shifts, a product manager can use the JTBD framework to guide the development of features that address these modern expressions of timeless job.

Go build innovative and outstanding products.

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