Using JTBD to move beyond surface-level tests

• What is the customer truly trying to get done right now?
• What frustrations are they avoiding?
• What outcomes are they hoping for?

How JTBD connects with better conversion optimization

More personalized tests, better campaign performance

Examples of JTBD in digital experiments

One of the most impactful ways to apply the Jobs to Be Done (JTBD) framework is by reassessing how you define and segment your audience. Traditional audience segmentation often relies on demographics, such as age, gender, or location. While helpful, these don’t always explain the “why” behind customer behavior. JTBD offers a more meaningful approach by centering segments around motivations and desired outcomes – the underlying jobs consumers are trying to accomplish through your product or service.

Why this matters for growth experiments

Growth experiments – like A/B tests or personalized ad campaigns – perform better when they’re targeted effectively. JTBD insights allow you to move beyond surface-level attributes and connect with users based on their goals. For example, instead of dividing customers by income level, you might uncover that they fall into two jobs-based segments: those trying to “organize family finances” vs. those wanting to “grow long-term wealth.” Each group will respond to different product messages, value propositions, and features.

Using JTBD for customer targeting

Here’s how JTBD can enhance your customer targeting strategy:

• Identify key motivations: Focus on what customers are trying to achieve, not just who they are.
• Uncover behavioral patterns: Segment based on usage scenarios or decision-making triggers.
• Tailor messaging by job: Serve more relevant ads or website content that speaks directly to a customer’s specific job-to-be-done.
• Prioritize high-impact segments: Find underserved jobs with high customer frustration or low solution satisfaction – these can be prime opportunities for testing new growth ideas.

Consumer insights rooted in behavior – rather than demographics – lead to smarter groupings that drive better decisions. When you iterate based on job-based needs, your tests become more insightful and your targeting more effective.

To bring the JTBD framework to life, let’s walk through some case examples of how growth teams can design tests using customer motivation as the backbone. These examples show how JTBD insights can help teams move beyond guessing to launch growth experiments with purpose.

1. Product messaging A/B test

Scenario: A wellness app knows people come to them either to “reduce daily stress” or “improve long-term sleep quality.” Instead of testing random taglines, they run an A/B test with two homepage versions – each tailored to a specific job.

Outcome: Click-through rates and sign-ups increase because users feel the app “gets” their reason for visiting. This is a classic example of how to use Jobs to Be Done in A/B testing to optimize for conversion.

2. Customer onboarding experiment

Scenario: A B2B software product finds two main jobs: users trying to “save time on reporting” and others trying to “share insights with leadership.” The team tests onboarding flows emphasizing different initial features based on the dominant job for each audience segment.

Outcome: Engagement improves as users complete onboarding faster and reach value sooner – a direct win for JTBD growth through behavior insights.

3. Digital ad targeting refinement

Scenario: A personal finance brand segments paid ads based on JTBD traction. Job 1: “Get out of debt.” Job 2: “Save for a major life event.” Each ad set uses wording aligned with that intent.

Outcome: Lower CPAs and improved ROAS, demonstrating how using JTBD for customer targeting boosts campaign performance through sharper relevance.

These are just a few examples of JTBD in digital experiments that show how aligning your efforts to the real “job” can lead to faster learning and stronger outcomes. Growth experiments with the JTBD framework not only improve results but make testing more strategic, grounded, and human-centered.

You don’t need a massive research budget or a full team of strategists to start using the Jobs to Be Done framework in your growth testing efforts. In fact, one of the most exciting parts about JTBD is how accessible it is to beginners who want to design smarter experiments.

Start small with what you already know

Begin by tapping into existing sources – customer interviews, support tickets, surveys, or sales calls – to spot recurring phrases about what people are trying to accomplish. Focus on the motivations behind their actions: What task were they hoping to complete when they tried your product? What problem were they trying to solve?

Sketch out a few core jobs

Then, frame those motivations as simple job statements. For example:

• “When I [situation], I want to [goal], so I can [desired outcome].”

Example: “When I switch accounts, I want to transfer all my data easily, so I can get back to work without losing time.” This provides a starting point for refining your product messaging or testing a new onboarding flow.

Apply jobs-based thinking to experiment design

Use JTBD insights to shape:

• A/B testing ideas: Write two variations of landing page copy, each targeting a different job.
• User testing prompts: Ask testers how well a product helps fulfill a specific job, not just whether they “like” it.
• Customer targeting rules: Segment email campaigns by job rather than only demographics or prior purchases.

Using consumer insights for A/B testing and marketing experiments doesn’t need to be complex. The key is anchoring each experiment in what your users are trying to do – their job to be done. This approach leads to better test ideas, clearer hypotheses, and insights you can trust.

With a bit of curiosity and JTBD thinking, any product or marketing team can design small, thoughtful experiments that add up to major growth wins.