You’ve built a tool that objectively solves a problem. Your code is clean, the UI is modern, and the logic is sound. Yet, when you look at your analytics, you see a “leaky bucket.” Users sign up, perform one task, and never come back.
This is the background anxiety of the builder with traction: “If it works, why don’t they keep using it?”
The mistake is assuming that utility equals value. In Advanced JTBD (AJTBD), we realize that a product isn’t just a “solution”; it’s an investment of the customer’s limited energy. If the energy cost of navigating your product—the clicks, the mental load, the data entry—exceeds the brain’s predicted benefit, the user will “fire” you immediately.
The Diagnosis: The Hidden “Tax Jobs”
Every time you force a user to do something that doesn’t directly contribute to their progress, you are charging them a tax. We call these Meaningless Steps or Tax Jobs.
Think about the last time you used a “simple” time-tracker. If you had to manually start a timer, then manually categorize the entry, then manually export a CSV just to email it to a manager, you weren’t just “tracking time.” You were performing three sub-jobs that your brain views as a bad investment.
Your users aren’t abandoning your features; they are avoiding a high energy cost. They are reverting to their “Same Old” workarounds because, however broken those workarounds are, the brain has already mapped the energy cost and feels “safe” there.
Reframing: Value is Energy Efficiency
To move from a leaky bucket to a sticky product, you must shift your definition of value.
- Utility: “My app lets you track expenses.”
- Value: “My app performs the job of tracking expenses more energy-efficiently than any other method”.
The most successful products don’t just “add features”; they kill jobs. They take a sequence of ten steps (the Job Graph) and collapse them into three. When a user expects a task to be hard but finds it unexpectedly easy, the brain experiences a Positive Prediction Error. This triggers a dopamine hit that creates actual customer satisfaction and long-term loyalty.
Practical Application: Auditing the Job Graph
To stop building “work” and start delivering “progress,” you need to map the Job Graph—the sequence of goals the user’s brain generates to reach their outcome.
- Identify the Prerequisite: What does the user have to do before they open your app? If they are cleaning data in a spreadsheet just to make your app work, you have an “Upstream” friction point.
- Audit the “Intermediary Steps”: Look for every “OK” button, every confirmation screen, and every manual data-sync. If the user is clicking through a defined series of steps while adding zero insight, those are steps that need to be killed.
- Measure the “Investment” vs. “Gain”: If the “Product Job” (Level 1: using the tool) is more exhausting than the “Core Job” (Level 2: the result) is rewarding, the user will churn.
Moving to Clarity
Building on intuition often leads to “bloated software”—a collection of features that look good on paper but feel like a chore in practice.
The alternative is modeling your market based on the mechanics of energy efficiency. When you understand the Job Graph, you stop guessing which buttons to move and start identifying exactly which steps can be eliminated to create that “wow” moment of effortless progress.
BHAG AI helps operationalize this by using AI + Advanced JTBD to model these Job Graphs and identify the “Tax Jobs” that are killing your retention. We help you move past the “noise” of what users say they want to the “signal” of what their brains are actually willing to invest in.
Stop building for utility. Start building for energy efficiency.