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Behavior Change Planning
Analyzing various challenges based on behavior change theories to propose optimal solutions at the application level.

Challenges in Behavior Change

Challenges in Behavior Change
You want to create apps and services to change people's behavior—for health promotion, learning habits, energy conservation, etc.—but are unsure how to create effective interventions. Numerous scientific findings and theories on "behavior change" exist, but they are often too specialized and difficult to understand, requiring experts to apply them to actual service development. It's difficult to establish a solid basis for designing what messages or features to provide, and at what timing, to increase user motivation and drive action.

With Behavior Change Planning Technology

With Behavior Change Planning Technology
You can understand the Mechanisms of Action (MoA), the psychological mechanisms that prevent behavior change, and find effective Behavior Change Techniques (BCT) based on scientific evidence.

The benefits of Behavior Change Planning Technology

  1. Effective App Design Based on Scientific Evidence
    • Leverage a database of organized academic knowledge to enable design that doesn't rely on intuition or experience.
    • The proposed technical elements (BCTs) also clearly state the reason for their expected effect (MoAs), allowing you to proceed with development with confidence.
  2. Streamlined Development Process and Cost Reduction
    • Automate the strategy design process that previously required consultation with behavior change experts, allowing for rapid decision-making.
    • In addition to advice, app mockups are also provided to accelerate the specification review process.

Demo
App Click here to try the demo app

Technical overview

Target Industry/Users

  • Companies, project planners, and developers aiming to create applications and services that encourage behavior change in customers or employees in fields such as healthcare, education, marketing, and HR.

Challenges in Target Industry and Operations

  • Lack of specialized knowledge in behavior change.
  • Long lead times from planning to Proof of Concept (PoC), requiring significant time and investment before effectiveness can be verified.

Technical Challenges

  • The factors influencing human behavior are complex and multifaceted, making it difficult to identify which ones to target.
  • There is no guideline for selecting the most suitable technique from the numerous existing behavior change techniques for a specific purpose or situation.
  • It is difficult to translate abstract theories into concrete application features and UI/UX designs.

Solutions

  • Leverages a knowledge base that links Behavior Change Techniques (BCTs) with their Mechanisms of Action (MoAs).
  • When a user inputs their desired goals and target audience characteristics in natural language, the AI cross-references this with the database to propose appropriate BCTs and concrete feature ideas to implement them.
  • Enables the construction of application prototypes by combining the proposed feature ideas, without requiring specialized programming knowledge.

Fujitsu's Technological Advantage

  • Recommends the optimal combination of BCTs from a vast range of options to meet diverse user needs, thereby improving the quality of the design.
  • Supports the entire process, from ideation to concrete feature design and prototyping.

Value of Behavior Change Planning Technology (Details)

Even users without expertise in behavioral science can use this tool to design effective, evidence-based interventions and continuously improve them.

  • Provides theories of behavior change, which were previously difficult for non-experts to grasp, in a form that anyone can utilize. This empowers more people to create effective services.
  • Supports a continuous improvement loop by accumulating and analyzing user responses and outcomes as data to further optimize intervention methods, allowing services to constantly evolve.

Use Cases

  • When considering strategies and application specifications for behavior change initiatives—such as promoting exercise, learning, or energy conservation—this technology can be used to formulate plans based on scientific evidence.

Model Use Cases

Category \ Industry Sales/CS Healthcare Education Local Government
Training AI Coaching for Service Quality AI Training for Patient Explanations - -
Habit Formation - Treatment & Self-Care Continuity Assist Learning Habit Development Assist -
Promotion - Medical Checkup Action Promotion AI - Community Revitalization AI Promoter

Case Studies

  • A PoC was conducted within Fujitsu to promote health and exercise. Interventions based on scientific theory successfully improved user retention rates.

Evaluations from Renowned International Researchers in the Field of Behavior Change

Anonymous to protect personal information. The essence of the opinions is based on the originals.

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Researcher A — Authority in Behavior Change Systems Research
Even considering the flow of related research and practice over the past 12–15 years, this was recognized as a very significant advancement and a cutting-edge initiative. Given that many existing studies on software automation end with paper publication, we received encouraging words to please continue the work.
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Researcher B — Researcher in AI and Application Development Automation
We received many technical comments on past approaches, configuration methods, and the mechanism of AI-powered app development automation. As it overlapped significantly with the researcher's own work, it became a lively exchange of mutual opinions.
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Researcher C — Expert in Healthcare × Behavior Change
The researcher who responded most enthusiastically during the presentation, calling it "a very cool system." We also received active feedback, with them expressing a strong desire to use it and asking us to get in touch.

Technical Trial

Demo
App Click here to try the demo app