In today’s business environment, where customer preferences shift rapidly and new technologies reshape industries overnight, understanding what truly drives customer behavior has never been more critical. Among the many frameworks that have emerged to explain buying decisions, the Jobs-to-Be-Done (JTBD) theory remains one of the most insightful — and increasingly relevant heading into 2025. JTBD transcends traditional demographics and surface-level psychographics by asking a deeper, more nuanced question: What “job” is the customer hiring this product to do?
First introduced by Harvard Business School professor Clayton Christensen, JTBD provides a foundation for discovering customer needs not through what they say, but through a better understanding of their goals, struggles, and desired progress in life or work. As companies across the globe strive for innovation and customer-centric strategies, JTBD has become a powerful tool for aligning product development with genuine customer demand.
The Core Premise of Jobs-to-Be-Done
At its heart, the JTBD theory posits that people don’t simply buy products or services — they ‘hire’ them to accomplish specific tasks. These “jobs” can be functional, emotional, or even social in nature. When analyzing any product or service, companies should be asking: “What job is the customer trying to get done when they choose this solution?”
This perspective shifts the focus away from who the customers are (age, income, gender, etc.) and places it squarely on why they make the choices they do. By moving beyond the surface, JTBD enables more effective product innovation, marketing, and customer journey optimization.
Turning Customer Research into Action
Applying JTBD effectively requires rigorous customer research — not simply traditional surveys or focus groups, but in-depth interviews that explore context, motivation, and unarticulated needs. In 2025, businesses are combining these qualitative insights with data analytics and machine learning to triangulate and validate jobs customers are trying to accomplish.
Here’s a step-by-step breakdown of how companies are putting JTBD into action in today’s competitive environment:
- Identify Job Candidates
Begin by exploring various situations in which customers use your product — or choose not to. These form the initial hypotheses about the ‘jobs’. - Conduct Deep Interviews
Go beyond “What do you want?” or “Do you like our product?” Instead, ask “What was going on in your life when you decided to look for a solution?” - Cluster Insights
Group stories and use-cases around common themes. Look for patterns in motivation, anxieties, and decision-making behavior. - Define the Job Statement
This includes the circumstances (“When…”), motivation (“I want to…”), and desired outcome (“…so that I can…”). Don’t forget the constraints — what must happen or be avoided? - Design Around the Job
Once the core job is identified, redesign product experience, messaging, and delivery mechanisms to optimize for completing that job.
This process transforms raw customer stories into actionable business insight. The goal is to uncover not just what customers want, but why they want it — and how your offering can solve for it better, faster, or more emotionally resonantly than alternatives.
JTBD in Emerging Technologies and Markets
As markets evolve and new technologies such as AI, augmented reality, and blockchain reshape customer expectations, JTBD becomes even more valuable. It allows businesses to address latent needs that customers might not yet be able to clearly articulate, especially in new product categories.
For example, in healthtech, a patient might not be looking for a wearable blood glucose monitor — they’re hiring a continuous monitoring solution to gain peace of mind, avoid emergency care, and feel in control of their health. Similarly, a blockchain-based identity solution may be hired not for tech novelty but to gain freedom from centralized data risk and create trust in online transactions.
The JTBD framework ensures that innovation is grounded in actual human progress, rather than speculative tech enthusiasm.
JTBD Success Stories: Real-World Examples
Across industries, companies are reinventing their approach to customer research using JTBD. Here are a few notable examples where JTBD in action has driven results:
- Spotify analyzed listening behaviors and discovered users were not simply “listening to music.” They were hiring playlists to focus while working, energize workouts, or boost mood on commutes. The result? Personalized playlists and real-time curation that aligned with specific emotional and functional jobs.
- Intercom, a SaaS communication platform, identified that early users were hiring it not just to chat with customers, but to organize customer support, reduce inbound queries, and scale personalization. This led to product pivots and a clearer value proposition.
- Hilti, a manufacturer of construction tools, realized their customers weren’t just buying drills — they were hiring Hilti to ensure uptime on the construction site, reduce capital investment, and keep teams productive. This insight led to a shift from one-time sales to an ongoing tool-as-a-service model.
Common Pitfalls and How to Avoid Them
While JTBD is a powerful methodology, it is not without its challenges. Organizations often make missteps in implementation. Here are several common pitfalls to avoid:
- Focusing on solutions, not jobs. Remember, JTBD is about understanding the problem. Don’t jump to your product’s features — first understand the underlying job.
- Overgeneralization. Vague or overly broad job definitions (“Become more organized”) don’t help. Make sure job statements are specific enough to generate insight and action.
- Ignoring emotional and social contexts. Jobs are not always rational. Customers’ decisions are often influenced by esteem, trust, or avoiding embarrassment.
- Skipping organizational alignment. JTBD should anchor not just product but marketing, service, and strategy. If only one department uses it, the insights will go unleveraged.
Getting cross-functional buy-in and investing in JTBD literacy across the organization are essential steps in ensuring the framework delivers value.
The Future of JTBD in 2025 and Beyond
The integration of AI in customer data analysis, behavioral logging, and semantic processing is making JTBD research more scalable and personable than ever. Natural language processing (NLP) is being used by leading firms to automatically extract “jobs” from customer feedback, reviews, and support logs. At the same time, usability testing tools enhanced with eye-tracking and heatmap data are offering new layers of insight into unstated user goals and behaviors.
We are entering a new frontier where JTBD won’t just be a standalone research method—it will be embedded into the digital fabric of customer insight, enriched in real-time, and accessible across teams through centralized data platforms.
Key 2025 JTBD Trends to Watch:
- AI-assisted job discovery from large-scale text and usage data
- Linking JTBD with customer journey mapping tools and platforms
- Micro-JTBDs that track contextual jobs throughout daily routines
- Hyper-personalized experiences designed in response to real-time JTBD detection
Conclusion
Jobs-to-Be-Done continues to lead the evolution of customer research and innovation strategy. It offers a profound lens for viewing human motivation and for designing offerings that do not just sell, but serve. As we look to 2025 and beyond, the competitive advantage will lie with organizations that can not only gather customer data, but translate it into meaningful, job-based action.
The brilliance of JTBD is that it simultaneously demands empathy and precision. It requires businesses to listen intently and to build intentionally. In a rapidly evolving world, those who understand the job will always outperform those who simply chase the sale.
