Senseshaping in QA: How Testers Discover Customer Needs

This article explains how senseshaping helps QA testers interpret customer cues, catch missing or misunderstood requirements early, and improve the user experience.

What is Senseshaping?

Senseshaping is a process of interpreting customer needs and communicating them effectively to a diverse team. Senseshaping is used by Product management and design personnel to drive application feature design. Product managers and designers gather feature ideas and requirements by observing customer actions and holding dynamic requirement discussions.

The purpose of senseshaping is to create innovative application features with an accurate understanding of customer needs. Senseshaping uses the human concept of sensemaking to help team members interpret and respond to cues, events, or customer actions. Senseshaping and sensemaking enable the development team to create the application features in the manner the customer needs and expects even if exact intentions are unclear.

The term comes from product innovation research. The paper How Product Managers Use Senseshaping to Drive the Front-end of Digital Product Innovation describes senseshaping as the repeated synthesis of product meaning that emerges from feedback between sensegiving and sensemaking. Sensegiving is the act of communicating an interpretation to other people so they adopt it. That makes senseshaping a two-way loop rather than a one-time handoff, which is why a QA tester who only receives the finished requirement sits outside the process.

Key Takeaway: Senseshaping interprets customer needs from observed customer actions and requirement discussions and communicates those needs to the whole team, so features are built the way the customer expects even when the customer intention is not stated exactly.

What is Sensemaking and how does it relate to Senseshaping?

Sensemaking is the process humans use to recognize, interpret and assign meaning to actions. Sensemaking answers two questions: What's going on and what do we do about it? Using sensemaking skills enables software development teams to improve product user experience by developing and designing based on customer needs, directly specified or indicated through actions or cues.

Sensemaking informs or formulates senseshaping. Essentially, senseshaping is a result of sensemaking. As humans, we start out making sense of actions, cues, and situations around or happening to us. As a result, we automatically begin to practice senseshaping or use our experiences and interpretations to answer what's going on and formulate an approach to manage it.

Sensemaking can be difficult because it gets compromised by the desire to normalize situations or apply preconceived notions. When cues and actions are not considered uniquely but normalized or covered over then we likely respond in incorrect or conflicting ways. Often people communicate with others and then act together to form a response. Or team members disengage or come up with a new response that addresses the issue or situation. The question then becomes, does the solution still fulfill the customer's need or requirement?

Key Takeaway: Sensemaking is how people recognize and assign meaning to actions, senseshaping is the response a team builds from sensemaking, and normalizing an unusual customer cue instead of treating the cue on its own leads to a solution that no longer fulfills the customer need.

How does Senseshaping impact Application Design?

Senseshaping takes the feedback gained from sensemaking and in the case of product development, creates a design or function that best satisfies the user or customer. Using continuous feedback loops between software development team members enables a natural communication of user needs. The back and forth communication and understanding of the requirements is the goal of the senseshaping process.

Senseshaping process steps include:

• Use sensemaking to gather information and context from diverse sources.
• Communicate with other sources not previously used to assimilate different views.
• Combine the sensemaking information acquired to merge both views and develop a unique perspective
• Communicate a common perspective or approach that most credibly meets the need or solves the problem

Essentially, the software development team uses senseshaping to create an application feature or product that solves the customer's need. By listening to customers and other team members the group creates an application that's innovative for the customer. If a product manager or designer works alone or only with team members with the same senseshaping experiences, then they lose touch with the customer. Likewise, if developers or testing team members spend more time innovating new items outside the senseshaping norm, they waste time and lose touch with the application's intent for the customer.

The best application design comes from a shared set of experiences. By using a wider array of sensemaking results, teams better understand customer needs. Instead of focusing on providing the latest and greatest technology for its own sake, the team comes to a better understanding of ways to solve problems and provide the functionality the customer needs.

Many teams now draft features, code, and tests with AI code assistants for testing, and that shifts where senseshaping matters most. An assistant reads the written acceptance criteria and produces work that matches those words exactly. It cannot see a customer cue that nobody wrote down, so a generated test suite can pass in full while the feature still misses the need behind the request. Treat generated tests as coverage of the stated requirement only. The team supplies the unstated part, and senseshaping is the process that surfaces it.

Key Takeaway: Senseshaping shapes application design through continuous feedback loops between team members, and a design built on a shared set of sensemaking experiences meets the customer need better than a design created by a product manager or designer working alone.

How can QA testers use Senseshaping to benefit the Customer Experience?

QA testers and QA testing teams can use senseshaping data or results to analyze if the customer needs are met. Are there functions customers want but haven't expressed? Are there cues the customer is not engaged with the application? Are customers dreading a new release? All questions are answered by analyzing the senseshaping information gathered from development team meetings and discussions.

Finding missing requirements during requirement analysis or user story analysis saves time for the development team and the customer. Missing requirements are missed cues or misunderstood requests that become defects after a code release. How can a QA tester determine if a cue has been missed or understood? Ask questions, if not of customers, then of developers, designers, and product managers.

Determine if any team member has a different understanding of the customer's need. Another option is to mindmap or create a prototype of the functionality. Analyze the result for gaps, or where a function is implemented but fails to deliver on the customer's implied need. As a QA tester ask yourself if a feature truly solves the customer's need or request.

Next, analyze if the feature or application is normalized. Is the team developing what works for the customer or what has been accepted in the past? In other words, is the team using their senseshaping information to create something innovative that responds to customer cues and actions, or is the design the same old status quo approach? The tendency to return what once worked or a standard design is easier, but it may not meet the customer's needs or expectations. QA testers can use senseshaping techniques and team data to ensure application features or solutions truly meet the customer's needs.

A senseshaping pass fits into backlog refinement. Next to each acceptance criterion, write the customer cue behind it in one line and name where that cue came from, such as a support ticket, a recorded session, a sales call, or a direct request. Any criterion with no traceable cue is an assumption rather than a requirement. Raise those assumptions before the sprint starts, because correcting a requirement in refinement costs far less than fixing a defect after release.

Key Takeaway: QA testers apply senseshaping during requirements and user story analysis by questioning developers, designers, and product managers, by mindmapping or prototyping the functionality, and by checking whether a feature solves the customer need or only repeats a design that was accepted in the past.

How should QA testers use AI tools for senseshaping?

Use AI tools to read the raw cue sources at scale, then check the rare cues by hand. Summarizers rank themes by frequency, and a missing requirement is usually rare. Support tickets, session notes, app store reviews, and sales call transcripts are the cue corpus most QA teams already hold and never read in full. A language model can read all of it in minutes. The limit is what happens after the reading.

A 2025 study, Can AI Truly Represent Your Voice in Deliberations, evaluated 18 language models on summarizing large sets of free-form written contributions. The authors report persistent underrepresentation of minority positions and sensitivity to the order of the input. Customer cues behave the same way. The handful of tickets that describe an unexpected workflow form the minority position in the corpus, and those are the cues senseshaping is meant to catch.

Input position matters as well. The Lost in the Middle study by Nelson F. Liu and co-authors found that models perform best when the relevant information sits at the beginning or the end of a long input, and degrade significantly when the model has to reach information in the middle. One bulk pass over the whole ticket archive is therefore not a reliable search. Run the corpus in small batches, ask the model for disagreements rather than themes, and keep the original quote attached to every cue you carry forward.

Then make the interpreted cue testable. ISO/IEC 25019:2023 defines a quality-in-use model of three characteristics that can influence stakeholders when a product is used in a specified context of use. Writing that context down, who the user is and what they are trying to finish, turns a soft cue into an acceptance criterion a tester can check.

Key Takeaway: AI tools can read a full archive of support tickets, session notes, and call transcripts in minutes, but language models underrepresent minority positions and lose information placed in the middle of a long input, so QA testers should run the corpus in small batches and check the rare cues by hand.

Conclusion

Senseshaping enables software development teams to create customer-focused applications that improve user experience. By using senseshaping to collect, analyze, and discuss, from various perspectives, development teams create applications that meet customer expectations. Meeting customer expectations improves user experience and creates a strong, loyal customer base.

Understanding that everyone makes sense of actions, cues, and life situations differently enables teams to use senseshaping to create an accurate understanding of customer requirements. An accurate understanding of customer needs ensures accurate functionality and design with the customer at the center. The tendency to normalize situations or make them fit a specific mold creates applications that fail customers and creates large defect or technical debt loads.

Use senseshaping with the software development team to enable a better understanding of customer requirements across the product, design, development, and testing team. QA testers can leverage senseshaping to analyze requirements or user stories and discover missing requirements and hidden defects before the release. QA testers can use senseshaping to ensure a higher quality application that meets customer needs and improves the customer experience.