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Hybrid Qualitative and Statistical Research Methods for Agile Product Design

Background 

Stephanie Battista is the founder of Humanity Innovation Labs, a product design consultancy based in Colorado Springs, CO. Her company collaborates with commercial, academic, and government organizations to develop IOE and edge computing technologies. The consultancy brings together experts in user experience, user research, user interface design, and industrial design, adopting a research-driven approach to systematically investigate how technology fits into users’ lives.

Bridging the Gap between research and design

With more than 20 years of experience in industrial design, Battista has always been passionate about consumer-facing devices. Her journey began at a UK-based biometric startup called Navigator, where she was introduced to cutting-edge security devices. However, as her career progressed, she noticed a disconnect between research and design due to organizational silos.

“At the time, I felt like I was brainstorming and sketching concepts without incorporating user input or feedback, which seemed superficial. How could I conceptualize a solution and articulate the product features, functionality, and requirements without understanding the users?” said Battista.

This feeling of disconnect was amplified by the nascent state of wearable computing devices, which lacked competitive products and historical references for informed design decisions. Her first real exposure to an interdisciplinary research approach was at Modern Edge with Samsung, where she participated in a multi-city ethnographic research program. This experience was a turning point in her career.

“I found that combining qualitative and statistical data was more effective in conveying ideas in an unbiased manner, compared to relying on intuition, which was often not repeatable and difficult to explain to others and typically had nothing to do with the end user,” Battista explained.

Bringing Qualitative Research into Agile Design

In today’s technology market, speed is crucial. The competitive pressure to bring products to market quickly means companies need to integrate research faster to design, iterate, and test prototypes efficiently. Many technology companies use Agile Methodology, a project management framework that emerged from the software industry in 2001, to accelerate product development. Agile works in short iterative cycles involving design, build, test, and launch phases, incorporating continuous feedback to improve product quality with each iteration.

Drawing from her experience with Samsung, Battista began incorporating qualitative research methods into her consultancy work. By gathering user needs and preferences through ethnographic and other methods, her team could make data-driven design decisions rather than relying on intuition.

What is an independent variable?

An independent variable is the factor you set or specify to examine its relationship with an outcome. In experiments, you manipulate the IV by assigning participants to levels (e.g., 0 mg, 5 mg, 10 mg). In observational studies, the IV is a measured predictor that is not under the researcher’s control (e.g., age, prior GPA). The IV should precede the outcome in time, have clearly defined levels or units, and be operationalized so others can replicate the procedure.

Plan how the IV is delivered or recorded, including timing, dose, or intensity, and assignment method. Randomization helps balance unmeasured influences; when randomization is not possible, document selection or grouping criteria. Name the reference category for categorical IVs and the scale for continuous IVs. Common errors include labeling post-treatment measures as IVs, collapsing categories in ways that hide variation, and failing to ensure temporal order, which weakens causal interpretation.

Using Qualitative and Statistical Research Methods to Support Design Clients

Battista employs various mixed method research techniques, including one-on-one interviews, surveys, user testing, A/B testing, focus groups, and usability pilots. These methods help her team identify user needs, behaviors, and motivations, understand user pain points, and determine if a product meets user needs.

Qualitative research uncovers the underlying issues users face and their motivations, while quantitative data reveals measurable patterns and trends. Battista believes that mixed methods research goes beyond the visual elements of product design, reaching into the “human connection” that users desire. The research analysis leads to the creation of data-driven user personas, user journeys, and experience maps, guiding design decisions and strategies for user interaction.

“At Humanity Innovation Labs, we’ve enjoyed creating a hybrid process that seamlessly integrates User Research, UX/UI Design, and Industrial Design. This repeatable approach helps us develop early-stage solutions that blend both software and hardware effectively,” Battista explained.

using NVivo for mixed methods product design research

Battista was introduced to NVivo by a former Intel client with extensive expertise in the semiconductor industry and industrial manufacturing. Together, they used NVivo to analyze both quantitative and qualitative data, simplifying the development of high-level strategies for product development.

NVivo stands out by offering the ability to import data sets from various online platforms, crucial for organizing large-scale longitudinal research. This feature makes it easier to leverage and build upon both quantitative and qualitative data.

Empowering mixed methods research

Battista’s fascination with combining qualitative and statistical research methods led her to develop Zeroes Plus Ones™, a user research platform connecting technology creators with users to develop new products and services. The platform collects and analyzes data using a blend of human and machine intelligence.

“There is something very tangible about research within developing new products and services that I am fascinated with,” Battista explained. “Data seems to make product development easier,” especially using NVivo to categorize and analyze data.

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