Generative Research: All You Need To Know

Aug 22, 2023 | User Research | 0 comments

Human-centred research should always be an integral component of any UI/UX design process than isolated from it. Furthermore, human-centred research approaches should always be flexible, allowing appropriateness to be the key determining factor in the selection of methods for information collection and the testing of ideas.

Generative research is an approach that focuses on developing a deeper understanding of users to uncover opportunities for solutions and innovation.

Sometimes referred to as exploratory research, discovery research or problem-space research, generative research helps organisations when they don’t even know what problem to solve for customers.

This article seeks to delve into all things generative research, its benefits as a discipline as well as the execution methods of its underlying principles.

What is generative research?

Generative research is essentially a qualitative research methodology expressly designed to help reveal ordinary users’ problems in order to find viable solutions.

This research methodology often entails interviews with customers, exploratory research, and observation of customers to comprehensively learn about who they are, what they do, why they do what they do in a specific way, and how they do it.

It can even go further to unpack what frustrates them, what really makes them happy, and in what contexts they take a specific action, etc.

Fundamentally, generative research seeks to deeply “generate” a deep understanding of who one’s customers are (as human beings, not as users), and what they experience in their daily lives.

For example, its methodical approach to interviewing goes beyond tactical inquiries (as typically seen with usability testing) to focus on digging into a person’s identity beyond their interaction with a product.

Why is generative research important?

The strategic approach that underpins generative research and focuses on direct collaboration with users enables UI/UX developers to uncover the mindset of users regarding a particular problem to later translate it into a feasible and executable solution.

This approach does not perceive users as passive consumers but as active stakeholders in the design process of a product. It reveals to product developers what users are thinking of at a given moment when using a product, removing biases they typically have.

This is because developers sometimes get stuck in a box when creating unique products and can become quite short-sighted.

In practice, generative research helps break those biases to devise solutions to a user’s exact problems.

In fact, a Nielsen Norman Group survey revealed that 83% of organisations that engaged in generative research on their last projects reported higher success rates in contrast to others that did not.

Types of generative research

Generative research seeks to get prospective users to tell stories about their lives that go beyond a product or service, revealing rich information about their overarching needs and motivations.

The different ways generative research achieves this outcome in contrast to other research methodologies can be summarised below:

Generative vs formative research

Generative research processes focus on identifying new hypotheses for a business as well as building an understanding of their domain.

In contrast, formative research methodologies focus on testing new hypotheses before and during the delivery of a product.

Consider this scenario. A startup company wants to launch a new fitness app but isn’t sure about the features and functionalities users would find most beneficial. They conduct interviews and surveys with potential users to gather insights about their fitness habits, preferences, and pain points. Based on the feedback, they identify a need for a feature that offers personalised workout plans based on individual health goals and constraints. This is generative research.

Now, after developing a prototype of the fitness app with the personalised workout plan feature, the startup wants to ensure it meets user expectations and is easy to use. They conduct usability testing sessions where users interact with the prototype. During these sessions, they discover that users are confused about setting up their initial health goals in the app. Based on this feedback, they refine the user interface and instructions to make the setup process more intuitive. This is formative research.

In essence, while generative research helped the startup identify a potential feature (personalised workout plans), formative research helped them refine and perfect it based on real user feedback.

Generative vs evaluative research

The objectives of generative and evaluative research differ but are both essential. Generative research defines the problem one would like to design a solution for. On the other hand, evaluative research helps developers to evaluate an existing design.

Furthermore, while generative research helps one uncover opportunities to advance customer-centric solutions, evaluative research is more product-centric.

Nonetheless, though disparate in their goals, generative and evaluative research methodologies go hand in hand. Generative research helps product developers to find the problems they need to solve, while evaluative research ensures they are solving these problems well.

How to determine if generative research is needed?

As already mentioned, generative research methodologies aren’t product-focused. This means that you will not test a hypothesis or gather feedback on a product prototype. Rather, you’ll focus on understanding a customer’s identity to uncover their unmet needs you can fulfill.

It is important to initiate a generative study at the very beginning of a product-development process. This helps to drive product direction, generate new ideas and exploit any innovative market opportunities.

Furthermore, its imperative to iteratively assimilate generative research into every stage of the product development lifecycle.

Generative research methods

Generative research methodologies help organisations move from a product-centric ethos to a user-centric one.

Thereby, it enables them to uncover rich insights about customer behaviours, opinions, and motivations to design better products that solve real-world problems for their users.

The different generative research methods one can exploit are:

1. Interviews: conducting in-depth interviews to gather rich qualitative data

During user interviews, multiple participants are engaged on a one-on-one basis, either remotely or in person. Subsequently, they are asked approximately 5-10 open-ended questions that strategically encourage them to share relevant opinions, stories and experiences about a product, topic or problem.

These interviews typically provide a wealth of qualitative information about one’s users that organisations can harness to generate product ideas and solutions.

Generative research questions

Generative research questions are designed to generally explore many possible vectors that focus on one key problem. This qualitative activity is designed to generate new ideas, understandings, and directions.

2. Observations: leveraging ethnographic and contextual observations

Ethnographies is a technique where one speaks with and critically observes participants’ social behaviours, interactions and perceptions as they execute tasks in their natural habitat, like at home or in the office.

Ethnographic studies help build empathy with users, enabling product designers to better understand the context of users’ daily lives and why they behave as they do.

This information can be leveraged to uncover potential product limitations and problems and devise solutions that address those exact customer needs.

3. Workshops and Co-creation: involving participants in idea generation and collaboration

Workshops enable researchers to group people together to generate executable solutions to rectify user challenges.

Typically, during workshops, participants are provided with some background information on the challenges at hand, and then given ample time to brainstorm and suggest potential solutions.

Workshops can also be employed to get feedback on potential solutions that product developers are already considering.

4. Diary Studies: capturing longitudinal data through personal journals or diaries

A diary study allows one to collect qualitative data about user habits, behaviours and experiences over a defined period of time. While interviews and surveys capture user perceptions during an exact moment in time, diary studies are rather longitudinal to attain a more in-depth view of users.

During diary studies, researchers ask participants to submit their thoughts and feelings over a specific time period. This is usually done via video logging, enabling them to analyse observable behaviour that words alone cannot capture.

At the end of the diary study, the findings are analysed to uncover trends in customers’ long-term behaviour, attitudes, habits and motivations.

How to plan a generative research study?

When seeking to engage in generative research, here are the common steps that one can follow:

1. Define the problem at hand

Before commencing, it’s imperative to clearly define the problem to determine what generative research approach best fits your intended outcome.

If your problem dictates discovery, exploration, and understanding, then generative research is probably the right approach.

2. Understand the objectives

After defining the problem, you will need to understand the objectives of the users. To do this, create a research plan to keep you on track and serve as a guide to help you focus your tasks. Your plan should clearly state the objectives of the research exercise, detail how you’ll select participants, and even determine incentives for the participants.

3. Participant selection

Afterwards, you’ll start recruiting participants for your generative research study to get the data you need to address your research questions.

4. Choose the research methods

After participant selection, you’ll proceed to choose the appropriate generative research methodology that aligns with your objectives, timelines, and overall goals.

5. Create a discussion guide

After selecting a research methodology, you’ll need to create a discussion guide for direction when engaging participants in order to meet your objectives or moderate your discussions whilst keeping them on track.

6. Conduct a generative research

In the last phase, you’ll proceed to commence your moderated generative research using the methods mentioned earlier. These include interviews, observations, workshops or diary studies.

You can employ transcription tools, Google Meet and Zoom and also create a user research repository to store all your insights.

Data Analysis in Generative Research

After performing the generative research exercise, you’ll need to synthesise and analyse the data at hand. You can execute this manually; however, it will probably be time-consuming and cumbersome.

As such, you can use tools like UserTesting to automatically discover relevant patterns and trends related to participants’ behaviours and motivations to create user-centric experiences.

You can also create affinity diagrams to discover the most common customer pain points using tools like Condens.io.

Real-World Applications of Generative Research

Generative research is currently being exploited in different industries like technology and healthcare to gain a deeper understanding of users’ problem space.

For example, it is being used in the technology sphere to engineer new digital products and services and uncover new areas for innovation.

In healthcare, generative research is being employed to comprehensively understand patients’ needs and experiences for healthcare companies to design products that meet the unique needs of their patients.

Conclusion: Future of generative research

All things considered; generative research helps organisations define users’ problems at the very beginning of the product cycle.

Based on the insights garnered, product designers can synthesise them and understand patterns to resolve user challenges.

As such, generative research will continue to be relevant to aid researchers in finding opportunities for constant innovation when iteratively creating solutions to common pain points.

With the advancement of AI, virtual reality and augmented reality, we foresee that generative research will be branching out into immersive environments. This may foster cross-functional collaboration to help to break down user-designer silos and create a more innovative and collaborative culture.

Reach out to us at Netizen Experience for conducting generative research for your next project!