Research thinking: a guide to understanding the milestones of the research process
I was wondering, why the design thinking exists but thе research thinkig is not? The research thinking is a fundamental base which is crossing the entire design thinking process. The design thinking doesn’t exist without the research but yet the research itself doesn’t get enough respect and receive less attention than it should. During the design thinking workshop teams usually concentrate on a delivering the final product as fast as possible, but the research loves well weighted hypotheses and questions and prospers in a quiet, calm environment. Above all of this, even conducting in-depth interview is a big deal (not to mention other methods, which are broadly distributed in the design thinking) because it is a combination of psychological, expert and scientific approach.
I must admit, it’s not that easy to describe researcher’s way of thinking and standardize all research approaches due to their diverse methods. Although, an idea is simple: the research is a combination of an intuition and science. They are enriching each other in order to validate the incoming information.
This guide is an average version of the research thinking process.
Small tips before you go
- Everything should be documented
Write down every tiny piece of information you found. - Don’t forget to rest
Our brain should rest and process all information in a calm environment. As long as you’re not resting as biased insights you’ll have and more money you spend to nowhere - Every task should be landed on a business reality
You should know the effectiveness of research efforts and understand the ROI of the researchOps itself. This means, that every task which is processing in the research should have strict metrics of success: if business wants to conduct research just for fun — decline the request. Do not set an amount of completed researches as a department’s KPI. - Show your work during preparation to everyone who can help you enrich the outcome
In order to reduce an amount of biases show your hypotheses list or any other artifact to people who have the expertise in the research - Avoid to store insights in a drawer and track the result
Once you presented the result it should be checked in a production. The research process never ends at the moment of presentation — the researcher has to track the outcome in business metrics as well as a product designer or a product owner. - Keep a transparency
Involve business stakeholders, developers, designers to the research process. Invite them to interviews with participants, try everything to finally let colleagues know what exactly do you do, how long it lasts and why it is important to create tasks in their backlog based on your recommendations after listening to your reports. Let the reality land teams to the ground, don’t try to do it yourself. - Don’t rush
An information processing and absorbing needs time. Defend your professional boundaries and never agree with unrealistic deadlines (there is a growth hacking to validate hypotheses faster).
The scheme
Let’s start from the scheme, don’t be afraid: it looks much more complicated than it is.
☘️ in the scheme shows the intuition (divergency) in the research process. If you see this leaf near the step it means that the significant role on this stage plays intuition.
🦉 in the scheme shows the science (convergency) in the research process. Seeing an owl means more grounded approach (opposite to intuition)
You may noticed that at the beginning of the process you encounter ☘️ more often than later and on the most significant steps it prevails. It means that being able to imagine, predict possible correlations and feel the direction is a key to a researcher’s mindset.
Without a divergency the researcher is just ChatGPT, a mechanism, a methodology operator.
The algorithm
Step 1. Forming/Receiving a task ☘️
The task can be received from any stakeholder or you can create your own task. The task should be accurate, simple, with metrics describing the possible result of a future insight integration.
step 1.1. Kick-off meeting: If the task came from a stakeholder — meet the stakeholder, ask as many questions as you can in order to prevent mistakes in the task understanding.
step 1.2. Stakeholder interview: Conduct all necessary interviews and gather the information from every stakeholder who could be involved into the process.
Step 2. Gaining a clarity 💲, ☘️🔑
A first key step (the most important step in the entire process): you should assure yourself that the task is valid and you need to start the research. You are an investigator here — gather analytics, historical data, old research reports, turn on a common sense to clarify the situation — everything which can be helpful. If you discovered that the whole research is not necessary and you can validate the task differently — return to the first step or end the process.
The cost of a mistake on this stage is insignificant: you just spend your own time ($/hour). The further you go in the process, the more expensive the research becomes.
Step 3. Choosing the methodology, defining metrics 🦉
Easy step: having a clarity is enough to decide how you will validate future hypotheses.
Step 4. Generating Hypotheses 1.0 ☘️
Think about all possible scenarios the task contains, all corner cases, everything that could be useful (even uncorrelated to the topic or unrealistic). Unrealistic hypotheses help to think out of the box, but be careful: in generating process you can start fantasizing and start working in non existing reality. Balance is your friend, always.
Step 5. Hypotheses grooming, clustering 🦉
This step is about finding correlations between hypotheses, merging and clustering them. It will help you to create a solid guide for an interview or a survey in the future.
Step 6. Indirect stakeholder interview or additional expert validation ☘️
Here you have to find an additional fresh point of view at all your hypotheses. You need to be sure that you’re not biased and kept in mind everything. It can be anyone: your boss, another researcher, your relatives, expert in an area you’re researching.
Step 7. Generating hypotheses 2.0 ☘️
The stage where you enrich and add more sense into your hypotheses, put an icing on the cake. Some hypotheses can be rejected, it’s ok.
Step 8. Defining an audience, counting a budget 🦉
Describe personas: people you want to invite. No matter how broad is the audience, you should be as much specific as you can. Calculate the budget: recruiting, compensation, SMS, push notifications — everything costs money.
Step 9. Final preparations 🦉
Writing/checking scripts, setting up a hardware and software, a landscape, a survey, prototypes etc.
Step 10. Recruiting & Scheduling 🦉
If you have an agency on board you can relax and wait while recruiting process is going. If you don’t — well, it’s time to create social media posts, grab a phone or whatever you need to hire participants. Be ready to face a people’s negativity: cold calls are dreadful, people don’t like to be disturbed by somebody they don’t know.
Step 11. Launch ☘️🦉
In case of a qualitative research — conduct the first interview (or any field research based on the chosen methodology). If you’re conducting a quantitative research you can launch it, sit and wait till a significant amount of data will be gathered and go-to step 13.
Step 12. Adaptation 💲💲, 🦉☘️ 🔑
Another key step in the process. After the first interview you should notice some mistakes you made during the preparation. You have to adapt artifacts to what you’ve known from the first participant. The cost of mistake on this step is exponentially increasing.
Condition 1. if participant seems unfit then go-to step 8
Condition 2. if all our assumptions = bullshit then go-to step 2
Condition 3. if n hypotheses missed or a bullshit then go-to step 4
If all is ok, you go to the loop:
step 12.1. 2 to n interview ☘️🦉: Conduct all interview you scheduled. During all interviews start looking for a pattern or watch how hypotheses is being validated
step 12.2. Checking a behavioral pattern existence and hypotheses validation (true or false) ☘️🦉: Moment of truth.
If you don’t see a pattern or don’t see the significant validation of hypotheses:
a. go-to step 2: assure that you’re looking in the right place
b. after to step 7: add more hypotheses based on found problems
c. after to step 8: add participants
If you need much broader audience go-to step 3 and change methodology.
step 12.3. N+1 interviews ☘️🦉: Conduct all necessary additional interview (add as much as you need to validate hypotheses)
Step 13. Processing data 🦉
Transcribing, re-listening, re-watching, looking for dependencies in data etc. — all you need to identify key moments in your research. Calculate metrics
Step 14. Analyzing patterns ☘️🦉
Same as we did on the step 5 with hypotheses: clustering, grooming. If you found a new pattern and it wasn’t validated then go-to step 1 creating new task. If it was validated — enrich the hypotheses list. Create a list of insights you found.
Step 15. Creating a coordinate system and mapping ☘️🦉
Coordinate system — is an abstract term. It’s an imaginary map where you put your insights and try to find new correlations with an original task: what if you missed something? Also, you can find something which refers to another product and you have to mark it somewhere and put on a bigger map of the whole product scope you’re studying.
Step 16. Checking biases ☘️
Ok, now you have a big picture, it’s time to become sure that all of it is not your fantasy. Take every insight and try to break it: isn’t it a bullshit you’re doing? Try to prove that you’re wrong in your insights. If you can’t do this — it’s a good sign, put it in your draft conclusion list, if you can — go think again or go-to step 1: put insight to another task as a hypothesis. You also can use a list of cognitive biases to help yourself to enterpret your own thoughts and detect wrong decision making tendencies.
Sleep and rest time
Stop here, sleep well before creating a report. Let your mind rest — it’s important to think clearly. Also, throughout the process there are a lot of “tea time” steps. Don’t neglect them.
Step 17. Making conclusions & writing a report 💲💲💲, 🦉☘️ 🔑
It’s the key step again. Start writing the report as a story — from the big picture to detailed insights. It’s also possible to find another insight form existed insights you’re writing about, put it to another task to validate later (go-to step 1).
step 17.1. Developing recommendations 🦉☘️: Your report should contain specific recommendations with a description how exactly this recommendation would affect business metrics.
step 17.2. Checking biases ☘️: Be specific and tell the truth. Every recommendation should be checked and checked again like on a step 16. You must be sure in what you are writing about.
What is a must in the report:
1. The research goal: why this research had been done
2. The methodology
3. Metrics: CX metrics — cSAT, CES; if it was usability research — add metrics describing the usability: SUS, SUM, UMUX, subjective scale of design satisfaction, etc.
4. Participant list: how much people took part in the research, who was that
5. Key insights: the big picture and main conclusions
6. Detailed insights: describe each key insight enriched with participant quotes (add screenshots, description for screens, graphs, etc.)
7. Uncovered insights: if you decided to put some insights which weren’t validated but you still want to mention them (carefully)
8. Relevant video or photo to dive listeners to the context
9. Hypotheses list: all hypotheses as an additional
10. Prototype and userstories being studied
The cost of mistake is higher than ever before. Be careful in what you put into the report: it will affect a business outcome.
Step 18. Final presentation 🦉
Gather all stakeholders and present them your report. Gather their feedback. Don’t let listeners go until they asked questions: if there weren't any questions it means only one thing — bad result and irrelevant insights. Create a task list based on your recommendations and put them into the product teams backlog.
Step 19. Feedback processing after the pitch 🦉
After the presentation you need to analyze the feedback from stakeholders. If there are some ideas about a new research go-to step 1 — add more hypotheses to validate.
Step 20. Checking results in production ☘️
Now it’s time to measure the success of an integration of our recommendations. If it was a success — you won, if it’s a failure — create a new task and check why it happened.
Conclusion
This process is a cycle or a spiral. You can’t just leave it by desire without the result – you have to proceed until something is validated. Not to be extra to mention, that the research is a continuous process at all, because the more you validate and process, the more insights you have to check again.
Above all of it, the core skills of the researcher is being unbiased and to understand that everything costs money and by doing the job the researcher is trying to find a business solution.
