With COVID the disruptor and the coming fourth industrial revolution triggering cyclonic changes in customer behaviour, it’s safe to say designing UX strategies on top of legacy assumptions will be… foolish, at best.
User-experience design will become a moving target of constantly shifting behavioral trends fueled by immersive new technologies.
Increasingly, predicting the future by looking at the past will become more difficult.
Here we’ll lay out a loose framework for how to do rapid UX research in 5 days to consistently fuel website journey and UX design decisions.
Evolve or Die: The Case For Rapid UX Research
Throughout 2020 and 2021 the stats and stories of retail doom and gloom were underpinned by commentary from industry figures anticipating a need for long-term adaptation to rapidly changing circumstances.
COVID changed the rules for UX research
“The coronavirus pandemic represents an existential threat to the entire retail sector and there will be fundamental changes to the longer-term business model.”
“We as an industry have reached an ‘evolve-or-die’ moment.”
Greg Petro, CEO at First Insight
The rapid UX research lessons of COVID
You don’t need to be a corporate CEO to appreciate the point here.
‘Evolve-or-die’ may sound alarmist, but for some industries the need to adapt to shifting user expectations and patterns of behaviour really is that urgent.
Learning to bake-in rapid UX research as a core business competency will set apart brands that stagnate from those that remain relevant, agile and scalable.
The fourth industrial revolution & the ‘internet of things’
The ‘Fourth Industrial Revolution’ will change user experience in ways previously imagined in the pages of science fiction novels.
Online experiences are set to leap out of our screens and into a matrix of inter-connected experiences that will pervade our everyday world.
Machine learning, robotics, AI, big data and augmented reality are set to blur the lines between the physical and virtual—the effect on how users engage with brands will be transformative.
The rapid UX research lessons of Industry 4.0
These lofty predictions of futuristic user experiences might not seem relevant to humble SMEs engaging with customers online today.
However, the reality is that the need for multi-level customer interaction across different channels and mediums will grow exponentially.
Successful brands will be the ones delivering big, bold user experiences that shape new user mental models and satisfy customer needs in increasingly innovative ways.
Rapid UX research will become an essential tool in that process—particularly because past observations about user experience and behaviour will become less and less relevant for informing the future.
What Is Rapid UX Research?
If customer needs, attitudes and behaviour are to change faster and faster, brands will need to develop new ways of finding the right insights more quickly to match the pace of change with relevant customer engagement models.
Rapid research is a method for uncovering as much customer insight in as little time as possible.
Rapid research will become particularly useful in:
- Creating greater competitive market advantages
- Anticipating shifts in customer needs and expectations
- Aligning with rapidly changing UX mental models
- Designing meaningful user experiences first time
Rapid user research will become a tool for shaping the customer mental models of what meaningful online (and offline) experiences should be.
As quickly as customer mental models start to set and harden, new ones will emerge take their place. Rapid research
A Framework for How to Do Rapid UX Research
Ok, let’s get started.
Here’ we’ll lay out a framework for how you can efficiently apply rapid UX research to quickly gain the actionable insight you need to keep in-tune with rapidly changing needs, attitudes and behaviours of users and customers.
Treat the ‘ideas’ stage of the framework below as your project needs. It could be a new website build, email marketing or paid advertising.
Day 1: Brief (One-Page Summary)
On day one of your rapid UX research phase create a one-page, table-based summary for each of these major project pillars.
1. Problem/Issue (what problems do users have that you hope to solve?)
2. Proposed solution (how will you fix those problems?)
3. Expected outcomes (what are the expected outcomes for the users and the organisation?)
4. Requirements & Tasks (what do you think is needed to achieve the outcomes?)
5. Background info / context (useful insight from previous projects, or ‘what you think you know’ about customer personas, etc)
When you kick off a new digital-marketing project it’s likely you’ve probably already planned around past user research data.
Include this ‘what you think you know’ insight as a starting point, but don’t assume it will be enough by itself. Part of your rapid UX research will aim to validate and build on what you think you already know.
Day 2: Preparation
‘Planning’ UX research has a habit of creating false confidence because it can promote a sense of anticipation.
The assumption can easily become ‘if we plan logically, the outcomes we expect will surely follow!’ If only.
Getting into a ‘preparation’ mindset
To prevent UX research-planning that steers you toward falsely anticipated outcomes, get into an open-minded ‘preparation’ mentality.
In other words, avoid designing bias into your chose UX research approaches.
Design UX research questions and interviews in a way that guides users within the scope of the research. But also in a way that allows users room to go where they want with interview feedback.
That way you’ll bring out the deep, unexpected insight that will help you create more meaningful user experiences for customers that factor for things outside of your line of sight.
Defining your rapid UX research methods
Because you’re doing rapid UX research, select methods that can feasibly be done in a single day that answer the questions:
What users SAY (attitudinal insight)
What users DO (behavioural insight)
From the cross section above your rapid UX research methods will be limited to everything above the horizontal axis.
In other words, a combination of:
Focus groups / participatory design / surveys / video diaries / in-depth interviews / diary studies
Day 3: Research
Traditional UX research can take weeks and months as you implement granular processes for gathering insight from end users.
Because rapid research doesn’t give you the time and luxury of accessing end users, you need to find alternative methods.
Bypassing the end user
You’ll need the next-best thing to the end user: the opinion of informed experience.
Suppose you’re researching to design a new piece of software, or section to a new website. In a rapid UX research context you’d prepare interviews with the person responsible for helping or guiding users through the experience.
This might be an account manager, customer-services representative or IT help desk assistant.
These personas are useful as substitutes for end users because:
1. They have direct access to users and are in-tune with what they dislike or find useful.
2. They’re invested in helping customers achieve what they need to achieve.
Developing research protocols
In rapid UX research, your research protocol is essentially the script that outlines how research will be performed, serving to keep things on the rails.
If you’re chosen method of research is usability testing, or interviews with a software IT department (in place of interviewing end users) then your research protocols will include information on:
- How much time you’ve set aside for the session
- A description or script for each session
- How you’ll record the interview or usability-testing findings
- How you’ll look after the data (for example, confidentially issue)
Effectively, your research protocols are a research plan within your overall research plan. Be thorough enough and your usability testing or interviews will remain focused and productive.
Day 4: Analysis
No matter what your chosen methods for rapid UX research, the analysis phase is the filter that converts raw data into actionable insight.
UX research analysis effectively asks the questions:
- What does the data mean?
- What does it tell you about what you’re designing and who for?
- How can you use the data gathered to inform the UX design process?
How you do your UX research data analysis will depend on your chosen method.
The key is…
Whether you’re looking at numbers or an interview script, you’re looking for discernible patterns about the user, the product or both.
Qualitative data is messy
The first step is to organise it
Interview notes, audio recordings and tons of questions to tons of answers. Qualitative research is messy.
Before you sit down to make interpretations, take the time to transcribe audio or convert things into digital formats. The more you’re able to convert the mass of data into a single, logical format, the easier you’ll find it to pull out the lessons.
Let the project dictate the process
Now’s the time to refer back to the goals and outcomes you defined in your rapid UX research brief.
This will help you get into the right gear to interpret your interview findings.
Suppose you’re designing an app.
Your objective should be to understand who your target users are and what their motivations might be for using your app.
So, now that you’ve conducted with the third parties who understand your target users (remember, rapid UX research means bypassing the end user), you’ll be looking for the following insights in the interview data.
Key demographic data
Persona and lifestyle habits information
How users feel about the product or the topic
A good way of pulling out these insights is to assign codes to the feedback data.
Assigning codes to qualitative research findings
A code is a label or index for organising different sections of text within, for example, an interview transcript.
Bear in mind, the code you assign to answers and feedback is simply a descriptor or label. Not an interpretation of its significance and meaning.
Work through interview transcripts line by line and sort each meaningful response under the different codes you’ve assigned for different types of feedback. For example ‘product feature feedback’ or ‘user attitude feedback’, etc.
Day 5: Reporting
Having painstakingly organised your qualitative research data by theme, you’re ready to start synthesising your data to build a meaningful picture of your rapid UX research.
You know what the themes are, but what’s the data actually telling you?
Findings vs. Insight
A finding: is simply a statement that tells us what’s happening. In your interviews this might be an answer an account manager gave about how their clients use a website.
An insight is different: Insights in this context will describe the underlying truth about a trend in users’ behaviours or attitudes.
To turn insights to findings:
1. Comb through the interview data you’ve organised
into coded themes and answers given.
2. Start with high-priority themes. For example, if your main objective was
to find out user pain points, pull out answers around that theme first.
3. Arrange the findings visually, perhaps on a whiteboard using sticky notes.
Now you can step back, see the big picture and draw the deeper inferences.
Your data synthesis process might look like this:
Theme: → Finding: → Insight:
Theme: customer pain points
Finding: Users abandoned the website frequently frustrated by the checkout process.
Insight: The current checkout process needs refining and simplifying.
Once you’ve repeated the data-synthesis process you should have a good body of rapid UX research insight. The conclusions you’ll draw and the actions you’ll take will depend on the nature of your chosen research methods.
Overall, though, you’ll be left with the kind of actionable insight that should help you design new user experiences that cater hand-in-glove to how your users are evolving.
Staying Relevant & Scalable
Over the coming years user behaviour will evolve repeatedly as technology blurs the line between on and offline experiences.
For today online world, learning the lessons or rapid UX research will be, in effect, learning how to remain relevant and scalable in a context of user demand for exponential convenience.
Thanks for reading.