Setting a new standard for customer research at JATO Dynamics.


JATO Dynamics



Business Intelligence

JATO mockup of laptop and various charts and diagrams


We're running a series of flagship customer research projects, helping JATO product teams to better understand their customer value proposition based on jobs-to-be-done, pains and expectations.


User research
Value proposition design

What we did

  • Drafted a research plan to make sure before we looked for answers, we were asking the right questions
  • Filled a new research repository with evidence from customer interviews, tagged and categorised by theme for future analysis
  • Visualised our findings as personas, value proposition canvasses, customer journeys and prioritised jobs-to-be-done
  • Presented our conclusions  back to senior stakeholders, prompting thoughtful discussions between teams.

Our work demonstrated the value of research in a successful product strategy.

Systematic qualitative insights analysis

Turning multiple long-form interviews into recommendations can be difficult. Our process makes this straightforward and ensures the evidence behind each conclusion  is clear and transparent.

All sources and evidence are recorded in a repository. So as more research is done, new data can be added, analysed and shared between teams.

We like to show our working and invite our clients to review the data and add their own insight to form new conclusions.

As one JATO stakeholder put it:
“Someone might disagree with your conclusions but they can't disagree with your process.”

Step 01. Evidence

Interviews are recorded and transcribed in their raw form 
so the context is never lost. These are then broken down into evidence snippets: shorter statements, opinions 
or other quotes.

Step 02.  Insights

Evidence is reviewed, de-duplicated and tidied up as a single list of insights. For example, if three people tell you about the same issue, three pieces of evidence become one insight.

Step 03.  Findings

These insights are then further grouped and themed to form our findings. This is what we have learned from our research. Perhaps one insight tells you the office is too hot, and another that the office is too cold. Your finding might be that the temperature is causing your colleagues discomfort!

Step 04.  Conclusions

Finally, we want to sum up our research as a handful of conclusions. These are forward-thinking and refer back 
to the research goals. Given everything we found out, what should be done next? (In the example on step 03, you might conclude your thermostat needs some maintenance!)
JATO research, process and conclusions chart
JATO research, process and conclusions chart

Mapping the underserved customer needs using jobs-to-be-done framework

We like ‘Jobs-to-be-done’ (JTBD) framework because it gets us closer to what we call the ‘why behind the why’. Or rather, what’s the fundamental need the user is trying to satisfy rather than simply the task they are trying to accomplish.

The classic analogy is hammers. People don’t really want a hammer – they want a picture on the wall.

“When we buy a product, we essentially “hire” something to get a job done. If it does the job well, when we are confronted with the same job, we hire that same product again. And if the product does a crummy job, we “fire” it and look around for something else we might hire to solve the problem.”
Clayton M. Christensen
Competing Against Luck: The Story of Innovation and Customer Choice

JTBD are expressed as a ‘job story’, a little like a user story.

JATO - When, Want, Can graphic
JATO - When, Want, Can graphic

These are then graphed according to their importance and the user’s satisfaction with the existing solution. This allows you to highlight the ‘underserved’ jobs – the opportunity to improve the user’s experience where it matters.

JATO - Mapping customer needs chart
JATO - Mapping customer needs chart

An agile research strategy, leveraging multiple different sources of data

We recommend a method called triangulation to combine evidence from multiple sources. This leads to better conclusions more quickly, but also de-risks the process by reducing reliance on any one source.

Our work with JATO was focussed on user interviews, but we recommended a balanced approach combining data from qualitative and quantitative research, along with existing organisational knowledge.

The chart below shows how we think about these different sources.

Quantitative data is best for providing scale, but quick gains can be achieved with simple desktop research methods. Qualitative research balances the two.

JATO quantitive data chart

On a typical project, you could use qualitative research to find a problem, then quantitative analysis to understand the scale. Alternatively, quantitative research might highlight an issue and provide specificity and focus to a qualitative phase to understand the user story behind the data.

The key is balancing methods and scale to tell a more complete story.

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