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This research consists of foundational research followed by an end-to-end testing phase, completed for a ground-breaking solution designed to integrate with an already-existing Suzuki car ecosystem. Our objective was to create a vehicle-to-everything (V2X) communication tech product that, when used in conjunction with appropriate infrastructure, traffic rules, and driver education, can help reduce traffic accidents and road congestion.


In addition to my role in leading the research, I was also a key contributor to the features and information architecture of the product as I was involved in the project from the start.


Primarily, there was a need to understand the user's pain points in the traffic, their intent and their personal aspirations (so that we can come up with the right marketing message). It was the first time these companies were building such a product for the India market and they requested a detailed foundational research to determine the set of features the V2X device should have.


Foundational Research

I chose in-depth-interview (IDI) as my method of research, administered in the form of semi-structured interviews. This way I could have an interview structure yet be free enough to discover unique insights and go deep (aka. in-depth) with each participant. So I bucketed my questions into several segments I want to investigate and conducted interviews with 25 people over a course of 1 month. The sample size is high for an IDI, that is to account for the 5 subsegments of the population (5 participant each for a subsegment).

Ideation workshop

The next step was to run the project through three specific rounds of evaluation: The first round lasted about a week and consists of brainstorming, assessments of market potential, and some light prototyping. 

We collaborated with designers in the IITH University, as well as with the developers for an ideation workshop. As a result of the affinity mapping and persona creation, we came up with a fairly focused set of features, and a design brief.

Usability Interviews

In the second round, the offering is refined further with recruited qualitative testing and deeper investigation of participants' specific behaviors in the traffic.

Pilot Testing

Finally, it seemed like the problem space still seemed to have legs at the end of the second round, we put it through an in-market pilot. This way we were able to understand people's behaviors in a real car setting and administer a contextual inquiry, rather than just face-to-face IDIs that required participants to recall what they have done / would do. This usually featured a functioning mock-up of the service we are testing.


Through many rounds of iterations we developed the final prototype. We had to immediately settle on a set of features that would be able to handle a wide range of user scenarios due to a very short timetable and a reach that included the entire India. To wrap-up the initial research and development phase we conducted end-to-end testing, including edge-cases. Participants were asked to use the system in their car like they would if they owned it.


When building reports-out, I organize findings by team / action owner, which usually means structuring the report around phase of the experience, or by discipline.

I also run through findings from the quant-driven beta being run in parallel, as well as the QA testings, and in my reports-out take care to explicitly call out how the findings from the two studies compare and whether they corroborate or contradict one another.

While the report-out slide deck is useful to go through the findings with the team and serve as a record of the study, I also provide excel spreadsheets with specific findings for prioritization and input into release train management tools.




The foundational research identified critical, previously unknown insights about the target user, resulting in 2 personas, widely adopted by the organisation. The evaluative research unearthed issues with product hardware, prompting a re-design of hardware QA practices.​


At the beginning of the end-to-end testing phase the percentage of intuitively understanding the system was %10, by the end, it was over %80,  a major improvement.



Evidence generated by the iterative design and testing was critical in building executive support for prioritizing experience quality.

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