Step #1 – Hold Kick-off Meeting
For this project, we worked with an elite advanced innovation division that reports to Faurecia’s global lead of engineering. They were developing a smart automotive seat technology that would allow consumers to optimize their vehicle’s seat fit and function for comfort and health benefits, and that also increased passenger safety. They were interested in evaluating consumers’ reactions to the inclusion of sensors that would map information gathered from the passenger’s body to specific seat functions, such as heating/cooling, massage, shape and contour management, etc. In addition, the smart seat could report on physical status for improved health monitoring and prescriptive services.
To kick off the project, we met with the Advanced Innovation Manager to hear more about the background of the product and discuss how we would disseminate the survey.
Step #2 – Refine Research Problem & Conduct Market Research
We recognized that our client’s research needs for evaluating consumers’ interest in a new product were broad. Knowing the constraints we faced, after conversations with our client we narrowed our research decision problems down to:
- Do consumers see value in a car seat with all these features?
- Which smart seat features are the most desirable to consumers?
- How do distinct consumer segments respond to the benefits of seat features?
One hurdle we faced was that there was no similar product currently on the market. We wondered how we would provide a context for survey participants to help them understand the value utility and ‘cool factor’ of this seat. We decided to explore the idea of asking survey participants to watch a video that described the product before taking the survey.
Next we did some secondary market research into Faurecia’s background and strategy in the area of car seat ergonomics and simulation, as well as their proprietary smartphone-based SmartFit technology. We also looked into sensor-based automotive accessories in order to understand consumers’ expectations, as well as what was currently available in the luxury car market.
Step #3 – Design & Pre-test Survey Questionnaire
We designed a 21-question survey with four sections:
- Section 1 – Personal Characteristics (1%)
- Section 2 – Attitudes Regarding Sensor Technology (55%)
- Section 3 – Demographics (22%)
- Section 4 – Personal Health (22%)
We dedicated a large portion of the survey to Demographics and Personal Health in order to better understand the factors that affect consumer interest in sensor technology. (Going into it, we believed health factors would be the most likely to affect interest.) We also asked standard demographic questions such as household size, household income, age and gender.
We would have liked to have expanded the Personal Characteristics section in order to learn more about participants’ histories regarding cars and personal technology, but we decided to prioritize keeping the survey to a reasonable length.
In terms of question format, we used majority Likert scale in the Attitudes section, with a few rank-order scale (including one that involved totaling points).
We pre-tested the survey by distributing a paper copy to about 25 classmates for their feedback.
Step #4 – Distribute Survey
After revising the survey questionnaire based on the feedback we’d received, we ran it by our client for approval. We then created a web-based version by programming the survey in Qualtrics. We distributed it to participants through a third party contracted by Faurecia. We told the third party who our target population was: people who had purchased a luxury car within the last three years. The first question on the survey acted as a screener, filtering out participants who didn’t meet that criteria.
Step #5 – Analyze Results & Prepare Report
Due to time constraints, we closed the survey after 300 completes. We then analyzed the results in SPSS, a standard statistical package used for business analyses. We cross-tabulated the responses to each of the Demographics and Personal Health questions with respondents’ level of interest in sensor technology. We determined statistical significance by running a CHI square test for every cross-tabulation. To make our results palatable for our client, we created a brief marketing persona for each cluster.
Our final step was to prepare a report for our client that included a recommendation of which customer segments to target, a ranking of car seat features and recommended next steps for future market research.