Rolling Labs Connected Car Research Method - MWC Feb 2014
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Rolling Labs connected car research presentation by Mike Courtney of Aperio Insights at Mobile World Congress 2014. Preso was given at the Mirrorlink conference. This short presentation highlights the use of digital ethnography as an observation tool to understand consumer behavior in automobiles for the purposes of developing new connected car applications and services
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Rolling Labs Connected Car Research Method - MWC Feb 2014
- 1. Revealing Insights for Clear Decisions Innovation Panel Developing New Apps & Services A Researcher’s Perspective February 25, 2014 www.aperioinsights.com
- 2. Mike Courtney — Researcher and Futurist Masters degree in market research, published author and angel investor. Educated and trained in both traditional research and long range scenario planning. Data Analysis | Ethnography Ideation | End User Requirements New Product Validation | Roadmaps 1 Revealing Insights for Clear Decisions
- 3. Exciting Times….. Has he seen this movie ? I forgot my wallet ! I can pay ! 2 Revealing Insights for Clear Decisions Not yet!
- 4. Now Playing… The Dashboard Mystery Rated LTE What’s going on in there? 3 Revealing Insights for Clear Decisions I can’t tell, and that scares me!
- 5. ROLLING LABS CONNECTED CAR RESEARCH 4 Revealing Insights for Clear Decisions
- 6. Changing Expectations That looks cool ! 5 Revealing Insights for Clear Decisions I love what this can do !
- 7. 6 Revealing Insights for Clear Decisions
- 8. 7 Revealing Insights for Clear Decisions
- 9. 8 Revealing Insights for Clear Decisions
- 10. 9 Revealing Insights for Clear Decisions
- 11. What We’ve Learned Hmmm… Interesting. So that’s how I get more traction ! 10 Revealing Insights for Clear Decisions
- 12. The Challenge — Integrating Research + Product Development Research Iterative Cycles Sketch Critique Product Development 11 Revealing Insights for Clear Decisions Present Higher Quality Solutions
- 13. Unstated Needs Tell More of the Story STATED NEED — Can you just build an iPad into my dashboard? 12 Revealing Insights for Clear Decisions UNSTATED NEED — I want familiarity, ease of use, high quality, choice of apps, etc. Source: http://www.phonesreview.co.uk/wp-content/phoneimages/2011/03/ipadcar.jpg
- 14. Low Fidelity is Useful Low Fidelity 13 Revealing Insights for Clear Decisions High Fidelity Source: architectradure.blogspot.com and www.lincah.com
- 15. Leverage Sensors & Machine Vision 14 Revealing Insights for Clear Decisions
- 16. Timeless Needs Pothole Up Ahead 15 Revealing Insights for Clear Decisions Thanks !
- 17. Developers, start your (app) engines — Ready, Set, Go! Mike Courtney e: mike@aperioinsights.com m: +1 469-363-0109 www.aperioinsights.com 16 Revealing Insights for Clear Decisions
Notes de l'éditeur
- Bring unconventional approaches to traditional methodologies
- Many of us are excited about the connected car spaceSome of our excitement is because we can imagine many great things that connected apps and services will bring to the automotive space. (Examples – better entertainment, ability to easily re-route around traffic and reminders that could mean we never forget to pick up milk and eggs) Some of our excitement is because we also expect to be surprised and delighted by innovations that we didn’t predict and had not yet imagined were going to be possible. We don’t yet know the specifics of exactly how the connected car evolution will turn out – it’s like a much anticipated movie – we’ve seen the trailer and we can’t wait to see how it unfolds and if there will be a surprise ending.
- Another Mystery The movie has another mystery in that we don’t really know much of what’s happened so far. Some of the surprise comes from not knowing very much about the characters in the movie. We know who they are and what they drive – but we know very little about what they really DO in their car. The researcher side of me was a little surprised at this – and took it as a challenge to create a methodology that could help developers understand WHAT consumers do in and out of the car (in context) Describe Rolling Labs(IMAGE = CARS AT A DRIVE IN MOVIE?? MOVIE SCREEN TEXT = “NOW PLAYING – CONNECTING CARS - RATED LTE) (OR HERBIE GOES DIGITAL?) Another Mystery Some of the surprise comes from not knowing very much about the characters in the movie. We know who they are and what they drive – we know the things they have told us, but we know very little about what they really DO in their car. A few years ago I was talking with an auto manufacturer who was talking about the need to understand WHAT consumers ACTUALLY do in the car. I thought the answer would be simple – pull a log file and check that out. Turns out it isn’t yet that simple. Most activity isn’t logged (electro-mechanical vs digital controls etc.) The researcher side of me was a little surprised at this – and took it as a challenge to create a methodology that could help developers understand WHAT consumers do in and out of the car (in context) As researchers we traditionally have used methods like surveys., focus groups and ethnography to uncover and better understand consumer behaviors. As researchers with a geek side we have finally found a reason to include tools like machine vision , automated coding and pattern analysis algorithms to make what we do not only faster but more detailed and insightful.
- The battle for automotive consumers is shifting to satisfying expectations of the in-car experienceIn the future, they key differentiators revolve around the in-vehicle experienceNew apps and services will be part of an ecosystem supported by new business models
- Increasingly complex in-car environment difficult to explore with traditional qual and quant methodologyOne interviewer ― single data sourceLabor intensiveIntrusive & biasedLimited & often less engaging, less insightfulOften unaware of context before and after the driving experienceIncomplete data and often capture human perceptions vs. actual dataIdeal methodology not humanly possible to capture sensor data
- A modular system that enables detailed and cost effective in-car ethnography in order to better understand consumer patterns of behavior in-context via observation. Menu of Data SourcesCar Centric DataPassive Mobile Device LogVisual Recordings of Physical In-Car Activities Supplemental Surveys, In-depth Interviews
- Understanding how consumers use/don’t use current technology is the baseline for planning future releasesExploring likes, dislikes and unmet needs is key to generating new ideas and innovative features
- ObservationsConsumer mindsets are often firmly rooted in the experiences, technology and solutions of what they already haveConsumers often have trouble identifying and verbalizing issues and opportunitiesConsumers have a hard time brainstorming complete new solutionsConsumers grow accustomed to dealing with inconveniences; they forget to mention certain pain points when you ask for their wish listsImplicationObservation will be key to better understand consumer patterns of behavior and identify innovative ways to serve timeless needsCombining qualitative observation with quantitative logs of actual behavioral data yields a richer contextual view of the consumer experienceInnovative concepts and solutions must be iteratively proposed and refined after observing consumer use and interactions
- Some thought people wanted same experience from PC to be on phoneCan’t just rely on what people ask for,Have to look at what people are doing and how they do itE.g. couldn’t just put a tablet in the dashboard as requested (show image of iPad mini glued into dash) => also serving unmet needs (not just timeless needs)versus “make it just like what I have already”e.g. “be productive during commute to work”=> e.g. all sorts of flavors of needs, hence have to consider different research approaches, to develop a comprehensive understanding of needsbut DO want it to be comfortable and familiar, even if just a perception of familiarityhttp://i106.photobucket.com/albums/m254/NeverEnuffBass/c9862ba732cc2f1d6b099bcefdf3fae0.jpg
- Guiding PrinciplesLow cost & off-the-shelf technology enables large, cost-effective studiesFlexibility to tailor the process to meet study objectivesAutomation to extract more information with less laborLeverage passive data capture to generate robust data pointsExtensibility to use technologies which might be adapted and embedded in production to continuously capture data over the life of the vehicleEnable insights to identify areas of opportunities for the car to out perform mobile devices on certain tasks and features