Nov 16, 2013
Giving old products upgrades through sensors
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Giving old products upgrades through sensors
Helpouts connects people who need help with people who can give help over live video. Get help across multiple topics right from your PC or mobile device.
Now Google will really help people manage their lives.
Group synthesis! We printed out individual data points from many different sources pertaining to Big Data, and then as a group, silently affinitized. Once we clustered our own data points, we came together as a group to find overlaps & discrepancies and further synthesize.
"Interviewing isn't the right approach for every problem. Because it favors depth over sample size, it’s not a source for statistically significant data. Being semi-structured, each interview will be unique, making it hard to objectively tally data points across the sample."
Steve Portigal, Interviewing Users
Doing an exercise to see how Big Data could immediately contribute to our process as service designers.
We started by asking ambiguous questions that formed during our contextual interviews, like "What contributes to customer perception of quality?" [yellow post-its]
We then generated factors on blue post-its that could potentially contribute to the yellow post-it questions. Lastly, we brainstormed obscure existing records and databases that could help us answer the questions.
"In principle the benefits are huge, not just in targeting and relevance, but in ease of use for the consumer. Imagine going into a shop, says Bayfield, "and it knows what your previous transactions were, and what you have just said on Facebook about where you are going tonight, and is able to lead you directly to where it thinks the most interesting things for you are."
"Monsanto said it was paying $930 million in cash for the company, which looks at data like historic rainfall and soil quality to help farmers predict crop yields."
I'd love to do a comparison of spotify, songza, and this new Beats music service to see if there really is a notable difference between human-based or algorithm-based curation.