The new technology analyses online and social media consumer comments about products to inform designers so they can create better products consumers will love.

Professor Daizhong Su and his team at Nottingham Trent’s Advanced Design and Manufacturing Engineering Centre says a recent design case study shows how innovative design can be achieved from a better understanding of consumer preferences.

“At our fingertips is an array of data which tells us the strengths and weaknesses of almost every product in the world,” said Professor Su. “We’ve developed a way to harness this valuable information and create a powerful approach which could change the way we think about design.

“It has the potential to make tomorrow’s products more innovative, user-friendly, sustainable and better informed of user requirements.”

Keywords are entered into the new computer program and it then categorises reviews - breaking down the positive and negative comments on products and product features. ( The program disregards spam comments.)

 

The research team worked with design students to test the technology with the design of a desk lamp. By using the algorithm to detect thousands of comments about desk lamps and to sort the positives and the negatives about them. The students then designed a lamp with the popular features.

The 'big data' desk lamp has an on/off switch that controls brightness, a sustainable bamboo base and LED casing, a brushed aluminium neck and an adjustable arm. An early stage example, but one that shows promise.

“The case study is part of our on-going research into the online data mining of consumer views,” said Professor Su.
 
“It shows how the use of big data can help customise consumer preferences into the product development process, helping determine important design decisions to meet customer needs more accurately.”

Note - This research is based on the outcome of a collaboration with industrial partners supported by EU FP7 and Eco-innovation projects.

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