Research Fellow
Capturing consumers’ attention is tougher than ever for businesses.
Computer scientists at Queen Mary University of London created an AI-driven tool that ensures designers and marketers create visual communications with instant impact on consumers.
Over 50 of the world’s biggest companies use Dragonfly AI to create evidence-based designs for product packaging and adverts.
Products supported by Dragonfly AI have benefited from increases in on-shelf attention by up to 45%, and sales uplifts worth hundreds of thousands of dollars.
The tool further cuts the length of the creative design process in half and its costs by up to 40%.
The attention economy has never been more competitive. Every day, we are confronted by thousands of images and messages, online and offline. Businesses invest heavily in design and marketing in the hope that their products will hook our interest amidst this intense noise.
Back in 2009, Professor Peter W McOwan (School of Electronic Engineering and Computer Science) was working on software that analysed how humans process visual information.
A fortunate encounter with a marketer opened his eyes to the value of the research for designers. Together with Dr Hamit Soyel, he translated their fundamental know-how into a support tool for designers, Dragonfly AI. Since its launch in 2018, creative professionals have used the tool to create designs that appeal to consumers, instantly.
Dragonfly AI’s story begins in 2009 when McOwan developed 'spot the difference' software to analyse how humans process visual information. Together with Soyel in 2011, McOwan first applied this fundamental research to robots to give them human-inspired visual skills.
But, after meeting a marketer at their Science Museum presentation in 2013, the team learned their work could have a very different outlet: visual communications.
McOwan, who sadly passed away in 2019, and Soyel built on their earlier research to refine the algorithm that now underpins Dragonfly AI. The algorithm reveals what people will notice most within a design, and what they will miss. Extensive testing with users ensures the algorithm produces reliable, actionable insights.
McOwan and Soyel co-founded a spinout business in 2018 to market Dragonfly AI. The tool is driven by a patented algorithm based on their knowledge of how humans process visual information.
Dragonfly AI’s scientific basis takes the guesswork out of design processes, allowing designers to create, with confidence, clear and digestible visual communications that stand out on the shop shelf or webpage.
It provides instant feedback on designs and guides decisions on:
Feedback from Dragonfly AI’s customers reveals that the tool’s instant insights cut creative production and testing cycles by up to 50%. Traditional design processes can take 4-6 months.
They further cut the costs of testing designs by up to 40% by reducing the need for expensive studies, such as focus group consultations and eye-tracking tests. A traditional testing cycle costs $30,000 -70,000.
Creatives and marketing teams in over 50 of the world’s biggest consumer product companies, including Unilever, Danone and Coca-Cola, use Dragonfly AI to steer their packaging and advert designs.
Feedback from Dragonfly AI’s customers reveals that consumers now pay more attention to their products on shop shelves and e-commerce platforms like Amazon. One global frozen food brand reports a 45% increase in on-shelf attention across their top three product lines after using the design support tool.
And the increased attention translates into stronger sales. One global household brand saw a $300,000+ sales uplift by improving their visual presence on the shop shelf. Another forecasts a sales lift of $440,000-500,000 on Amazon after tailoring their packaging design for the platform.
Dragonfly AI’s basis in fundamental human visual processing makes it particularly valuable for global brands as its insights apply across different cultures and markets.
For Soyel, his foundational research in human visual processing, and the algorithm that followed, has immense potential beyond marketing.
Future uses could include:
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