2024
Brief:
Pollenize are a nonprofit working to protect honey bees. They challenged us - along with DEFRA who manage invasive species - to create a solution to halt the influx of Asian hornets, an invasive species to the UK and a major predator to honey bees.
Lead Product Designer, 90% remote
Role:
Activities:
Conducting user research with beekeepers and relevant SMEs, and the public, defining the user experience and flow of the app, building and maintaining the design system, UI design, user testing, iteration, marketing materials
Background
The Asian hornet poses an increasing threat to UK biodiversity, with sightings rising year on year since it was first found in the UK in 2016. There were 73 confirmed sightings in 2023.
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The Asian hornet is listed as an invasive species, meaning there is an existing mechanism in place to report potential sightings. This involves submitting a photo of the insect via the Asian Hornet Watch app which is then forwarded to a team of experts who independently review each report.
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20,000 images were submitted last year.
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99% of these were false reports.
The problem
There are a vast number of wasp, bee and hoverfly species native to the UK, and it can be difficult to distinguish between them without an expert eye.
The current process does not allow for quick identification, which is crucial to track down and destroy nests, and this provided an ideal use case for the application of emerging technology.
The solution
A mobile app that:
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Utilises AI to identify Asian hornets in seconds with a 98% success rate
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Integrates with Pollenize’s NestSweeper device – an Asian hornet attractant vaporiser which lures Asian hornets in to feed, providing the opportunity to capture a photograph
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Provides a scalable solution that can cope with the antipated increase in Asian hornet in the UK
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Allows experts at DEFRA to focus on eradication in the field rather than identification at a desk
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Maintains user engagement by visualising sightings in real-time via map feature
My role
I was the Lead Product Designer for this project, managing the end-to-end process from organising and conducting research and interviews, to delivering UI designs and working with engineers to implement them. Another product designer joined to support me during research and user testing.
To provide structure to the project, we followed the double diamond framework.
What I delivered
User research
The team at Pollenize are well connected in the world of beekeeping, so they provided a list of SMEs from DEFRA, the National Beekeeping Unit and APHA as well as a group of passionate beekeepers who could all provide useful insight into the Asian hornet problem and the impact on honey bee colonies.
I arranged interviews over Teams with all participants, wrote interview guides and conducted the interviews with support from 2 team members. Each call last around 45 minutes with a lead interviewer and notetaker, and all notes were documented in Mural. Once the interviews were wrapped up we synthesised the research down and generated key insights: this is where we uncovered the extent of the problem in terms of scale.
We also determined some key principles for the solution to ensure its suitability for usage in the field. For example:
1. Beekeepers often tend to be wearing gloves that might be sticky, so any solution would need to have minimal amount of touch points to account for this.
2. Apiaries can be located in remote areas without good signal or wifi, so the solution would need have the option to report sightings retrospectively.
Interview notes
As-is journey map
Journey mapping
To provide context and visualise the insights, I created personas and mapped out the as-is process for reporting Asian hornet sightings, clearly highlighting key pain points and opportunities. These assets provided a key mechanism in playing back the research.
Feature ideation
I designed and ran a workshop with the wider team along with the co-founders of Pollenize, to play back the user research and insights, with the aim of moving the project into the develop phase. We concluded the workshop with an ideation session to outline potential features that would solve key pain points.
Feature ideation
Feature prioritisation
Feature prioritisation
Following the workshop I worked closely with the product owner and engineering lead to prioritise features based on value and complexity. We then arrange the features across the MoSCoW framework. Key features that made the cut include quick camera access, a map to visualise sightings and a detailed report form to enable more detailed information around sightings - key for finding nests.
To-be journey and app navigation
Once the key features were agreed, I created a to-be journey and app flow to validate our thinking with the guys at Pollenize, after some minor iteration, these were shared with the engineering team so create alignment on what we were building. During this time the engineering team had been focussing on the AI model, so this was the first time the front-end experience have been discussed with them in detail.
To-be journey
App navigation flow
Design system
Design System
I set to work with UI tasks, first setting up the project in Figma and adding the design system. NestSweeper is a sub brand of Pollenize, and having previously worked on another Pollenize project, I had already set up the design system in Figma, so this was a case of setting up the NestSweeper logos and adding any new components and assets to the library as and when.
UI designs
I then began to design the individual UI components, starting with low fidelity outlines before adding elements of the Pollenize/NestSweeper brand. I also continued to add relevant components and icons to the design system.
Feature ideation
Design system
Content design
With the support of a junior colleague, we curated accurate information on Asian hornets and created a guide on the best way to capture images of them. Once we completed a first draft we sent the copy to our research SMEs for review.
User testing
I designed and ran individual user testing sessions with the research group. We conducted a mix of A/B testing, content review exercises and questioning on the app flow to ensure we collated useful feedback for iteration.
Feature ideation
Figma
Dev handover
Once user testing and iteration was complete, we handed the UI designs over to the engineers. I worked with them on any queries they had and worked with them to iron out any wrinkles in the flow.
Marketing Materials
I then concluded the project by creating app store visuals and packaging all research material and visuals into polished decks to achieve the final deliverables to Pollenize and DEFRA, and also for the wider team for playback and demo activities. I also wrote an article for the external Capgemini website, and a detailed case study for our internal teams website.
Marketing materials
Conclusion
The project has gained a lot of attention within Capgemini, already being showcased at innovation days in Portugal, The Netherlands and France. The app is available to download now and the project was also picked up by Wired just as we kicked off.
Download NestSweeper in the Apple app store here or Google Play store here
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