Weflip is an online energy comparison site launched by the GoCo Group, designed to help customers save money by switching to better energy deals. Initially contracted to prototype, design, and develop the front-end for its launch, I returned multiple times to help define its future through ongoing discovery and prototyping. Similar to my work on GoCompare, my focus was to improve conversion, increasing user retention and enhance personalisation. Additionally, I explored options to increase market share through the integration of AI and voice recognition technologies.
Weflip was launched in just 10 weeks. In a sprint against time, I designed, prototyped and developed the front end, aligning it for a successful product launch. As with any product comparison site, the objective was conversion. My particular focus was on the journey, ensuring the interface was intuitive, user-friendly, and required minimal effort from users to convert. Information was structured to encourage users to progress and encourage engagement; with trust elements strategically used at expected pain points.
I used detailed Axure prototypes with conditional logic to illustrate functionality, closely replicating the desired end product. This approach streamlined the sign-off process and significantly accelerated the development cycle.
Drop me an emailWeflip UI designs: Information and user journey
Weflip mobile UI designs: Conversion rates for mobile in Fintech are traditionally lower so Weflip adopts a mobile first approach.
Weflip UI designs: account dashboard, preferences and settings.
Beyond user retention and personalisation, my other focus at Weflip was to explore and prototype alternative methods from the current to improve conversion and increase market share. This included developing prototypes to demonstrate how tech such as voice recognition could potentially streamline the completion of question sets; as this would make the process quicker and more convenient for users to switch energy providers.
Within this, I also looked at how leveraging datasets could be used to gather customer information to again reduce the effort involved.
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