Understanding users needs and expectations
Our partner Independer is the largest digital comparison and advice platform in the Netherlands for insurance and banking products, mortgages and energy. I worked as part of the iptiQ team, a global InsurTech providing digital insurance platforms, underwriting capabilities and life and non-life insurance products.
For a brand-new household insurance product we had to create a landing page (LP). In the first iteration, this was linked to Independer aggregator where the insurance was sold. In the second stage, instead of being linked with only an aggregator, the user could also go through the sales journey on the Mintley website.
UX Designer, UX Researcher
Jun 2022- Jun 2023
Card Sorting, Interviews, Empathy Mapping, Affinity Mapping, Mid-fi, Hi-Fi wireframing.
UXTweak, Miro, Figma, Mouseflow, Tableau, Confluence.
UX designer (Me), a UX researcher, a content writer, a project manager, marketing, data analysts, and engineering team.
To better understand past and current behaviours, needs, and expectations of our users in general regarding insurance landing pages.
We decided to approach this by triangulating data from card sorting, interviews and data analysis from Tableau and Mouseflow.
Interview:
Card Sorting:
Interviews insights are organised in an affinity diagram to identify patterns and themes in the data
Clustered insights into an empathy map to understand users' needs, pain points and external facts that affect their decisions/behaviour.
The card sorting analysis allowed us to understand the distribution of cards across standardised categories with a higher percentage of agreement.
Based on the card sorting and interview findings we created an LP structure template. Explanation of Main Outcomes
This helped us to take into account different areas and not just needs as there are factors around them that also affect how they interact with it and what they expect. We analysed pains and gains, what type of actions they take to solve them and what we should do to address the different pain points.
We triangulated the information from analytics, interviews and card sorting. Based on the users' needs we defined each section needed to focus on specific users’ priorities, needs and expectations we uncovered in the research. This was used as starting point in the solution definition when we did a competitor analysis and started wireframing ideas. The goal with this template is to be able to reuse it and validate it (via a survey) for different stakeholders, markets and partners.
First I conducted a semantic differential workshop with stakeholders. A semantic differential is a tool for measuring users' perception on designs, brands or images. It consist on a scale of usually 7 options between two opposite adjectives. I decided to use this tool for the following reasons:
Then I created a brand library. At iptiQ, we create white-label products that can easily adapt their look to fit any brand by using a design system of components, which are like building blocks. Each component has parameters that stay the same across all brands and variables that change and adapt for each brand, called design tokens. These design tokens are stored, maintained, and shared in the Brand Library to ensure brand consistency throughout all products and to streamline the process of building, maintaining, and scaling products with their design system. Design tokens also allow for flexibility in making changes and scaling quickly and effectively.
I conducted a desk research analysing how our competitors have addressed the needs of our our target audience by sections. This provided me with valuable insights into best practices, as well as areas that could be improved. I was able to identify opportunities for innovation and differentiation that can enable our company to stand out from the competition.
The next step was to create several sketches and mid-fidelity wireframes. I created each section covering each of the users needs uncovered in the research and ordered based in the card sorting results. Those iterations were carefully reviewed and analysed with the input of various stakeholders, including the engineering team, to ensure technical feasibility and timely delivery of a minimum viable product (MVP).
We used too many categories and cards in the card sorting so it was more difficult to have significant percentages of agreement.
Even if we got many good ideas on how to solve the problem we prioritised simpler designs to achieve the launch on the expected date. We aim to iterate and learn from its performance.
As a new brand, we needed to put more effort into building confidence and building trust in users. It was difficult to provide the right trust-building elements.
This comparison was done taking the average data of other partner LPs:
Engagement:
150% higher
Visit time:
Increased from 40s to 2minutes
We need to analyse this data carefully as was taken two months after it launched and it was just linked with the aggregator. This means users actively searched online for the brand (as is new in the dutch market) and they were interested in getting to know more about it.
