Insurance Landing Page

Understanding users needs and expectations

Check IMPLEMENTED designs

Context

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.

Challenges

  1. Users need a quick, positive overview of a brand before continuing their sales journey
  2. Uncover what's the best Information Architecture for our Landing Pages to fit user's needs and expectations
  3. Deliver a Hi-Fi to our partner before the deadline, the LP couldn't be too difficult to implement as needed to be delivered in short period of time.
  4. Built trust on users for a new brand in the competitive dutch insurance market
  5. Our first Dutch landing page launch involved understanding unique user needs and expectations for this new market for us.

Summary

Role

UX Designer, UX Researcher

Timeline

Jun 2022- Jun 2023

Methods

Card Sorting, Interviews, Empathy Mapping, Affinity Mapping, Mid-fi, Hi-Fi wireframing.

Tools

UXTweak, Miro, Figma, Mouseflow, Tableau, Confluence.

Team

UX designer (Me), a UX researcher, a content writer, a project manager, marketing, data analysts, and engineering team.

Defining the problem

Research Planning

Goal

To better understand past and current behaviours, needs, and expectations of our users in general regarding insurance landing pages.

Methodology

We decided to approach this by triangulating data from card sorting, interviews and data analysis from Tableau and Mouseflow.

  1. Data analysis: We started analysing data we already own as video recordings, information about engagement time, time per visit, most clicked sections, etc and performance data of our current LPs for other partners to better understand users’ behaviours.
  2. Interviews: We conducted 10 interviews with dutch people to understand the needs and expectations of the users.
  3. Card sorting: We sent out a card sorting exercise to 20 participants to understand what users want and expect to see in the LP and what’s more important for them.
Hypothesis

Interview:

  1. Users with a good relationship & good previous experience with their current insurance won't be interested in switching.
  2. Users that visit our LP are already interested in switching and looking actively for other companies.
  3. Users will get to the LP via organic search after seeing it on the aggregator to know more about the brand and understand if it’s trustworthy.
  4. Most people need more than 2 touch points

Card Sorting:

  1. Users need to trust in the insurance company
  2. Users want to know what's the added value of the company
  3. Users want to know how to switch insurances

Research Process Overview

Main Outcomes

Empathy Map

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.

Landing Page Template

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.

Finding the solution

Design process overview

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:

  1. It helped me to reach a common agreement  between stakeholders about the brand personality.
  2. It set the declaration of intent at the beginning of the visual design phase.
  3. It worked as a guide and reference to keep designs and visual aspects close to this agreed personality.

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).

Final Hi-Fi

Designs were handed over to the development team with documentation for guidance.

Conclusion

Main learnings

📚 Card Sorting

We used too many categories and cards in the card sorting so it was more difficult to have significant percentages of agreement.

⏳ Time constrains

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.

🤝 Focus on trust

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.