Unlocking User Data Feedback: A Case Study on Insurance and Energy Journeys

Author: Pavithra Aravindan

In a recent talk by Paul Izod, a UX/UI designer at Compare the Market, he dives into the nuances of sourcing user data from third-party organizations, focusing on the context in which this data is presented back to users. You can watch the full discussion here.

Contextual Differences in UX Journeys

Izod examines two different user journeys through their product offerings: home insurance and energy switching. Both journeys appear similar at first glance but yield significantly different feedback from users. This highlights the importance of understanding user context and how it influences their experience.

Home Insurance Journey:

• Involves long forms requiring substantial user input, typically demographics or property details. Users can recall much of this information easily.
• Implemented data sourcing from third-party bodies to pre-fill forms, resulting in 38 participants providing overwhelmingly positive feedback.
• Key Metrics:
  • 95% of users felt it was a convenience.
  • Minimal privacy concerns were raised, with only 8% worried about data validity.

Energy Switching Journey:

• This journey contains fewer questions, yet requires specific numeric details (e.g., kilowatt-hours), which users often do not know offhand.
• Initial user testing with 48 participants yielded a negative reaction from 29% when they saw their data presented.
• Key Metrics:
  • 66% didn’t understand what kilowatt-hours represented.
  • 8% felt their privacy was invaded.

Permission Dynamics

Izod experimented with user permission during the energy journey to explore if explicit consent changed perceptions. After modifying the prototype to include a consent checkbox, results showed a slight improvement. However:

• 95% of users gave permission, but 17.5% still had a negative experience upon data sourcing.
• Only 5% were able to accurately identify what information would be sourced.

This highlights a critical insight: merely acquiring user permission does not guarantee positive user reception.

Revising the Approach

Izod further iterated on the design:

• Converted the checkbox to a clear yes/no toggle emphasizing what data would be sourced.
• Offered contextual information and reassurances via an FAQ to alleviate fears about information usage.

The revised design resulted in 83% of participants feeling secure about the data sourcing, and notably, 100% of those who accepted the data felt positively about it. This contrasts starkly with earlier feedback.

Comparative Insights

1. Precedents Matter: Users had prior experience with data sourcing in home insurance, setting an expectation that lessened anxiety. In contrast, the energy market is still establishing these norms.

2. Perceptual Context: The perception of what data means is crucial. For home insurance, users viewed the data as property-related, whereas for energy usage, it felt deeply personal—touching upon their habits and behaviors.

3. Giving Control: Users appreciate control over their data. Despite some users opting out, they engaged in manual entries, suggesting they don’t oppose inputting data; they object to its sourcing.

4. Clear Communication: Ensuring users understand what they are consenting to is vital. Misalignment between expectations and actual experiences can lead to negative reactions.

Implications for UX Practice

This case study presents critical lessons for UX designers:

• Contextual understanding is essential when dealing with user data. Tailor your approach to the specific user journey’s context and data type.
• Forecast possible negative responses by being aware of industry norms and data perceptions.
• Always prioritize transparency in how user data is sourced and utilized. Informative communication can mitigate privacy concerns.
• Incorporate user preferences through explicit options and effectively communicate expectations.

This detailed analysis of the disparities in user responses based on context serves as a foundational case for UX practitioners focusing on data usage in their product designs. Understanding and addressing these disparities can significantly enhance user satisfaction and trust.