UX Design

Improving Enquiry Type Selection at MTVH

Role

Sole UX Designer responsible for the end-to-end design process, from user research and workshops to wireframing, prototyping, and usability testing.

Duration

3 Months

Tools

Figma, Miro, Confluence, Jira

Overview

Redesign Enquiry Type Case Management Tool to reduce complexity for staff by simplifying enquiry choices, while improving the accuracy of data captured in Salesforce to enhance service delivery and reporting

Problem
  1. The system contained 188 enquiry types, which was overwhelming and unclear for staff.

  2. 60% of cases were logged under the “General” category, leading to inaccurate reporting and poor data integrity.

  3. Poor case management handling caused inconsistencies in how enquiries were tracked and resolved.

  4. Locating the correct enquiry type in Salesforce was slow and inefficient, adding friction to staff workflows.

Project Goals

Goals were grouped into three key areas to ensure both efficiency in daily workflows and reliability in data for strategic decision-making.

Clarity

Consolidate and remove unnecessary enquiry types. Redesign webforms to be intuitive and user-friendly.

Efficiency

Improve Salesforce CRM usability to reduce time and errors in case handling. Streamline the process of locating and selecting enquiry types.

Accuracy

Ensure enquiry types are accurately mapped to Salesforce. Enhance reporting to help managers track and identify trends.

To understand why staff were struggling to select the right enquiry types in Salesforce,I conducted two types of research to understand the issue:

  1. Data Review an Analysis :Over a year’s worth of CRM reporting data was analysed to uncover patterns and pain points in how enquiry types were being used.
  2. Workshops with agents: Led workshop sessions with Homeownership and Lettings teams to identify UX and operational pain points
Solution / Recommendation

Based on data analysis and user insights, I drafted UX recommendations that included removing unused enquiry types, improving layout and search, and introducing clear categorisation.

I presented these to the Product Manager and Head of Digital, gaining buy-in to move forward into the ideation phase.

Card Sorting to Define Information Architecture

Using Miro, I conducted an open card sorting exercise with five users , including frontline agents and managers, to understand how staff naturally grouped enquiry types. Each user was assigned a board with 188 enquiry types and the flexibility to create groups based on their options.

Best practise and Landscape Analysis

To validate and inspire best practices, I also conducted a landscape analysis of companies like Tesco, Argos, and Amazon to study how these organisations structure and surface support enquiries or help topics.
I also documented UX best practices around enquiry selection, data capture, and case handover.

Userflows and Low Fidelity Wireframes

Using findings from the card sort, best practices and landscape analysis, I mapped out userflows and  sketched low-fidelity concepts to rethink how users select enquiry types in the CRM.

I presented my design concept in a stakeholder workshop and facilitated a collaborative ideation workshop in Miro to ascertain technical feasibility, co-generate new ideas and prioritise features based on feasibility and impact.

High Fidelity Wireframes
  1. Removed “General Enquiry” and introducing a clearer fallback option.
  2. Grouped enquiry types into categories for easier navigation.
  3. Aligned the layout with Salesforce UI components to support integration.
Usability tests

Tested designs with agents who confirmed the new structure was clearer but highlighted that the two-step model added time. Adjustments were made to balance simplicity and speed and re-tested.

Results
Challenges
  1. Salesforce constraints limited UI flexibility, making it difficult to fully implement a seamless step-by-step experience.
  2. Simplifying the enquiry list without losing important detail was a constant balancing act, as some teams needed more specificity.
  3. Webforms often didn’t align with backend enquiry types, which caused confusion and required frequent manual corrections.