Citizen Modelled Data

UX Case Study: Enhancing Demographic Data Management in EngagementHQ

Product

Engagement HQ is an all-in-one digital engagement platform trusted by 1000+ Government organisations across local, state, and federal governments in Australia, New Zealand, the United Kingdom, and Canada. 

At its core, Engagement HQ is a Content Management System that hosts a set of data collection tools that can be analysed and reported on to aid in making more informed governance decisions. 

Research

Analysis workshop

Journey map

User flows

I facilitated a discovery workshop with our customer success team to analyse customer feedback & product analytics. 

  • Users were finding it difficult to ascertain deeper insights into their community engagements. 

  • Users were confused regarding how to handle the updating of their sign up form questions without breaking previous engagements and their reports. 

  • Citizens were choosing to skip data-gathering questions within the signup form. 

  • Citizens were abandoning signing up all together and not taking part in the consultation. 

I created a journey map to illustrate a high level view of the users overall experience.

I created user flows for:

  • Onboarding

  • Signup

  • Reporting

To highlight and identify any further pain points related to the core issue.

Quantitive analysis

Demographic data-point type and formatting analysis

User interviews

Armed with findings gained from the discovery work I wrote and conducted user interviews with 10 active users to help get a deeper understanding of their pinpoints, organisation structures and processes. I also wanted to ascertain what were the core data points users wanted from citizens to analyse and report against.

Citizen use test

I designed a use test to take citizens through the onboarding process of an affected citizen sign-up flow to help understand their pain points.

Persona creation

During the interviews I asked persona questions to help form a clear picture of the different types of users and their responsibilities, processes and place in the organisation.

Information architecture

I mapped out the information architecture to show that there are different data point types being used and due to their variance, they should be structured differently.

Demographic research

I researched the different demographic formatting options used in the markets EHQ was sold in to learn if there were any variances we should be aware of when designing solutions.  

Research findings

All signup form questions asked during onboarding are custom worded and custom formatted.

  • The answers to the onboarding questions are what users can filter against when analysing their engagement data. 

  • The user that initially authors the sign-up form questions when onboarding onto EngagementHQ is rarely the user creating and managing individual engagements. 

  • In lieu of having functionality that allows users to ask engagement-specific questions to citizens, users have been adding these question types to the general onboarding questions, blowing out the IA for filtering and analysis and making reporting convoluted. 

  • These core demographic questions were the most commonly asked questions among all users.

    • Age

    • Gender

    • Location

    • Ethnicity

  • The formatting of the core demographic questions was inconsistent from user to user.

  • If a user deletes a signup form question. All previous reports that relied on that data to filter and analyse will break. 

  • Users wanted analysing and reporting to be less convoluted at a base level, and they wanted the ability to ask more granular questions of their citizens when necessary. 

  • Citizens were apprehensive about the length of the signup forms. They commonly stated that they felt like they were giving away too much and getting too little. 

  • Citizens mistrusted forms/organisations that seemed to ask too many focused questions during onboarding. They reported ‘not being sure’ as to why all the data was needed for the task they wanted to complete. 

Problem definition

The initial implementation of citizen onboarding was designed too broadly. The decision to enable and expect the user to define their own signup questions and their formatting whilst not providing any education on the topic nor another avenue to collect data points of a different type has led to the convolution of the signup form as well as the filtering when analysing and reporting. This heightens the learning curve for users whilst creating too many variances from user group to user group for the Customer Support Team to manage.

This ultimately leads to shallow insights, leading to poorer governance decisions and, eventually, market share loss. 

Solution

Signup form

Implement the set of core demographic questions as static questions with specific formatting for the users region. 

This will:

  • Shorten the signup flow

  • It will give all users a consistent database of core demographic data points against which to analyse. 

  • Relieve customer support.

  • Improve citizen engagement

Include informative, educational content for the citizen at the time of signing up to educate them on the benefits of providing your demographic details. 

Reporting

Redesign the analysis and reporting filtering to allow for two sets of data points (core demographics & engagement specific) to be used to gain further insights into your engagements.

Engagement specific data

Provide functionality for users to be able to collect engagement specific citizen data points from a more apt juncture in the customer journey.

Considerations

Progressive rollout

To achieve the solution in its entirety, a new database needs to be developed, which will take time. To progress efficiently, the engagement-specific data section was rolled out in stages. 

Stage 1

Separate the core demographic questions from the engagement-specific questions within the signup form settings and the reporting filtering options. Allow functionality to show/hide these question types as they may be legacy in nature, but deleting them will break legacy reports that may still need to be referenced.

State 2

Begin a new project to examine the best way to implement engagement-specific questions at the tool level.

Design system

New designs must adhere to the new Design System, and any new patterns, etc., need to be developed, approved, and added to the component library before the project is finalised. 

Future work

Implement engagement specific questions  at a tool level.

Goals

Reduce support calls regarding the sign-up form and reporting by 33% over 6 months from completion.

  • Decrease Citizen abandonment of the Signup form by 25% over 6 months from completion.

  • Increase use of reporting by 12.5% over 6 months from completion.

Design/Testing

Prototype - Lofi

User testing

  • Signup form page (user)

  • Reporting/Analysis filtering (user)

  • Signup form (citizen)

I performed two sets of user tests against all prototypes.

Users—I tested the user prototypes against 10 active users. The design passed, though there was still a little confusion regarding the placement and use of the engagement-specific questions at Stage 1. This was to be expected, as the IA at this stage isn’t optimal or intuitive. 

Citizens - I tested the prototype against 5 active users.

Component design

The Citizen sign-up form had to be resigned to match the new Design Systems pattern of ‘Progressive Disclosure”. 

Prototype - Hifi

Signup form page (user)

Reporting/Analysis filtering (user)

Signup form (citizen)

Planning, Documentation & Hand-off

I worked collaboratively with the Product and Development teams to document and hand off the designs to the developers to be broken up into workable sprints.