Mable ‘Support Provider’ Journey and Support teams

Client
Mable
Scale-up product company in disability and aged care

Timeline
Ongoing 12 weeks and 6 weeks

Role
Service design (50%), User Research (50%), mostly working independently

Regular collaborators
Other designers, product managers from 3 squads, data analytics and product designers

Stakeholders
Chief Design Officer, Chief product officer, decision makers from Marketing, Operations and Support

Delivered as two separate projects:

  • Customer journey map

  • Conceptual models of delivery care teams

  • Insights and recommendations of tested assumptions

  • Behavioural archetypes

Background

Mable experienced a period of rapid growth and VC funding investment. During this time, they were looking for new initiatives to build the business and therefore had scaled the teams up from 50 to 200 in 12 months. The north-star metric used by the business is ‘hours of delivered care’

Mable is a two-sided marketplace connecting support seekers (demand) to support workers (supply). The support provider was so far considered secondary with primary focus on clients.

There was a supply gap and high demand for skilled support workers. The business had noted customer pain points and losses due to not finding right level of care along with other issues.

The business had a strategic opportunity to now focus on the Support provider as an equally important user. This would solve problems for both the supply and demand side of the marketplace

Focussing question 1

How might we see the Support Provider as an integral partner of our business, develop better relationships and give them the best user experience?

The solution

A baseline customer journey map that helps the business understand how their service experience is delivered today

Mable were looking to the Service Design team to suggest what to tackle next in order to use the funding to improve their metrics for ‘delivered care’ so we did journey maps for all different types of users. I led and delivered the Support worker/provider journey map.

Key needs of the journey mapping visual

Show the end to end journey from acquisition, onboarding, use, retention and exit

Baseline the current experience to compare current versus future improvements

Show all the various paths a user may take to reach a goal at every stage

Map touchpoints like emails, phonecalls, app features and periodic notifications sent to users

Make it easy to understand for the business at every level (C-suite to lowest level squad member

Derive opportunities for new features, or redesign of existing processes/features

Work in progress visual of journey mapping in Miro

  1. Creating a skeleton map based on assumed knowledge

  2. Working through previous research, Confluence documentation and experiencing first-hand app flows

  3. Workshopping with tenured colleagues in the design team familiar with the user journeys

  4. Workshopping with squads such as product, marketing, support

  5. Iterating on the map with evidence based ideas shared from around the business

  6. Getting help from visual designer to help create an appealing pattern library and file layout.

The process to create the journey map

Helping the whole business navigate their way using this map

Support provider Journey map

  • End to end customer journey including goals, needs, actions, processes, touch-points, pains and gains and opportunity areas. The service design team helped the new teams use this map as follows:

  • Product squad ownership meant squads could take information from this and build and improve features focussing on quantifying the highest impact pain points, partnering with Data Analytics team.

  • Marketing team used this to focus on the steps for acquisition and retention of customers using targeted content and notifications.

  • Operations team used this to understand where support was required and helped improve their processes for onboarding verifications, retention and safety.

Impact of journey map and precursor to project 2:

  • Due to this journey map, our team received further engagement from squads to do more service blueprint work as extension of journey maps.

  • One of the squads had ideas for delivering team-based care and they wanted to explore this further using service design methods so that they could build a case for this.

  • While there was resistance due to ignorance of service design research tools, I came up with the plan to help them elaborate on their idea as business model, going beyond just product-features and UI functionality.

  • This approach and outcomes are explained below.

Focussing question 2

How might we create new models of care with multi-disciplinary teams for Support seekers with complex needs?

The approach

Concept testing “models” of team-based care delivery with both user groups (seekers and providers)

The situation

Switching the business model from one-on-one support to group support would greatly change the underlying technology, requiring investment.

The squads mostly have experience in testing features through 5 x users testing or UI feature testing and don’t know how to test desirability of the idea

Previous workshops and ideation sessions failed to clarify product-market fit, resulting in low confidence from the C-suite.

Designing the research for “Support Provider teams”

I undertook these steps to design the desirability testing for this idea by employing skills of service design discovery.

Service Blueprinting

Map the conceptual service blueprint of support provider(SP) teams to understand tech and background processes, partnering with Engineering

➜

Riskiest Assumption Mapping

Facilitate an assumption mapping activity with Product, Engineering and Design to know what low-confidence and high risk Assumptions to test

➜

Creating testable hypotheses

Create business models and experience concepts as visuals with provocations from Assumptions

➜

Recruit from both user groups (provider and seeker of support) specifically non-Mable customers to negate bias of known product.

Test with ‘potential’ customers

Service Blueprint

User Research

1:1 interviews

  • 60 min videocall interviews

  • 5 x support workers and 5 x support seekers who were caregivers.

  • Combination of contextual inquiry and concept testing.

  • Conversation led by participant

  • Encouraged blue sky thinking by keeping script loose

Material to test

  • Tested the business models of care delivery with both user groups to develop them. Shown as cards one by one.

  • Probing, 5 Whys.

  • Building on ideas with the customer (a form of co-design)

  • Deeper understanding of customer context - needs, environment and difficulties.

Delivered Actionable Insights

  • 6x Behavioural archetypes of an ‘ideal customer profile’ to target/not to target for further research and testing

  • 10+ Riskiest Assumptions proven false or true and ‘why’ and further direction on what else to test.

  • Connecting insights to projects in other parts of the business and starting LEAN canvases to initiate projects from high confidence ideas to know feasibility and viability

  • Now, Next, Later as desirability roadmap

Impact

  • Teaching the design team and product team a new way to test ideas besides A/B and usability testing features +50%

  • Researcher’s ‘point of view’ as an independent of single squad’s metrics but looking across the board improving inter-squad communication by +20%

  • Nailing true quick wins (low effort, high impact) for the squads to action. 5x small changes that were easy to action were implemented as front-end content tweaks.

Design impact

Business Impact

  • +30% confidence in pursuing the right ideas and putting others on the back-burner on the roadmaps or killing them. Helped product managers and engineers grasp the complexities of solutions needed for users with challenging needs that were currently not fulfilled by the platform

  • +25% Ability to communicate with C-suite with clarity for business cases using this as real-world research

  • +25% Business reducing overlap and wasted funding in initiatives based on this research by consolidating certain initiatives.

  • Inter-squad collaboration was improved. 2 key insights were taken up by squad working on machine-learning algorithms to further their exploration.

  • 1 key insight used by human-in-the-loop matching project for complex needs clients.