CRU Online

CRU is a business intelligence company, and they have an online platform which subscribers use to access articles and data about commodities based on research and expert knowledge from analysts.

Outcomes

45%  increase in platform use

New product features to help increase platform subscriptions

Small screen engagement increased

Improved internal workflows to cut production costs

GenAI pilot Product Strategy and Design

How can we bring subscribers back to the platform?

  • Many users were relying on information sent them in email communications
  • Editorial teams needed improvements to their workflows
  • Analysts needed a better search experience for finding key intelligence

Research and User Journeys

By looking at analytics I could see that users had a hard time searching and navigating the platform to find the information that they needed (articles or the latest relevant data).

From interviews and customer feedback data I also learnt that user journeys were not optimal for finding content, and there was a lot of extra ‘noise’ in the form of updates and notifications. So I drafted some proposals for better user journeys.

User journey flows

Redesigning the Content Model and IA

The platform was suffering from Information Architecture that was a manifestation of the way customers were subscribing to services – not how they expected to find and use content and data. Content was being siloed in a strict hierarchy in the site, with a lot of cross publishing and duplication.

Therefore I proposed to ‘flip’ the model upside down to allow more flexible ways to find and organise content.

Content model whiteboard

Content Strategy

I also identified the need to codify and implement a content strategy. I explained that this was needed to support:

  • Successful IA and design
  • A more efficient and effective workflow for internal teams
  • Getting essential content to users at the right times

I engaged with our client develop a formalised content strategy. This can be a daunting task, but by explaining what content strategy means and then breaking it down into a stepped process I helped the content team to start to build out a clear strategy for what content to publish, how, who it was for and what need each type of content was serving.

My main learning from working on this is that it takes time, but you have to start somewhere.

Prototyping user journeys

I worked with stakeholders and users to validate a wireframe prototype to communicate what the experience of navigating the site would be like.

Wireframes

Business Goals and Metrics

To formulate a good analytics strategy, I set out a brief guide and rationale for what was needed from a UX perspective. This included revisiting the major business goals and thinking about:

  • People – who will manage, interpret and most importantly take actions with data
  • Process  – the process of report and alert distribution
  • Tools – choosing the right analytics tools and integrating the data
  • Measures – information overload is the challenge – finding the right measures to use in dashboards, alerts and for optimisation is needed to get the most from analytics

I then took the HEART analytics framework from Google Ventures and linked each aspect with the business goals, what signals to use and the metrics that we would then be able to measure desired business outcomes.

Usability Testing

I was also looking to bake in usability testing into our sprints, so that we would get early feedback from users, and get some early seeds growing for platform champions and changing the client mindset to a user-centred one. I also wanted to have usability testing and research as part of adding new features and services to the platform as the product matures.

Design system and Agile build

Following all this work I then worked with a visual designer to create a new visual identity and UI patterns and components for the platform. I wanted the engineering team to feel fully involved, so they joined us through the design process, and together we produced all the assets and specifications they would need to implement the new UI.

After the initial design phase was completed, I took on the role of breaking out, managing and expanding the Design System and working with our developers to optimise consistency and accessibility.

Dashboard and data cards design

New product features that I am proud of are the design of commodity dashboards and data cards.

I worked closely with the client to research ideas, I then also ran some user research sessions to uncover what information clients need regularly at a glance. We co-created dashboard wireframes which we then workshopped with the whole team to make sure that all necessary content could be delivered.

That allowed me to design some scalable, interactive dashboards and data cards that would become a big selling point for new subscriptions.

Dashboard

Introducing GenAI into the platform

CRU knew from customer feedback that a key priority for many users was the ability to get summaries of analyst research, as customers often have limited time to get information to support their needs.

So they wanted to launch a GenAI pilot where users could ask questions around commodities research. The model would be trained on a limited dataset, so we could gauge the quality of responses returned.

My process

To support the initiative I took ownership of the PRD from the start, to make sure that we were clear about the customer needs, aims and scope of the project. I needed to coordinate and collaborate on the UX with the main stakeholders, a third party company doing all the AI model training and our development team.

Then I began to mockup some quick wireframe prototypes to get agreement on the UX for the pilot features. Following that I could work with our Frontend Engineers to assemble the interface using our design system. I tried to make the UX/UI as simple as possible for the pilot because:

  • The real objective was to test and assess the quality of the responses
  • We had a very tight deadline
  • We already have well-recognised interaction models for GenAI that users are familiar with

The pilot is now undergoing testing and validation with clients and internal analysts.


Posted

in

by

Tags: