Halfway to the finish line—

In approaching our end-of-semester presentation, we wanted to offer an opportunity to our clients at PNC to react to our design direction. In order to best serve our clients, our design intervention addressed the insights from our research with the overall objective of reducing the total number of phone calls made by clients to PNC’s treasury management client care team.

From our analysis of the call data, we had a clear goal in mind - to better support users to perform accounting tasks in PINACLE on their own by teaching them how to use the tool more effectively.

Through our ideation and concept validation process, we realized that we were considering both heuristic changes and flow overhauls. Therefore, in our presentation, we presented our selections in terms of micro and macro design interventions.

On the micro level, we could augment the PINACLE user experience through heuristics and tweaking features. We posit that small changes could make a big difference in supporting accountants’ use of the portal.

On the macro level, we introduce novel omnichannel experiences to disrupt current user flow with new features. These interventions present opportunities for proactively equipping users with tools to give them more autonomy and confidence.

Many of our micro design concepts are not groundbreaking; rather, they are established design patterns that we think could lead to increased user autonomy and understanding of the tools within PINACLE. Designing for these features to be included in the platform, we can enhance users’ experience without changing the core flow of PINACLE Express or PINACLE Commercial (demo).

Wizards
“Captcha” understanding checks
Daily tips
Version control
Undo function for transfer actions
“Syntax check” for batch preparation
Plain text translation (numbers into letters)

From a macro perspective, we envision disruptions to the user flow in PINACLE through our proposed, novel, omnichannel experiences. In this case, these interventions are not limited to specific tasks that might be performed in PINACLE; rather, the macro level design interventions respond to the need for flexibility and confidence-building that our user research indicates.

Faceted NLP search
Practice Mode
Human + bot chat
Shopping cart

We delivered our presentation to an audience of our clients, our faculty, and our peers. Because the majority of the people in the room did not come from an accounting background, we spent time contextualizing the corporate banking space, as well as introducing our personas and other design artifacts that we referenced throughout our process. Our presentation touched on our research process and ideation work and introduced our design directions and possibilities to our audience, walking through macro and micro design approach possibilities.

Our presentation was met with a high level of engagement from our clients. After our pitch, they joined us for an ideation session in which we reflected on our work thus far and looked forward into the summer. While the possibilities that we presented in our slide deck were not off base, together we worked with our client to build out a better model of what we're actually trying to do: effectively surface data to PINACLE users in order to ease their burden of use and more effectively perform their jobs, reducing the number of calls made to PNC’s treasury management client care.

We built and tested multiple, divergent designs before reaching our final concept.

For the first round of testing of our PINACLE support UX, our concept was still in flux and we A/B tested four different paper prototypes with PINACLE users to learn more about how a design intervention might enable or disrupt their flow.

We choose to do paper prototyping for two reasons. First of all, the flexibility of paper allowed our designs to take a lower fidelity form without it distracting users, as nothing was truly clickable. Secondly, in our Wizard of Oz-ed experience, we made use of the multi-modality of paper by inquiring about the allocation and flexibility of space on the screen of our different design interventions. Paper proved to be much more flexible with testing the dragging elements than its digital counterparts.

We built several divergent interface prototypes, including a chatbot for issue resolution; an NLP-driven global search bar; a module that slid onto the screen to provide help; and a drag-and-drop wizard. We also asked each user to co-design a chat or search interface in order to better understand how these tools might be most useful.

From our user tests on paper, we learned a lot about how user workflows might be augmented or disrupted through our design proposals.

Trial and error is not only the default way of learning how to use a new tool; it's preferred.

Users frame their problems in terms of actions, using tasks and verbs to express discrete challenges.

Use of screen real estate should enable flow through flexibility and modularity.

In our next iterations, we designed in response to what we learned from our paper-based user tests. We built prototypes in InVision that followed linear user flows and proceeded to test them with users both in person and online through UserTesting.com. Each prototype had a clear machine learning component to them: parsing out text to auto-fill forms to help initiate payments, providing suggestions, and providing help documentation based on user (in)activity.

Some friction is good, but too much treads on efficiency.

Contextual, step-by-step information alongside the relevant actions is most valuable to users.

Users are reticent to make use of search functions because their own expectations are not well-defined.

From this testing, we were able to eliminate several features from our possible user experience. Within our target audience, text-entry-based interfaces are seen as time-intensive and less likely to be integrated into users’ workflows. That is not to say that they (in particular, chat) are not worthwhile endeavors for our client; rather, they are not solving the problem we are focusing on, the improved user learning experience of PINACLE.

The insights we synthesized from our early rounds of user testing helped us to focus on what users want, and we proceeded to build out more robust interaction flows that integrated desirable and impactful features, continuing to test and iterate until we produced our final design concept.