How We Customized User Experiences To Increase Client Retention

If users lack confidence in a system’s recommendations and tools, they can’t make informed decisions. Creating tailored dashboards and contextual workflows encouraged users to engage with the system, which improved retention rates.

Role: Design Director

AT A GLANCE:

increase in engagement identified during user testing

25%

The Challenge

Prescient AI’s original optimizer platform catered primarily to campaign managers. It struggled to offer customized recommendations and actionable insights to its users with diverse roles and vastly different needs. Users' lack of trust in the system’s tools limited their ability to make informed decisions, creating inefficiency, which reduced the platform's perceived value. We saw an opportunity to balance the tactical demands of daily campaign managers with the strategic needs of high-level executives.

The original Optimizer relied on users entering a series of inputs before returning any recommendations. This was an opportunity to passively deliver budget recommendations to the user’s dashboard on a regular basis.

“My team has 5 people, and we generate 60 percent of the revenue for the entire company. I'm not comfortable taking a recommendation at face value.”

— A Marketing Manager when reviewing existing tools

The Fix

As Director of Design, I know transparency is key and clarity builds trust in AI-driven tools. When interviewing users across workflows, feedback highlighted the need for clarity in "Forecasting and Recommendations." This prompted my team to optimize ad spend and customize navigation and features to better serve each user's needs. We partnered with engineering to implement AI-driven features, such as personalized dashboards, visual aids, and forecasting tools.

Whiteboarding sessions with users and the product team led to clear feedback and product direction.

Venn diagram with three overlapping circles labeled Strategize, Optimize, and Collaborate, illustrating user role intersections.

Our research identified that the three main users, Marketing Agencies, Tactical Managers, and Executive Leaders, often overlapped in their responsibilities.

Defining new schemas and taxonomies helped architect the new user experience.

“It’s hard to pull out small optimizations manually, but these recommendations make it easier to decide what to focus on … You guys knocked it out of the park.”

— Stephen, Head of Advertisement, E-Commece

The Results

Beta testing revealed that clear navigation, new dashboards, and user-driven recommendation tools would lead to a 25% increase in engagement with performance analysis tools. Users reported improved confidence in making optimization decisions, enhancing daily and weekly retention.

This new approach focuses on jobs for each of our archetypes.