Alerts Feature UX Research

Overview

As the Pricing Data platform transitioned away from Informagic, I began exploring the opportunity to redesign Alerts. Without initial direction or support from our Product Managers, I took the initiative to investigate whether Alerts were still relevant and valuable to clients. At the same time, my UX colleague working on Home Lending, another product at Curinos, identified a related challenge, as clients needed to log into the platform and manually search for data to stay informed, adding friction to their workflow.

Starting from a shared hypothesis that proactive notifications could improve efficiency and client engagement, I conducted a deep dive into the existing Alerts experience within Pricing Data, identified usability issues, and tested concepts directly with clients. Together with my colleague, we went through two iterations of wireframes, synthesized findings across both platforms, and developed an initial Product Requirements Document (PRD) that defined minimum viable product (MVP) requirements grounded in research, discovery, and client testing.

The challenges

We’re solving for 2 core challenges.

  1. Users struggle to stay informed about key market shifts without logging into the platform.

  2. Existing alerts are generic, cluttered, and often ignored leading to disengagement and missed opportunities for action.

Here are some of the experiences of alerts currently in Pricing Data and Home Lending.

The problem

We are solving the issue of discoverability, accessibility, and usability of market data. The goal is to provide timely, digestible, and actionable updates in a format that matches user needs and behavior.

The benefits

  • Receive timely summaries/statistic changes of key market shifts via email

  • Access visual cues for easier interpretation of insights

  • Customize delivery and content preferences

  • Drill down into insights via the platform

  • Download raw data for deeper analysis

  • Share with other colleagues

The goals

  • Enable users to stay updated on market trends without needing to log in daily

  • Empower users to personalize how and what insights they receive

  • Drive platform engagement through timely and valuable insights

  • Reduce friction in accessing raw data and deep analysis

  • Provide exposure on different types of insights for users

The success metrics

  1. Email Engagement

  2. Platform Engagement

  3. User Efficiency & Satisfaction

Our hypothesized solution

We are proposing a progressive solution that delivers timely, personalized, and visually intuitive insights through both email and platform experiences, tailored to the needs of different user types.

Research and early lessons

The purpose of the initial research phase was to reach out to clients from both products and interview them about existing alerts and how they manually gather data for themselves.

We tested with a wide range of external clients to capture different perspectives:

  • Tier 1 bank - Tier 3 banks

  • Analysts to Senior Vice Presidents

The main focus of our interviews was to consolidate feedback in relation to these categories:

  • Usage of alerts

  • Pain points (alerts vs. no alerts)

  • What is missing?

  • Future Opportunities

Pain points

  • Customize what specific alerts they want to see and dive deeper if interested to see more

  • Share functionality/see same alerts as everyone else

  • Better sorting that is consistent on platform and on email

  • Better way to showcase data

  • Lack of proactive change notifications

  • Manual reporting workflows

  • Information overload vs. actionability gap

We learned asking abstract questions wasn’t enough.

Overall the initial research phase gave us limited but enough feedback to create an interim Product Requirement Document in collaboration with the Product Management team.

From there, UX moved forward with our design thinking processes to help design the wireframes.

UX thinking quadrant

  1. First, we explored ideas visually with mood boards.

  2. Then, we mapped user flows to understand behavior and potential placement for alerts.

  3. Next, we sketched low-fidelity wireframes to test structure.

  4. Finally, we iterated towards polished low-fidelity wireframes to test with clients.

Each step was informed by research and brought us closer to what out clients could interact with.

With our polished wireframes in hand, we went back to clients for a second round of feedback. While Home Lending provided initial insights, the second round focused exclusively on Pricing Data, where client feedback directly helped shape our preliminary requirements.

Feedback loop → design iterations

In the testing phase, I included both internal and external clients to ensure all stakeholders were represented. There was a wide range of clients in each vertical from the Pricing Data platform:

  • Deposit Rates

  • Deposit Fees

  • Retail Lending

I wanted to see if the wireframes had clear feedback patterns and to validate which parts of the design were complimented and which needed refinement.

After 11 hours of recording from our UX testing sessions, I went back to listen and took notes specifically on:

  • Quotes from clients

  • Pain points

  • Recommendations

  • Must haves/nice to haves

  • Not applicable to client

What’s next for UX?

UX will continue testing, measuring adoption, and refining designs. This illustrates that UX is a continuous learning process and is always iterating to meet real clients needs.

From there, one of our Senior Product Managers will be finalizing design requirements needed for the MVP designs and then we will be shepherding designs through development so the value of UX is carried out through production.

Low fidelity wireframes

Here are some wireframe iterations we designed to provide visuals for our client testing.

High fidelity designs

Here are some conceptual high-fidelity designs that includes color.