Reputation Analytics Dashboard

About the Project

After delivering two key MVP features for the Review Response and Boost product at Loyal (see case study here), I recognized the need to track their success metrics. To address this and showcase the value of these features, I designed a dashboard that helps clients monitor their performance in review response and boost.

MY ROLE

I collaborated with a PM, an engineering manager, a data analyst, and several engineers to design and implement the dashboard in Power BI, later turning it into a standardized process adopted across the company.

IMPACT

The dashboard allowed users to easily monitor their reputation and clearly see the impact they could achieve using Loyal’s product, significantly enhancing the product’s competitiveness in the market and increasing the sales pipeline.

Overview

There are two key MVP features for the Review Response and Boost product:

Through client meetings and discussions with the sales team, I recognized that reporting and analytics was an immediate need following the delivery of the two MVP features. Customers not only rely heavily on analytics to track and report their performance in ratings and reviews, but they also want to understand the impact of using our product. Providing robust analytics was essential for making our product competitive in the market.

Understanding Users

The dashboard was mainly helpful for marketing leads or reputation management leads who oversee high-level insights and trends regarding the health system’s reputation.

USER GOALS

From conversations with sales and prospects, I identified that users primarily need the dashboard to:

• Monitor the performance of their listings with respect to ratings and reviews
• Measure and showcase the impact of their work
• Analyze areas for future improvements

Gathering Data

SUCCESS METRICS

To ensure alignment, I worked closely with my PM to define the key success metrics for both the product and healthcare marketing teams.

BRAINSTORMING

Based on the success metrics and user goals, I started brainstorming potential data to display to users. I focused on five key types of data that I believed would be most relevant to their needs:

I listed all potential data points and their implications, then worked with my PM to narrow down the scope. Keeping both business and user goals in mind, I was cautious in considering the factors influencing each data point and selected data that accurately reflected the value delivered by each feature.

Achieving full alignment was challenging with just text descriptions of each metric, so I secured basic alignment on the data to include and decided to finalize the scope after adding visualizations to better facilitate collaboration with my team.

Visualizing Data

After aligning with my PM on the basic scope for the data in the dashboard, I began creating visualizations for each data point. I carefully selected the chart types to ensure the data could be interpreted easily and accurately, without introducing bias.

Once the charts were created, I used the visualizations to further align with my PM and collaborated with engineers to gather additional input and feedback.

Wireframe

After iterating based on team feedback and getting full alignment on the data to include, I started to design the layout of the dashboard.

Design

Implementing Dashboard in Power BI

DESIGN HANDOFF

After finalizing the design, I compiled a comprehensive document detailing each data point, how it is calculated, how to interpret, and its potential implications for the user. Since the data analyst was not familiar with the product, this documentation, along with my walkthrough of the product and dashboard design, were crucial to ensure accurate extraction and calculation of the data.

NAVIGATING TECHNICAL CONSTRAINTS

While the data analyst was implementing the dashboard, I held several working sessions with her to address technical constraints of Power BI. We collaborated closely to develop alternative solutions and iterate on the design, aiming to preserve the intended user experience as much as possible.

Outcome

The Power BI dashboard received a lot of positive feedback from both clients and prospects, significantly contributing to the product’s sales enablement. Additionally, the process and insights I documented and shared for collaborating with data analysts on Power BI dashboards were adopted by other designers for future projects.

Beyond this Dashboard

In addition to this dashboard, I collaborated with a data analyst to develop two more dashboards: one for listing management and one for service recovery. I also created a comprehensive dashboard that consolidates data from multiple sources across products. Feel free to ask if you’d like to learn more about any of these projects.