Proactive Customer Health Dashboard.

A predictive customer health dashboard that unifies sales and service data in Tableau Next, helping account managers to proactively identify at-risk accounts and take targeted action to reduce churn.

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Inspiration

Our inspiration came from a critical, universal business problem: customer churn. We realized that in most companies, sales and customer service teams work in silos. Sales doesn't know about a customer's urgent support tickets, and service doesn't know if a customer's sales activity has suddenly stopped. This communication gap means at-risk customers go unnoticed until it's too late. We were inspired to build a single source of truth—a unified dashboard that bridges this gap and empowers teams to be proactive, not reactive, in retaining their most valuable customers.

What it does

The Proactive Customer Health Dashboard is a command center for account managers. It uses Tableau Next to connect directly to Salesforce data and visualizes the two most critical leading indicators of customer churn:

High-Priority Support Cases: It instantly flags which accounts have the most urgent, unresolved issues, allowing managers to intervene and ensure problems are being solved.

Customer Inactivity: It tracks the number of months since an account's last closed deal, immediately identifying customers who are becoming disengaged.

By presenting these two key risk factors side-by-side on a single, clean dashboard, the solution gives managers an at-a-glance, actionable priority list to focus their retention efforts where they will have the most impact.

How we built it

We built this solution entirely within the Tableau Next and Salesforce ecosystem, embracing the challenge of a low-code/no-code approach.

We started by connecting Tableau Next directly to our provisioned Salesforce org, establishing relationships between the Account, Case, and Opportunity objects to create a unified data model.

Inside the Tableau visualization editor, we created two powerful calculated fields to quantify our key risk factors: Open High-Priority Cases and Months Since Last Activity.

We then built two separate, clear visualizations (horizontal bar charts) to display each risk factor, sorted to show the highest-risk accounts at the top.

Finally, we combined these visualizations into a single, cohesive "Proactive Customer Health Dashboard," designing it for maximum clarity and immediate, actionable insight.

Challenges we ran into

Our biggest challenge was navigating the specific technical constraints of the hackathon's Tableau Next environment. We initially tried to build a single, complex "Health Score" calculation directly in the Semantic Model but ran into persistent aggregation and data type errors. This forced us to pivot our entire strategy. We overcame this by radically simplifying our approach—creating the calculated fields inside the visualization editor, which was more flexible. This challenge ultimately led to a better, clearer final product that focused on distinct risk factors instead of a single, abstract score.

Accomplishments that we're proud of

We are incredibly proud of successfully building a high-impact, business-critical solution in such a short amount of time using a 100% no-code approach. Our greatest accomplishment was turning our biggest technical challenge into a strategic advantage. Pivoting from a complex, single-score model to a cleaner, multi-factor "Risk Factor Dashboard" resulted in a final design that is more intuitive, actionable, and valuable for a real-world business user. We are also proud of the final dashboard's design, which tells a clear and compelling story at a single glance.

What we learned

This hackathon was a deep dive into the power and intricacies of the Tableau Next platform. We learned that the key to a successful data project isn't always complexity; it's clarity. We also learned the critical importance of adapting our strategy when faced with technical hurdles. Our journey of debugging the Semantic Model taught us invaluable lessons about Tableau's aggregation logic and the importance of choosing the right place (Semantic Model vs. Visualization Editor) to build calculations. Most importantly, we learned that a well-designed dashboard can transform raw data into a powerful tool for making proactive, money-saving business decisions.

What's next for Proactive Customer Health Dashboard

The future of this dashboard is all about automation and deeper insights. The next steps would be:

Slack Integration: Create automated Slack alerts that instantly notify an account manager when one of their customers appears on the dashboard (e.g., "Warning: Account ABC now has 3 open high-priority cases").

Adding More Risk Factors: Integrate data from Salesforce Data Cloud to track product usage metrics, such as "days since last login," adding a third, powerful predictor of churn.

Actionable Buttons: Embed "Tableau Actions" directly into the dashboard, allowing a manager to click a button next to an at-risk account to instantly create a "Follow Up" task or send an email from within Tableau.

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