How to Build an AI Business Dashboard in Bubble.io
A dashboard that only shows numbers is half a dashboard. A dashboard with AI-generated narrative tells you what the numbers mean and what to do about them. This guide shows you how to build a complete business intelligence dashboard in Bubble.io with AI interpretation built in.
What You Will Build
The metrics layer
The foundation of the dashboard: structured data tables in Bubble.io storing your key metrics with timestamps. Revenue (daily, weekly, monthly), new leads (by source), active clients (count and health score distribution), team utilisation (billable hours vs capacity), and any other metrics critical to your business. Data flows in from your connected systems via Make.com — accounting software, CRM, project management tool — updated on the appropriate schedule (daily for financial metrics, real-time for operational metrics).
The AI interpretation layer
On top of the metrics layer, a daily AI analysis workflow passes the current metrics with their historical context to Claude. The output: a narrative interpretation of each metric area (what moved, by how much, vs what benchmark, and the likely reason), flagged anomalies (anything outside expected range requiring attention), and weekly recommendations (the 2 to 3 actions most likely to improve the metrics that need it). Stored in Bubble and displayed alongside the metrics — numbers and meaning together.
The alert layer
Proactive notifications when metrics cross defined thresholds — delivered to Slack, email, or SMS before the executive checks the dashboard. Critical alerts (metric more than 30% outside expected range), warning alerts (metric trending wrong direction for 3+ days), and positive alerts (metric achieved a milestone worth celebrating). The alert layer ensures the dashboard drives action rather than just providing information to those who remember to look.
Step by Step in Bubble.io
Design your database structure
Create three main data types. MetricRecord: metric_name (text), value (number), period_type (text: daily/weekly/monthly), period_date (date), source (text). AIAnalysis: analysis_date (date), metric_area (text), narrative (text), anomalies (text), recommendations (text). Alert: alert_date (date), alert_type (text: critical/warning/positive), metric_name (text), message (text), acknowledged (yes/no). This structure stores all metrics historically, all AI analyses by date, and all alerts with acknowledgment tracking.
Build the data ingestion workflows
Create Make.com scenarios for each data source. Xero/QuickBooks: daily at 7am, retrieve previous day’s revenue and expense totals, store as MetricRecord entries. GoHighLevel: daily at 7am, retrieve new contacts created yesterday, leads by source, and pipeline values, store as MetricRecord entries. Bubble project database: daily at 7am, calculate team utilisation rate (billable hours logged vs capacity hours), store as MetricRecord. Each scenario runs automatically — no manual data entry. By the time the team arrives, all yesterday’s metrics are already in the dashboard.
Build the AI analysis workflow
A daily Bubble scheduled workflow runs at 7:30am (after data ingestion completes). For each metric area (financial, sales, operations), retrieve the past 30 days of MetricRecord data. Pass to Claude: Analyse the following metrics for [company name] for [date]. Current period vs 7-day average vs 30-day average: [data]. Generate: a 2-sentence narrative for each metric area (what is notable today), any anomalies (values more than 15% outside the 7-day average with likely explanation), and the top 2 recommended actions based on today’s data. Store the response as an AIAnalysis record. Display on the dashboard below the metric charts.
Build the dashboard UI
Design the dashboard page in Bubble with: a header showing today’s date and a one-line AI summary of overall business health (pulled from the latest AIAnalysis record), metric cards showing current value + trend arrow + comparison to target for each key metric, a chart section showing 30-day trends (Bubble’s built-in chart element or an integrated Recharts library via Plugin), an AI insights panel displaying today’s narrative, anomalies, and recommendations (formatted as readable paragraphs, not raw data), and an alerts section showing any unacknowledged alerts with one-click acknowledgment. Role-based access — executives see the full dashboard; team leads see their relevant metric area only.
Connect alerts to Slack and email
A Make.com scenario monitors the Alert data type in Bubble. When a new critical Alert is created: send a Slack message to the #business-alerts channel with the metric name, the current value, the expected range, and the AI’s suggested reason. Send an email to the metric owner with the same information plus the link to the full dashboard. For warning alerts: Slack only, no email. For positive alerts: Slack with a celebratory tone. Alerts ensure the dashboard informs action proactively rather than reactively.
How do I handle metrics from systems without API access?
Some older systems or local software do not have APIs. For these, build a manual data entry workflow in your Bubble dashboard: a simple form where a team member enters the metric values for the day. To encourage consistency, add a daily reminder (automated email or Slack message) reminding the relevant person to enter the data. Over time, as you upgrade systems, replace manual entry with API-based ingestion. Start with the highest-value metrics even if some require manual entry — an imperfect dashboard you actually use beats a perfect specification you never build.
Should the dashboard be accessible on mobile?
Yes — build the dashboard as mobile-responsive from the start. Executives often check business performance outside of office hours and on mobile devices. Bubble’s responsive engine handles most of the mobile layout automatically if you use Bubble’s responsive layout settings correctly. Test on both desktop and mobile during the build phase. The AI narrative panels are particularly important on mobile — summary text that fits a phone screen is more useful than charts that require pinching and zooming.
Want Your Business Dashboard Built in Bubble.io?
SA Solutions builds custom Bubble.io business intelligence dashboards with AI interpretation, automated data ingestion, alert systems, and role-based access — giving your leadership team real-time visibility with context.
