37 Free Monitoring Dashboard Report Templates and Examples (Data Studio, Power BI, Tableau, Google Sheets, Excel)

What is a monitoring dashboard?

Use a monitoring dashboard to track daily marketing performance and catch unusual changes. Compare sessions, key events, ad spend, and leads with their typical levels to see when something is off. Each morning, marketing leads and analysts can check the dashboard, then drill into the channel, campaign, or page behind any unexpected movement.

The templates on this page are built for marketing and sales monitoring, not server or network monitoring. Windsor.ai brings data from 350+ sources, including GA4 and HubSpot, into Data Studio, Power BI, Tableau, Excel, and Google Sheets.

Which monitoring dashboard template to pick

The table lists all 37 templates in this gallery, grouped by data source. Google renamed Looker Studio back to Data Studio in April 2026, but some template pages still say Looker Studio.

Monitoring dashboard example: daily GA4 sessions against a same-weekday baseline

This example uses Windsor.ai’s GA4 property for Q3 2026 (1 July to 30 September) in the Google Sheets GA4 Report template. It adds one tab that compares each day with the same weekday in the previous four weeks and flags the days that differ by more than 25%.

Step 1: Connect GA4. Sign in at onboard.windsor.ai, choose the GA4 connector, and select your property.

Step 2: Load the template. Copy the Google Sheets GA4 Report template. Install the Windsor.ai extension for Google Sheets. In Windsor.ai, choose Google Sheets as the destination. Copy your API key from that page. In the sheet, click Login in the extension and enter your API key. Then click Get Data into Sheet to run the template’s GA4 query.

Start the date range four weeks before the first day you want to check, because the baseline needs those weeks. For Q3, that means loading 3 June to 30 September. The Windsor.ai field for GA4 key events is conversions.

Step 3: Add a daily check tab. Put one row per day with sessions (column C), engaged sessions, and key events. Add three columns: Baseline in G, Change vs. baseline in H, and Alert in I. Cell B3 holds the alert threshold (25%).

A same-weekday baseline matters because weekend traffic is lower. On windsor.ai, an average weekend day in July and August had 50% of the sessions of an average weekday.

In July and August, every day stayed within 12% of its baseline, so the check raised no alerts. In September, it flagged 20 days. The first two were Saturday 5 and Sunday 6 September. On Thursday 3 September, sessions were 12.5% above baseline, below the threshold. Saturday 5 September gained about the same number of sessions, but its weekend baseline was half the size, so the change was +26.4%.

Step 4: Split the flagged days by source. Pull sessions by source and medium for the flagged days and for the same weekdays four weeks earlier, then divide each source’s increase by the total increase. This example compares 21 to 24 September with 24 to 27 August.

Sessions from chatgpt.com and claude.ai brought 43% of the increase. Their share of daily sessions rose from 1.9% on 8 September to 10.3% on 9 September, and to 24.2% on 21 to 24 September.

Sessions returning from Google’s sign-in page (accounts.google.com) rose in the same weeks. These are visitors coming back after signing in with Google. Add accounts.google.com to the list of unwanted referrals in GA4 to keep those sessions under the source that brought them. The engagement rate stayed above its same-weekday baseline on 18 of the 20 flagged days. On 21 to 24 September, 71% of chatgpt.com sessions were engaged, against 62% for the whole site on the same days.

The alerts stopped on 27 September because the baseline now averaged the higher September weeks. From 27 to 30 September, sessions stayed above the same weekdays in late August but within 25% of the baseline. When a change lasts, note the date it started (the first week of September here) and compare later weeks with the weeks before that date.

The numbers show a stable site for two months, then a lasting rise in sessions from early September, and AI assistant referrals brought 43% of the increase from 21 to 24 September. The Google Sheets GA4 Report template shows the same daily sessions and engagement rate, split by source and medium.

What KPIs does a monitoring dashboard track?

Track these metrics every day, each next to its usual level. Windsor.ai pulls the fields from the source; calculate the baselines and changes in the dashboard.

• Change vs. baseline: the day’s value divided by the average of the same weekday in the previous four weeks, minus 1. Set the alert threshold above the usual day-to-day change. In the example above, 25% raised no alerts in two normal months.
• Engagement rate: engaged sessions divided by sessions. A jump in sessions with a falling engagement rate points to bots or broken tracking.
• Key events per session: key events divided by sessions, to see whether extra visits also bring sign-ups or purchases.
• Share of sessions by source: each source’s sessions divided by all sessions. A new source with a growing share shows where a change comes from.
• (not set) share: sessions GA4 couldn’t assign to a source, divided by all sessions. A rising share points to a tagging or consent problem.
• Spend vs. baseline: daily ad spend divided by the average of the same weekday in the previous four weeks, minus 1, for the templates that include ad platforms.
• Change in new contacts and deals: for HubSpot templates, new contacts and deals this week divided by the average of the previous four weeks, minus 1, with contacts by lifecycle stage and deals by deal stage.
• Net follower change: new followers minus lost followers per day, for Instagram and Facebook Page templates.

What to include in a monitoring report

A monitoring report shows which metrics moved outside their usual range, when the change started, and which source, campaign, or page explains it.

Keep the same layout every day so readers know where each number is. Split the data by date, source and medium, campaign, landing page and device.

For example, a marketing lead’s daily report could show sessions, engagement rate, and key events at the top, with each metric compared against its baseline. Next, include an eight-week trend chart with the baseline and a table highlighting flagged days and the three sources that changed most. Finish with the latest complete day available in GA4, noting that daily figures can take 24 to 48 hours to settle.

Browse the full template gallery for dashboards by platform and tool, or see the GA4 dashboard templates for reports built on GA4 alone. How to use Windsor.ai for web analytics shows how to ask an AI assistant which channels and pages changed.