The UX Metrics Dashboard Template Every Team Needs (+ Free Download)

Most analytics dashboards tell you what happened. Pageviews went up. Bounce rate went down. Sessions are flat. None of that tells you why — or more importantly, what to do about it.

A UX metrics dashboard is different. It connects behavior signals (rage clicks, scroll depth, form abandonment) to outcome signals (conversion rate, revenue per session, churn) so you can see the chain from user experience to business impact. When a metric moves, you know where to look.

This template covers 25 metrics across five categories. The downloadable CSV is formatted to import directly into Google Sheets or Notion — just paste in your numbers each week.

How to Use This Dashboard

The dashboard is designed for a weekly review cadence:

1. Monday: Pull current values from your analytics stack
2. Tuesday: Flag anything outside benchmark range
3. Wednesday: Trace flagged metrics to specific pages or user segments
4. Thursday–Friday: Run one experiment based on findings

One dashboard, one experiment per week. That cadence compounds. Teams that run 50 UX experiments a year consistently beat teams running 5, regardless of resources.

Category 1: Engagement Metrics

These tell you whether users are actually paying attention to your content.

| Metric | Formula | Benchmark | Tool | |--------|---------|-----------|------| | Average scroll depth | Avg % of page scrolled per session | 50–65% | Heatmap tool | | Time on page | Total time / sessions (excluding bounces) | 2–4 min for articles | GA4 | | Pages per session | Total pageviews / total sessions | 2–3 | GA4 | | Return visit rate | Sessions from returning users / total sessions | 20–35% | GA4 | | Content engagement rate | Sessions where user scrolled >50% OR spent >30s | 40–60% | GA4 |

What to watch for: Scroll depth below 40% on long-form content pages suggests the content isn't earning attention — usually a structure problem (the lead paragraph doesn't deliver on the headline) or a layout problem (page signals it's longer than it is). Time on page below 90 seconds on anything over 800 words is a red flag.

Segment this by:

• Device type (mobile users scroll less — that's expected, but the gap shouldn't be enormous)
• Traffic source (paid traffic often has worse engagement metrics — they landed on a page without intent)
• New vs returning visitors

Category 2: Behavior Signals

These come from heatmaps and session recordings. They're the "why" behind the engagement numbers.

| Metric | Formula | Benchmark | Tool | |--------|---------|-----------|------| | Click-through rate on primary CTA | Clicks on CTA / sessions on that page | 2–8% | Heatmap tool | | Rage click rate | Sessions with ≥3 rapid clicks on one element / total sessions | <0.5% | Session recording | | Dead click rate | Clicks on non-interactive elements / total clicks | <5% | Session recording | | Form start rate | Sessions where user clicked into a form field / sessions with form visible | 30–60% | Session recording | | Form completion rate | Form submissions / form starts | 50–75% | Analytics + form tool | | Form abandonment by field | Drop rate per field | First 2 fields: <10% | Session recording |

What to watch for: A rage click rate above 0.5% usually points to a specific element — a button that doesn't respond, a link that goes nowhere, or a filter that doesn't update the page immediately. Session recordings let you isolate the exact element. Fix one element at a time and track whether the rate drops.

Form abandonment by field is one of the highest-signal metrics you can track. A field where 40% of users start typing and then stop is telling you something specific: the field label is confusing, the validation requirement is unexpected, or there's a friction point (e.g., requiring a phone number that users don't want to give).

Segment this by:

• Page type (product pages vs landing pages have very different CTA CTR baselines)
• Traffic source (organic search visitors often have higher intent than social)

Category 3: Conversion Metrics

These connect UX to revenue. They're where the business case for UX investment gets made.

| Metric | Formula | Benchmark | Tool | |--------|---------|-----------|------| | Overall conversion rate | Conversions / sessions | 1–4% (varies enormously by industry) | GA4 | | Micro-conversion rate | Micro-conversions (email signup, PDF download, etc.) / sessions | 2–8% | GA4 | | Funnel completion rate by step | Users completing each step / users starting funnel | 60–80% per step | GA4 | | Funnel drop-off by step | Users leaving at each step / users entering that step | Goal: <30% per step | GA4 | | Revenue per session | Total revenue / total sessions | Depends on AOV and CVR | GA4 (e-commerce) |

What to watch for: Funnel drop-off by step is the single most actionable conversion metric. If 70% of users make it through step 1 but only 30% make it through step 2, you have a specific, bounded problem to solve. Compare a session recording filter of "users who dropped at step 2" against "users who completed step 2" — the behavioral differences are usually obvious.

A micro-conversion rate below 2% on a content site usually means the lead magnet isn't relevant enough to the content around it, or it's not visible enough. A heatmap will tell you whether users are even scrolling to the opt-in placement.

Segment this by:

• Traffic source (this is where ROI calculations live — if paid traffic converts at 0.5% and organic at 3%, your paid strategy has a problem)
• Device type (mobile conversion rates are typically 30–60% lower than desktop for most industries)

Category 4: Navigation and Site Health

These identify structural problems — pages users leave from, paths that dead-end, search behavior that reveals missing content.

| Metric | Formula | Benchmark | Tool | |--------|---------|-----------|------| | Exit rate by page | Exits / sessions on that page | Homepage <30%, articles <50% | GA4 | | Bounce rate by traffic source | Single-page sessions / sessions by source | Varies by channel | GA4 | | Site search usage rate | Sessions with search / total sessions | >5% suggests nav problems | GA4 | | Top site search queries | Count of searches per query | — | GA4 | | 404 rate | 404 sessions / total sessions | <0.5% | GA4 + server logs |

What to watch for: Site search usage above 5% almost always indicates a navigation problem — users can't find what they're looking for through the menus and resort to search. The specific queries tell you what's missing or mislabeled. If "pricing" is your top search query, your pricing page is either buried or missing from the nav.

Top exit pages that aren't obvious endpoints (checkout confirmation, thank you pages) need investigation. Pull session recordings filtered to "exit on this page" and watch three sessions. The pattern is usually immediately clear.

Segment this by:

• New vs returning (returning users who use site search often signal they remember something exists but can't find it)

Category 5: Technical Performance

Slow pages create UX problems that no amount of copy or design optimization can fix. These belong in the same dashboard as behavior metrics.

| Metric | Formula | Benchmark | Tool | |--------|---------|-----------|------| | Largest Contentful Paint (LCP) | Time until largest visible element renders | <2.5s (Good), <4s (Needs improvement) | Lighthouse / CrUX | | Cumulative Layout Shift (CLS) | Sum of unexpected layout shift scores | <0.1 (Good), <0.25 (Needs improvement) | Lighthouse / CrUX | | Interaction to Next Paint (INP) | 75th percentile interaction response time | <200ms (Good) | CrUX | | Mobile vs desktop LCP delta | Mobile LCP / Desktop LCP | <2× — if mobile is 3× slower, investigate | Lighthouse |

What to watch for: LCP above 4 seconds reliably correlates with higher bounce rates — users leave before the page finishes loading. The most common culprits are unoptimized hero images, third-party scripts (including some analytics and heatmap tools) loading synchronously, or slow server response times.

CLS above 0.1 causes visible layout jumps that trigger rage clicks — a user clicks a button that moves the instant they tap it, and the click lands on something else. This is a common source of rage click alerts in session recordings. Fix the layout stability first, then check if rage click rates drop.

The Full Dashboard in One Table

| Category | Metric | Your Value | Benchmark | Status | |----------|--------|------------|-----------|--------| | Engagement | Average scroll depth | | 50–65% | | | Engagement | Time on page | | 2–4 min | | | Engagement | Pages per session | | 2–3 | | | Engagement | Return visit rate | | 20–35% | | | Engagement | Content engagement rate | | 40–60% | | | Behavior | CTA click-through rate | | 2–8% | | | Behavior | Rage click rate | | <0.5% | | | Behavior | Dead click rate | | <5% | | | Behavior | Form start rate | | 30–60% | | | Behavior | Form completion rate | | 50–75% | | | Behavior | Form abandon by field | | <10%/field | | | Conversion | Overall conversion rate | | 1–4% | | | Conversion | Micro-conversion rate | | 2–8% | | | Conversion | Funnel completion by step | | 60–80%/step | | | Conversion | Funnel drop-off by step | | <30%/step | | | Conversion | Revenue per session | | — | | | Navigation | Exit rate by page | | <30–50% | | | Navigation | Bounce rate by source | | — | | | Navigation | Site search usage rate | | <5% | | | Navigation | Top search queries | | — | | | Navigation | 404 rate | | <0.5% | | | Performance | LCP | | <2.5s | | | Performance | CLS | | <0.1 | | | Performance | INP | | <200ms | | | Performance | Mobile vs desktop LCP delta | | <2× | |

Setting Up Your Dashboard in Google Sheets

1. Download the CSV template — ux-metrics-dashboard-template.csv
2. Open Google Sheets → File → Import → Upload the CSV
3. Add a "Week" column with ISO date format (2026-05-16) so you can chart trends over time
4. Add conditional formatting to the Status column: green if within benchmark, amber if borderline, red if outside

For a Notion setup, paste the full table above into a Notion database and add a "Status" property with ✅ / ⚠️ / ❌ options.

Connecting Behavior to Outcomes: A Quick Workflow

The most useful thing you can do with this dashboard is trace a behavior metric to an outcome metric in both directions:

When a conversion metric drops:

1. Filter session recordings to sessions from the previous week that did not convert
2. Look for rage clicks, dead clicks, or form abandonment on the conversion page
3. Check scroll depth on the page — are users reaching the CTA?
4. Fix the highest-signal behavior issue first, then re-check the conversion metric

When a behavior signal spikes:

1. Identify the page and element (heatmap + rage click report)
2. Check whether the exit rate on that page has changed
3. Watch 5 session recordings filtered to "rage click on [element]"
4. Fix the element, deploy, and track the rage click rate over the next 7 days

Tools That Power This Dashboard

You'll need data from three places to fill in all 25 metrics:

• Google Analytics 4 — engagement, conversion, navigation, and session-level data
• Core Web Vitals / CrUX — performance metrics (Google Search Console → Core Web Vitals report)
• Heatmap and session recording tool — behavior signals (scroll depth, rage clicks, CTA CTR, form abandonment)

For the behavior metrics, you need a tool that exposes this data cleanly. UXHeat is designed specifically around this dashboard structure — the AI insight engine surfaces the behavior metrics that have moved the most week-over-week, so you don't have to manually pull 11 separate reports.

Benchmarks in this guide are derived from industry research across B2B SaaS, e-commerce, and content site categories. Your actual baselines will vary by industry, audience, and traffic quality — use these as starting points, not targets.