Build an AEO Dashboard in Looker Studio: Free Template + Step-by-Step Guide

What should an AEO dashboard show a CMO at a glance?

An AEO dashboard for executives should show seven KPIs in scorecards at the top and three trend lines below. The KPIs answer one question: is our brand getting cited more, less, or differently across AI search this week?

The seven KPIs we ship in the template:

#	KPI	Source	Why it matters
1	AI Share of Voice (%)	Profound / Otterly	Your slice of brand mentions vs competitors across tracked prompts
2	Citation Rate (%)	Profound / Otterly	% of tracked prompts that cite your domain at least once
3	AI Referral Sessions	GA4	Sessions from ChatGPT, Perplexity, Gemini, Copilot, Claude
4	Prompt Coverage (%)	Manual Sheet	% of priority prompts where you appear in the answer
5	Sentiment Score	Manual Sheet	Net positive vs negative mentions, weighted
6	AI Overview Impressions	GSC	Impressions on queries flagged as AI Overview eligible
7	Competitor Gap	Profound / Otterly	Your SoV minus #1 competitor SoV

According to HubSpot's 2026 AEO metrics guide, inclusion, share of voice, prominence, sentiment, and citations are the consolidated metrics every AEO program should report on. The dashboard above maps directly to that framework, with two add-ons (referral sessions and AI Overview impressions) for owned-channel attribution.

How do I combine Profound + GSC + GA4 in one Looker Studio dashboard?

You combine them by using five separate data sources that share a common date dimension, then blending them with date as the join key. Looker Studio handles the blending; you do not need a warehouse.

The five data sources:

1. Profound or Otterly -- visibility, citations, share of voice. Otterly's native Looker Studio connector is the fastest path; Profound exports via API or CSV through their MCP server into a Google Sheet.
2. Google Search Console -- query-level impressions, including AI Overview-eligible queries. Use the native GSC connector in Looker Studio.
3. GA4 -- session andconversion data. Filter to a custom channel group called "AI Traffic" (regex below).
4. Google Sheets: Prompt Tracker -- your manual weekly test of 25 priority prompts.
5. Google Sheets: Competitor Benchmark -- weekly snapshot of competitor SoV from your AEO tool.

In Looker Studio, click Resource > Manage blends > Add a blend, drop in any two sources, and join on Date. The result is one chart that pulls from multiple systems, no SQL required.

How do I set up the GA4 "AI Traffic" channel for the dashboard?

Create a custom channel group in GA4 called AI Traffic before connecting GA4 to Looker Studio. Otherwise, AI sessions land in Referral or Direct and you cannot isolate them.

Steps in GA4:

1. Go to Admin > Data display > Channel groups > Create new channel group.
2. Name it AI Traffic with paid or similar.
3. Add a rule above the Referral rule:
   • Condition: Source matches regex
   • Regex: chatgpt|openai|perplexity|gemini|bard|copilot|bing\.com\/chat|claude|anthropic|you\.com|phind|poe\.com
4. Save and apply.

Per MarTech's 2026 analysis, AI browsers like ChatGPT Atlas and Perplexity Comet often strip referrer headers, so a chunk of true AI traffic still hits as Direct. Document this caveat in the dashboard footnote. The channel group catches what is catchable.

In Looker Studio, when you add the GA4 source, the new channel group appears as a dimension. Filter every GA4 chart on Default channel group = AI Traffic.

How do I pull Profound or Otterly data into Looker Studio?

Otterly has a native connector. Profound does not (yet), so you bridge through Google Sheets.

Otterly path (fastest):

1. In Otterly, open the Integrations tab and click Connect to Data (Looker) Studio.
2. Select your workspace and Brand Report.
3. Authorize with Google. Per Otterly's docs, the connector exposes Brand Coverage %, Share of Voice %, Brand Rank, and citation metrics.
4. The data refreshes automatically -- no manual export.

Profound path (via Sheets):

1. Generate an API key in Profound's settings.
2. In Google Sheets, install the Profound MCP or use a simple Apps Script that calls the visibility endpoint daily.
3. Push results to a sheet named profound_daily with columns: date, prompt_id, brand_mentioned, citation_count, share_of_voice, competitor_top1.
4. Connect that sheet to Looker Studio as a data source.

If you are choosing between the two tools, see our Profound vs Otterly comparison. For dashboard purposes, Otterly is plug-and-play; Profound gives more granular agent-analytics data once you do the API work.

What manual data inputs does an AEO dashboard need?

Two Google Sheets cover the manual inputs: a prompt tracker and a competitor benchmark. These fill the gaps that automated tools miss -- specifically, sentiment grading and prompts your tool does not track.

Prompt Tracker sheet schema:

Column	Type	Example
date	date	2026-05-03
platform	string	ChatGPT, Perplexity, Gemini, Copilot, Claude
prompt_id	string	P-014
prompt_text	string	"best AEO tools for SaaS"
intent	string	comparison, definition, recommendation
brand_mentioned	bool	TRUE/FALSE
position	int	1-10, blank if not mentioned
sentiment	int	-1, 0, 1
competitors_mentioned	string	"Profound, Otterly"
response_url	string	Permalink if available

Run 15 to 25 priority prompts weekly, per Discovered Labs' AEO measurement framework. That is the minimum to get a stable Prompt Coverage % and Sentiment Score. Less than 15 and your week-over-week numbers swing on noise.

The Competitor Benchmark sheet is simpler: one row per competitor per week with their SoV % from your AEO tool. The dashboard subtracts your SoV from the leader's SoV to compute the Competitor Gap KPI.

How do I show AI share-of-voice trends over time?

Use a time series chart with Date on X, Share of Voice % on Y, and break down by Platform (ChatGPT, Perplexity, Gemini, Copilot, Claude). One line per platform.

In Looker Studio:

1. Add a Time series chart.
2. Data source: your Otterly connector or profound_daily sheet.
3. Date dimension: date.
4. Breakdown dimension: platform.
5. Metric: share_of_voice with aggregation AVG (not SUM -- SoV is a percentage).
6. Add a comparison: Previous period to show last 7 vs prior 7 days as a delta arrow.

For the second chart, plot Citation Rate the same way. For the third, plot AI Referral Sessions from GA4.

According to HubSpot's AI share-of-voice guidance, strong B2B SaaS companies target 10-15% citation rates on category queries; market leaders exceed 30%. Add a horizontal reference line at 15% on the Citation Rate chart so the CMO sees instantly whether you are above or below the leader benchmark.

Keep the trend window to rolling 90 days by default. AEO data is volatile, and 30 days hides the trend while 12 months drowns the recent signal.

How do I add AI Overview impressions from Google Search Console?

You cannot get AI Overview impressions as a separate metric in GSC -- Google still bundles them into total query impressions. The workaround is to flag AI Overview-eligible queries and trend their impressions as a proxy.

Process:

1. In GSC, export the top 200 queries by impressions (last 28 days).
2. Manually verify which queries trigger an AI Overview by searching them in an incognito Chrome window. Mark aio_eligible = TRUE in a Google Sheet.
3. In Looker Studio, blend the GSC data source with that flag sheet on query.
4. Filter the impressions chart to aio_eligible = TRUE only.

Per Coupler.io's 2026 GSC connector guide, GSC's API retains 16 months of data, so backfill the flag sheet quarterly. As of early 2026, pre-AI baseline data from late 2023 is rolling off, so freezing your own snapshots is critical for year-over-year comparisons.

The KPI scorecard reads: AI Overview Impressions (28-day) with delta vs prior 28 days. The chart below it shows the trend. Together, they tell you if your AI Overview presence is growing in the queries that matter to you.

Can I build an AEO dashboard without an enterprise tool?

Yes. The minimum viable AEO dashboard runs on GA4 + GSC + a manual prompt-tracking Google Sheet, with zero paid tools. You lose share-of-voice automation, but you keep five of the seven KPIs.

Free-tier build:

• Skip Profound and Otterly.
• Run 25 priority prompts weekly across ChatGPT, Perplexity, Gemini, Copilot, Claude. Log results in the Prompt Tracker sheet.
• Compute Share of Voice manually: (your mentions) / (total branded mentions across all rows).
• Compute Citation Rate manually: (rows where brand_mentioned=TRUE) / (total rows).
• Pull GA4 AI Traffic and GSC AI-Overview-flagged queries as described above.

This works for solo founders and pre-Series A teams. Once you cross 100+ prompts or need cross-domain citation tracking, you graduate to Profound or Otterly because manual logging stops scaling.

For the upgrade path, see our roundup of AI search visibility tools. The dashboard structure stays identical -- you just swap the Profound/Otterly source for the manual sheet.

How do I copy the free Looker Studio AEO dashboard template?

The template is published in the Looker Studio public gallery as Growth Engineer AEO Dashboard v1. To copy:

1. Open the template link (linked at the bottom of this article).
2. Click File > Make a copy or the copy icon in the top-right.
3. Looker Studio prompts you to map each data source. Plug in your own Otterly connector / Profound sheet / GSC property / GA4 property / Prompt Tracker sheet.
4. Click Copy Report.

The template includes:

• Page 1: 7 KPI scorecards, 3 trend charts, 1 competitor leaderboard
• Page 2: Per-platform breakdown (ChatGPT, Perplexity, Gemini, Copilot, Claude)
• Page 3: Prompt-level detail table with sentiment heat map
• Page 4: AI Overview query trends from GSC

A companion Google Sheet with the Prompt Tracker schema and a 25-prompt starter library ships alongside the template. Both are licensed CC-BY: copy, modify, ship to your team. If you publish your version publicly, a link back is appreciated and helps the page accumulate co-mention signals (which, per Princeton's GEO study, boost AI citation rates around 30%).

How often should the AEO dashboard refresh?

Set the dashboard to refresh on a weekly cadence for executive review and daily for the operator running the program. Anything more frequent and you chase noise; anything less and you miss algorithm shifts.

In Looker Studio: File > Report settings > Data freshness > 12 hours for the operator view. For exec view, schedule a PDF email delivery via File > Schedule delivery > Weekly, Monday 8am.

Match the manual prompt run to that cadence: every Monday morning, the operator runs the 25 priority prompts, updates the Prompt Tracker sheet, and the dashboard auto-refreshes by 9am for the standup.

According to our guide to AEO KPIs that matter, weekly is the right cadence for AI search visibility because new content enters citation pools within 3-5 business days, and platform algorithms shift on roughly bi-weekly cycles. Daily is for tactical chasing; monthly is for the board deck. Weekly hits the operating rhythm.

Data source	Cost	Connector type	Refresh	Covers
Otterly	From $89/mo	Native Looker Studio connector	Auto, hourly	SoV, citations, brand coverage across 5 AI engines
Profound	Custom (enterprise)	API + Google Sheets bridge	Daily via script	SoV, citations, agent analytics, deep prompt-level data
Google Search Console	Free	Native Looker Studio connector	Auto, daily	AI Overview-eligible query impressions and CTR
GA4	Free	Native Looker Studio connector	Auto, hourly	AI referral sessions, conversions, channel group filter
Prompt Tracker (Sheets)	Free	Native Sheets connector	On manual update	Sentiment, prompt-level coverage, competitor mentions
Competitor Benchmark (Sheets)	Free	Native Sheets connector	Weekly manual update	Competitor SoV gap, leaderboard