Shopify Analytics to Google Sheets: Automate Your Reporting

Google Sheets gives you what Shopify's built-in analytics does not: custom metrics, cross-source data, team sharing, and reporting that works exactly the way your business thinks. Connecting Shopify analytics to Google Sheets lets you build dashboards you own, combine data from GA4 and Shopify in one view, and automate weekly reports that update without manual work.

Shopify's analytics dashboard is useful for quick checks. But the moment you need to compare this month's conversion rate against last year's, track custom KPIs, or share a report with someone who does not have Shopify admin access, you hit limitations. Google Sheets solves these problems with zero vendor lock-in.

This guide covers three methods -- from free manual exports to a fully automated GA4-to-BigQuery-to-Sheets pipeline -- plus a dashboard template with the five reports every store needs. For a broader look at Shopify's built-in reporting capabilities, see our Shopify reporting guide. Analytics Agent's GA4 Audit ensures the analytics data flowing into your sheets is accurate -- garbage in, garbage out applies to spreadsheets too.

Why Google Sheets for Shopify analytics

Shopify has a reporting dashboard. GA4 has a reporting dashboard. Why add a spreadsheet to the mix?

Custom metrics without code

Shopify reports show standard metrics. Google Sheets lets you create calculated fields: blended ROAS across channels, customer acquisition cost by source, contribution margin per product. You define the formula once, and it recalculates every time the data refreshes.

Cross-source data in one view

Your business runs on more than one data source. Shopify has order data. GA4 has behavior data. Your ad platforms have spend data. Google Sheets is the neutral ground where these sources merge. A single spreadsheet can show Shopify revenue alongside GA4 conversion rate and Meta ad spend -- something no single platform dashboard can do natively.

Team sharing without admin access

Not everyone who needs analytics data should have Shopify admin access. Sheets lets you share specific views with team members, investors, or agencies. View-only access, comment access, or edit access -- you control who sees what without managing Shopify user permissions.

No tool lock-in

Spreadsheets are portable. If you build your reporting in a proprietary tool and later switch, you start over. Google Sheets data is exportable, duplicatable, and works with hundreds of integrations. Your reporting investment compounds rather than resets. For more on the broader landscape, see our Shopify dashboard alternatives guide.

Historical data preservation

Shopify's dashboard shows limited historical comparisons. Google Sheets preserves every data point you import. After 12 months of weekly imports, you have a full year of granular data for trend analysis, seasonality planning, and year-over-year comparisons.

Method 1: manual export from Shopify admin

The simplest approach. No tools, no cost, no setup. Works for stores that update reports monthly or less frequently.

Step-by-step export

1. Log into Shopify Admin. Go to Analytics > Reports.
2. Select a report. Choose from Sales, Customers, Acquisition, Behavior, or Finance reports.
3. Set the date range. Use the date picker to select your reporting period.
4. Click Export. Shopify exports a CSV file with the report data.
5. Open in Google Sheets. Go to Google Sheets > File > Import > Upload > select the CSV. Choose "Replace current sheet" or "Insert new sheet."

What you can export

Limitations

• Manual process. You export, import, and format every time.
• No real-time data. The export reflects the data at the time of export.
• Limited metrics. Shopify exports only what its dashboard shows. No GA4 behavior data, no custom calculations.
• No automation. There is no way to schedule exports.

This method works for monthly board reports or quarterly reviews. For weekly or daily reporting, use Method 2 or 3.

Method 2: Google Sheets add-ons

Add-ons connect Shopify (and other sources) directly to Google Sheets. They pull data on a schedule and populate your spreadsheet automatically.

Supermetrics

The most established data connector for marketing analytics. Supermetrics has a Google Sheets add-on that pulls from 100+ sources including Shopify and GA4.

Setup:

1. Install the Supermetrics add-on from Google Workspace Marketplace.
2. Connect your Shopify store and GA4 property.
3. Build queries in the sidebar: select data source, metrics, dimensions, date range.
4. Schedule automatic refreshes (daily, weekly, or monthly).

Pricing: Starts at $69/month for the Google Sheets connector. Includes Shopify and GA4 as data sources.

Best for: Marketing teams that need data from multiple ad platforms alongside Shopify and GA4.

Coefficient

A newer add-on focused specifically on ecommerce data imports. Coefficient connects to Shopify's API natively and supports real-time syncing.

Setup:

1. Install Coefficient from Google Workspace Marketplace.
2. Connect your Shopify store via API credentials.
3. Select data objects: orders, products, customers, inventory.
4. Map fields to columns and set refresh schedule.

Pricing: Free tier available (limited rows and refreshes). Paid plans start at $49/month.

Best for: Stores that want Shopify operational data (orders, inventory, customers) in Sheets rather than just analytics summaries.

Coupler.io

A data integration tool with a Google Sheets destination. Coupler pulls from Shopify and 60+ other sources.

Setup:

1. Sign up at coupler.io and install the Sheets add-on.
2. Connect Shopify as a data source.
3. Select the data type (orders, products, customers).
4. Set the destination sheet and schedule.

Pricing: Free tier (100 rows, manual refresh only). Paid starts at $49/month with scheduled refreshes.

Best for: Stores that need scheduled data syncing with simple setup.

Add-on comparison

Choose Supermetrics if you need GA4 + ad platform data alongside Shopify. Choose Coefficient if you primarily need Shopify order and inventory data with real-time updates. Choose Coupler for straightforward scheduled imports.

Method 3: GA4 to BigQuery to Sheets pipeline

The most powerful method. Free (within BigQuery's generous free tier), fully automated, and gives you access to raw, hit-level GA4 data that the GA4 interface cannot show.

Why this method is worth the setup

GA4's interface limits you to pre-aggregated reports and a 14-month data retention window (for the free tier). The BigQuery export sends raw event-level data to Google's data warehouse -- every session, every event, every parameter. From BigQuery, you query exactly what you need and pipe it to Google Sheets.

This method gives you:

• Unlimited data retention. BigQuery stores data indefinitely within the free tier (10 GB storage, 1 TB queries/month).
• Hit-level granularity. Analyze individual sessions, event sequences, and user journeys.
• Custom aggregations. Calculate metrics GA4 cannot: session-level conversion rate by landing page, time-between-events analysis, custom attribution.
• Automated refresh. Scheduled queries update your Sheets daily without manual intervention.

Step 1: Link GA4 to BigQuery

1. In GA4, go to Admin > Product Links > BigQuery Links.
2. Click Link and select your Google Cloud project (create one if needed -- the free tier is sufficient).
3. Choose Daily export (streaming export uses more BigQuery resources).
4. Select your data location (choose the region closest to your team).
5. Click Submit. Data starts flowing within 24 hours.

There is no cost for the GA4-to-BigQuery export itself. BigQuery's free tier covers most Shopify stores: 10 GB of free storage and 1 TB of free queries per month.

Step 2: Write your queries

BigQuery uses standard SQL. Here are three queries every Shopify store should start with:

Daily revenue and conversion rate:

SELECT
  event_date,
  COUNT(DISTINCT CASE WHEN event_name = 'session_start' THEN concat(user_pseudo_id, cast(event_timestamp as string)) END) as sessions,
  COUNT(DISTINCT CASE WHEN event_name = 'purchase' THEN concat(user_pseudo_id, cast(event_timestamp as string)) END) as purchases,
  SUM(CASE WHEN event_name = 'purchase' THEN ecommerce.purchase_revenue END) as revenue
FROM `your-project.analytics_PROPERTYID.events_*`
WHERE _TABLE_SUFFIX BETWEEN FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())
GROUP BY event_date
ORDER BY event_date DESC

Traffic sources with conversion rate:

SELECT
  traffic_source.source,
  traffic_source.medium,
  COUNT(DISTINCT user_pseudo_id) as users,
  COUNTIF(event_name = 'purchase') as purchases,
  SUM(CASE WHEN event_name = 'purchase' THEN ecommerce.purchase_revenue END) as revenue
FROM `your-project.analytics_PROPERTYID.events_*`
WHERE _TABLE_SUFFIX BETWEEN FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())
GROUP BY 1, 2
ORDER BY revenue DESC

Top products by revenue:

SELECT
  items.item_name,
  items.item_category,
  COUNT(*) as units_sold,
  SUM(items.price * items.quantity) as product_revenue
FROM `your-project.analytics_PROPERTYID.events_*`,
UNNEST(items) as items
WHERE event_name = 'purchase'
  AND _TABLE_SUFFIX BETWEEN FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())
GROUP BY 1, 2
ORDER BY product_revenue DESC
LIMIT 50

Step 3: Connect BigQuery to Sheets

Two options:

Option A -- Connected Sheets (built-in):

1. In Google Sheets, go to Data > Data connectors > BigQuery.
2. Select your project and dataset.
3. Write or paste your SQL query.
4. The results populate directly in your sheet.
5. Click Refresh to update, or set up a scheduled refresh.

Option B -- Scheduled query + Apps Script:

1. In BigQuery, save your queries as scheduled queries (run daily at 6 a.m.).
2. Set the destination table for each query.
3. In Google Sheets, use an Apps Script to pull from the destination tables on a trigger.

Option A is simpler. Option B gives more control over timing and formatting.

Dashboard template: the 5 reports every store needs

Regardless of which method you use, structure your Google Sheets dashboard around these five reports.

Report 1: Revenue dashboard

Report 2: Traffic sources

Include AI referral traffic as its own row. This channel is growing faster than any other for most ecommerce stores, and most reporting dashboards miss it entirely. See our ChatGPT traffic analytics guide for setup details.

Report 3: Conversion funnel

Track each step's conversion rate weekly. A drop at any step signals a specific problem. For GA4 setup on Shopify, make sure all ecommerce events fire correctly before building funnel reports.

Report 4: AOV and basket analysis

Report 5: Acquisition efficiency

Automating weekly refreshes

The dashboard is only useful if the data stays current. Three automation options, from simplest to most robust.

Google Apps Script

Free. Built into Google Sheets. Use it to trigger data refreshes on a schedule.

function refreshData() {
  // Refresh all Connected Sheets queries
  var sheets = SpreadsheetApp.getActiveSpreadsheet().getSheets();
  for (var i = 0; i < sheets.length; i++) {
    var dataSourceTables = sheets[i].getDataSourceTables();
    for (var j = 0; j < dataSourceTables.length; j++) {
      dataSourceTables[j].refreshData();
    }
  }
}

Set a time-driven trigger: Edit > Triggers > Add trigger > refreshData > Time-driven > Weekly > Monday 7 a.m.

Zapier or Make

For add-on-based setups, use Zapier or Make to trigger data refreshes:

• Trigger: Schedule (every Monday at 6 a.m.)
• Action: Run Supermetrics/Coefficient/Coupler refresh
• Action 2: Send Slack notification with key metrics summary

Cost: Zapier starts at $19.99/month. Make starts at $9/month.

BigQuery scheduled queries

For the BigQuery pipeline (Method 3), scheduled queries run automatically:

1. In BigQuery, open your saved query.
2. Click Schedule > Create new scheduled query.
3. Set frequency: daily at 5 a.m.
4. Set destination table (overwrites previous results).
5. Connected Sheets automatically picks up the new data on next refresh.

This is the most reliable automation because it runs entirely within Google's infrastructure with no third-party dependencies.

How this affects your AI visibility

Accurate reporting in Google Sheets helps you measure the return on your AI visibility investments. When you track AI referral traffic alongside traditional channels in a unified dashboard, you can see how AI search optimization efforts translate to sessions, conversions, and revenue.

Most stores do not track AI referral traffic at all. Adding a dedicated row for ChatGPT, Perplexity, and AI Overview traffic in your Google Sheets dashboard gives you visibility into the fastest-growing channel in ecommerce. That data informs how much to invest in structured data, entity authority, and AI-targeted content.

Analytics Agent's Mission Briefs deliver weekly analytics summaries that complement your Google Sheets reporting -- surfacing AI visibility insights, conversion anomalies, and growth opportunities that spreadsheet formulas cannot detect.

FAQ

Can I connect Shopify directly to Google Sheets without add-ons?

Not automatically. Shopify does not have a native Google Sheets integration. You can manually export CSV reports from Shopify Admin and import them into Sheets, but there is no built-in auto-sync. For automated connections, use an add-on (Supermetrics, Coefficient, Coupler) or the GA4-to-BigQuery-to-Sheets pipeline. The GA4 pipeline is free and provides richer data than Shopify's exports.

Is the GA4-to-BigQuery-to-Sheets pipeline really free?

For most Shopify stores, yes. BigQuery's free tier includes 10 GB of storage and 1 TB of query processing per month. The GA4 daily export typically uses 1-5 GB per month for stores with moderate traffic. The free tier handles this comfortably. You only pay if you exceed the free limits, which requires very high traffic volumes or very complex queries.

How often should I refresh my Shopify analytics Google Sheets dashboard?

Weekly is the right cadence for most stores. Daily refreshes create noise -- single-day fluctuations distract from trends. Weekly data smooths variance and makes trends visible. Exception: during promotions, product launches, or active ad campaigns, switch to daily refreshes so you can react to performance in near-real-time.

What is the difference between using Shopify data and GA4 data in Google Sheets?

Shopify data is transactional: orders, revenue, products, customers. It is accurate for financial reporting. GA4 data is behavioral: sessions, pageviews, events, conversion paths. It shows how users interact with your store before purchasing. The best Google Sheets dashboards combine both: Shopify for revenue accuracy and GA4 for behavior insights. When the two sources show different numbers, see our guide on comparing Shopify and GA4 data correctly.

Which Google Sheets add-on is best for Shopify analytics?

It depends on your needs. Supermetrics ($69/month) is best if you need multi-source data (GA4 + ad platforms + Shopify) in one sheet. Coefficient ($49/month with free tier) is best for real-time Shopify operational data (orders, inventory). Coupler.io ($49/month with free tier) is best for simple, scheduled data imports. If budget is a concern, the GA4-to-BigQuery-to-Sheets pipeline is free and provides the richest data, but requires SQL knowledge for setup.