Shopify Analytics with Mixtable

Mixtable calculates analytics from your Shopify store data and delivers the results in a spreadsheet you can sort, filter, extend with formulas, and export. You can build a sales leaderboard, follow results by month or year, or place calculated performance metrics beside the Shopify products, customers, collections, and other records you already work with.

There are three ways to do it. They are not competing features, they are three shapes of answer, and most stores end up using all three. This page explains each one, then covers the metrics, dates, and filters they share.

Choose the right approach

The quickest way to pick is to ask what a row should represent.

Approach	What each row is	What the columns are	Best for
Analytics columns on a Shopify data worksheet	One Shopify record, such as a product, variant, customer, or collection	Shopify fields plus calculated metrics	Acting on individual records
Time Series worksheet	A metric, or a group such as a vendor	Recent months or years	Trends, seasonality, and direction of change
Pivot Table worksheet	A group you define, such as a vendor or Market	Metrics you select	Ranking and comparing groups

The last two are Reporting worksheets, where Mixtable groups your data and calculates each row. The first is a Shopify data worksheet, where your live Shopify records stay as the rows and you add calculated columns beside them.

You can tell them apart at a glance. A Shopify data worksheet uses green headers and a green button, and a Reporting worksheet uses blue headers and a blue button. In both, the bolt button is how you add or change what a row or column contains.

Before you begin

Install Mixtable Analytics Spreadsheet, then open the spreadsheet where you want the report.

Available metrics depend on what you are analyzing. Product-variant worksheets can calculate cost and margin, order worksheets can calculate fulfillment and delivery timing, and customer worksheets can calculate lifetime and attribution metrics. Mixtable only offers the metrics supported by the worksheet you are configuring.

Analytics columns on a Shopify data worksheet

What it is

A Shopify data worksheet holds your real Shopify records, one per row: one product, one variant, one customer, one collection. An analytics column adds a calculated metric to that worksheet, so every row gets its own result.

The point is that performance sits beside the record itself. Units sold appears next to units in stock, net sales next to cost per item, lifetime spend next to the customer’s email. Everything a decision needs is on one row, so you never leave the report to look something up.

How it works

Each analytics column defines one metric, one timeframe, and any filters, then calculates that for every row.

1. Open a supported Shopify data worksheet, then select an empty column or insert a new one. Empty columns have a non-green header; a green header means the column is already linked to Shopify data

2. Click the button in the column header

3. Choose Analytics

   

4. Under Which metric?, select the metric you want

5. Under Over what time period?, choose All time, Fixed dates, Rolling period, Calendar year, or Calendar month

6. Under Limit which orders count, add any optional filters supported by the metric

7. Click Save Column

Add as many columns as you need. Because each one is independent, you can add the same metric two or three times with different timeframes or filters and compare them side by side.

Supported objects include products, product variants, collections, customers, orders, companies, and company locations.

What you can do with it

• Rank products by net sales while keeping SKU, price, cost, inventory, and status visible
• Build a customer list with lifetime spend beside names, emails, and tags, then export it for your email tool
• Compare this year against last year in adjacent columns, then add a formula for the change
• Compare two customer segments or two sales channels product by product
• Spot a variant selling out and act on it, since the record is right there

If you also use Mixtable Spreadsheet Editor, you can edit the Shopify fields on the same worksheet, review pending changes, and sync them. The report and the fix happen in one place.

See add analytics columns to a Shopify data worksheet for the full workflow.

Time Series worksheets

What it is

A Time Series worksheet turns a total into a trend. Time periods run across the columns as recent months or years, and each row is either a store metric you are following or a group you are comparing.

This is the view for direction. A single number tells you where you stand, but only a sequence tells you whether things are improving, and seasonality is invisible until you see the same month across two years.

How it works

The layout depends on the breakdown you choose.

Choose Store and each metric becomes its own row: Net Sales, Gross Sales, Orders Count, Average Order Value, Net Quantity Sold, Total Refund Amount Excluding Tax, Refund Count, and Total Discount Amount. This is the classic monthly store summary.

Choose a business dimension and each group becomes a row instead, with one metric measured across the periods. Available breakdowns are vendor, product type, Shopify Market, customer segment, and last-touch marketing channel.

1. Click the + button beside the worksheet tabs
2. Select Reporting worksheet, then click Continue
3. Under Time series, choose a ready-made report, or choose Blank time series under Start from scratch
4. Click Continue
5. Under Break down by, choose Store or a business dimension
6. Under Metrics or Measure, choose what the rows should calculate
7. Under Time periods, choose By month or By year, then how many recent periods to include
8. Click Create Worksheet

Mixtable can create up to 36 monthly columns or 10 yearly columns. You can also add your own rows afterward with the button, which is how you get rows a breakdown cannot produce.

What you can do with it

• Produce the monthly store report you would otherwise rebuild by hand every month
• Compare the same month across years to separate seasonality from real growth
• Watch whether refunds or discounts are growing faster than sales
• See which vendors, Markets, or segments are gaining ground and which are fading
• Track one campaign channel’s contribution month by month
• Add growth and variance formulas beside the generated columns

See create a Time Series worksheet for Shopify data.

Pivot Table worksheets

What it is

A Pivot Table worksheet is built for comparison. Each row is a group of Shopify records, each column is a metric, and every group is measured the same way over the same timeframe.

Once you have more than a few hundred products, the useful pattern usually lives one level above the product. Which supplier earns the most, which category absorbs the most discounting, which segment places the largest orders: those are questions a ranked list of individual products cannot answer.

How it works

Choosing a breakdown generates every row at once. The options are vendor, product type, Shopify product category, product tag, Shopify Market, and customer segment.

1. Click the + button beside the worksheet tabs
2. Select Reporting worksheet, then click Continue
3. Under Pivot table, choose a ready-made report, or choose Blank pivot table under Start from scratch
4. Click Continue
5. Under Break down by, select the group that should become the rows
6. Under Metrics, select the calculated values for the columns
7. Under Time period, choose the dates the metrics should cover
8. Review the sample preview, then click Create Worksheet

Breakdowns are a starting point, not a limit. Using the button in an empty row header, you can define a row yourself: pick the Shopify object it analyzes, then either include every record or write conditions that select exactly the ones you want. A row can be one vendor’s tagged products, your variants above a cost threshold, or your customers in a particular country, and it sits beside the generated rows in the same report.

What you can do with it

• Rank vendors, categories, or collections by net sales, margin, or refund rate
• Find where discounting is concentrated, which is usually a category habit rather than a product decision
• Compare customer segments by what they are worth rather than how many people they contain
• Compare Shopify Markets side by side when you sell internationally
• Build custom rows for groups no single Shopify field describes, such as one vendor’s tagged products beside their untagged ones
• Sort by any metric, then add formula columns for shares and ratios

See create a Pivot Table worksheet for Shopify data.

How the three fit together

They answer the same question at different altitudes, and a real investigation usually moves between them.

A vendor Pivot Table worksheet shows that one supplier is behind a drop in net sales. A Time Series worksheet shows whether that vendor has been sliding for months or just had one bad one. A Shopify data worksheet with analytics columns then shows exactly which of that vendor’s products to reorder, discount, or drop.

Start wherever your question starts. Nothing stops you keeping all three in the same spreadsheet.

What you can analyze

All three approaches draw on the same metric catalog:

• Sales and quantities: Net Sales, Gross Sales, Total Sales, Net Quantity Sold, Gross Quantity Sold, and Refunded Quantity
• Orders and customers: Orders Count, Average Order Value, customer purchase behavior, segment membership, and average order quantities
• Refunds and returns: Refund Count, refund amounts, refunded-order percentage, return requests, return rate, returned quantity, open returns, and time to close
• Discounts: Total Discount Amount, discount campaign order counts, and allocated discount amounts where supported
• Profitability: Gross Profit, % Gross Margin, Amount of Cost of Goods Sold, and Orders Net Profit on supported variant reporting
• Order charges: Tax, shipping, duties, and additional fees
• Fulfillment: Fulfillment volume, fulfilled quantities, time to first fulfillment, and delivery speed
• Attribution: First-touch and last-touch sources, UTM values, attribution coverage, and time to conversion

Availability varies by what you are analyzing. Use the Shopify analytics metrics reference to compare definitions and see which metrics belong together.

Control the dates and orders included

Each Pivot Table metric or analytics column can use All time, Fixed dates, Rolling period, Calendar year, or Calendar month. Time Series worksheets use separate columns for recent months or years instead.

You can also limit which Shopify orders count toward a result. Depending on the metric, filters include customer segment, customer country, discount campaign, fulfillment status, B2B order type, company, order source, retail location, Shopify Market, attribution values, fulfillment details, and return details.

Getting these two settings right matters more than any other choice, because comparing a partial month with a complete one, or forgetting a filter, is the easiest way to reach a confident but wrong conclusion.

• Choose Shopify analytics timeframes
• Filter Shopify analytics reports

Every report is still a spreadsheet

Whichever approach you choose, the result is a normal Mixtable worksheet. You can:

• Sort rows to find leaders and outliers
• Filter the worksheet without changing the underlying calculation
• Add formulas for growth, variance, ratios, targets, or rankings
• Add columns for notes and decisions
• Export the worksheet to CSV or the full spreadsheet to Excel

This is what makes it different from a fixed dashboard. When a report needs one more calculation specific to your business, you add it yourself: divide Total Discount Amount by Gross Sales for a discount rate, or compare this year’s Net Sales with last year’s for growth.

Reports and spreadsheet templates are different

A ready-made report adds one worksheet to the spreadsheet you already have open. A reporting template creates a whole new spreadsheet, sometimes with several worksheets and many preconfigured columns.

Choose a ready-made report when you want to add one focused analysis to current work, and browse them in the report library. Choose a reporting template when you want Mixtable to build the whole spreadsheet for you.