Analytics / New feature

Physical storefront reports
Isolate in-store sales with "Is physical storefront"

The new "Is physical storefront" filter separates in-store activity from the rest of your business. Compare physical storefront locations against other locations and channels right inside Reports and Explore—no spreadsheet exports required.

On this page
  1. What actually changes (understand it in 30 seconds)
  2. How to use it: filtering / grouping
  3. How this dimension behaves (important: snapshot model)
  4. Old vs. new filter comparison
  5. Setup notes (the physical storefront flag)
  6. 5 points developers should know
  7. 3 use cases you can apply to your work
  8. One-line summary for proposals

1What actually changes

A new filter called "Is physical storefront" has been added to analytics.
With it, you can isolate in-store (physical storefront) sales and activityfrom your online store and other locations, and compare them right inside Reports / Explore. The aggregation you used to do by exporting to a spreadsheet is no longer needed.

Before: manual separation

When you wanted to see physical storefront numbers alone, you exported the report and sorted locations by hand in a spreadsheet.

Now: a single filter

Just filter or group by "Is physical storefront." You can compare instantly within the Reports and Explore screens.

2How to use it: filtering / grouping

All locations Physical storefront / online store / warehouse POS / wholesale ... mixed Reports / Explore Is physical storefront Filter / dimension Physical storefront = Yes Extract in-store activity only Physical storefront = No Online store & other channels Compare side by side No export needed
as a filterand as a group-by dimensionyou can use it either way. Both "show physical stores only" and "compare physical stores vs. everything else" are covered by the same dimension.

3How this dimension behaves (important: snapshot approach)

This dimension reflects each location's "current settings" In other words —

Every location currently flagged is included

It includes every location whose "physical storefront" flag on the location detail page is currently ON.

Sales timing doesn't matter

It doesn't matter "when" the sale happened. Past transactions are also sorted by the current flag state.

Note that it sorts by "current state," not history.If you mark a location as a physical store, that location's past sales are also retroactively classified as "physical store." Conversely, if you remove the flag, past sales are removed too. It's not suited for analysis that needs the strict "state at that point in time" over a timeline (as the article notes, this is a snapshot of the current settings).

4Legacy vs. new filter comparison

ItemLegacyIs physical storefront
Separating in-store sales Manual export → spreadsheet In-screen One filter
Comparing physical stores vs. other channels Sort by hand Group by Line them up as a dimension
Existing point of sale dimension — Can combine Can be used together
Saving to custom reports — Supported Can be saved
Classification basis — The location'scurrentphysical storefront flag

5Setup tips (physical storefront flag)

1

Open the location settings

Go to the target location's detail page.

2

Turn "physical storefront" ON

Mark as a physical storefront.

3

Reflected in reports instantly

Once marked, that location is immediately included in the dimension.

Because toggling the flag on/off directly affects the classification,keeping each location's physical-storefront flag set correctlyis the prerequisite for this analysis to work.

65 points engineers should keep in mind

1. The classification is a snapshot of the "current setting"

It sorts by a location's current physical-storefront flag, not by its state at the time of sale. Factor in that historical data is also retroactively reclassified when designing your reports.

2. Can be used alongside existing POS dimensions

Stated explicitly as "works alongside your existing point of sale dimensions." You can build multi-axis breakdowns that combine the physical-storefront flag with POS axes.

3. Can be saved to custom reports

Save conditions that include "Is physical storefront" as part of your custom reports, then reuse them as a template for ongoing monitoring.

R E

4. Available in both Reports and Explore

The same filter works not only in standard Reports but also in Explore for exploratory analysis. You can align the axes across ad-hoc analysis and recurring reports.

fields ?

5. See the Help Center for the full list of supported fields / No mention of the API

The complete list of which fields it can be used on is left to the Shopify Help Center (the article doesn't enumerate them). The article also says nothing about how it's handled in ShopifyQL or the Admin API. If you're aiming for automation or external BI integration, verify separately in the Help Center and a sandbox.

73 use cases you can apply to your operations

USE CASE 1

Compare weekly "performance by channel" for physical store vs. online, no code required

Challenge
In an OMO rollout with both physical stores and an online shop, isolating in-store-only sales and customer counts required an export plus manual aggregation every time.
Approach
Build a report grouped by "Is physical storefront" and save it as a custom report. Just open it weekly.
Result
Comparing in-store and online performance is done instantly on screen. You can monitor it continuously with zero aggregation effort.
Technical note
Since the same axis works in both Reports and Explore, you can align the axes for recurring reports and ad-hoc deep dives.
USE CASE 2

"Store portfolio analysis" for multi-store chains

Challenge
With stores, warehouses, pop-ups, and online all mixed together, it's hard to tell which ones are "physical storefronts" in the reports.
Approach
Set the physical storefront flag only on physical store locations → filter to "physical stores only" and compare sales and inventory sell-through per store.
Result
You can evaluate a pure storefront portfolio with the noise of warehouses and online stripped out. It becomes input for closing and opening decisions.
Technical note
The classification follows the current flag. Taking stock of location types and setting the flags correctly is the prerequisite for accuracy.
USE CASE 3

Verify the impact of in-store initiatives (BOPIS, events) on a per-store basis

Challenge
You want to see the impact of store-only campaigns or BOPIS, but the online portion mixed into company-wide reports dilutes the effect.
Approach
Compare reports filtered by "Physical storefront = Yes" across your campaign period. Combine it with the existing POS dimension to also slice by payment method and time of day.
Impact
Clean impact measurement that isolates in-store activity only. Reusable as evidence for campaign ROI write-ups.
Technical notes
Past data is reclassified against the current flag, so lock the target locations' flags and don't change them before or after the campaign.

8One-line summary for your pitch

"The new 'Is physical storefront' filter separates in-store sales and activity from online and warehouse.
In both Reports and Explore it's a single filter with no export needed. It works alongside the existing POS dimension and can be saved to a custom report.
Classification is based on the location'scurrentphysical-storefront flag, so keeping your flags tidy directly translates into analysis accuracy."