# Connect an existing listing export

Use your existing GA4 and BigQuery setup for Shopify listing attribution.

## What you need

Your existing listing GA4 property/stream and daily BigQuery export, its project ID and dataset location, plus a query credential with access to that export and query jobs. Reuse an existing working setup; a new Google project is not a HeyCrust requirement.

## Steps

1. In Shopify’s listing tracking settings, confirm the intended GA4 measurement ID and matching stream Measurement Protocol secret for install events. Check Shopify’s [listing tracking instructions](https://shopify.dev/docs/apps/launch/marketing/track-listing-traffic).
2. Inspect your existing GA4 BigQuery link and stream selection. HeyCrust reads daily `events_YYYYMMDD` tables in `analytics_<numeric property ID>`; it does not read intraday tables. If a link is missing, your account administrator can follow [Google’s link instructions](https://support.google.com/analytics/answer/9823238?hl=en).
3. Open the program’s Tracking area and choose **Connect listing GA4 export**. Enter the Cloud project ID, numeric GA4 property ID, numeric stream ID and the dataset’s actual location. The UI starts with `US`; replace it when your dataset uses another location.
4. Leave **Shop URL event parameter** as `shop_url` and **App identity event parameter** as `api_key` unless your actual export uses different names. `api_key` must be the Shopify client ID, not the numeric Partner app ID.
5. Supply the service-account JSON only when needed. A blank field reuses an app-saved or configured server credential; with neither available the query cannot run. The credential may originate in another project if it has the required dataset/job access. Keep JSON private.
6. Save, inspect validation, then **Refresh listing attribution evidence**. Follow an actual referral link/install and wait for its daily export before evaluating continuity.

## Expected result

A validated project/property/stream/location and queryable daily export, followed by explicit matching evidence when actual listing and install rows arrive. Configuration success and production attribution readiness are distinct.

## What HeyCrust matches

The reader looks for `page_view` on the canonical `apps.shopify.com` listing and `shopify_app_install` for the expected app identity. It uses exported session/user information and referral markers including `hc_click`, with merchant parameters such as `shop_url` and `shop_id`. This is evidence-based matching, not a promise of cross-device attribution.

Queries are bounded: four UTC days per batch, a 100 MB billed-byte cap per job, a 30-second job deadline and an overall two-minute/20,000-row read boundary. A limited read can require another refresh. Delayed exports and continuity are checked separately from access validation.

Connect this source through HeyCrust; do not change an unrelated analytics or billing setup. See [Tracking verification](/docs/app-owners/affiliate-tracking).

## Troubleshooting

Check the exact dataset, region, selected stream and service-account access. A wrong `G-...` measurement ID in a numeric field fails validation. Daily export can delay evidence; absence in an intraday table proves nothing for this reader.