Transparency update on what we've learned so far.

As we've been digging deeper into the revenue calculation pipeline, we've uncovered a significant amount of hidden logic embedded across our system — particularly around how tax, returns, and refunds are computed. Many of these calculations have implicit rules and edge cases that were never clearly documented or aligned with product specifications.

For example: tax-inclusive vs tax-exclusive pricing, partial refund adjustments, cross-month return attribution, and order-level vs line-item-level discount allocation each have their own quirks that interact in non-obvious ways. Some of this logic was written years ago to handle specific Shopify behaviors, but the reasoning behind it was never captured — making it fragile and hard to verify.

We're planning to work closely with our product team to review and refine these calculation rules from the ground up — ensuring every formula is clearly defined, well-documented, and testable. This won't happen overnight, but it's the right investment to prevent these kinds of issues from recurring.

In the meantime, we're continuing to fix the immediate accuracy issues and verify numbers shop by shop.

Working on the next root cause — the pending refund discrepancy.

When a merchant issues a refund, Shopify sometimes creates a PENDING_REFUND_DISCREPANCY adjustment after the refund webhook fires. Our system only captured data at webhook time, so this late adjustment was missed — causing return numbers to be slightly off for affected orders.

The fix: instead of relying solely on webhook timing, we're integrating the Shopify Agreements API to fetch the complete, final adjustment data directly from Shopify. This ensures we always have the full picture, regardless of when Shopify finalizes the refund.

We've already verified our revenue formula across 9,281+ orders on 5 different shops with exact parity against Shopify's own reports. This fix will close another significant gap.

Major milestone — we've deployed 13 production releases across our order processing and reporting services. All identified code-level bugs are now fixed.

We also built a comprehensive 4-source comparison tool that cross-references your data across Shopify GraphQL API, ShopifyQL reports, our database, and the TrueProfit dashboard. This lets us verify accuracy down to the cent for any shop.

Here's what we've fixed so far:

Fixed Ghost/phantom records — stale data snapshots created duplicate line items that inflated gross sales by $5K-$20K on affected shops
Fixed Missing refund timestamps — refund records lacked the refund_at field, making refunds invisible in date-based reports
Fixed Duplicate report entries — a code path was writing two sets of base records for the same order, doubling revenue for those entries
Fixed Discount allocation gaps — order-level discount codes weren't being properly distributed to individual line items
Fixed Order sync race condition — database writes were completing after message dispatch, causing downstream reads of stale data

We're now working on historical data repair and continuing to investigate for any additional issues. We're not stopping until every number matches.

Deployed two critical fixes today:

Refund timestamp backfill — We discovered that refund records in our sales reports were missing the refund_at timestamp entirely. When your account uses date-based refund attribution, our calculator tried to match refunds by this field and found nothing — making those refunds completely invisible in your reports. We've fixed the code and backfilled 357,000 historical refund records from the source data.

Duplicate record cleanup — A code path in our report generator was writing records with an empty event field. This created a second set of base records for the same order — effectively doubling the revenue for affected orders. Fixed the filter logic and cleaned up the duplicates.

Two more fixes shipped:

Ghost/phantom records — This was the biggest contributor to revenue overstatement. When orders are edited after purchase (e.g., items removed or quantities changed), our old sync logic kept the original line items as "ghost" records. These phantom entries inflated gross sales by $5K-$20K per affected shop. We now cross-reference every record against the live Shopify API and remove entries for line items that no longer exist.

Discount allocation — Some orders had discount codes applied at the order level, but the discount amounts weren't being distributed to individual line items in our reports. This made discounts appear lower than they actually were. Added a proportional fallback calculation that correctly allocates discounts even when the raw line-item data is incomplete.

First fix deployed: order sync race condition.

We found that when a new order comes in from Shopify, our system was dispatching the processing message to the queue before the database write completed. This meant our reporting service sometimes read stale or missing data. We reordered the operations so the database write always finishes first — ensuring downstream services always work with fresh, complete data.

Full investigation launched. After analyzing merchant reports, we've confirmed that a code change deployed on March 20 disrupted our sync and sales report pipeline. An initial fix attempt made things worse — it introduced data inaccuracies and further broke the synchronization flow.

We're now building a comprehensive comparison tool that cross-references data across 4 sources — Shopify GraphQL API, ShopifyQL analytics, our database, and the TrueProfit API — to identify every single discrepancy and its root cause.

Your Shopify store data is completely safe. No data has been lost or corrupted — this is entirely within our reporting pipeline. We'll post detailed updates here as we fix each issue.

Incident started. A code change to our sales report pipeline unintentionally disrupted the sync and calculation process, causing data to stop updating for some merchants. We attempted an immediate fix, but it was done incorrectly — leading to data inaccuracies and further disruption to the synchronization flow.

We're aware of the issue and working to understand the full scope of impact.