Parker reconciles Meta, Google, and TikTok claims against Shopify's actual orders. Real lift, de-biased ROAS, daily.
Meta says 4.2x. Google says 3.8x. TikTok claims its share. Sum the platform reports and the attributed revenue runs 30 to 70 percent above what Shopify actually booked.
Brand searches, repeat buyers, and organic demand get rolled into ad-driven conversions. A meaningful slice of every account is non-incremental spend the platforms are happy to claim.
Meta prospecting feeds Google brand. TikTok awareness feeds Meta retargeting. Platform dashboards do not see across each other and cannot reconcile the overlap.
Most teams know last-click is broken. The alternatives required a data team, a holdout, and weeks of reporting. So million-dollar decisions keep running on the wrong number.
Each capability maps to a specific job: attribute across platforms, strip the inflation, reconcile against finance, alert on the gap, and feed the rest of the workforce.
A single attribution graph across Meta, Google, and TikTok, deduped against Shopify orders so no conversion gets counted twice.
Example. Meta 4.2x and Google 3.8x reconciled to one 2.1x blended view
Brand cannibalization, repeat buyers, view-through, and promo pull-forward stripped out layer by layer until only incremental revenue remains.
Example. 4.2x platform ROAS resolves to 1.8x true incremental
Platform-claimed revenue reconciled against Shopify orders every morning. The gap is the inflation number, sized in dollars.
Example. $184K platform-claimed against $112K Shopify-booked, gap logged
When platform claims drift from real lift, the alert fires within 24 hours, not at month-end close.
Example. Meta lift gap widened 14 points overnight, flagged at 7:12 AM
Feeds Felix the de-biased baseline, validates Sam's scenarios, and trusts Dana's reconciled inputs. No silo, no double-counted revenue.
Example. Sam tested a 30% Meta shift; Parker priced incremental, not claimed
One workweek, hour by hour. Specific numbers vary by account.
Pulls overnight platform claims from Meta, Google, and TikTok and matches them order-by-order against Shopify's booked revenue.
Strips brand-search cannibalization out of Google credit. Logs the adjusted lift and the dollars removed.
Detects 18 percent inflation gap on Meta retargeting overnight. Most of the lift is repeat buyers who were already in the funnel.
Felix asks for the de-biased baseline before the weekly forecast. Parker hands over a 1.9x blended ROAS, not the 3.4x the platforms are reporting.
TikTok view-through claims diverged 22 points from Shopify match. Routed to Slack with the channel breakdown attached.
Sam's +30% Meta scenario lands. Parker validates the assumed lift against the last 90 days of incremental data and returns a reality-checked range.
Delivers the weekly attribution recap to Slack. Inflation gap sized in dollars, two divergences logged, one campaign quietly killed for non-incremental spend.
Attribution is not a single number. Parker walks the gap from what the platforms claim to what Shopify actually booked, layer by layer. Stage values below are illustrative; specific numbers vary by account.
Platforms claim
Sum of what Meta, Google, and TikTok report. Includes brand searches, repeat buyers, and view-throughs the platforms counted as their own.
Real lift
Brand cannibalization and repeat-buyer credit stripped out. What remains is closer to genuinely influenced demand, but still not the final number.
Inflation gap
Example dollar gap between platform-claimed revenue and Shopify-booked revenue for the period. The size of the lie, priced.
Reconciled
True incremental ROAS, matched order-by-order against Shopify. The only number to scale against. Felix forecasts on this; Sam tests scenarios against this.
Multi-touch attribution + Shopify order match, recalculated nightly
Parker runs on a purpose-built attribution stack: multi-touch graphs, Shopify-grounded reconciliation, and shared memory across the workforce.
Meta, Google, and TikTok ad platforms via OAuth. Dana feeds reconciled, deduped events so the attribution graph never trains on noise.
OAuth-based, no warehouse copy
Slack for divergence alerts and the weekly recap. Sheets for the reconciled attribution table the finance team actually opens.
Inflation gap delivered as a dollar figure, not a chart
Felix forecasts on Parker's de-biased baseline. Dana keeps inputs clean upstream. Sam validates scenarios against real lift before pricing them.
Shared memory, not message-passing
Multi-touch attribution graph with finance reconciliation. Platform claims matched order-by-order against Shopify and netted of refunds.
Reconciled nightly, calibration sharpens weekly
Ready when you are
The pilot connects your accounts to all seven agents. Parker's first reconciliation lands in under 24 hours.
Looking for something specific? Felix forecasts on real lift →, Dana keeps inputs clean → or Sam tests scenarios →.
