Source / Medium attribution grid with four models, five lookback windows, paid / new-customer filters, and CSV export — the Triple-Whale-equivalent acquisition breakdown, inside your Admaxxer workspace.
Marketing Acquisition is the revenue-by-source, revenue-by-medium view at the heart of Admaxxer’s analytics surface. It ingests every session from the first-party pixel, joins paid spend from Meta, Google, TikTok, and Klaviyo, and pivots everything onto a single source / medium grid. You get one sortable, filterable, exportable table that answers the question every operator asks on Monday morning: which channels brought revenue in last week, and at what efficiency?
Admaxxer ships four attribution models out of the box. last_click is the default because it matches what Meta Ads Manager and Google Ads report natively — it credits the final touch before conversion and keeps your spend-vs-revenue math directly comparable to platform dashboards. first_click flips the credit to the acquisition touch, which is the right lens when you are evaluating top-of-funnel campaigns. linear_all distributes credit evenly across every touch in the journey, paid and organic alike. linear_paid does the same but only across paid touches, which is how most DTC brands audit incremental-paid efficiency.
Every model runs against the same underlying pixel events, so flipping the dropdown re-renders the table instantly without a re-fetch. There is no silent re-weighting, no opaque “data-driven” black box — each model is a documented formula you can reproduce from the raw event stream.
Choose 1 day, 7 days, 14 days, 28 days, or Lifetime as the attribution window. Shorter windows surface the channels that closed this week; longer windows surface the channels that seeded this quarter. Lifetime is the right lens for evaluating cohort LTV against acquisition source — which is where DTC brands usually find the disconnect between “cheap” and “good” channels.
Marketing Acquisition displays the Pixel CVD gap for every source/medium row — the delta between what the ad platform reported and what the first-party pixel observed. A gap under 10% usually means your Conversions API (CAPI) integration is healthy. A gap above 30% is a red flag that platform-reported numbers are inflated or that ad-blocked traffic is distorting the model. The gap column is the fastest way to find which channels are lying to you before you re-allocate budget on bad data.
The paid-only toggle strips organic, direct, and referral rows so you can audit paid efficiency in isolation. The new-customer toggle restricts the table to first-purchase events, which is the right lens for evaluating acquisition channels (not retention channels). The platform multi-select filters to any combination of Meta, Google, TikTok, and Klaviyo — so you can answer “how did Meta + Google do together last week, ignoring TikTok?” in one click.
Every view has a one-click CSV export. The file preserves the currently selected attribution model, window, and filters, and emits all numeric columns as raw floats (no formatted dollar strings), so it drops straight into Excel, Google Sheets, or BigQuery without clean-up.