The full Triple-Whale-style Summary for DTC operators — eight sections, ~75 KPI tiles, sparkline-on-every-tile, pin-to-top affordance, and four attribution models × five lookback windows. Built for Monday-morning budget decisions.
Marketing Acquisition is Admaxxer’s flagship Summary surface — the full Triple-Whale-style view of every marketing metric that matters to a DTC operator. It ingests every session from the first-party pixel, joins paid spend from Meta, Google, TikTok, and Klaviyo, layers in store revenue + refund + AOV data, and surfaces roughly 75 KPIs across eight thematic sections. Every single tile includes a 7-day sparkline and a one-click pin-to-top affordance so the numbers that matter most to your brand float to the Pinned section and stay there between sessions.
The split is deliberate: /dashboard is the 30-second executive overview (two highlight strips + Get-Connected checklist). /marketing-acquisition is the full Summary with every marketing metric. /dashboard/analytics is the deep web-analytics dashboard. Pick the right surface for the question you’re answering.
Your starred tiles float to the top of the page, scoped per-page. Pin Blended MER, CAPI match rate, Blended ROAS, and New Customers if those are your north stars — they persist per-user and render as the very first block you see on every page load. The pin preference is stored under a page-specific scope (marketing_acquisition) so pins here don’t collide with pins on the /dashboard overview.
User-defined derived KPIs you create from raw inputs. Every DTC brand needs a few bespoke metrics — contribution margin after shipping, first-order net margin, repeat-customer MER, or whatever your operating model calls for. The Custom Metrics section renders them with the same sparkline and pin affordance as every other tile, so your custom math sits alongside the stock metrics without ceremony.
The core marketing-efficiency block. Blended revenue is total store revenue observed by the first-party pixel. Ad spend is the sum of blended paid spend across Meta, Google, TikTok, and Klaviyo for the same window. ROAS is platform-reported return on ad spend. MER (Marketing Efficiency Ratio) is total store revenue divided by total marketing spend — the pixel-backed blended ROAS that Triple Whale popularized. CAC (Customer Acquisition Cost) is ad spend divided by new customers. AOV (Average Order Value) is revenue divided by orders. Orders and New Customers round it out. Every tile respects the active attribution model (last_click, first_click, linear_all, linear_paid) and lookback window (1d, 7d, 14d, 28d, Lifetime).
The top-of-funnel block sourced from the first-party pixel. Sessions, Visitors, Pageviews, Conversion Rate, Bounce Rate, and Average Session Time. This is the cleanest view of whether your site is pulling its weight — a flat conversion rate with rising sessions is a messaging problem, not a traffic problem. The deep site-level drill-down lives on /dashboard/analytics.
The revenue + merchandising block. Gross Revenue, Net Revenue (after refunds), Refunds, AOV, Repeat-Purchase Rate, and Returning-Customer Revenue. These are the numbers that tell you whether your acquisition efforts are stacking or leaking — a healthy MER with a collapsing repeat-purchase rate means you’re buying one-and-done customers, which is an LTV crisis in disguise.
The Meta-platform-native block. Spend, Revenue, ROAS, CPM, CTR, CPA, and CAPI Match Rate. CAPI Match Rate is the killer metric here — it measures the overlap between Meta’s server-side Conversions API events and Admaxxer’s first-party pixel events. Anything below 70% is a measurement emergency, and the tile surfaces the gap before it bleeds through to your ROAS.
The Google-platform-native block, MCC-aware. Spend, Revenue, ROAS, CPC, CPM, Impressions, and Conversions. The cost_micros normalization is already handled — you get raw dollars. If you run an MCC (My Client Center), the section rolls up across child accounts with a drill-down that matches the same sparkline + pin behavior as every other tile.
The blended-profit block. COGS, Shipping, Payment Fees, and a Blended-Profit Proxy. This is where Admaxxer closes the loop from “MER” to “is this campaign actually profitable after the cost of fulfilling the order?” The proxy is deliberately transparent — it’s net revenue minus ad spend minus the expense aggregate, so you can audit every input from the tile itself.
Every KPI tile across all eight sections includes a 7-day sparkline below the number. A flat line means steady-state; a spike means something changed and you should drill in; a slow drift means you’re trending off baseline before it shows up as a headline number. The sparkline is powered by a single time-series pipe that returns daily values for every tile in one query, so the page renders in a single analytics round-trip rather than 75 sequential queries.
Hover any tile in any of the seven non-Pinned sections and a pin icon appears. Click it and the tile joins the Pinned section at the top of the page. Pins persist per-user and are scoped per-page — your /marketing-acquisition pins don’t show up on /dashboard, and vice versa. This is how operators curate their “morning-check” view without committing to a custom dashboard builder.
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 Summary 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.
The Meta Ads section surfaces CAPI Match Rate as a first-class KPI. A match rate above 85% usually means your Conversions API integration is healthy. Anything below 70% is a red flag that platform-reported numbers are inflated or that ad-blocked traffic is distorting the model. The tile is the fastest way to find whether Meta is lying to you before you re-allocate budget on bad data.
When the compare toggle is on, every tile shows a percentage delta against the immediately preceding window of the same length — so a 7-day view compares against the 7 days before that, using the same attribution model and filters. This is apples-to-apples week-over-week health in one glance across all 75 tiles.
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.