Tracking Audit & Reconciliation
A full event inventory across GA4, Meta, Google Ads, Klaviyo and Shopify, reconciled against order data to quantify exactly where and how much data is lost.
Chicago, IL
Analytics, Tracking & Data in Chicago, IL
Server-side tracking and reporting for Chicago companies where the argument is not just which channel worked, but which system is telling the truth.
Delivered remotely for brands across Chicago and Illinois.
Scale · Chicago
Why Chicago brands come to us for this
- Reporting reconciled to Shopify first, then to the ERP, with a documented definition per metric
- Freight and cold-pack cost carried into contribution margin instead of averaged away
- Wholesale, EDI, marketplace and direct revenue separated cleanly in one reporting layer
- Server-side tracking and CAPI targeting match quality of eight or better before spend scales
- Cohort views built so the direct channel can be proved additive rather than assumed
In most markets the analytics problem is three dashboards disagreeing about yesterday's orders. In Chicago it is usually four, because there is an ERP in the room too, and it has been the system of record since long before anyone installed GA4. The Monday meeting becomes a debate about whose number is right rather than a decision about the business.
We rebuild the measurement layer underneath everything else. Server-side tracking through a first-party endpoint, Conversions API with real match quality, a documented GA4 event schema, consent mode wired to your CMP, and — the part that matters most here — a reporting layer that reconciles to Shopify and then to the ERP, so finance and marketing stop arguing across a gap neither of them created.
The harder question for a Chicago brand is what you are measuring against. When the same product sells direct, through a regional grocery or hardware chain, through a foodservice distributor and on a marketplace, channel-level ROAS is close to meaningless. Contribution margin by cohort, calculated after freight and returns, is the number that survives contact with a CFO.
Local context
Reconciling a business with four revenue channels
Chicago brands are unusually likely to carry mixed revenue: direct, wholesale on Shopify B2B, EDI to a national retailer, and a marketplace presence someone set up years ago. Each has its own definition of an order, its own timing, and its own cost structure — and freight is genuinely material when the product is heavy or refrigerated. Building reporting that a Chicago operations lead trusts means agreeing definitions first: does an order count when placed, when allocated, or when it leaves the dock in Bolingbrook? Does a wholesale unit count at invoice or at sell-through? We settle those questions in writing, then build the dashboard on top, so the weekly number means the same thing in six months as it does today. That is also what makes cohort-level contribution margin possible, which is the only view that tells you whether the direct channel is genuinely additive or just relocating margin.
Scope
What Analytics & Data includes
The same standard of work we run for every client — applied to a Chicago brand’s realities.
Full service detailServer-Side Tracking
Server-side GTM on a first-party subdomain, resilient to ad blockers and ITP, with deduplication between browser and server events done properly.
Conversions API Integration
Meta CAPI, Google Enhanced Conversions and TikTok Events API with hashed identifiers, targeting event match quality of 8 or above.
GA4 Event Schema
A documented, consistent eCommerce event and parameter specification across every surface, so reports mean the same thing in six months as they do today.
Consent Mode & Privacy
Consent mode v2 wired to your CMP with modelled conversions, plus Shopify's customer privacy API and regional compliance handled correctly.
Executive Reporting Layer
One dashboard for blended MER, contribution margin, cohort LTV, new-versus-returning revenue and channel payback. Reconciled to Shopify, refreshed daily.
Scoped and quoted for your Chicago store
We do not work off a rate card. Every Chicago engagement starts with a fixed statement of work — named deliverables, named dates, one number — written after we have looked at your store, not before. If a smaller first step would serve you better, we will say so.
Get this scopedHow it runs
From kickoff to results
Audit & Quantify
We measure the gap between platform-reported and actual orders per channel. Most stores we audit are losing 15-30% of conversion signal before we start.
Specification
A written measurement plan: events, parameters, identifiers, consent states and destinations. Signed off before implementation begins.
Implement
Server-side container, CAPI, enhanced conversions and consent mode built in a staging environment and validated event by event.
Validate
Order-level reconciliation against Shopify for a full week, plus match-quality checks in each platform. We do not sign off on a screenshot of a tag firing.
Report & Maintain
Dashboards built, team trained, and monitoring in place to alert on event volume anomalies before someone spots them in a monthly report.
Proof
Analytics & Data results
Anonymised under NDA. Figures pulled from the client’s own analytics.
Consumer Electronics & Accessories
~$9M/yr, 210 SKUs, US + AU · Shopify Plus (migrated from BigCommerce)
Meta ROAS had slid from 3.6x to 1.9x in a year and the team had spent twelve months buying new creative to fix it. The real cause was measurement: the BigCommerce checkout dropped 22% of purchase events and the Conversions API had never been installed, so both ad platforms were optimising on incomplete data. The named constraint: peak season was 14 weeks out, and the replatform had to be live and stable well before Black Friday traffic arrived.
1.9x → 3.4xMeta ROAS, once the 22% event gap closed60 days after server-side tracking went live, spend up 18%. Most of that is signal we recovered, not performance we invented — the honest number is the blended CAC below, which is measured against Shopify orders
-32%customer acquisition cost$44 to $30 blended across Meta and Google
4.1s → 1.7smobile LCPdesktop went 2.9s to 1.2s over the same window
+47%peak-season revenueBlack Friday through Cyber Monday, year over year
In their words
Clients on this work
GA4/Shopify gap 14% → under 2%
“Paid audit, and worth every dollar. Forty pages on where our measurement was lying to us — duplicate purchase events, CAPI never configured, GA4 and Shopify off by 14% — each one ranked by the revenue it was hiding. No pitch deck at the end. We fixed six of the items ourselves before we ever signed a retainer.”
FounderHome goods brand, ~$3M/yr · Denver, CO
Verified client, 2026FAQ
Analytics & Data in Chicago — your questions
Usually neither is wrong; they are answering different questions. The ERP typically recognises revenue at invoice or shipment, Shopify at order placement, and the gap widens with backorders and partial shipments. We document which system owns which definition and build reporting that reconciles between them rather than picking a winner arbitrarily.
It can, but only if the definitions are settled first. Wholesale sell-in and retail sell-through are different events and mixing them produces a number nobody trusts. We separate the streams, agree the recognition point for each, and then blend them into a contribution-margin view that finance and marketing can both use.
Because the ad platforms optimise on the signal you send them. Poor event match quality means Meta and Google are effectively guessing who converted, and you are paying for the guess. Fixing server-side tracking and Conversions API first often lifts measured performance by double digits before a single bid changes.
Increasingly yes. State privacy laws now cover a meaningful share of US traffic, and Illinois has its own biometric and privacy exposure that makes casual data handling a bad idea. We wire consent mode to your CMP properly so modelled conversions fill the gap rather than the data simply vanishing from reporting.
Browser tracking loses 15-30% of conversions to ad blockers, ITP and consent rejections. Server-side sends events from your own infrastructure, which recovers most of that signal. Better signal means better algorithmic bidding, so it usually pays for itself in media efficiency within a quarter.
Four to six weeks for a typical Shopify store, including the validation week. Complex setups with subscriptions, multiple markets or a headless front end run six to ten. The audit and specification phase takes about a third of that and is the part that determines quality.
Yes. We use Shopify's Web Pixels API and customer events for checkout tracking, which is the supported path since checkout.liquid was retired. Order-level data comes through the server side, so checkout tracking no longer depends on scripts Shopify will not let you inject.
Next step
Analytics & Data for your Chicago brand.
Thirty minutes with the strategist who would actually run your account. We screen-share your store, read your data live, and tell you the three highest-value things we can see from the outside.
Shopify or Shopify Plus stores doing $150k/mo or moreFounder, CEO or eCommerce lead on the callNo deck and no pitch — we open your store instead
Prefer to write it out? [email protected] gets a real reply the same business day, Mon-Fri, 9am-6pm MT.