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.
Kansas City, MO
Analytics, Tracking & Data in Kansas City, MO
Measurement for Kansas City stores where a channel can look profitable right up until the freight cost is added back in.
Delivered remotely for brands across Kansas City and Missouri.
Scale · Kansas City
Why Kansas City brands come to us for this
- Real fulfilment cost — carrier, packaging, dimensional weight, shipping subsidy — carried into contribution margin
- Shipping cost broken out by destination zone, which is where heavy-product profitability actually differs
- Wholesale and DTC reported separately, so one pallet order does not flatter a week of consumer marketing
- Server-side GA4 and platform tracking with deduplication across Shopify's checkout and thank-you events
- A written definitions document, because most reporting arguments are about definitions rather than data
For a store shipping heavy goods, most standard ecommerce reporting is misleading by construction. Revenue and ROAS say nothing about a fourteen-pound case going to a far zone at a rate that eats the entire margin on the order. The reporting job in this metro therefore starts by getting real fulfilment cost — carrier charge, packaging, dimensional adjustments, the shipping subsidy your threshold creates — into the same view as channel spend, so profitability is visible at the level where decisions actually get made.
Then there is the wholesale and DTC split. A brand selling to grocery, clinics and distributors alongside a consumer store cannot read a blended number and learn anything. Wholesale orders are large, infrequent, and often the outcome of consumer demand created months earlier by a channel that never gets credit for it. We separate the two in reporting and build a view that shows account acquisition and reorder rate next to consumer metrics, rather than letting one pallet order flatter a week of paid social.
Underneath that sits the plumbing. Server-side tracking through GA4 and the ad platforms, correct handling of Shopify's checkout and thank-you page events, deduplication so a single purchase is not counted three times, consent handling that is defensible, and a definition document so everyone agrees on what a conversion, a new customer and a return actually mean. Most of the disagreements we get called into are definitional, not technical.
Local context
Zone-level margin, because geography costs you money here
Kansas City sits at the crossing of four interstates with major intermodal capacity nearby, which means ground shipping reaches a large share of the country quickly and cheaply from this node — but not evenly. A parcel to Chicago or Dallas is a very different cost from one to Seattle or Miami, and on heavy products that gap decides whether an order was worth having. So we build reporting that carries shipping cost by destination zone into contribution margin, which regularly changes where a brand chooses to spend. It also usually reveals a threshold problem: the free-shipping line that works for close zones is subsidising far-zone orders into a loss. On top of that we set up local versus national reporting, because a market stall, a pickup order and a wholesale delivery inside the metro have completely different economics from a parcel crossing the country, and blending them hides both.
Scope
What Analytics & Data includes
The same standard of work we run for every client — applied to a Kansas City 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 Kansas City store
We do not work off a rate card. Every Kansas City 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 Kansas City — your questions
By bringing carrier cost into the order-level view rather than treating it as a monthly expense line. We pull real charges including dimensional adjustments and surcharges, attach them to orders, and report contribution margin by product, zone and channel. That view usually changes two things quickly: which products get promoted and where the free-shipping threshold sits.
Separate them at the data layer, not with a mental adjustment. Wholesale orders get tagged at source, excluded from consumer channel reporting and given their own view covering account count, reorder interval and revenue per account. That also stops a single large purchase order from making a paid campaign look extraordinary in a week it did nothing.
Partly, and honestly about the limits. We can tag list signups by event, track first orders from those subscribers, and use unique codes or landing pages to attribute what is attributable. What we cannot do is capture the person who tasted something at a stall and searched the brand three weeks later on a different device — so we report that as a known blind spot rather than pretending a model has solved it.
It depends on what the app is reading. Most reporting tools inherit whatever tracking is already installed, so if the underlying events are duplicated, blocked or missing shipping cost, the dashboard presents the same flawed numbers more attractively. We fix the collection layer first. After that, keeping a tool you like is often the right call and we will say so.
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 Kansas City 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.