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.
Sacramento, CA
Analytics, Tracking & Data in Sacramento, CA
Tracking for Sacramento merchants whose numbers are distorted by preorders, club rebills and a wholesale side the storefront never sees.
Delivered remotely for brands across Sacramento and California.
Scale · Sacramento
Why Sacramento brands come to us for this
- Preorder revenue reported against the right period, so a September charge for a November shipment stops distorting both months
- Club rebills separated from acquisition, so recurring billing stops inflating the return on last quarter's campaigns
- Tasting-room and farmers-market POS revenue brought into the same reporting frame with a channel attached
- Consent mode v2 wired to your CMP with California opt-out signals honoured and passed on to ad platforms
- Server-side GTM on a first-party subdomain with clean browser-to-server deduplication and a documented event schema
Standard ecommerce reporting assumes an order is placed, paid and shipped in one motion. Very little here works that way. A preorder is charged in September and shipped in November. A club shipment is billed on a schedule with no session and no campaign behind it. A wholesale order arrives through a company account on net terms. Drop those into a default GA4 setup and you get a picture where autumn looks miraculous, February looks dead, and paid media appears to have caused revenue it had nothing to do with.
So the first job is a reconciliation: every event across GA4, Meta, Google Ads, Klaviyo and Shopify counted against actual order data to quantify exactly what is missing and what is double-counted. That is also where the ugly discoveries happen — subscription rebills firing purchase events and inflating campaign returns, preorder revenue landing in the wrong month, POS sales from a tasting room or market stall either absent or arriving with no channel attached.
Then the plumbing. Server-side GTM on a first-party subdomain so ad blockers and browser restrictions stop quietly removing a chunk of your data, Conversions API and Enhanced Conversions with properly hashed identifiers, and deduplication between browser and server done correctly rather than hopefully. On top of that, an event schema written down so that a report means the same thing in twelve months, and reporting that separates one-off purchases, first club shipments, recurring rebills and wholesale — because those four numbers describe four different businesses and averaging them tells you nothing.
Local context
California privacy rules and a multi-channel producer make consent a real design problem
California's privacy regime gives your customers explicit opt-out rights over the sale and sharing of personal information, including an on-site mechanism and honouring browser-level opt-out signals, and it applies to businesses well below enterprise scale. In practice that means consent mode wired properly to your consent tool, with modelled conversions filling the gap rather than a reporting hole nobody mentions, and opt-out choices propagated to your ad platforms instead of ending at the banner. The second local wrinkle is that Sacramento producers are rarely online-only. Revenue arrives through the storefront, a tasting room, farmers markets, a wholesale desk and sometimes a distributor, and only one of those is instrumented by default. We bring POS and B2B revenue into the same reporting frame with channel attached, so when you decide whether the September push paid for itself you are looking at the whole business rather than the fraction that happened to run through a browser.
Scope
What Analytics & Data includes
The same standard of work we run for every client — applied to a Sacramento 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 Sacramento store
We do not work off a rate card. Every Sacramento 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 Sacramento — your questions
Because the rebill is almost certainly being counted as a purchase and attributed to whatever campaign last touched that customer, sometimes months earlier. It is one of the most common distortions in a subscription business, and it leads directly to overspending on channels that produced nothing. We tag recurring orders distinctly at source and exclude them from acquisition reporting, so the campaign numbers describe new customers only.
Consistently, and with the decision written down. Charging in September for a November shipment means order date and fulfilment date differ materially, and picking one silently makes every year-on-year comparison unreliable. We define the treatment with you, apply it identically across GA4, your reporting layer and your finance view, and label it so the person reading the dashboard next year knows which basis they are looking at.
It applies more broadly than most owners assume, and the thresholds turn on revenue and the volume of personal information handled rather than on being a large company. Rather than guessing, the sensible posture is to implement the mechanics — a working opt-out, honouring browser opt-out signals, consent passed to your ad platforms — because they are not expensive to build correctly and are painful to retrofit. Where the answer depends on your specific numbers, that is a question for your counsel, not your agency.
Partially and honestly, which is better than the fiction most dashboards offer. Where the same customer record exists in both, POS and online purchases can be joined so lifetime value reflects the whole relationship. What cannot be claimed is that a specific ad caused a specific in-person sale. We report the overlap plainly — how many online buyers also purchase in person and what that does to their value — rather than inventing an attribution path.
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 Sacramento 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.