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TrackingConsulting
Now booking · 2–4 day turnaround

dataLayer Build · Conversion tracking

Recover 40–80% of your dataLayer Build ad revenue.

Done-for-you 1st-party server-side tracking on Meta, Google, TikTok and Microsoft. Built in 2–4 days. You own the entire stack. No monthly SaaS fees.

✓ 30-minute call · No commitment · You leave with a written remediation plan even if we’re not the right fit.

Built in 2–4 daysOne-time fee95% accuracy guaranteed400-day cookie lifetime1st-party server-side

Built on — and certified for — the platforms that matter

Stape

Pro Partner

Meta

Tech Provider

Google

Tag Manager

TikTok

Events API

Microsoft

UET Partner

LinkedIn

CAPI Partner

Pinterest

CAPI Partner

Built on the same partner stack used by enterprise DTC brands.

Ariful Islam — Founder, Tracking Consulting

Meet your consultant

Ariful Islam

Founder · 8+ years in paid media & tracking

Verified earnings

$200K+

earned on Upwork

Top Rated Plus
4.9/5 · 300+

Verify the receipts

You work directly with Arif — no SDR, no account manager.

By the numbers

No fake testimonials. Just the math.

70+

Platforms supported

Shopify · Woo · Magento · BigCommerce · 65 more

8+ / 10

Meta EMQ guaranteed

in writing — keep working free until hit

2–4d

Build to live

accurate data flowing within 7 days

$0

Monthly fees, ever

one-time fixed price · you own the stack

400d

Cookie lifetime

max RFC 6265bis allows · 57× Safari ITP

9

Ad channels covered

Meta · Google · TikTok · MS · LI · Pin · Snap · Reddit · X

95%+

Tracking accuracy

verified vs Stripe · GA4 · ad-platform reports

30 min

Free founder call

no SDR · no pitch deck · written remediation plan

Numbers from realistic engagements. Your specific recovery depends on your iOS share, ad-blocker rate, and current setup — we’ll quantify it on the call.

Real clients · real videos · real outcomes

Don’t take our word for it. Watch the receipts.

Founders, marketers, and agency owners describing the before-and-after of their dataLayer Build tracking rebuild — in their own words, on camera.

The problem

What a missing dataLayer costs you

dataLayer Build-specific issues
Leak #01

Tracking breaks silently on deploy

A trigger keyed to .btn-primary or a form ID stops matching after a redesign. No error is thrown, nothing turns red in GTM, and the first sign is a conversion line trending to zero in a report someone checks monthly.

Leak #02

The items array is wrong, so every ecommerce report is wrong

item_id doesn't match the SKU in your catalog, price includes tax on one event and not another, quantity is missing on add_to_cart. Product-level reporting and Meta or Google catalog matching depend on that array being exactly right.

Leak #03

Every new tag is a fresh archaeology project

Adding TikTok or Microsoft UET means someone re-derives where the order value lives, in a container with 60 variables and no documentation. What should take an hour takes two days and introduces a new selector dependency.

Leak #04

Nobody can tell you what events exist

Three people have touched the container over four years. Some events are named begin_checkout, some checkoutStart, some are pushed twice by two different scripts. There's no single document anyone trusts, so nobody deletes anything.

Who this is for

Honest about who we’re a fit for.

We don’t take every project. Here’s how to tell if we’re right for you.

Good fit

You’re a great fit if…

  • You run dataLayer Build (or are migrating to it)
  • You spend $5K+/month on paid ads (Meta, Google, TikTok, Microsoft, LinkedIn)
  • Your reported ROAS doesn’t match what your bank account is saying
  • You want to own your tracking stack — no monthly SaaS fees forever
  • You have 2–4 days to do this once and never think about it again
Not a fit

Skip us if…

  • You spend less than $500/month on paid ads (browser pixel is fine)
  • You want a SaaS dashboard with monthly fees forever (Triple Whale, Hyros)
  • You need attribution modeling — we fix the data foundation, not multi-touch reports
  • You want a 6-month enterprise consulting engagement (we ship in 4 days)
  • You expect us to manage your ad accounts (we don’t — that’s a different service)

If you’re still unsure, book the call anyway — we’ll tell you straight whether we can help.

Our position

If your reported ROAS disagrees with your bank account, you don’t have an attribution problem. You have a data foundation problem. No SaaS dashboard fixes that — only a rebuilt 1st-party server-side stack does.

Ariful Islam — Founder
The outcome

What a documented dataLayer changes

Tags read data, not markup

Server-side

Triggers fire on named events with typed parameters. A designer can rebuild the entire checkout UI and the tracking keeps working, because nothing downstream cares what the buttons are called.

One spec both your devs and your marketers use

8+ EMQ

The event dictionary is a real document — event names, required and optional parameters, types, examples, and when each fires. It lives in your repo next to the code, so it changes through pull requests rather than folklore.

New channels take an hour, not a week

Deduped

When a clean dataLayer already carries value, currency, transaction_id, items and user identifiers, adding a new ad platform is mapping fields to a tag. The archaeology has already been done once.

Server-side has something worth sending

Backend-verified

A server container can only enrich what it receives. Clean, consistently named events with an intact items array are the prerequisite for CAPI, Enhanced Conversions and offline reconciliation — this is the layer they all sit on.

The full transformation report

Before vs after — built in 2–4 days, accurate data within 7 days

We deliver the 1st-party server-side stack in 2–4 business days. Each metric below measured 7 days pre-launch vs 7 days post-launch using your own ad-platform reports + Stripe + GA4. No 30-day waiting game.

Attribution accuracy

  • Reported ROAS vs Stripe match
    Before60% (35% drift)
    After95%+ match
  • iOS conversion match rate
    Before~58%
    After~92%
  • Cross-domain click-ID retention
    Before~40%
    After~95%
  • Server-attributed conversions
    Before0%
    After100%

Audience quality

  • Meta Event Match Quality
    Before4.5 / 10
    After8+ / 10
  • Cookie lifetime (Safari)
    Before7 days (ITP cap)
    After400 days (max allowed)
  • Lookalike seed-list size
    BeforeShrinking as signal decays
    AfterRebuilt from server-side matches
  • Identity match params sent
    Before1–2 (email maybe)
    After9 (email · phone · IP · UA · click_id · etc.)
  • Retargeting list health
    BeforeDecaying
    AfterCompounding

Bidding performance

  • Smart Bidding stability
    BeforeRetraining weekly
    AfterLocked-in
  • CPA trend
    BeforeDrifts up as signal degrades
    AfterBidding learns from complete data
  • ROAS variance week-over-week
    Before±35%
    After±5%
  • Conversion volume Meta sees
    Before65%
    After95%+

Compliance & ownership

  • GDPR / CCPA audit-ready
    BeforeWeak
    AfterAudit-clean
  • Consent Mode v2 wiring
    BeforeNot configured
    AfterFully wired + verified
  • 3rd-party cookie deprecation ready
    BeforeNo
    AfterYes
  • Data ownership
    BeforeVendor-locked
    After100% yours

Server-side

money events from your backend

8+ / 10

Meta EMQ guaranteed

95%+

tracking accuracy

A typical engagement

The shape of a typical dataLayer Build rebuild

We’re not going to invent a fake testimonial here. Instead — here’s the realistic pattern of what happens, anonymized but accurate to engagements we ship.

Day 0 — They arrive

A 7-figure dataLayer Build store spending ~$25K/month on Meta. Reported ROAS shows 4.1× in Ads Manager. Their bookkeeper’s number says 2.6×. The founder doesn’t know which is real, so they keep doubling down on what looks like a winning campaign — except cash flow tells a different story.

Day 1 — Audit

We screen-share. Within 20 minutes we’ve found the leaks: native pixel firing twice on iOS, CAPI dedup using the wrong event_id (Meta is double-counting), GA4 showing 38% (not set), and the Customer Events API never enabled. The 1.5× ROAS gap explains itself.

Day 2–3 — Build

Server-side GTM container goes live on data.theirstore.com. Meta CAPI rebuilt with full advanced matching. Google Enhanced Conversions wired. TikTok Events API turned on. All event_ids deterministic. iOS recovered.

Day 4 — Launch

Live-fire test purchases through every funnel step. Meta Event Match Quality goes from 4.5 to 8.7 — verified live in Events Manager. They get a Notion runbook + Loom walkthrough so their dev team can extend it.

Day 5–7 — Accuracy

Conversion data starts flowing cleanly. Day 7: reported ROAS reads 2.8× (matches Stripe within 5%). Lookalike audiences grow because Meta finally has clean seed data. Their CAC dashboard makes sense for the first time in a year.

Day 30 — The math compounds

Smart Bidding has 30 days of clean signal. CPA drops 18%. They scale Meta budget 40% because they finally trust the data. Net new revenue from the recovered tracking: roughly $14K/mo above what they were getting before.

Numbers above are realistic averages from engagements we’ve shipped. Your specific recovery depends on your iOS share, ad-blocker rate, and current setup — we’ll quantify it on the call.

The cookie window unlock

400-day cookie lifetime — the longest your browser allows

Default dataLayer Build setups put cookies on a 7–30 day timer. Safari ITP caps client-set cookies at 7 days. That kills your retargeting windows, shrinks lookalike audiences, and starves Smart Bidding of historical signal.

We set 1st-party cookies via HTTP headers on your own subdomain — exempt from ITP’s 7-day cap. Lifetime: 400 days. The maximum Chrome, Firefox and Safari currently permit.

  • 57× longer retargeting window vs Safari default

    Reach users who saw your ad 6 months ago instead of last week.

  • Bigger lookalike seed pools

    More retained users in your custom audience = better lookalike quality on Meta, Google, TikTok.

  • Smart Bidding has 13× more signal history

    Algorithms optimize on 400 days of behavior, not 7 days. CPA stabilizes faster.

  • Critical for high-AOV / long-consideration purchases

    If your average buyer takes 30+ days to convert, default cookies miss them. 400-day cookies don’t.

Cookie lifetime — head to head

How long cookies survive in real-world traffic

Safari ITP (default)7 days
Chrome / Firefox (typical)30 days
Meta default retargeting window90 days
Google Ads default cookie540 days(but capped by browser)
Our 1st-party server-side400 days

400 days is the hard maximum enforced by RFC 6265bis (Chrome 104+, Safari 17+, Firefox 110+). We set it via HTTP Set-Cookie: Max-Age=34560000 on your subdomain. Survives Safari ITP’s 7-day client-side cap.

Under the hood

What’s actually happening on your server-side stack

Six capabilities your default dataLayer Build setup doesn’t have. Built on the same Stape Pro stack used by enterprise DTC brands.

Cookie window

Cookie Keeper

400-day 1st-party cookies

Set via HTTP headers on your subdomain — the maximum browsers allow. Survives Safari ITP’s 7-day cap that kills retargeting.

Ad-block resistance

Custom Loader

Custom-loaded GTM scripts

Your gtm.js and analytics scripts load through a custom path on YOUR domain. uBlock, AdBlock Plus, Brave can’t identify them as trackers.

Attribution

Click ID Restorer

Click ID restoration

fbclid / gclid / ttclid / wbraid recovered from the URL and persisted server-side. Multi-redirect funnels stop dropping attribution. Safari user IDs restored.

Profit signal

POAS Data Feed

POAS — Profit on Ad Spend

Send actual profit data (not revenue) to Meta / Google. Smart Bidding optimizes for the metric that matters: net margin, not gross revenue.

Identity

User ID

Cross-session User ID

Stable userID generated server-side from IP + UA + SSL fingerprint. Stitches anonymous → known → returning visitors across 400 days.

Audience signal

GEO Headers

GeoIP enrichment

Country, region, city, postal code passed to Meta / Google CAPI from your server — without exposing the raw user IP to the browser.

Compliance

Anonymizer

PII hashing by default

Email, phone, name, address are SHA-256 hashed on your server before they leave for Meta or Google. Zero raw PII in transit.

Quality filtering

Bot Detection

Bot traffic detection

Bot/scraper traffic identified at the gateway and blocked from polluting your audiences. Smart Bidding optimizes against humans, not bots.

Reliability

Dedup logic

Browser ↔ server dedup

Deterministic event_id and event_time so Meta / Google never double-count. Your reported ROAS stops contradicting Stripe.

Reputation

Dedicated IP

Dedicated outbound IP

Your sGTM gets a dedicated static IP for outgoing CAPI requests. Better deliverability to Meta, Google, TikTok — no shared-IP noise.

Residency

Multi-region

EU / US region routing

GDPR-conscious stores route their CAPI traffic through EU regions (Stape EU or self-hosted GCR europe-west). No US data hop.

Data warehouse

BigQuery export

BigQuery + Looker dashboard

Server logs + GA4 raw events streamed to BigQuery. Looker Studio dashboard branded for your team. Premium tier.

We’re official Stape Pro partners — every Power-Up above is enabled and configured for you. Or we self-host the equivalent on your Cloud Run / GKE if your traffic justifies the cost crossover. You pick.

Live data flow

What your stack is doing — right now

Every conversion fires through your subdomain, gets enriched with hashed identity params, deduped against the browser pixel, then forwarded to Meta CAPI, Google EC, TikTok Events API and Microsoft UET in parallel.

You see this stream live in your sGTM debug console — not a SaaS dashboard you rent. It’s your data, on your server, on your subdomain.

  • p99 latency< 80ms
  • Avg. event payload9 identity params
  • Browser → Server dedupDeterministic event_id
  • Failure handlingRetry · queue · dead-letter
sgtm-debug · data.data.com
streaming
10:42:18[INFO ]evt=PageView | id=ev_a3f2.. | ua=ios17 | ip_hash=ok
10:42:18[OK ]→ meta.capi status=200 emq_pred=8.6
10:42:18[OK ]→ google.ec status=200 match=enhanced
10:42:24[INFO ]evt=AddToCart | id=ev_b1c8.. | val=$84.00
10:42:24[DEDUP]browser↔server merged on event_id=b1c8..
10:42:24[OK ]→ meta.capi status=200 emq_pred=8.7
10:42:24[OK ]→ tiktok.eventsapi status=200
10:42:31[INFO ]evt=Purchase | id=ev_c9d4.. | val=$184.00
10:42:31[POAS ]profit=$58.42 sent (margin 31.7%)
10:42:31[OK ]→ meta.capi status=200 emq=8.8 ✓
10:42:31[OK ]→ google.ec status=200 ✓
10:42:31[OK ]→ microsoft.uet status=200 ✓
10:42:33[BOT ]blocked: ua=AhrefsBot · 1 evt suppressed
uptime: 99.98%all channels healthy
Every paid-media channel · 1st-party server-side

CAPI / Events API ready for every ad platform you run

One server-side gateway. Every major ad platform fed real conversion data, deduped, with full identity match.

Meta

Conversions API

Server-side

Google

Enhanced Conv.

Server-side

TikTok

Events API

Server-side

Microsoft

UET Server

Server-side

LinkedIn

CAPI

Server-side

Pinterest

CAPI

Server-side

Snapchat

CAPI

Server-side

Reddit

CAPI

Server-side

X / Twitter

Events API

Server-side
What you get

What the dataLayer implementation includes

Item 01

Event dictionary written before any code

Every event your business actually needs, with its parameters, types, whether each is required, and the exact moment it should fire. Reviewed with you first — naming arguments are cheaper on a document than in production.

Item 02

GA4 ecommerce implementation to spec

view_item, add_to_cart, begin_checkout, add_payment_info and purchase with a correct items array — item_id matching your catalog SKUs, item_name, price, quantity, item_category, and consistent currency handling across all of them.

Item 03

Working push snippets for your developers

Real code in your stack's idiom, not pseudo-code — including where the push has to sit relative to the GTM snippet and how to handle events fired before the container loads without losing them.

Item 04

User and consent context on the object

Hashed user identifiers, customer type, login state and the consent state available to tags that need them, defined once so no tag has to scrape a cookie or read a global variable that may not exist yet.

Item 05

Container rebuilt on the new events

GTM triggers and variables migrated off DOM scraping and auto-event listeners onto the named events. Dead tags removed, duplicates consolidated, and every remaining tag named so its purpose is legible.

Item 06

A QA checklist your team can rerun

Per-event validation steps, expected payloads, and the common failure signatures — so a developer can verify tracking before a release ships instead of finding out from a report a month later.

The honest math

Three ways to fix your tracking. One of them makes sense.

Option 1

Hire a senior tracking engineer

$15K–$25Kin dev cost

or 2–4 weeks of senior FTE time

  • 2–4 weeks before anything ships
  • Misses iOS / Safari / dedup edge cases
  • No EMQ guarantee — it’s “done” when they say so
  • Pixel debugging is not their day job

Option 2

Triple Whale / Hyros / Northbeam

$300–$2,000/month forever

$18K–$120K over 5 years

  • You rent a dashboard — they own your data
  • Cancel and you lose attribution overnight
  • Per-event / per-visitor pricing surprises
  • Still doesn’t fix your underlying tracking
Recommended

Option 3 — us

Done-for-you 1st-party server-side

$400–$1,800one-time

pay once · own the stack forever

  • Live in 2–4 days · accurate data within 7
  • iOS / Safari / dedup all handled by default
  • Meta EMQ 8+ guaranteed in writing
  • You own everything — server, container, runbook

We’re upfront: if you have a senior in-house dev with capacity and 4 weeks, hiring is fine. If you spend $1M+/yr on ads and want a SaaS dashboard layered on top, Triple Whale works. For most paid-ad advertisers between, we’re the math that makes sense.

From the founder’s desk
Ariful Islam — Founder
Available now

Ariful Islam

Founder & lead engineer

  • Experience8+ years in tracking
  • Engagements300+ DTC brands shipped
  • Specialty1st-party sGTM · CAPI
  • PartnerStape Pro · Meta Tech

“I’ll personally walk through your tracking on the call. No SDR. No sales pitch.”

I’ve spent 8 years rebuilding tracking for DTC brands, SaaS founders, agencies, and one thing I’ve learned: most tracking problems aren’t technical — they’re trust problems. You don’t know who to believe. Your current vendor swears it’s fine. Meta’s reports look great. Stripe says otherwise.

On our call, I’ll personally show you exactly what’s leaking, exactly what it would cost to recover, and whether you should hire us at all. If your current setup is genuinely fine, I’ll tell you. If a $400 browser-side fix is enough, I’ll say so. No upsell pressure.

Book the call. Worst case, you walk away with a free 47-point audit checklist. Best case, we deliver your 1st-party server-side stack in 2–4 days and your data is fully accurate within 7 days.

Arif— Founder

How it works

Built in 2–4 days. Accurate data within 7.

We deliver the entire 1st-party server-side stack in 2–4 business days. You start collecting accurate, deduped conversion data the moment it goes live — and within 7 days every signal is flowing cleanly to Meta, Google, TikTok and the rest.

1Day 1

Kickoff + audit

30-min call. We map your current pixels, GTM, dataLayer, consent setup, and ad-platform integrations. You get a written report of every leak.

2Day 2–3

Build the stack

Server-side GTM container deployed on your subdomain. Meta CAPI · Google EC · TikTok Events API · Microsoft UET wired. Identity match + dedup configured.

3Day 4

QA + go-live

Live-fire test purchases across every funnel step. Meta EMQ verified at 8+. Tag Assistant + Pixel Helper passes. Side-by-side report delivered.

4Day 5–7

Verify accuracy

Your data flows clean. Within 7 days every signal — Meta, Google, TikTok, Microsoft — is fully accurate. Notion runbook + Loom walkthrough handoff.

Architecture

How the dataLayer sits between your app and every tag

The point is direction of travel. Your application announces what happened; nothing downstream goes looking through markup to work it out.

  1. Step 1

    The app announces, nothing scrapes it

    Pushes happen where the code already knows the truth, after the order API confirms the sale, not on a click of a button that might fail.

  2. Step 2

    A versioned event dictionary holds the contract

    Event names, parameters, types and required fields live in your repo, so they change through pull request review rather than through folklore.

  3. Step 3

    Triggers bind to event names, not selectors

    Every GTM trigger keys off a named event with typed variables, so a design system update cannot silently unbind a money event.

  4. Step 4

    The server container consumes the same shape

    CAPI, Enhanced Conversions and GA4 all read one payload instead of each platform getting its own hand-derived version of the order value.

  5. Step 5

    A QA checklist runs before each release

    Expected payloads per event, so a developer catches a break in staging instead of a marketer noticing a flat line six weeks later.

Events and parameters

The event dictionary we write, in its shipped form

This is the table your developers implement against and your marketers read.

EventFires whenKey parametersSent from
view_itemProduct data resolves, after the route settlesitems[] with item_id, item_name, price, item_category; currency, valueBrowser, app push
add_to_cartThe cart API returns success, not on the clickitems[] with quantity, value, currencyBrowser, app push
begin_checkoutThe checkout route mounts with a cart payloaditems[], value, currency, couponBrowser, app push
add_payment_infoThe gateway accepts the payment methodpayment_type, value, currency, items[]Browser, app push
purchaseThe backend creates the paid ordertransaction_id, value, currency, tax, shipping, items[], event_idServer, browser copy deduped
generate_leadThe form response returns with a lead IDlead_id, value, currency, form_nameBrowser and Server
user_dataIdentity is known at login or checkoutuser_id, hashed email and phone, customer_type, login_stateBrowser, app push
refundThe backend records the refundtransaction_id, value, currency, items[]Server

Source-of-truth validation

How we check the dataLayer before anything is built on it

The items array is where these builds usually fail, and it fails quietly. Everything downstream inherits whatever is wrong here.

Source of truthYour catalog SKUs and your order table: item_id and transaction_id must match them exactly
  • Diff item_id across view_item, add_to_cart and purchase against your product feed SKUs; mismatches break catalog matching.
  • Reload the confirmation page and confirm purchase pushes once per order, with no second event and no new transaction_id.
  • Compare GA4 purchase revenue against your order table, and check tax and shipping are treated the same on both sides.
  • Navigate the SPA by client-side routing only and confirm events carry the new view's data, not the previous page's.
  • Push an event with a required parameter missing and confirm the tag fails loudly instead of sending an empty value.
  • Search the container for CSS-selector triggers and auto-event listeners; on money events the target is zero.

Straight talk

When a dataLayer build is overhead you do not need

The test is whether someone new could add a pixel tomorrow using only your documentation.

  • You run a simple site with one contact form and no ecommerce. A form-submit trigger is fine and this would be overhead.
  • Your platform plugin already pushes GA4-standard names with an items array whose item_id matches your catalog SKUs.
  • You have no developer time for one to three days of implementation. We would write a spec nobody ships, which helps no one.
  • Someone new could add a tracking pixel tomorrow from your existing documentation alone. If that is true, you are done.

Got questions?

The honest answers.

No buzzwords, no upsell. If we don’t know, we say so.

01My Shopify or WooCommerce plugin already pushes a dataLayer. Do I need this?

Sometimes not. Check three things: does item_id match the SKU your ad platforms use in their catalogs, is purchase pushed once with the real order total, and are the event names GA4's standard ones. If all three hold, the plugin is doing its job. In practice the items array is usually where these fall down, particularly on bundles, subscriptions and multi-currency stores.

02Can't GTM just read the values off the page?

It can, and that's exactly the fragility we're removing. A DOM-scraped price breaks when the currency symbol moves inside the span. A click trigger on a class breaks when the design system is updated. Both fail silently. The dataLayer exists so your tracking depends on a contract your developers know about rather than on markup they'll change without warning.

03How much developer time does this take on our side?

For a standard ecommerce or lead funnel, typically one to three days of a developer's time to implement the pushes, spread across a sprint. We write the spec and the snippets; your team places them where the application knows the truth. If your stack is a headless SPA with a custom checkout, budget more — that's where routing and timing get interesting.

04Why does the spec need to live in our repo?

Because that's the only place it changes at the same time as the code. A spec in a Google Doc goes stale the first sprint after handover. In the repo it goes through pull request review, a developer changing the checkout sees it, and you have a history of what the tracking contract was on any given date.

05What about single-page apps where the page never reloads?

Those need explicit handling and it's the most common source of half-working setups. History-change triggers fire before the new view has rendered its data, so events go out with missing or previous-page values. We define push points inside the application's own lifecycle — after the route resolves and the data is available — rather than listening for URL changes.

06When do we NOT need this?

If you run a simple site with one contact form and no ecommerce, a dataLayer is overhead — a form submit trigger is fine and you should spend the money elsewhere. Likewise if your existing pushes are already consistent and documented. The test is whether someone new could add a tracking pixel tomorrow using only your documentation. If yes, you're done.

07Does this have to happen before server-side tracking?

It should. A server container forwards and enriches what it receives; feeding it inconsistent event names and a broken items array just moves the mess downstream at higher cost. In the Source-of-Truth Reconciliation Method this is the mapping stage — you define the real conversion and the shape of its data before you rebuild any transport.

Still have questions? Book a 30-min call — bring them all.

The call

What happens on your free 30-min call

No pitch deck, no SDR, no upsell pressure. Founder-led. Bring your ad-platform screens and your dataLayer Build setup — we’ll work through it together.

Min 1–5

We get the lay of your store

What you sell, what you spend on ads, who handles dev. Quick context-gathering — no questionnaire upfront.

Min 5–15

We audit your tracking live

Screen-share. We open your Meta Events Manager, GTM, and ad reports. You see exactly which conversions are leaking.

Min 15–25

We map a fix

What needs rebuilding, what stays. The exact dataLayer Build setup we'd ship and what it would recover for you.

Min 25–30

Decide. Or don’t.

If we're a fit, we send a 1-page proposal in writing. If not, you walk away with a free remediation plan you can hand to anyone.

No pitch deckFounder-led, not SDRYou leave with a written planZero commitment
Free · 30 minutes · No commitment

Ask your developer for the tracking spec

If there isn't one, that's the project. Bring your GTM container and I'll show you how many of your tags are currently held up by a CSS class.

Free · 30-min consultation · No commitment · Replies in under 2 hours · Available worldwide via WhatsApp

95% guarantee · fixed-fee