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Now booking · 2–4 day turnaround

How we measure accuracy · Conversion tracking

Recover 40–80% of your How we measure accuracy 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 How we measure accuracy tracking rebuild — in their own words, on camera.

The problem

What goes wrong without a defined ratio

How we measure accuracy-specific issues
Leak #01

"Accuracy" usually names neither number

Most accuracy claims never say what was divided by what. With no stated numerator and denominator, any figure at all can be produced and none of it can be checked by you afterward.

Leak #02

Measuring one platform against another platform

Holding Meta's purchase count next to GA4's compares two attribution models. Neither is a record of money received, so the comparison can't settle whether tracking is working.

Leak #03

Counting across two different clocks

Platforms date a conversion to the ad click; your backend dates it to the order. Compare on mismatched timestamps and a perfectly healthy setup looks broken at both edges of the window.

Leak #04

Over-counting gets read as a win

A deduplication failure pushes the platform's number above the backend's, and a team asking "did we recover conversions" will celebrate it. It's the same defect as under-counting, pointed the other way.

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 How we measure accuracy (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 defined ratio changes

You can check the work without asking us

Server-side

The formula, the window and the exclusions are fixed in writing. Export your own orders any month, run the same division, and see whether the number still holds.

Disputes become arithmetic instead of opinion

8+ EMQ

When a figure looks wrong, we go to the rows that failed to match and the reason code on each, rather than trading impressions about whether tracking feels better than it did.

Bidding gets a stable signal, not a one-time jump

Deduped

Holding the ratio near parity month after month matters more to Smart Bidding and Advantage+ than any single reporting change, because the algorithms learn from consistency.

Refunds and test orders stop distorting the read

Backend-verified

Pulling them out before counting means the ratio measures data delivery — not your return rate, and not how many test checkouts your QA team ran last week.

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 How we measure accuracy 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 How we measure accuracy 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 How we measure accuracy 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 How we measure accuracy 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.measurement.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 accuracy measurement produces

Item 01

The ratio, stated per platform

Meta, Google Ads, GA4 and anything else you run each get their own figure. A single blended number hides whichever platform is actually broken.

Item 02

A matched-order export

Your backend orders for the window joined to the platform's received events by transaction ID, with a match or miss flag on every single row.

Item 03

A miss-reason breakdown

Every unmatched order labeled with why: consent denied, event never fired, payload rejected, landed outside the window, or excluded by rule. With counts per reason.

Item 04

The exclusion list, itemized

Test and staff orders, cancellations, refunds inside the window, zero-value orders and internal IPs — listed by order number so you can add them back and re-check.

Item 05

The over-count check

The same join run in reverse: platform events with no matching backend order. That direction is how duplicate fires and phantom conversions surface.

Item 06

A written guarantee scope

One page naming what the 95%+ covers, what it excludes, how it gets re-measured, and what we do if a re-measure comes in under the floor.

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 ratio is built: window, key, exclusions

Accuracy here is one division — conversions the platform received, over real conversions in your source of truth. Everything else is the set of rules that makes both sides countable.

  1. Step 1

    Denominator: real conversions, from one system

    Orders in the store backend, charges in the payment processor, or closed-won deals in the CRM — whichever we named as the source of truth, never a blend of them.

  2. Step 2

    Numerator: events the platform received

    That platform's own count of conversion events it accepted for the window, calculated per platform, excluding modeled or estimated conversions.

  3. Step 3

    Window: dated by the backend, settled 14 days

    Both exports use the backend order timestamp and identical date boundaries, pulled only once the period has been closed 14 days, because platforms keep writing into it.

  4. Step 4

    Match key: transaction ID, value and currency

    A row matches when the same order or transaction ID appears on both sides with identical currency and a value equal within rounding — never on volume or on timing proximity.

  5. Step 5

    Exclusions: itemized, never summarized

    Test and staff orders, cancellations and refunds inside the window, zero-value orders and internal IP traffic come out first, listed by order number so you can put them back.

Diagnostic sequence

Compute your own accuracy ratio, step by step

This needs a spreadsheet and about an hour, and it will tell you whether you have a problem worth paying anyone to fix.

  1. 1

    Pick a month that closed at least 14 days ago

    Anything more recent is still being written into by the platforms, and a perfectly healthy setup will look broken at the edges. Note the exact start and end dates — both exports must use them.

  2. 2

    Export the source of truth, dated by order time

    Shopify order export, Stripe charge list or CRM closed-won report for that window, with order ID, value and currency on every row. This is your denominator's raw material.

  3. 3

    Strip the exclusions, and keep the removed rows

    Take out test and staff orders, anything canceled or refunded inside the window, zero-value orders and known internal traffic. Keep them in a second tab so you can see how much they moved the result.

  4. 4

    Export the platform's conversions with the order ID

    In Meta, Google Ads or GA4, pull that same window's conversions with the transaction or order identifier attached. If your setup never sent that ID, you've found something bigger than the ratio.

  5. 5

    Join on the ID and divide, one platform at a time

    Matched platform events divided by remaining backend rows is that platform's ratio. Don't blend platforms into a single number — a blend hides whichever one is actually broken.

  6. 6

    Run the join in reverse to catch over-counting

    Platform events with no matching backend order mean duplicate fires, a rebill counted as a new purchase, or modeled conversions sitting in your export. Anything above 100% is a failure, not a bonus.

Source-of-truth validation

What we check before certifying a 95%+ result

A ratio clearing 95% isn't enough on its own — it has to be clean in both directions and reproducible by you without us. The figure also has a stated scope: it covers conversion data arriving and matching your backend, not attribution credit, not ROAS, not platform-side modeling, not visitors whose consent denial we honor, and not changes another vendor or a theme update makes after handoff.

Source of truthShopify or WooCommerce orders · Stripe charges · CRM closed-won
  • Both exports cover identical date boundaries, dated by backend order time, on a window that has been closed for at least 14 days.
  • The reverse join is near zero: platform events with no backend order are a dedup failure, and above 100% blocks sign-off.
  • Every unmatched order carries a reason code: consent denied, event never fired, payload rejected, outside window, excluded.
  • The exclusion list is itemized by order number, and the ratio is recomputed with them added back so you see their weight.
  • The ratio is calculated per platform, because a blended figure can clear 95% while one platform sits well below the floor.
  • The scope is written down: what the figure covers, when it gets re-measured, and what we do if a re-measure lands under 95%.

Straight talk

When measuring this formally isn't worth it

The ratio costs real hours to produce, and there are situations where those hours buy you nothing.

  • You already compare monthly orders to platform counts and they land within a few points. You have the measurement — formalizing it changes nothing.
  • One platform, one checkout path, modest spend. A rough manual comparison answers the same question the formal ratio does, for free.
  • Your conversion has no stable transaction ID on both sides yet. Fix that first, because without a match key the ratio can only be estimated.
  • You're mid-migration on the store or the CRM. Measure once the new order pipeline is live, or you'll certify a system you're about to replace.

Got questions?

The honest answers.

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

01What exactly are the two numbers in the ratio?

The numerator is the count of conversions the platform reports receiving for the window. The denominator is the count of real conversions in your source of truth for the same window — orders in the store backend, charges in the payment processor, or won deals in the CRM, depending on what we named in step two. Divide the first by the second.

02Why a 14-day settled window?

Because platforms keep writing conversions into a period for days after the event, so measuring too early undercounts a working setup. We count by the backend's order timestamp, then wait until the window has been closed for 14 days before pulling either export. Both sides get the same date boundaries — that part matters more than the specific length.

03What counts as a match?

The same transaction or order ID present on both sides, with the currency identical and the value equal within rounding. We don't match on volume or on timing proximity, because two events happening to land in the same hour proves nothing. If the ID isn't there, it's a miss and it gets a reason code.

04What do you exclude, and doesn't excluding things flatter the number?

It could, which is why the exclusions are itemized by order number rather than summarized. We exclude test and staff orders, orders canceled or refunded inside the window, zero-value orders, and traffic from internal IPs. You can add any of them back and recompute. If the exclusions are doing heavy lifting in the result, that will be visible.

05Why is above 100% also a failure?

Because the platform can't legitimately receive more real conversions than your backend recorded. Over-count means a browser and server event failed to deduplicate, a tag double-fired, a rebill got counted as a new purchase, or modeled conversions got mixed into a count of received events. We treat it as an equal-severity defect and fix it before sign-off.

06What does the guarantee not cover?

It covers conversion data arriving in the platform and matching your backend. It does not cover attribution credit, ROAS, or where a platform decides to assign a sale. It doesn't cover platform-side modeling, users whose consent choice means we honor a denial and send nothing, platform API outages, or changes another vendor or a theme update makes after handoff. Those are real limits, not fine print.

07When do we NOT need this measured?

If you already export orders monthly and compare them to your platform counts, and they land within a few points of each other, you have the measurement and you don't need us to formalize it. Low spend on a single platform is the same story. The ratio earns its keep when several platforms disagree and nobody can say which one to believe.

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 How we measure accuracy 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 How we measure accuracy 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

Run the ratio on your own numbers first

One month of backend orders and one platform export is enough to tell whether you have a problem worth paying to fix. If you'd rather we ran it, the audit does exactly this and stops there — no build attached.

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

95% guarantee · fixed-fee