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TrackingConsulting
Now booking · 2–4 day turnaround

Attribution Consulting · Conversion tracking

Recover 40–80% of your Attribution Consulting 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 Attribution Consulting tracking rebuild — in their own words, on camera.

The problem

Why your platforms will never agree on their own

Attribution Consulting-specific issues
Leak #01

Every platform counts on a different clock

Meta reports a conversion back on the impression date and restates history as it learns. Google Ads books it on the click date. GA4 books it on the conversion date. Before anyone deduplicates anything, the same week is already three different weeks.

Leak #02

View-through is counted by some and ignored by others

Meta's default includes a 1-day view, YouTube counts engaged views, GA4 counts none at all. Whether an impression can earn credit is a policy decision, and if you haven't made it, three vendors have each made it for you.

Leak #03

Credit is claimed, not allocated

Meta and Google each report the sale they believe they influenced, in full. Add platform-reported revenue together and you'll exceed the money that reached the bank. That isn't fraud — it's two ledgers with no shared user identifier between them.

Leak #04

Real data loss hides inside the disagreement

Part of the gap is definitional and will never close. Part of it is a purchase event that stopped firing on one payment method or a match key that was never sent. Most teams spend a year arguing about the first and never go looking for the second.

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 Attribution Consulting (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 changes when one number runs the budget

Three numbers with three defined jobs

Server-side

One for allocating budget, one for feeding in-platform optimization, one for diagnosing what happened. Nobody argues about which dashboard is right, because each one is finally being asked the question it can answer.

The gap gets split into two piles

8+ EMQ

A written reconciliation showing how much of the variance is window and view-through policy, and how much is signal we can actually go recover. The second pile is the one worth spending money on.

MER is anchored to margin, not to a benchmark

Deduped

Your blended spend-to-revenue target is derived from contribution margin and payback period, so it reconciles to the P&L instead of to a number someone quoted on a podcast.

Incrementality tests replace opinions

Backend-verified

A geo holdout or platform lift design you can genuinely run, with the sample, duration and read-out rules agreed before the money goes in rather than argued about afterward.

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 Attribution Consulting 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 Attribution Consulting 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 Attribution Consulting 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 Attribution Consulting 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.attribution.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 an attribution engagement produces

Item 01

Cross-platform reconciliation model

Meta, Google Ads, TikTok, Microsoft, GA4 and your order table placed side by side for the same period, same timezone, same currency, with each definitional difference named and quantified.

Item 02

Attribution window and view-through policy

A per-platform decision on click and view windows, written down once and then applied consistently inside the ad accounts and in every report that leaves the team.

Item 03

The measurement charter

Two pages naming the source of truth, the decision metric, who owns each number, and what has to be true before anyone moves budget on the basis of it.

Item 04

Signal-loss audit

Browser, server, consent and CRM signals checked against backend orders using the Source-of-Truth Reconciliation Method, so recoverable loss is separated from the gap that no implementation will ever close.

Item 05

MER and channel target model

A contribution-margin-based blended target with per-channel guardrails, plus the explicit condition under which a platform-reported ROAS number gets overridden.

Item 06

Incrementality test plan

Geo holdout or conversion-lift designs, sized and sequenced by which channel your reconciliation says is most likely overstating itself, with the decision rules written before the test runs.

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

The decision model: three numbers, three separate jobs

This engagement doesn't build a container. What it installs is a hierarchy that tells each number which question it's allowed to answer.

  1. Step 1

    Tier 1: the ledger that settles disputes

    Orders in your store, charges in Stripe or closed-won in the CRM — the one system that reconciles to the bank and outranks every dashboard.

  2. Step 2

    Tier 2: the metric budget moves on

    A single blended number, usually MER read against contribution margin, defined once with its window, timezone and currency written down.

  3. Step 3

    Tier 3: platform numbers, for bidding only

    Meta, Google Ads, TikTok and Microsoft figures are treated as optimization fuel and directional read, never summed into a revenue total.

  4. Step 4

    The variance ledger between the tiers

    Every gap is written down and labeled either definitional attribution difference or recoverable signal loss, and only the second kind gets a budget.

  5. Step 5

    The override rule, agreed in advance

    A written condition for when a platform-reported number is overruled by the ledger, and the named person who is allowed to make that call.

Events and parameters

What actually gets measured, and where each number comes from

Advisory work produces a measurement inventory rather than a tag spec, so this is the list and its provenance.

What we measureDefinition we hold it toWhere the number comes fromDecision it drives
Net revenuePaid orders minus refunds, on order date, one timezoneStore order export or Stripe chargesThe denominator every other number reconciles to
Blended MERTotal paid media spend divided by net revenue, same periodPlatform spend exports plus the ledgerWhether total spend goes up or down
Platform-reported ROASValue each platform claims under its own window and view policyMeta Ads Manager, Google Ads, TikTok, MicrosoftIn-platform bidding and creative calls, not budget splits
Window and view policyClick and view windows chosen per platform, applied everywhereAd account settings, recorded in the charterHow much variance is expected before anyone investigates
New vs returning revenueFirst-time buyer flag taken from the customer recordStore or CRM customer objectWhether acquisition is growing or repeat is carrying it
Signal delivery rateShare of backend orders that reached each platform with match keysServer container logs against the order tableWhether the gap is policy or genuine data loss
Meta Event Match QualityMatch key coverage score per event, trended monthlyMeta Events ManagerWhether match keys need rebuilding before modeling is trusted
Incrementality readGeo holdout or lift result against pre-agreed decision rulesTest design plus the ledgerWhether a channel's claimed credit survives being switched off

Source-of-truth validation

How we check the reconciliation actually holds up

A reconciliation you can't reproduce is an opinion with a spreadsheet attached. Everything here is designed so your own team can re-run it without us.

Source of truthYour order table or CRM closed-won — order date, one timezone, one currency
  • Export the same 30-day period from Meta, Google Ads, TikTok, GA4 and the order table, normalized to one timezone and currency.
  • Restate Meta on conversion date rather than impression date before it is compared with anything else.
  • Model each definitional difference — click window, view-through, reporting date — and record how much of the gap it closes.
  • Trace the unexplained remainder: sample twenty real orders and check whether each one reached each platform at all.
  • Confirm someone outside the project can reproduce every figure in the charter from the exports alone.
  • Re-run the whole reconciliation a month later; a moved explained-share means policy changed or something broke.

Straight talk

When an attribution engagement is the wrong spend

This is advisory work, and advisory work is easy to buy too early.

  • One paid channel, one product, same-day purchase. That's a tracking problem, not an attribution problem — fix the events instead.
  • Your purchase event is visibly broken. Rebuild the signal first; reconciling numbers you know are wrong just confirms it expensively.
  • Nobody in the room can actually move budget on the answer. Without that authority the charter becomes a document everyone ignores.
  • Spend is small enough that misallocating it costs less than the engagement. Blended MER in a spreadsheet is genuinely enough there.

Got questions?

The honest answers.

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

01Can you just make the platforms match?

No, and anyone who says otherwise is selling you something. Meta, Google and GA4 are measuring different things over different windows with different rules about views. The realistic goal is explained variance: you know why each number differs, by roughly how much, and which one to act on. Identical numbers would actually be evidence something is wrong.

02Isn't unattributed revenue the same as lost revenue?

No, and this distinction matters more than almost anything else here. The orders still happened — they're in your store, your bank and your ledger. What you lost is the platform's ability to learn from them and your ability to allocate budget correctly. The cost is real, but it's misallocation and worse optimization, not missing sales.

03Should we just use blended MER and ignore the platform numbers?

MER is the only number that reconciles to the bank, so it belongs in the budget conversation. But it can't tell you which channel to cut, and it moves for reasons that have nothing to do with media. Platform numbers overlap and overstate, but they're what the bidding algorithms actually consume. Use both, for the two different jobs they're each good at.

04Do we need marketing mix modeling?

Usually not yet. MMM wants years of history and real variation in spend across channels to say anything trustworthy, and it costs accordingly. For most mid-market advertisers a reconciliation model plus two or three geo holdout tests answers more of the actual questions for far less. We'll tell you honestly if you're at the scale where MMM starts earning its keep.

05What about modeled conversions — do those count?

Meta's modeling, Google's Consent Mode modeling and GA4's behavioral modeling are all estimates filling gaps left by consent and platform restrictions. They're reasonable in aggregate and directionally useful. What you shouldn't do is reconcile a modeled number to your order table row by row, because there are no rows underneath it.

06Do you implement the fixes, or only advise?

Either. The deliverables are deliberately vendor-neutral so your in-house team or your existing agency can execute them. If you'd rather we rebuild the signal layer ourselves, that's a separate scope with its own price, and you're under no obligation to take it.

07When do we not need this?

If you run one paid channel, sell one product, and people buy the same day they click, you don't have an attribution problem — you have a tracking problem, and it's cheaper to fix the events than to hire someone to think about windows. This engagement earns its money when there are multiple channels, a consideration period, and a real argument happening in your budget meeting.

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 Attribution Consulting 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 Attribution Consulting 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

Bring us the four numbers that don't match

Export the same period from every platform and your order table. We'll show you what's definitional, what's broken, and which number should be driving decisions.

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

95% guarantee · fixed-fee