Attribution, run as revenue intelligence
Marketing attribution consultant: one operator, one number
Built the growth engine that took cnvrg.io to its acquisition by Intel.
I’m Yaniv Goldenberg, a Fractional CMO & Head of Growth. When ad platforms, product analytics and billing disagree, I trace the same customer event through each source, document the gaps and implement the agreed repair. The output is a usable budget decision with its evidence limits, not a promise to identify every touch.
- Elementor100x$200K to $20M ARR as acquisition lead
- Riverside+337%MRR growth driven as fractional growth operator
- Across engagements$100M+in total ad spend managed across roles - every dollar tracked to revenue
From channel spend to a defensible revenue decision
I’m Yaniv Goldenberg, a Fractional CMO & Head of Growth. I lead the attribution work and personally implement the agreed event tracking, data connections and reporting. For SaaS, I connect acquisition and product behavior to subscriptions, MRR, expansion and churn; for commerce, to orders, refunds and contribution margin. To connect attribution to event definitions and revenue data, see full-funnel analytics.
What I implement and how we decide
The first output compares the same conversion definition, customer cohort and time window across campaign, product, CRM and billing records. I document event names, identifiers, duplicate rules, consent conditions and source-to-destination checks, then separate deterministic matches, inferred attribution and unknowns. The GA4 and GTM tracking evidence checker can inspect public setup signals before that work; it cannot certify private event delivery or reconcile your revenue.
The working measurement scorecard
Every attribution metric is logged with its source, a baseline, the eligible cohort, an owner and an observation horizon. Where we cannot observe a value, we keep it unknown. Targets follow from your business data, agreed with you.
| Metric | Definition and denominator |
|---|---|
| Revenue reconciliation | Matched eligible billing or order value / eligible source value; document exclusions |
| Identity coverage | Eligible conversions with deterministic session or account linkage / eligible conversions |
| Unknown attribution | Conversions without sufficient source evidence / eligible conversions; report separately |
| Cohort payback | Measure acquisition cost against realized gross profit for the same acquired cohort |
Two hires, two numbers, zero accountability
Separate suppliers can leave an ownership gap unless diagnosis, implementation and the budget decision have named owners. I can personally lead and build the agreed measurement work so those responsibilities are explicit.
Your actual revenue is a fraction of what both platforms report combined.
Before choosing an attribution model, agree who investigates mismatched records and who reviews the resulting budget recommendation. A dashboard and a channel plan need shared definitions, source checks and a continuing owner.
Last-click attribution is the most common failure. You are running Meta and Google together. Google claims every conversion that touched search. Meta claims every conversion that touched a social ad. Your actual revenue is a fraction of what both platforms report combined. You have no idea which channel actually drove the customer.
Illustrative journey: a B2B buyer sees a LinkedIn ad, reads a case study, searches the brand and converts later. First-touch and last-touch assign different credit. Available CRM and event records can help explain the path, but a credit model does not recover every touch or establish what caused the purchase.
One head, one number
I am not an analytics vendor plus a strategy consultant. I am one operator who owns both.
When I run a growth engagement, I set the channel strategy AND build the measurement infrastructure that validates it. Those two jobs cannot be separated. If you make budget decisions based on broken tracking, the strategy is broken - even if the logic looks sound.
I have managed $100M+ in total ad spend across roles. Every dollar required a defensible answer to where it went. That answer came from server-side tracking, proper identity resolution, and cross-channel attribution models I built and maintained - not from platform dashboards I trusted at face value.
And there are no handoffs. No junior account manager learning on your budget, no telephone game between the strategist who promises and the analyst who delivers. The person who reads your dataLayer is the person who presents the number to your board. An agency promises senior attention; a solo operator structurally cannot give you anything else.
Platform-attributed return, recorded revenue and cash received are different measures. I reconcile the eligible source records using agreed definitions and show unmatched, delayed or refunded transactions separately.
What an engagement looks like
How I run attribution work
Stack audit
I map every tracking touchpoint: pixels, dataLayer, server events, UTM hygiene, CRM sync. I find the gaps before we talk strategy.
Server-side foundation
Where the source systems and consent choices permit collection, I implement and test server-side events, identifiers and deduplication. server-side tracking with proper deduplication so you are not double-counting.
Identity resolution
I connect permitted session, account or customer records where identifiers and source evidence support a match. Inferred connections and unknown identity remain separate from deterministic linkage.
Attribution model selection
Last-click, data-driven, time-decay, position-based - each makes different assumptions. I pick the model that matches your actual sales cycle, not the one that flatters your biggest channel.
Cross-channel reconciliation
Platform-reported conversions vs actual revenue vs CRM. I build the reconciliation layer that tells you which numbers to trust and why.
Decision framework
What does the data tell you to do? I translate attribution output into budget allocation decisions, channel mix changes, and creative strategy.
Scope
What a marketing attribution consultant covers
Included in scope
- GA4 audit and server-side event repair. GA4 audit with purchase capture validation. Meta CAPI implementation and deduplication. Google Ads enhanced conversions. UTM taxonomy design and enforcement. Cross-channel attribution reporting. Budget reallocation decisions based on actual data.
Out of scope
- Platform campaign management is outside this attribution scope unless separately agreed. We scope measurement depth around the decision, available records, cost and implementation effort rather than a universal ad-spend cutoff.
Engagement model
How an attribution engagement actually works
A marketing attribution consultant is not a reporting vendor. The engagement is architecture first, then measurement, then decisions. Here is what that looks like in practice.
Week 1-2: Diagnostic
Before touching anything, I map what you have: your current tag architecture, where data is collected versus where it is lost, how your CRM and ad platforms reconcile (or do not), and the one number your team argues about most. This produces a written gap map, not a slide deck. It is the only way to scope what needs to be built versus what needs to be fixed.
Week 3-6: Foundation build
I personally implement the agreed first-party event, server-side or offline-conversion work where access and permissions support it. For an offline CRM outcome, document the source stage, event time, permitted matching identifiers and duplicate rule. Test an eligible record and a rejected or unmatched case, inspect the destination result and retain unresolved records. A sent request is not proof that a conversion was accepted or caused extra revenue.
Week 7-10: Model calibration + decisions
With clean data in place, we select the attribution model that matches your sales cycle and I test it against your pipeline reality. Last-touch, data-driven, time-decay: these are not philosophical positions, they are bets. The calibration step is where the bet gets checked against what actually happened in your CRM. Then we use the model to make decisions: which channels to scale, which to trim, where the next dollar goes.
Ongoing: Reconciliation cadence
Attribution is not a one-time project. GA4 changes, iOS breaks signals, your sales team adds a new stage. The engagements that stick are the ones with a monthly reconciliation loop: platform-reported versus CRM-reported, anomaly detection, and one clear decision each cycle. That cadence is what turns attribution from a project into institutional memory.
Before you hire
Attribution engagement FAQ
How long does a marketing attribution engagement take?
The diagnostic starts when you need it and is scoped to your stack; it can take as little as a day. The foundation build, calibration and first decisions follow on a timeline set from what the diagnostic finds. If your existing tracking is relatively clean, that compresses. If you are working from broken pixel data with no server-side layer, it takes longer. I give you the honest estimate once I have seen what exists, not before.
What does the client need to commit to?
Access to your ad platforms, GA4, CRM, and a technical contact for access and approvals, plus a developer for application-code changes outside my agreed tracking build. Weekly check-ins of 60-90 minutes during the build phase, then monthly during the calibration cycle. The work does not require a large time commitment from your team, but it does require real access and real decisions. If approvals take weeks, the engagement stalls.
Do you deliver a dashboard or a strategy?
Neither, in isolation. The deliverable is a working measurement system plus the decision process it enables: which channel numbers to trust, how to reconcile platform-reported versus CRM-reported revenue, and the standing logic for budget allocation. If you want a BI dashboard on top of that, I can scope it, but a dashboard on top of broken data is a liability, not an asset.
What is the difference between a marketing attribution consultant and an analytics agency?
Compare the actual proposal: who diagnoses the issue, who personally builds the change, who validates the receiving records and who reviews the budget decision. I can own those agreed responsibilities directly. An agency may also provide diagnosis and implementation; the operating scope matters more than the label.
Do you work with companies outside Israel?
Yes. I work remotely in English with clients outside Israel, with call overlap agreed for the engagement. The implementation must fit the actual systems, access, recipient or customer permissions and applicable regional requirements.
What does a marketing attribution consultant actually do?
How is this different from hiring an analytics agency?
How long does an attribution engagement take?
Do you work with GA4, or do you replace it?
What size company is this right for?
What is included in scope and what is not?
The agreed scope may include GA4 investigation, server-side events, repeated-event checks, enhanced or offline conversion work, UTM rules and cross-channel reporting. I personally perform that work. Campaign operation and additional dashboards are separately agreed; measurement depth follows the buyer decision and available evidence rather than a fixed spend threshold.
Which attribution model do you use, last-click or multi-touch?
We choose a model supported by your sources, sales cycle and decision. Each model assigns credit using assumptions; reconciliation checks those records against CRM or billing. Incremental impact requires a suitable comparison or other defensible method. Modelled and unknown credit remain labeled.
Is there a minimum contract term for an attribution engagement, and how do I end it?
Contract terms, including duration and notice period, are agreed per engagement. I agree attribution scope and capacity for each client or project, and ending a fractional engagement involves no severance. We agree the scope, review points and contract terms before work starts.
Can Yaniv own the data implementation and the growth decision?
Yes. I define the measurement model, implement the agreed tracking and reporting, reconcile it with billing or orders, and use the result to prioritize acquisition, activation and retention work. Engineering access and ownership are agreed first.
Does a dashboard prove that marketing caused revenue?
A reconciled dashboard supports attribution decisions. Causal impact requires a suitable experiment or other defensible identification method. Time-window matches and self-reported sources remain labeled as inferred evidence.
Connected specialties
Start with evidence: the free growth leak audit reads the public fingerprints of your measurement stack and emails you the fix list before we ever talk.
Experience you can check
My Riverside case study describes multi-touch attribution and server-side conversion work used in paid-channel decisions. My Elementor case study describes event tracking, cohort analysis and revenue attribution alongside acquisition and lifecycle work. They show the scope I worked on. Their company growth figures do not measure the isolated return from an attribution implementation.
Elementor: acquisition work and company ARR growth
Next step
Fix the gap between your ad platforms and your revenue
15 minutes. I will tell you whether attribution is your real problem and what fixing it requires.
How attribution breaks
Where the numbers fall apart
Multi-touch models that ignore sales cycles
Illustrative risk: with a 90-day buying cycle, last-touch can assign all credit to a late retargeting interaction while omitting earlier touches. That can distort the budget recommendation. Compare the available path, sales-cycle maturity and model assumptions before changing allocation.
GA4 and CRM reporting different realities
GA4 shows 80 conversions. Salesforce shows 47 closed deals. Nobody investigates the gap. Marketing claims 80 wins. Sales says the leads are bad. The real answer: GA4 fires on form submit, CRM fires on opportunity close. Both correct. Neither comparable. A marketing attribution consultant maps the gap and stops the blame game.
Offline conversions invisible to digital
A sale closed on a call or offline may be absent from the campaign’s conversion record. Where permissions and matching identifiers support it, connect the recorded CRM outcome to the approved offline-conversion process. Report match coverage and unknowns instead of assuming a fixed offline share.
Platform-native attribution vs reality
Meta says a campaign drove 120 conversions. Google says it drove 95. Combined they claim 215. You only closed 80 deals. Both platforms use self-attribution, so overlap is invisible. I reconcile the observed records with CRM revenue and document what remains unmatched. The chosen model assigns credit; it does not prove a channel caused additional revenue.
How Google Analytics attributes conversions: Google Analytics docs · My operating history: Yaniv Goldenberg on LinkedIn
“If two people own two different numbers, nobody owns the number that matters. Attribution isn’t a dashboard - it’s a decision about who’s accountable for revenue.”
Yaniv Goldenberg
Work with Yaniv
Fractional Head of Growth for B2B SaaS, B2C, and e-commerce. Revenue that compounds, not spikes. Any channel, any motion, any stage.