Traffic in, revenue out.
Marketing Operations & Martech
The data layer, automation layer, and tooling layer that makes everything else work. Attribution, tracking, CRM, automation, dashboards, and the integrations between them.
- Elementor100x$200K to $20M ARR as acquisition lead
- Riverside+337%MRR growth driven as a growth operator
- Across engagements$100M+ad budgets managed across paid social and search
From the problem to an executable decision
Tools create value when the data, workflow and operating owner fit together. I connect the agreed marketing stack, campaign process, CRM and reporting so the team can execute and see where work or data stops.
- Process and stack
- Source contracts
- Implemented workflow
- Operating cadence
What I lead and implement, and what you receive
| Decision | Work and deliverable |
|---|---|
| Stack inventory | Map each tool to a job, data owner, integration and cost. Identify duplication and missing connections before recommending a replacement. |
| Campaign operations | I implement agreed campaign templates, naming, approvals, workflow connections and reporting. A finished asset has a release owner and a measurable next action. |
| Change control | Document what breaks when a field, integration or definition changes. Keep monitoring and a recovery procedure with the system instead of leaving them in a slide deck. |
A measurement worksheet you can use with your team
Record the definition, source, eligible cohort or period, baseline, owner and review date. Leave unknowns blank; targets are not results.
- Campaign cycle time
- Data freshness by source
- Unresolved operational exceptions
Measure campaign cycle time from the agreed brief to a release-ready asset. If it slows, distinguish approval delays, stale source data and broken connections. Review open exceptions by owner before adding another tool to the stack.
Relevant experience with clear attribution
I am Yaniv Goldenberg, a Fractional Head of Growth & CMO. I lead strategy and personally execute across the revenue funnel. cnvrg.io — growth and go-to-market work My published cnvrg.io case study describes growth and go-to-market work for a technical B2B product: translating the product into buyer-facing messages and acquisition paths. Historical results belong to that engagement and are not a forecast for your business.
At the start, we define the deliverables, the work I personally execute and the dependencies on your team. Access, budget, product truth and message approval come from their responsible owners. The handover records the implementation, checks, continuing owner and decisions still open.
Marketing operations martech that maps spend to revenue

A stack can contain duplicate tools, conflicting definitions or broken handoffs. I personally investigate the source records and implement the agreed fields, connections and reporting. Each output names its source, operating owner and unresolved gaps so the team can review spend and pipeline using compatible definitions.
Agree the source data, required access, validation rules, permitted actions and responsible owner before connecting a workflow.
Keep submitted, approved, paid and refunded states distinct where they exist; reconcile revenue to its agreed source.
Test normal transitions and failed actions. Route duplicates, missing fields and exceptions to a named reviewer.
Use defined rules for routine checks; any separately scoped AI task needs clear boundaries and human approvals. Compare follow-up with a consistently defined baseline.
I first compare the definitions and available records behind conflicting reports. Possible causes include duplicate events, missing sources, different time windows or different commercial states. I led acquisition at Elementor during its reported growth from $200K to $20M ARR; that history informs the work without proving a single operations change caused it.
We sequence the build around the supported constraint. Agree event names, required fields, source ownership, permissions and duplicate handling before connecting systems. I implement the agreed CRM, analytics and workflow changes and test their actual destination state; delivery latency and unsupported cases stay visible.
The reporting separates first-touch, recent-source and modelled credit where evidence supports them. I compare those definitions with accepted opportunities or billing outcomes before recommending a budget change. Attribution does not itself prove which channel caused additional revenue.
Each tool needs a defined job, owner, cost basis and maintenance path. I compare existing capabilities with the workflow before adding or removing software. A small team still needs escalation for access failures, changed APIs and infrastructure work. For implementation context, I consult the GA4 Measurement Protocol guidance for server-side events.
I separate branded and other observed sources, document attribution windows and report qualified pipeline using a consistent definition. My Riverside case reports 337% Net MRR growth during my broader growth work. That experience does not isolate the causal return of an attribution or martech implementation.
A repaired handoff can reduce correction work or reveal an unsupported campaign assumption, but payback needs observed benefits and full costs over a stated window. I retain my historical $100M+ budget-management experience as context and measure each client implementation against its own baseline.
If your stack is fighting you instead of feeding you, that is the work I do. Strong marketing operations martech is not a tool decision, it is a revenue decision, and I build it to be measured.
Related
Frequently asked questions
What does a marketing operations martech engagement actually deliver?
I personally implement the agreed stack connections, source definitions and reporting. Illustrative acceptance check: a demo request keeps its captured source and lifecycle stage, reaches the assigned owner once, and shows an explicit missing-source status when the input is absent. We test a repeated record, a rejected write and an overdue handoff. The delivery records the receiving result, response target, exception owner and maintenance responsibility; an agreed response target is not a proven service level.
How is marketing operations martech different from just hiring an analytics person?
Compare who investigates the inputs, implements the repair and maintains the reporting. I personally perform the agreed diagnosis and build. An analyst may also own those capabilities; we define the split rather than assuming a job title guarantees it.
How long before the martech stack starts paying back?
We agree the implementation milestones and a review window for handling effort, exceptions and commercial outcomes. Record build, tool and maintenance costs alongside observed benefits. Shipping the stack does not guarantee a payback date.
Do I need to rip out my current tools to do this?
Usually not. I start by auditing what you have against four jobs: capture, route, measure, activate. Most stacks have duplicates and gaps, not a need for a full rebuild. I remove tools that overlap, fix the wiring on the ones that earn their place, and only add a tool when an existing one cannot do the job. The goal is lean, not new.
Will this work if I only have a small marketing team?
I can build a focused operating setup for a small team, with agreed responsibilities, documentation and exception handling. Required capacity depends on the integrations and review workload; technical support or an administrator may still be needed.
We already have GA4. Do we need more?
Start by asking which decision GA4 can answer using the available setup. I review event collection, CRM or billing connections and workflow requirements before proposing another tool. Server-side collection can be useful, but it is not a universal prerequisite for every revenue report or a guarantee of accuracy.
Can you work with our existing tools?
Yes. I audit what you have, fix what's broken, and only recommend new tools when the existing stack can't do the job. No rip-and-replace for the sake of it.
What happens on the 15-minute call?
It is 15 minutes with no decks, just a conversation about your growth bottleneck. I will tell you whether this is your next move, or whether your money is better spent elsewhere. You bring one real number and one real problem, and that is all the first call needs.
Are you taking on new clients right now?
I agree the scope, time commitment and availability for each client or project before work starts. To find out where things stand, book a 15-minute call or send a message. I reply within one day.
Is this a fit if we are pre-product-market-fit?
Not automatically. If you are pre-PMF, we first need to establish whether a scoped engagement is appropriate for your funding, product readiness and growth problem. The companies that fit best have product market fit and real traction. Growth work compounds on a real product; it cannot manufacture demand for a broken one.
How do you handle attribution?
I can report observed first-touch and recent-source records alongside clearly labelled modelled credit, pipeline and customer outcomes. We document windows, matching coverage and unknowns. A model assigning credit does not show that a channel caused additional demand.
Is there a minimum term, and how do I end the engagement?
There is no minimum term. I work month-to-month, and either side can end the engagement with 30 days notice. Ending a fractional engagement involves no severance. Scope and exit terms are agreed before we start. If progress stalls, we review the scope and next steps under the agreed contract terms.
Marketing ops is invisible when it works and catastrophic when it doesn't. I build the infrastructure: analytics implementation, server-side tracking, CRM configuration, automation workflows, attribution models, and the dashboards that make data trustworthy. If your marketing team can't answer 'how much revenue did organic generate last month,' this is where we start. To compare workflow cost and benefit assumptions before implementation, see marketing automation ROI calculator.
What's Included
Analytics implementation (GA4, Mixpanel, Amplitude)
Server-side tracking and conversion APIs
CRM setup and lifecycle automation
Marketing automation (n8n, HubSpot, Braze)
Attribution modeling and revenue reporting
Dashboard building and executive reporting
Tool evaluation, migration, and integration
Data hygiene and governance: lead definitions and handoff rules
Track Record
Elementor: $200K to $20M Riverside: +337% Net MRR cnvrg.io: Intel Acquisition
Discuss your growth prioritiesReady to Talk?
15 minutes. No decks. Just a conversation about your growth bottleneck.
Book a 15-Min CallNext step
Let's turn this into measurable revenue
Book a 15-min call. I will tell you whether this is your next move, or whether your money is better spent elsewhere.
“Marketing operations is the plumbing nobody photographs. Get it wrong and every campaign leaks before it reaches the customer.”
Yaniv Goldenberg
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