AI marketing audit

$3,000. One Week. Every Automation Gap Mapped.

Before you commit to new tools, new headcount, or an AI vendor’s proposal: a one-week $3,000 AI marketing audit reads your full marketing stack and maps what it actually needs. Every automation gap found. Every opportunity priced by ROI. Clear direction on what to build first and what NOT to build at all. Not a slide deck. Working documents you can hand a developer or run in n8n yourself.

Most marketing stacks have the same problem: too many tools bought at different stages, connected by copy-paste and hope, with no single person who knows what actually fires when a lead converts.

This audit reads the whole thing end to end. Ad accounts, GA4, CRM, automation layer, content pipeline. It finds the gaps, prices the ROI of closing each one, and tells you what to build first and what NOT to build. The output is a 90-day implementation roadmap, an automation readiness score, and a prioritized list of AI opportunities ranked by impact per hour of effort. The free AI Visibility Audit scans your public web surface. This one gets inside the stack.

Investment

$3,000. One time. One week.

AI Marketing Audit
$3,000
one-time assessment
Full stack audit + automation readiness score + AI opportunity map + ROI projections + 90-day roadmap. Delivered in 5 business days. Audit cost offsets against AI Foundation if you move to a retainer within 60 days.
Book the Audit
What is included
5
deliverables
Marketing stack audit. Automation readiness score. AI opportunity map (ranked by ROI). ROI projections per automation with payback periods. 90-day implementation roadmap.
What is NOT included
0
ongoing management
This is a diagnostic, not an engagement. No ad account management. No implementation. No monthly retainer. The roadmap tells you what to build; AI Foundation builds it.
See AI Foundation
The problem

The Stack Grew Faster Than the Measurement Layer

The typical post-PMF SaaS stack has 12-20 marketing tools. Three attribution models that disagree. A paid team running on platform ROAS. A content team posting without a distribution system. Automations that were built two hires ago and nobody has touched since.

The cost of this is invisible until you try to scale. You double the paid budget and CAC goes up. You hire a content lead and output doubles but pipeline stays flat. You ask for a single number on marketing contribution to revenue and get three spreadsheets with different answers. Every one of these is a measurement or automation problem, not a strategy problem.

The audit finds all of them and prices what fixing each one is worth. Most clients find $20-80K per year in recoverable ROI in the first week. That number is not invented; it comes from the gap between your current state and what running automation closes.

Fit

Who this audit is for. Who it is not.

Right fit

B2B SaaS post-PMF spending $20K+ per month on acquisition

Teams with more than 10 marketing tools and no clean attribution layer

CEOs who fired their agency and want to know what to build next

Marketing leaders preparing to hire and wanting to know what the system should look like first

Companies evaluating AI Foundation or AI Premium and wanting a scoped first step

IL SaaS and cyber teams with a fragmented tool stack and no dedicated ops lead to sort it out

Not a fit

Pre-revenue or pre-PMF: no funnel to audit, no automation to map

Anyone who wants a free consultation or strategy call; this is paid diagnostic work

Consumer brands with offline acquisition as the primary channel

Companies where the CEO is not involved: the audit output requires an owner

Deliverables

Five Outputs. All Working Documents.

01

Full marketing stack audit

Every tool in your stack reviewed: ad accounts (Meta, Google), analytics (GA4, attribution), CRM (HubSpot, Salesforce, or equiv), automation layer (n8n, Zapier, Make), and content pipeline. What is connected, what is not, and what is firing wrong.

02

Automation readiness score

A 0-100 score across five dimensions: data quality, integration depth, trigger coverage, human-review loops, and monitoring. Tells you what can run on autopilot today versus what needs a measurement layer first.

03

AI opportunity map

Every identified automation opportunity ranked by ROI per hour of implementation effort. Includes the automation type (n8n workflow, LLM pipeline, agent), the input/output, and the dependency on other items in the map.

04

ROI projections per automation

For each item on the opportunity map: the current cost of the manual process, the automation cost to build, the payback period, and the ongoing value. Conservative numbers based on your actual stack, not benchmarks.

05

90-day implementation roadmap

A sequenced roadmap with weeks 1-4 as immediate wins (low effort, high ROI), weeks 5-10 as infrastructure builds (measurement + core automations), and weeks 11-13 as compound systems. Flagged by whether each item needs a developer or can run no-code.

Timeline

Five Days. Here Is How They Run.

Day 1-2

Stack access and diagnostic interviews

Read access to ad accounts, GA4, CRM, automation tools, and content systems. Two 45-minute interviews: one with the marketing lead, one with whoever manages analytics or ops. No slides needed; we work from live data.

Day 3-4

Opportunity mapping and ROI modeling

Every gap mapped, every automation opportunity priced. ROI model built per item against your actual numbers, not industry benchmarks.

Day 5

Roadmap session and handoff

90-minute working session to walk through findings, rank priorities with you present, and lock the 90-day roadmap. You leave with all five deliverables and a clear first move.

AI marketing audit by Yaniv Goldenberg: $3,000 one-week assessment mapping automation gaps, ROI projections, and a 90-day implementation roadmap
Five deliverables in five days. Automation gaps found, priced, and sequenced into a 90-day roadmap.

Before you commit to new tools or headcount, know exactly what your stack needs. Most stacks have a measurement problem dressed up as a strategy problem.

Proof

The same operator who built Elementor’s engine now audits yours.

Elementor
$200K → $20M ARR
100x growth as acquisition and growth lead. Organic built into the #1 channel without link buying.
Riverside.fm
+337% MRR
Fractional growth operator. First deliverable was multi-touch attribution; paid scaled to $450K/mo only after measurement was clean.
cnvrg.io
Intel acquisition
Inbound up 180% YoY, SDR pipeline up 1,500%. Demand generation through the Intel acquisition.
This vs. alternatives

Why an independent audit beats every other option

OptionWhat you getThe problem
Free AI Visibility AuditPublic surface scan: GEO, schema, citability, titlesCannot access ad accounts, GA4, CRM, or automation layer. Different scope entirely.
Agency AI auditVague deliverables, often a pre-sales exerciseOutput is a recommendation to hire the agency. No independent ROI model.
Marketing consultant strategy call30-90 minutes of opinionsNo data access, no automation map, no priced roadmap. Good diagnosis requires reading the stack.
In-house reviewYour team auditing themselvesSelection bias. The gaps you find are the ones you already knew about.
$3K AI Marketing AuditFull stack audit + 5 working deliverables in 5 daysNone. This is what the others should be.
FAQ

Questions on the AI Marketing Audit

What is the difference between this and the free AI Visibility Audit?

The free audit scans your public web surface: AI crawler access, schema, llms.txt, and title/meta hygiene. The $3,000 audit is a week inside your stack: ad accounts, GA4, CRM, automation tools, and content pipeline. Different inputs, different scope, different outputs. Most clients run the free one first, then book this one when they see the depth they are missing.

What data access do you need?

Read access on: Google Ads, Meta Ads Manager, GA4, your CRM (HubSpot, Salesforce, or equiv), your automation tool (n8n, Zapier, Make), and your content calendar. Write access is not needed for the audit. Everything is reviewed in read-only mode and nothing is changed without a follow-on engagement.

What do I walk away with?

Five deliverables: a full stack audit, an automation readiness score (0-100), an AI opportunity map ranked by ROI, ROI projections per automation with payback periods, and a 90-day implementation roadmap. These are working documents, not a slide deck. You can hand the roadmap to a developer or an n8n freelancer and they will know exactly what to build.

What if I want to implement the roadmap after the audit?

AI Foundation is the natural next step. It takes the roadmap and builds it: measurement layer, automation stack, AI content pipeline, and dashboards. The $3,000 audit cost offsets against Foundation if you move to a retainer within 60 days. Most clients do.

Do I need a technical team to use the output?

Some items on the roadmap need a developer; most do not. The audit flags which is which. No-code automations (n8n, Make, Zapier) are labeled separately from infrastructure builds (server-side tracking, CRM integrations, custom pipelines). You will know what requires engineering before you commit to any item.

How many clients do you take per month?

One new AI audit client per month. The week-long engagement requires full attention; more than one in parallel dilutes the output. If you are outside the current booking window, the contact form goes to the next available slot.

Related

Where the audit fits in the AI Growth Systems ladder

Next step

Book the $3,000 AI Audit

One week. Five deliverables. Every automation gap in your stack mapped and priced. Booking is a 15-minute call to confirm scope and access requirements.