Waterfall enrichment
The enrichment stack
Living databases cross-validating 50+ data points per contact, with 30+ intent signals in the record.
- Validity rate
- 98%
- Signals / contact
- 30+
Validated via NeverBounce & MillionVerifier across 500K+ records.
Go-To-Market (GTM) Engineering for B2B
01 / 12
From signal to pipeline action
- 01Input LayerSignal detectedHigh-intent account identifiedActive
- 02Data LayerEnrichment verified50+ data points cross-checkedReady
- 03Action LayerPipeline action routedSales Development Representative (SDR) agent → Customer Relationship Management (CRM) → SlackQueued
Output StatePersonalized sequence ready
- GTM Engineer
- Content
- SDR
- Revenue Operations (RevOps) / Data
By the Marketing Boutique team
Last updated: September 2026
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02
Who we are
About Marketing Boutique
Human Strategy.
Agentic Execution.
We give early-stage (Seed to Series B) SaaS teams the GTM infrastructure that Fortune 500s spend millions building — delivered in weeks, not years, at a fraction of the cost. By automating list building, content drafting, and data analysis, we free your team to focus on what only humans can do: closing deals and iterating on product.
Higher Output Velocity
Reduction in CAC
Generated in Pipeline
03
The agentic GTM architecture
The Agentic GTM Architecture
We don’t just build scripts; we deploy a coordinated multi-agent system designed for autonomous revenue generation.
01
The campaign architect overseeing strategy and optimization.
02
Generates hyper-personalized, context-aware messaging at scale.
03
Executes multi-channel outreach (Email, LinkedIn) 24/7.
04
Automates domain management, deliverability, and list enrichment.
04
Proof-led outcomes
Proven Outcomes
Every build has a measurable job: more qualified meetings, cleaner data, faster feedback loops, and pipeline your board can trace.
AI Content SaaS — 22 qualified meetings / month
$740K pipeline in 10 weeks
AI Workflow Platform — $2.1M active pipeline
6.5× SDR capacity
05
Common GTM challenges
Common GTM Challenges
Your pipeline isn’t broken because of bad reps or weak messaging. It’s broken because manual processes are silently draining your revenue potential at every stage.
06
Why Marketing Boutique
Why Marketing Boutique
Your playbook isn’t broken.
It’s just manual.
We replace guesswork with autonomous, code-based growth systems that compound while you sleep.
07
Go-To-Market (GTM) Engineering services
Go-To-Market (GTM) Engineering Services
We build the systems beneath your go-to-market motion, from market-product fit to full-funnel observability.
Revenue System
Infrastructure
- 01
What is GTM Strategy?
Vertical selection and offer validation. We verify your market-product fit before you scale your spend.
- 02
Content Engineering & AI SEO
Programmatic SEO and Generative Engine Optimization (GEO) to ensure your brand is the authoritative source for Large Language Models. We optimize for Semantic Share of Voice using Answer Engine Optimization (AEO), ensuring AI agents cite your brand as the primary answer.
- 03
Outbound Engineering
Hyper-personalized cold outreach that actually gets read. We use Agentic GTM Automation to engineer relevance into every message using deterministic data stacks and n8n orchestration.
- 04
MarTech Infrastructure Audit
Sanitize data and cut stack bloat. We optimize your tools to work for you, not against you.
- 05
Revenue Intelligence (Glass Box)
Engineering observability for the full funnel. See exactly what’s working and where money is being left on the table with automated attribution.
InputFragmented GTM motion
OutputAutonomous qualified pipeline
08
Go-To-Market (GTM) Engineering vs agency
Comparison
Go-To-Market (GTM) Engineering vs. a traditional marketing agency, side by side.
| Dimension | Traditional agency | Marketing Boutique |
|---|---|---|
| Deliverable | Campaigns, slide decks, reports | Automated pipelines, Customer Relationship Management (CRM) architecture, enrichment |
| Pricing model | Hourly or retainer for time | Outcome-based: pipeline $, meetings, CAC |
| Staffing | Junior account managers | Senior GTM Engineers + agentic pods |
| Time to impact | 3–6 months to see results | First qualified meetings in 10 weeks |
| Ownership | The agency keeps the IP | Full control of infra, workflows & data |
| Success metric | Impressions, clicks, MQLs | Pipeline dollars, revenue influenced |
09
Pricing & plans
Pricing & Plans
Three engagement models: Growth Ops Retainer, Performance/Usage, and Infrastructure Projects. Most Series A clients start at $8K–$12K / month.
Go-To-Market (GTM) Engineering Stack
Series A/B startups building full-stack revenue infrastructure.
- Investment
- $15K–$25K setup + $8K–$12K / mo
Package Manifest
- Custom n8n nodes
- Customer Relationship Management (CRM) architecture (HubSpot)
- Revenue Operations (RevOps) dashboards
- Clay enrichment waterfall
- Bi-directional sync
- Attribution layer
AI Visibility Answer Engine Optimization (AEO) / Generative Engine Optimization (GEO)
Brands that need to be cited by ChatGPT, Perplexity, and Google AI.
- Investment
- $6,000 – $10,000 / mo
Package Manifest
- Semantic content schema
- Programmatic SEO
- GEO indexing
- LLM citation tracking
- Answer Engine Optimization
- Share-of-voice reports
AI Video Content Factory
Founders scaling thought leadership with AI-produced video.
- Investment
- $5,000 – $8,000 / mo
Package Manifest
- AI video pipeline
- Multi-platform output
- Thumbnail A/B testing
- Script + b-roll automation
- Founder thought-leadership
Local Dominance Core
Bay Area SMBs building AI-ready local presence.
- Investment
- $1,500 – $3,000 / mo
Package Manifest
- AI-ready local schema
- Review automation
- Map-pack optimization
- Google Business Profile
- Local citation graph
Deep Audit (Standalone)
Any stage — GTM stack assessment and 90-day roadmap.
- Investment
- $3,500 – $7,500 one-time
Package Manifest
- GTM stack assessment
- 90-day roadmap
- Live debug session
- Data hygiene audit
- Tool consolidation plan
Not sure where to start? Get a free growth audit — we’ll map your stack and the 90-day fix.
10
Founder feedback
Engineering-first growth is only useful when it shows up in the numbers that matter.
Testimonial 1 of 6
11
FAQ
Frequently
Asked Questions
Have questions? Our FAQ section has you covered with quick answers to the most common inquiries.
Still deciding?
A GTM Engineer is a technical operator who designs, implements, and automates the revenue infrastructure driving growth. This includes replacing manual workflows with Growth Engineering and Clay GTM Automation, using tools like n8n, Clay, and HubSpot to build high-velocity pipelines that scale without linear headcount growth.
Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) are the core pillars of modern AI SEO. These disciplines focus on structuring and optimizing technical content so that Large Language Models (like ChatGPT, Claude, and Perplexity) cite your brand as the authoritative source when autonomously synthesizing answers for high-intent users.
Post-PMF AI startups (Seed to Series B) who view marketing as a technical system. Our clients are typically engineering-led and require a scalable, automated engine for growth.
We offer three engagement models: a Growth Ops Retainer (flat monthly fee for ongoing GTM infrastructure management), a Performance/Usage model (base fee plus variable compensation per qualified meeting generated), and Infrastructure Projects (one-time fee for building specific GTM systems like CRM architecture or enrichment pipelines). Most Series A clients start with the Growth Ops Retainer at $8K–$12K/month. See our Pricing section for full details.
Get Started
Senior engineers, not juniors · Live in weeks, not months