Building a Demand Gen Engine from Zero to 150 MQLs/Month

The Problem

A fast-growing European B2B SaaS company had product-market fit and happy customers, but no scalable way to generate new pipeline. Their go-to-market was entirely founder-led sales:

• Zero inbound leads: Website had no conversion paths beyond “Contact Us”
• No marketing infrastructure: No CRM/marketing automation, no tracking, no data
• Manual follow-up: Sales reps manually emailing cold prospects from spreadsheets
• No nurture strategy: Leads went cold if not ready to buy immediately
• Unknown unit economics: No visibility into CAC, conversion rates, or channel performance
• Founder dependency: Growth bottlenecked on founder availability for demos

The founding team knew they needed predictable, scalable lead generation to hit their growth targets, but didn’t know where to start. They needed someone who could both design the strategy AND build the technical infrastructure.

The Approach

Phase 1: Foundation & Strategy (Weeks 1-2)

Market & Buyer Research:

• Interviewed 12 existing customers to understand buying journey and pain points
• Analyzed competitor positioning and content strategies
• Mapped buyer personas and typical buyer journey stages
• Identified key search terms and intent signals

Core Insights:

• Buyers researched 6-8 weeks before engaging sales
• Technical evaluators wanted hands-on product exploration
• Economic buyers needed ROI calculators and case studies
• 73% of traffic was technical (developers, DevOps engineers)

Strategic Framework:

1. Top of funnel: Educational content targeting pain points + search intent
2. Middle of funnel: Product-led conversion (demo videos, ROI tools, comparison pages)
3. Bottom of funnel: Sales enablement (case studies, pricing transparency)
4. Nurture: Multi-track sequences based on engagement and firmographic fit

Phase 2: Technical Infrastructure (Weeks 3-4)

Built the marketing technology stack:

HubSpot Setup:

• Configured Marketing Hub with proper tracking and attribution
• Built custom contact properties for lead scoring and segmentation
• Created lifecycle stage automation (Subscriber → MQL → SQL → Opportunity)
• Integrated HubSpot with Salesforce for sales handoff

Analytics & Attribution:

// Custom multi-touch attribution model
// Tracks full buyer journey from first touch to closed-won

const attributionModel = {
  firstTouch: 0.3,    // First campaign that drove awareness
  leadCreation: 0.2,  // Campaign that converted to lead
  opportunity: 0.3,   // Campaign active when opp created
  closedWon: 0.2      // Campaign active at close
};

// HubSpot workflow to calculate campaign credit
// Runs on deal stage changes and updates campaign ROI reports

function calculateCampaignAttribution(deal) {
  const touchpoints = deal.marketingTouchpoints;
  const dealValue = deal.amount;

  const firstTouch = touchpoints.find(t => t.type === 'first');
  const leadTouch = touchpoints.find(t => t.type === 'lead_conversion');
  const oppTouch = touchpoints.find(t => t.stage === 'opportunity_created');
  const closedTouch = touchpoints.find(t => t.stage === 'closed_won');

  // Distribute revenue credit across touchpoints
  return {
    campaigns: [
      { id: firstTouch.campaignId, credit: dealValue * 0.3 },
      { id: leadTouch.campaignId, credit: dealValue * 0.2 },
      { id: oppTouch.campaignId, credit: dealValue * 0.3 },
      { id: closedTouch.campaignId, credit: dealValue * 0.2 }
    ]
  };
}

Lead Scoring System:

• Behavioral scoring: content downloads, demo requests, pricing page views
• Firmographic scoring: company size, industry fit, technology stack signals
• Engagement scoring: email opens, website visit frequency, content consumption
• Automated MQL threshold with sales notification workflow

Data Enrichment Pipeline:

• Clearbit integration to append firmographic data on form submission
• Automated company size, industry, and technology detection
• Lead routing rules based on enriched data (enterprise vs. SMB)

Phase 3: Conversion Assets (Weeks 5-7)

Built high-converting landing pages in Webflow:

Landing Page System:

1. Product landing pages (3 pages): Feature-specific pages targeting bottom-of-funnel search
2. Resource landing pages (5 pages): Gated content (whitepapers, guides, templates)
3. Comparison pages (4 pages): “Alternative to [Competitor]” targeting competitive search
4. Use case pages (6 pages): Industry and role-specific value propositions

Conversion Optimization Framework:

• A/B tested headlines, CTAs, form lengths, and social proof placement
• Implemented progressive profiling to reduce form friction on repeat visitors
• Added exit-intent popups with alternate offers (newsletter vs. content download)
• Built custom thank-you pages with next-step CTAs and Calendly integration

Example: High-Converting Demo Request Page

Conversion rate improved from 3% to 12% through systematic testing:

Phase 4: Multi-Channel Acquisition (Weeks 8-12)

Launched coordinated campaigns across channels:

Google Ads Strategy:

• Search campaigns: High-intent keywords (solutions, comparisons, alternatives)
• Display remarketing: Multi-stage creative nurture for site visitors
• YouTube pre-roll: Educational content targeting competitor audiences
• Budget allocation: 60% search, 25% remarketing, 15% YouTube

LinkedIn Ads Strategy:

• Sponsored content: Thought leadership articles and case studies
• Lead gen forms: Native LinkedIn forms for gated content (reduced friction)
• ABM campaigns: Account-based targeting of 200 high-fit companies
• Audience segmentation by seniority, role, and company size

Content Marketing:

• Published 2 long-form guides per month targeting specific buyer pain points
• SEO optimization for bottom-of-funnel keywords (implementation guides, comparisons)
• Syndicated content to industry publications for backlinks and awareness

Email Nurture Sequences: Built 8 automated nurture tracks:

1. Educational nurture (7 emails, 3 weeks): For early-stage leads not sales-ready
2. Product nurture (5 emails, 2 weeks): Feature education and use case examples
3. Trial nurture (9 emails, 30 days): Onboarding and activation sequence
4. Competitor comparison (4 emails, 2 weeks): For leads evaluating alternatives
5. Event follow-up (3 emails, 1 week): Webinar/event attendee nurture
6. Re-engagement (5 emails, 3 weeks): Win back cold leads
7. Champion nurture (ongoing): Keep engaged users informed of new features
8. Sales-assist nurture (3 emails, 1 week): Support active sales conversations

Phase 5: Optimization & Scaling (Weeks 13-26)

Continuous optimization based on data:

Channel Performance Analysis:

• Weekly reviews of channel metrics: impressions, CTR, CVR, cost per MQL
• Monthly CAC payback analysis and LTV:CAC ratio tracking
• Identified Google Search as highest ROI channel (3.2x ROAS), scaled budget 4x
• Paused underperforming LinkedIn campaigns, reallocated budget to winners

Landing Page Testing:

• Ran 23 A/B tests across conversion pages
• Tested headlines, imagery, form placement, social proof, CTAs
• Average CVR improvement: 38% across all optimized pages
• Created playbook of winning patterns for future page builds

Automation Refinement:

• Tuned lead scoring model based on MQL→SQL conversion rates
• Adjusted email send times based on engagement patterns (Tuesdays 10am best)
• Implemented lead decay for inactive contacts to keep database clean
• Added win/loss analysis automation to track campaign influence on deals

The Results

Lead Generation Growth

Month 1-2: Infrastructure build, no leads (expected) Month 3: First 18 MQLs from initial campaigns Month 4: 42 MQLs - Google Ads scaling + LinkedIn launch Month 5: 89 MQLs - Content nurture sequences driving conversions Month 6: 150 MQLs - Multi-channel optimization working in sync

6-month totals:

• 449 total MQLs generated
• 127 SQLs (28% MQL→SQL conversion)
• 34 closed-won deals (27% SQL→Customer conversion)
• $2.1M in pipeline generated from marketing

Conversion Performance

• Landing page CVR: 12% average (industry benchmark: 2-5%)
• Email nurture engagement: 28% open rate, 4.2% click rate
• Demo request→demo held: 73% show rate (up from 42% before automation)
• Content download→MQL: 31% conversion within 30 days

Economic Efficiency

• Cost per MQL: Started at $450, optimized to $89 by month 6
• CAC: $2,890 (target: <$3,000)
• CAC payback period: 5.3 months
• Marketing-sourced revenue: 67% of total new business

Channel Breakdown (Month 6 snapshot)

Team & Process Impact

• Sales cycle time: Reduced from 87 days to 61 days (marketing-qualified leads had better context)
• Sales win rate: Increased from 14% to 27% (better lead quality and nurture)
• Founder time: CEO freed from lead gen, focused on closing enterprise deals
• Predictability: Established repeatable playbook for $150K/month in pipeline generation

Technical Highlights

Custom Attribution Tracking

Built custom HubSpot workflow to track multi-touch attribution:

// Workflow: "Calculate Campaign Attribution on Deal Close"
// Trigger: Deal stage = Closed Won

const deal = enrollment.deal;
const contact = deal.primaryContact;

// Retrieve all campaign touches from contact timeline
const campaignTouches = contact.timeline
  .filter(event => event.type === 'campaign_interaction')
  .sort((a, b) => a.timestamp - b.timestamp);

// Identify key touchpoints
const firstTouch = campaignTouches[0];
const leadConversion = campaignTouches.find(t =>
  t.timestamp <= contact.becameLeadDate &&
  t.timestamp >= contact.becameLeadDate - (24*60*60*1000)
);
const oppCreation = campaignTouches.find(t =>
  t.timestamp <= deal.createdDate &&
  t.timestamp >= deal.createdDate - (7*24*60*60*1000)
);

// Distribute revenue credit
const revenueCredit = {
  firstTouch: { campaign: firstTouch.campaignId, credit: deal.amount * 0.3 },
  leadConversion: { campaign: leadConversion?.campaignId, credit: deal.amount * 0.2 },
  oppCreation: { campaign: oppCreation?.campaignId, credit: deal.amount * 0.3 },
  closedWon: { campaign: deal.lastTouchCampaign, credit: deal.amount * 0.2 }
};

// Update campaign revenue tracking
updateCampaignMetrics(revenueCredit);

Progressive Profiling System

Reduced form abandonment by 58% through progressive profiling:

// HubSpot form embed script with progressive profiling logic
// Shows different fields based on known contact data

<script>
  hbspt.forms.create({
    portalId: "PORTAL_ID",
    formId: "FORM_ID",
    onFormReady: function($form) {
      // Check if visitor is known contact
      const hutk = getCookie('hubspotutk');
      const knownFields = getKnownContactFields(hutk);

      // Hide already-known fields
      if (knownFields.includes('email')) {
        $form.find('input[name="email"]').parent().hide();
      }
      if (knownFields.includes('company')) {
        $form.find('input[name="company"]').parent().hide();
      }

      // Show progressive fields for known contacts
      if (knownFields.length >= 3) {
        $form.find('.progressive-field').show();
      }
    }
  });
</script>

Automated Lead Scoring Workflow

Dynamic lead scoring that adapts based on engagement:

// HubSpot workflow: "Calculate Lead Score"
// Trigger: Any contact property change or page view

let score = 0;

// Behavioral scoring
if (contact.downloadedWhitepaper) score += 15;
if (contact.viewedPricing) score += 20;
if (contact.requestedDemo) score += 40;
if (contact.startedTrial) score += 50;
if (contact.pageViews30Days > 5) score += 10;
if (contact.emailEngagement === 'high') score += 15;

// Firmographic fit scoring
if (contact.companySize >= 50 && contact.companySize <= 500) score += 20; // ICP size
if (contact.industry === 'Technology' || contact.industry === 'SaaS') score += 15; // ICP industry
if (contact.jobTitle.includes('Director') || contact.jobTitle.includes('VP')) score += 10; // Seniority
if (contact.technologyStack.includes('AWS') || contact.technologyStack.includes('Azure')) score += 10; // Tech fit

// Recency boost
const daysSinceLastActivity = (Date.now() - contact.lastActivityDate) / (1000*60*60*24);
if (daysSinceLastActivity < 7) score += 10;
if (daysSinceLastActivity < 3) score += 20;

// Update score and trigger MQL if threshold met
contact.leadScore = score;
if (score >= 60 && contact.lifecycleStage !== 'MQL') {
  contact.lifecycleStage = 'MQL';
  notifySalesTeam(contact);
}

Key Learnings

1. Start with buyer research, not tactics: Understanding the buyer journey before building campaigns led to 3x better conversion rates than “best practice” templates.

2. Technical + strategic is a moat: Competitors could copy campaign ideas, but couldn’t replicate the tight integration between strategy, landing pages, automation, and attribution.

3. Attribution drives smarter decisions: Multi-touch attribution revealed Google Search had 4.2x ROI while LinkedIn was 2.1x, enabling confident budget reallocation.

4. Progressive profiling reduces friction: Asking for less information upfront (4 fields vs. 8) increased form submissions by 58% while still capturing data over time.

5. Nurture is where magic happens: 64% of MQLs came from nurture sequences, not direct conversions. Most buyers need 6-8 weeks of education before they’re ready.

6. Content quality > quantity: Publishing 2 deep, buyer-focused guides per month outperformed competitors publishing 10 shallow blog posts.

7. Speed to lead matters: Responding to demo requests within 5 minutes (via automation) increased demo show-rate from 42% to 73%.

When This Approach Fits

This type of end-to-end demand gen build makes sense when:

• You’re relying on founder-led sales and need scalable lead generation
• You have product-market fit but no marketing infrastructure
• You need someone who can both strategize AND implement technically
• You want integrated campaigns, not siloed channel tactics
• You need attribution and unit economics visibility from day one
• Your team doesn’t have time to learn marketing automation tools

Need to build or scale your demand generation engine? A Strategic Sprint can launch your first campaigns, or HubSpot Consulting can build the automation infrastructure to support growth.