Trend · 01
AI in lead scoring crosses the majority
61% of B2B teams use AI for scoring (vs 23% in 2024) and improve conversion by 25-30%. AI in scoring has gone from feature to standard.
● GTM Engineering
Leadgen.
We build a leadgen engine that produces qualified leads consistently: multi-source, with AI scoring, sub-minute speed-to-lead, intelligent nurturing and real lead-to-revenue.
The context
Why it matters today more than ever.
Leadgen is where GTM strategy turns into real pipeline. And where most companies break: 79% of leads marketing generates never end up in a sale, and only 13% pass from MQL to SQL. The difference between those that grow and those that don't is operations, not creative campaigns or marketing budget.
Trend · 02
Sub-minute speed-to-lead is the standard
Every extra 10 minutes of waiting reduces qualification chances by 4×. Automatic lead routing and conversational AI are the answer, not more SDRs.
Trend · 03
Intent data > lead volume
Combining intent signals with first-party data improves lead quality by 34% and MQL→SQL conversion by 41%. The «more leads» era is over.
The problem
Where your system always breaks.
Symptoms vary from company to company, but the patterns repeat. These are the four structural pains we find in practically every leadgen audit we run.
01
«Leads» that aren't leads
Any form-fill gets counted as a lead. PDF download, webinar signup, event attendance. Marketing celebrates 500 leads/month that sales converts into 3 deals. And both teams argue about the numbers.
Impact
The SDR loses 4-6 h/day qualifying junk. At €35,000/year, that's €15-23k per rep in wasted time.
02
No shared MQL/SQL definition
Only 37% of organizations have a formal marketing-sales SLA. The rest operate with implicit definitions that differ between teams. «MQL» in marketing is very different from «lead worth pursuing» in sales.
Impact
Without documented alignment, MQL→SQL conversion is 36% worse than with SLA.
03
Horrible speed-to-lead
The lead arrives at 11:00. The SDR sees it at 16:30. Every extra 10 minutes of waiting reduces qualification chances by 4×: and at 24 h, the probability of SQL drops from 53% to 17%.
Impact
Conversion 7× worse than with sub-minute response time. The competitor that responds first closes the deal.
04
Leads that cool off without nurturing
The lead isn't ready today, but could be in 3 months. Without automated nurturing (intelligent sequences, content relevant by stage), they cool off and are lost.
Impact
47% of large purchases come from nurtured leads. Without nurturing, that revenue doesn't exist.
We generate 500 leads a month, and sales converts 3 into deals. And by the time I reply to the lead, they've already talked to the competition.
, What we hear in discovery calls
The cost
What it costs to leave it unfixed.
7×
worse MQL→SQL conversion if you respond to the lead in 24 h instead of in the first hour (53% vs 17%).
Source · MIT Lead Response Study
An uncomfortable conclusion
The cost of poorly operated leadgen isn't what you pay for leads, it's what you don't convert from the ones you already have. Improving MQL→SQL conversion from 13% to 30% multiplies revenue by 2.3× with the same budget.
The solution
A system, not a tool.
The most common mistake when tackling leadgen is treating it as a series of campaigns: a webinar, an ebook, a paid push. The difference between those who produce pipeline consistently and those who don't is building an operational engine: shared definitions, AI scoring, real speed-to-lead, automated nurturing and attribution all the way to revenue.
01
Shared definitions and SLA
MQL and SQL defined with hard criteria (fit + intent + behavior). Written SLA between marketing and sales: response time, ownership, feedback cycle. Without this, everything else fails.
02
Coordinated multi-source
Inbound (organic, paid, content), outbound (cold) and allbound (intent-driven) operating in the same system. A single lead, a single view, regardless of source. Coordination, not silos.
03
AI lead scoring (fit + intent + behavior)
Scoring that combines firmographics (does it fit ICP?) + behavior (which pages did they visit?) + intent (what buying signal do they show?). Top quartile rejects 30% of MQLs before SDR touch.
04
Sub-minute speed-to-lead
Automatic lead routing, instant SDR alerts, conversational AI to qualify inbound on the spot. The goal: contact in under 5 minutes for high-intent leads. Conversion 7× better.
05
Automated intelligent nurturing
Sequences segmented by buyer journey stage and by scoring. Relevant content for each type. Automatic re-engagement when there's a return signal. 47% of large purchases come from here.
06
Lead-to-revenue attribution
Multi-touch attribution from first-touch to closed deal. Dashboards for cost per SQL, per source, per campaign. The final metric is revenue per euro invested, not lead volume.
The tools
2 platforms, one technical decision.
«The goal isn't «more leads». It's «more SQLs produced predictably and at optimizable cost». The tool is a decision derived from the engine design, not the other way around.»
Enginy
European AI-native leadgen platform. Waterfall enrichment across 30+ sources (80% contact discovery vs 40-50% single-source). AI Agent that qualifies conversations autonomously, practically a digital SDR. ISO 27001 and GDPR by design.
Ideal for
When AI Agent autonomy adds value: continuous leadgen with human SDR qualifying afterwards. European companies, regulated sectors, mid-market teams of 5-10 SDRs. When data quality offsets the price.
Apollo
Mainstream leadgen engine with massive database (275M+ contacts, 30M companies). Real free tier to start. Basic sequences, dialer, AI agents and deal management on a single platform.
Ideal for
When you want to validate outbound leadgen without committing budget (real free tier). Companies with global focus or US expansion. Startups and SMBs starting a leadgen engine from scratch. High volume over surgical precision.
03—Our methodology
The process.
A sequence proven in 200+ companies. Each phase has deliverables before moving to the next, and is developed in collaboration with your internal team.
01→
Diagnostic
We audit existing processes and the current stack. We map bottlenecks and optimization opportunities to ensure the success of the following phases.
02→
Planning
We define target architecture, rollout plan, roles, and metrics before getting into the weeds.
03→
Build
We execute in short iterations with your team. We create, adapt, and integrate with your existing tools.
04→
Rollout
We start with a test and expand after validation. We train your team so adoption feels natural.
05✓
Follow-through
We measure and listen to feedback throughout so the result truly becomes yours.
Results
What changes when it works.
A well-designed leadgen engine shows up in three distinct dimensions: marketing stops fighting with sales over lead quality, SDRs chase leads that close, and leadership sees predictable pipeline month after month, not random peaks and valleys.
13% → 30%+
MQL→SQL conversion
Going from sector average (13%) to top quartile (30%+) with AI scoring + SLA + speed-to-lead. Lifts revenue by 18% with just 5 points of improvement.
<5 min
Speed-to-lead
From hours or days to under 5 minutes with automatic lead routing and conversational AI. Conversion 7× better than with 24 h response time. The competitor no longer arrives first.
+50%
Sales-ready leads with −33% cost
With automated intelligent nurturing. Leads not ready today stay warm until they are. 47% of large purchases go through here.
2-3×
Sustained monthly lead generation
Verified result from Enginy customers: «Double or triple monthly lead generation». An engine that produces continuous pipeline, not campaigns with spikes.
Marketing and sales finally don't fight over lead quality. And those who don't buy today stay warm, they come back in 3-6 months with the deal done.
, Head of Marketing, B2B SaaS scale-up
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