Essential definitions for CEOs, growth leaders, and marketing executives navigating revenue systems, MarTech, and AI-powered growth strategies. Compiled by Florian Nègre, Fractional Chief Growth Officer specializing in Financial Services and B2B SaaS.
Last updated: January 2026 | Version Française
A Fractional Chief Growth Officer (CGO) is a senior executive who provides strategic growth leadership on a part-time or project basis, typically working 6-10 days per month with multiple companies.
Key characteristics:
Why companies choose fractional vs. full-time:
When full-time makes more sense: Companies with €30M+ ARR, established product marketing teams, or need for daily on-site presence.
See also: Technical CEO Advisory, RevOps
RevOps (Revenue Operations) is the strategic alignment and integration of Marketing, Sales, and Customer Success teams, processes, and technology to optimize the entire revenue generation lifecycle.
Rather than operating in silos, RevOps creates unified systems for lead management, pipeline visibility, customer lifecycle tracking, and revenue forecasting.
Core components:
Impact metrics: Companies with mature RevOps typically see 15-20% higher revenue growth and 10-15% improvements in customer retention compared to siloed operations.
For Financial Services: RevOps is particularly critical due to regulatory requirements (ESMA for rating agencies, Basel III for banks, PSD2 for payment platforms) requiring tight data governance and audit capabilities.
See also: MarTech, Data Governance, Pipeline Velocity
MarTech (Marketing Technology) refers to the software, platforms, and tools used to plan, execute, measure, and optimize marketing activities.
Typical B2B MarTech stack components:
Common challenge: The average B2B company uses 15-25 different tools, often disconnected. MarTech stack complexity leads to data silos, redundant costs, and integration headaches.
Strategic MarTech architecture focuses on:
See also: Marketing Automation, CDP, Technical CEO Advisory
GTM (Go-to-Market) is the strategic plan for how a company brings a product or service to market, acquires customers, and achieves competitive advantage.
A comprehensive GTM strategy includes:
For spin-offs and new ventures (common in Florian's FinTech background with Shopper, Chiib, Gualet, LendInc), GTM strategy is particularly critical as it determines product-market fit and early traction velocity.
Impact: Effective GTM reduces time-to-revenue and increases capital efficiency—especially important for funded scale-ups with 12-18 month runways.
See also: MQL & SQL, Pipeline Velocity, CAC
Marketing Automation is the use of software platforms to automate repetitive marketing tasks, personalize customer communications at scale, and track engagement throughout the buyer journey.
Key capabilities:
Common platforms: Pardot (Salesforce), Marketo (Adobe), HubSpot, ActiveCampaign, Brevo (formerly Sendinblue)
Expected results: Marketing automation typically delivers 15-20% increase in qualified leads and 10-15% improvement in conversion rates when properly implemented.
Critical success factors:
See also: Lead Scoring, MQL & SQL, Data Governance
MQL (Marketing Qualified Lead) is a prospect who has shown interest through marketing engagement and meets basic fit criteria, but has not yet been vetted by sales.
MQL qualification typically includes:
SQL (Sales Qualified Lead) is an MQL that has been vetted by sales, confirmed to have genuine buying intent, budget, authority, need, and timeline (BANT framework).
Critical metric: MQL→SQL conversion rate typically ranges from 15-30% in healthy B2B funnels. Low conversion rates indicate:
RevOps impact: Companies with strong RevOps alignment typically see 20-25% higher MQL→SQL conversion rates due to clearer definitions, faster routing, and better handoff processes.
See also: Lead Scoring, RevOps, Pipeline Velocity
AI Revenue Systems are integrated platforms and workflows that apply artificial intelligence and machine learning to revenue generation processes, automating repetitive tasks, improving decision-making, and accelerating pipeline velocity.
Key applications:
Applied AI vs. Generic AI Hype: Focus on practical, compliance-aware implementations using tools like ChatGPT, Claude (Anthropic), Perplexity, and industry-specific platforms—not bleeding-edge ML research.
Critical for regulated industries (Financial Services):
See also: Applied AI Apps, Lead Scoring, Data Governance
Applied AI Marketing Applications are fast-shipping, purpose-built tools that leverage AI (Claude, ChatGPT, Perplexity) to solve specific marketing challenges through test-and-learn approaches.
Unlike enterprise platforms requiring months of implementation, these applications are built in days or weeks using modern AI capabilities (Claude Code, API integrations, web automation), allowing rapid experimentation and iteration.
The fast-shipping methodology:
Examples of applied AI marketing apps:
AI-curated B2B growth insights delivered daily. Claude analyzes 100+ sources (industry blogs, VC insights, growth experiments) to surface the most relevant tactical insights for B2B marketers and founders.
Use case: Stay ahead of growth trends without spending 2 hours reading newsletters
Regulatory intelligence radar for Financial Services. Tracks enforcement actions, regulatory changes, and compliance deadlines across ESMA, EBA, SEC, FINRA for banks, fintechs, and rating agencies.
Use case: Proactive compliance monitoring instead of reactive crisis management
Instant access to B2B SaaS and FinTech industry benchmarks. AI-powered dashboards pulling real-time data on CAC, LTV, conversion rates, churn benchmarks by vertical, company size, and geography.
Use case: Data-backed decision making without expensive market research reports
Why this approach works:
Common tools for fast-shipping AI apps: Claude Code (Anthropic), OpenAI API, Perplexity API, Make.com/Zapier (automation), Supabase/Firebase (backend), Vercel/Netlify (hosting)
See also: AI Revenue Systems, MarTech
Data Governance in B2B Marketing is the framework of policies, processes, and controls ensuring data quality, security, compliance, and ethical use across marketing systems.
Essential components:
For Financial Services companies (banks, fintechs, rating agencies), data governance is non-negotiable due to regulatory requirements:
Business impact:
See also: RevOps, AI Revenue Systems, CDP
Lead Scoring is a methodology for ranking prospects based on their perceived value and likelihood to convert, using a points-based system that combines behavioral engagement (explicit scoring) and demographic/firmographic fit (implicit scoring).
Behavioral Scoring examples:
Firmographic Scoring examples:
AI-Powered Predictive Lead Scoring: Advanced implementations use machine learning models analyzing thousands of historical conversions to identify patterns invisible to rule-based systems, typically improving conversion predictions by 20-30%.
MQL threshold: Typically set at 75-100 points, though this varies by sales cycle length and average deal size.
Best practice: Review and recalibrate scoring models quarterly based on actual conversion data.
See also: MQL & SQL, AI Revenue Systems, Marketing Automation
Pipeline Velocity measures how quickly deals move through the sales pipeline and generate revenue.
Formula:
(Number of Opportunities × Average Deal Size × Win Rate) ÷ Sales Cycle Length
This metric is critical for revenue forecasting and identifying bottlenecks in the sales process.
Key drivers:
How to improve pipeline velocity:
RevOps North Star Metric: Teams typically focus on pipeline velocity because it synthesizes multiple revenue drivers into a single, actionable number.
Impact: Companies improving pipeline velocity by 20% see corresponding 15-20% revenue growth within 6-12 months.
CAC (Customer Acquisition Cost) is the total expense required to acquire a new customer.
Formula:
(Total Sales & Marketing Expenses) ÷ (Number of New Customers Acquired)
Typically calculated monthly or quarterly.
Comprehensive CAC includes:
Critical metrics:
How to optimize CAC:
For funded scale-ups: High CAC is acceptable early if LTV supports it, but CAC must decrease as efficiency improves.
Rule of 40: Growth Rate + Profit Margin ≥ 40%
See also: LTV, Attribution Modeling, Pipeline Velocity
LTV (Lifetime Value or Customer Lifetime Value) is the predicted total revenue a company will earn from a customer relationship over its entire duration.
Formula for subscription businesses:
(Average Revenue Per Account × Gross Margin %) ÷ Churn Rate
Example: ARPA €500/month, 80% gross margin, 5% monthly churn = LTV of €8,000
Key components:
Healthy SaaS metrics:
See also: CAC, Pipeline Velocity
Attribution Modeling is the process of determining which marketing touchpoints receive credit for conversions and revenue, enabling data-driven budget allocation and channel optimization.
Common models:
Why it matters for B2B: Companies with long sales cycles (90-180+ days) and multiple touchpoints (15-25 interactions typical) need multi-touch attribution because single-touch models severely distort reality.
Impact: Companies with mature attribution see 15-25% improvements in marketing ROI through better budget allocation.
See also: Marketing Automation, CDP, CAC
A CDP (Customer Data Platform) is a centralized system that collects, unifies, and activates customer data from multiple sources to create a single, persistent customer view accessible to marketing, sales, and service teams.
How CDPs differ:
Core capabilities:
Popular CDPs: Segment, mParticle, Tealium, Adobe Real-Time CDP, Salesforce CDP
ROI typically comes from:
See also: MarTech, Data Governance, RevOps
Technical CEO Advisory is strategic guidance for non-technical CEOs navigating complex MarTech decisions, vendor evaluations, and AI marketing integration.
This service helps CEOs without a technical marketing background make informed decisions about:
MarTech Stack Selection:
Vendor Due Diligence:
AI Implementation Strategy:
Common triggers for Technical CEO Advisory:
Strategic positioning: This service often serves as an entry point for deeper engagements (Fractional CGO, RevOps Architecture) once trust and strategic alignment are established.
Typical engagement: 2-4 focused advisory sessions over 4-8 weeks, deliverables include decision frameworks, vendor comparison scorecards, implementation roadmaps, and risk assessments.
See also: Fractional CGO, MarTech, Applied AI Apps
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