Intent signals, scoring, CRM, LinkedIn Ads, attribution: one chain, from target account to signed deal. Freelance GTM Engineer in Paris, formerly at Skello.
Worked with
Target, activate, convert, measure. I build each link and wire them together, so your sales team calls the right accounts at the right time.
Find the accounts with a reason to buy now, not the ones that might be interested.
Reach those accounts where they are, with a message that names the fact you detected.
A CRM that tells the truth, a score your sales team understands, alerts that arrive in time.
Know which campaign produced which deal, not just which lead.
Find the accounts with a reason to buy now, not the ones that might be interested.
Reach those accounts where they are, with a message that names the fact you detected.
A CRM that tells the truth, a score your sales team understands, alerts that arrive in time.
Know which campaign produced which deal, not just which lead.
Every figure comes from a CRM, an ad account or a script I can run again.
annual growth the acquisition system contributed to
Skello · 7 markets
domains scanned in 2 hours to detect who pays for a mapping API
Woosmap · signal detector
cost per lead on a US launch, against a $249 LinkedIn benchmark
Audion · LinkedIn Ads
paid markets taken over without a delivery gap, LinkedIn and Meta
Spendesk · UK, FR, DE, ES
Every project starts with a real acquisition problem. Here is how I solved it, and with which numbers.
Woosmap sells an alternative to Google Maps Platform to retailers and platforms. The best prospect is not the one who might be interested, it is the one already paying a geo bill worth moving. No technographic database on the market can tell you that. I built the detector.
Spendesk sells a spend management platform to mid-market finance teams across Europe. Its Growth Lead left with no replacement, leaving a multi-market paid setup (LinkedIn, Meta, Google) with nobody at the wheel. Take over cleanly first, measure next, expand last.
A simple observation: marketing teams spend thousands on Meta Ads without knowing which leads actually close. I built Optimzd to solve that: a SaaS platform connecting Meta Ads to HubSpot, using AI to optimize attribution and predict which leads will convert. Deployed across 7 countries.
At Skello, I helped build the acquisition system across 7 European markets: reliable server-side tracking, a conversion-focused site redesign, RevOps automations between HubSpot and Salesforce, then CRM and outbound. Collective result: +40% annual growth, and an attribution SaaS, Optimzd, born from that need.
Woosmap sells an alternative to Google Maps Platform to retailers and platforms. The best prospect is not the one who might be interested, it is the one already paying a geo bill worth moving. No technographic database on the market can tell you that. I built the detector.
Spendesk sells a spend management platform to mid-market finance teams across Europe. Its Growth Lead left with no replacement, leaving a multi-market paid setup (LinkedIn, Meta, Google) with nobody at the wheel. Take over cleanly first, measure next, expand last.
A simple observation: marketing teams spend thousands on Meta Ads without knowing which leads actually close. I built Optimzd to solve that: a SaaS platform connecting Meta Ads to HubSpot, using AI to optimize attribution and predict which leads will convert. Deployed across 7 countries.
At Skello, I helped build the acquisition system across 7 European markets: reliable server-side tracking, a conversion-focused site redesign, RevOps automations between HubSpot and Salesforce, then CRM and outbound. Collective result: +40% annual growth, and an attribution SaaS, Optimzd, born from that need.
A graduate of IIM Paris La Défense, I quickly realized the best marketing teams were blocked by tech, and the best developers understood nothing about business. I decided to become both. At Skello, I helped build the acquisition system across 7 European markets: server-side tracking, a conversion-focused site redesign, HubSpot to Salesforce automations, then CRM and outbound. Collective result: +40% annual growth, and an attribution SaaS, Optimzd, born from that need. Today, at Bulldozer, I design ABX machines for B2B SaaS and mid-caps: signals, scoring, CRM, LinkedIn Ads.
I build in code rather than no-code, because a pipeline you can read, test and replay is the only one that survives the departure of whoever built it. What I deliver is yours from day one: repository, documentation, training. If we can't measure it, we don't do it.
My journey on LinkedInIt's not the tool that delivers results, it's how you use it. But here are the ones I work with every day.
Airscale · Pharow · Lusha · FullEnrich · Dropcontact · Sirene & BODACC · France Travail API · DECP · Exa · Apify · Bright Data · Snitcher
LinkedIn Campaign Manager · Matched Audiences · Thought Leader Ads · Lead Gen Forms · Meta Ads & CAPI · Google Ads · Lemlist · Human Linker · n8n
HubSpot Private Apps · Salesforce · Pipedrive · Everwin CXM · Boostr · Attio · Supabase · Postgres · SQLite
GTM server-side · GA4 · PostHog · Conversions API · Optimzd · Power BI · Looker Studio
Python · TypeScript · Next.js · Claude API · MCP · Vercel · Railway · Webflow · Shopify
From the people who've worked with me.
Essential training to get started in the world of AI, very rich content. The trainer is attentive with very hands-on practical exercises. I highly recommend.
Audrey Loudieux
AI Training Participant · Exosphere
Intent signals, scoring, CRM, LinkedIn Ads, attribution: what I learn while building.
AI watch, September 18, 2026: ChatGPT ads land in HubSpot and Shopify, Claude moves to editable documents, and voice agents finally make economic sense.
Anthropic ships Fable 5, the US government bans foreign access 4 days later, and Microsoft drops its own MAI family. The AI watch for June 2026.
Anthropic hits $965B and eclipses OpenAI, Claude Opus 4.8 retakes the coding crown, and OpenAI files its S-1. The AI watch for May 22-29.
What my clients ask before we start working together, and what you type into Google.
A GTM Engineer (go-to-market engineer) builds and runs the technical machine behind B2B acquisition: targeting data, intent signals, scoring, CRM integrations, campaigns and measurement. Where a growth marketer picks the channels, the GTM engineer writes what makes them run together. In practice, I don't recommend a strategy: I code it, wire it to your HubSpot and measure it.
An ABX machine (account-based experience) is a pipeline that starts from a list of target accounts, enriches them, detects buying signals, computes a score, then pushes into the CRM the accounts to call along with the reason for the call. It trades volume for relevance: fewer contacts, but the right moment and a message that names a real fact. I build it in code, one pipeline per client, and your CRM only receives the useful projection.
Clay is excellent for prototyping, expensive at scale, and does not do what it cannot do. I build in code (Python, TypeScript, SQLite or Supabase) with two or three APIs: waterfall enrichment where every value keeps its source and reliability, deterministic scoring you can audit line by line, custom signal detectors. The pipeline belongs to you, it is documented, and it depends on no €700-a-month subscription.
By fetching the data where it lives rather than buying a database. Hiring for a telling role, public tenders, a warehouse project in the regional press, the office suite inferred from DNS records, a mapping API key in a website's source code: each signal is detected with a script, scored with a reliability, and expires over time. For Woosmap, I scanned 322,000 domains in two hours to find who was already paying for a mapping API.
Yes, on the basis of legitimate interest, under three conditions I set before any send: a clear sender identity, an accessible prospecting policy page, and an opt-out mechanism that works and syncs to the CRM. The French CNIL fined Kaspr €240,000 precisely for failing that information duty. I add source traceability for every contact and deletion of the working database at the end of the engagement.
A free 30-minute discovery call to understand your acquisition problem. Then an audit of your CRM and ad accounts, because what they contain changes the strategy in almost every case. Then a plan with scope, budget and timeline, a two-to-three-month build phase, and a run phase where I train your team to take the machine over. Written weekly update, shared Slack, no black box.
Project-based or monthly retainer, depending on scope: a CRM audit is counted in days, a full ABX machine in months. I don't quote a fixed rate before seeing your CRM and your accounts, and the discovery call is exactly for that. What I can tell you upfront: tools are subscribed in your name, never mine, and you leave with the code.
No pitch, no slides. Just 30 minutes to understand your problem and see if I can solve it.
30 min · free · no strings attached