Sales playbook from Pierre Fertout, Chief Sales Officer @Weglot
About Pierre
Pierre Fertout leads Sales at Weglot, a fast-growing web translation startup serving 70,000+ global customers. With a background in engineering and prior experience at CoachHub, Pierre is now building Weglot's outbound muscle, combining experimentation, partner plays, and sharp AI workflows.
Outbound is still new at Weglot: until recently, 100% of pipeline came from inbound. But in just a few months, Pierre's early outbound efforts have landed high-value logos, sparked scalable reseller deals, and begun shaping a repeatable process, supported by agency Scalability and tools like Clay, GPT, and lemlist.
10+ years of XP as B2B tech sales leader
Proudest Achievement
Closed a high-value deal with Auchan through signal-based outreach—"perfect timing" triggered by website analysis and personalized messaging.
Turn this playbook into your next action.
About Weglot
Weglot instantly turns any website into a fully translated, SEO-ready, multilingual experience, zero code, zero developer time.
ICP & persona:
- Mid-size companies (2,000–3,000 employees) with international presence
- Roles: Marketing, Digital, Localization
- Agnostic of industry
Deal size & sales cycle:
- €25,000 average ARR
- ~3–4 month sales cycle (shorter for inbound)
Team setup:
- 3 full-stack AEs (2 inbound vs 1 outbound)
- 1 CSM, 1 Partnerships Manager, 1 SE
- New outbound AE joining full-time in Q4 2025
Tools used
lemlist, Clay, HubSpot, GPTs, Perplexity, Mojo, Claap
Outbound target:
- 4,000 prospects contacted each month
- 40 meetings/month (i.e. 1% interest rate)
- Reply rate: ~2–5%
- Conversion rate (meeting → opp): 30–40%
"We don't chase opens. We track replies and meetings. That's what matters."
Lead sourcing and qualification
Pierre and Scalability defined 58 intent-based signals to identify high-potential prospects.
These include:
Top-performing signals
- High traffic from international regions with no translated website (e.g. 20% traffic from Germany, no German site)
- Change in CMS (e.g. switching from WordPress to Shopify)
- Job openings in localization teams
- Following Weglot customers or competitors on LinkedIn
- Website shows signs of scaling but lacks multilingual support
If I see 20,000 monthly visitors from Germany and no German version of the site, that’s a clear opportunity.
Data sources used
- LinkedIn, Sales Navigator
- SimilarWeb, Ahrefs
- Apollo, Clay, lemlist enrichment
- HubSpot sync with customer lists to exclude existing users
We score leads not just on fit—but on current context. That’s how we prioritize.
Outreach strategy
Pierre and Scalability run a multichannel, signal-first approach that adapts to both persona behavior and geography. Their guiding principle: "Sharp, snackable, shareable."
Every touchpoint is intentional, personalized, and part of a connected story.
🔁 Sequence structure
3 cold emails:
- Intro – short, signal-driven hook (e.g. "20% of traffic from Germany, no German site?")
- Follow-up – "Did you see my last email?" + 1 new insight
- Final bump – one-liner recap with clear CTA
3 LinkedIn touches:
- Profile view + connect (no message)
- DM referencing email ("Sent you a quick note via email—was this relevant?")
- Follow-up message or voice note (depending on engagement)
We don’t pitch five times—we build context. Each step references the last. That’s how we feel human.
🌍 Geo-based variations
- In EMEA, LinkedIn often outperforms email. During the first month, their best campaigns ran LinkedIn-only.
- In other regions, email leads with better results.
It’s not one-size-fits-all. We test by region, adapt fast, and double down on what works.
🧠 Personalization tactics
Pierre’s team uses layered personalization: from macro signals to micro cues that connect 1:1.
1. Signal-based company insights
- Language gaps on the website
- CMS changes
- Localization hiring or job posts
- Follows competitors or Weglot clients
- High traffic in new markets
2. Human-level cues
- Same school or background (e.g., ESSEC)
- Former employers in common
- Role-specific pain points (based on LinkedIn activity or past experience)
I always use the school connection. Even if the email is mid, they reply.
🧩 DISC-style copy personalization
Pierre tailors tone and structure based on how the prospect thinks and communicates—what he refers to as a “DISC-inspired approach.” His key insight: some people want logic, others want simplicity. Customize accordingly.
Here’s how he adapts:
DISC Type | Style | Email Format |
|---|---|---|
D (Dominant) | Straight to the point | 1-line value + 3 bullet points + clear CTA |
I (Influencer) | Conversational, friendly | Add light humor, keep it informal |
S (Steady) | Trust-first | Use customer proof, low-pressure ask |
C (Conscientious) | Detailed, logical | Include more data, product explanation, credibility links |
I’m a ‘D’. To sell to me: one sentence of context, three bullets, one CTA. That’s it. But others need more proof, or a friendly tone. AI helps us get the balance right.
Pierre even uses GPT prompts to adjust tone based on DISC-like assumptions from someone's LinkedIn profile, industry, or writing style.
🤖 Tools to scale personalization
Pierre doesn't do this alone. Here’s how his tech stack supports this approach:
- Clay – Enriches data, auto-generates signals (e.g. website gaps, CMS, job posts)
- Lemlist – Injects dynamic variables & sequence logic
- Custom GPTs – Generate personalized email drafts, suggest DISC tone, auto-analyze websites
- Mojo – Post-call follow-up sequence generation (weeks to months)
If I don’t know how to use a tool like Clay, I hire someone who does. Because great personalization at scale is a competitive advantage.
Unique strengths & differentiators
1. Signal-first targeting
Rather than guess fit, Pierre uses deep signals like CMS changes, language gaps, and team hiring to trigger campaigns. These aren’t theoretical—they’re sourced and ranked before outreach starts.
Fundraising is overused. Signals like localization hiring or CMS migration are gold.
2. AI-powered prep & personalization
Pierre built multiple GPTs for:
- Pre-call research
- ABM profiling
- Proposal drafting
- Post-demo follow-up sequences (1 week to 12 months)
Before a meeting, I just enter the prospect’s name and domain, and GPT gives me a full prep sheet in seconds.
He also uses Mojo to auto-generate follow-up email sequences from call recordings.
3. Partnership-powered outbound
Pierre doesn't rely solely on SDR motion. Weglot also runs outbound via:
- Partnership campaigns with resellers and localization agencies
- Bundled sales plays where Weglot is embedded in larger offers
A recent win: major reseller Aptegi closed after a tailored business case.
If you can’t go direct, go through someone who already has trust. Partnerships scale differently.
Dissecting success stories
- Target: Head of Digital at a major retailer (Luxembourg region)
- Signals used: Missing local language, regional presence, news alert
- Channel: Multi-touch: 3 emails + LinkedIn
- Outcome: Meeting booked after 3rd touch
- Why it worked: Timing + high signal match + triangulated personalization
She told me, ‘I never reply to cold emails—but yours hit exactly at the right moment.’
Templates & resources
Favorite intro email snippet
Subject : 20% of your traffic comes from Germany
Hi [First Name],
Noticed your site gets significant traffic from Germany, but there’s no German version yet.
With Weglot, you could go multilingual in 2 clicks—no dev needed.
Here if you'd like a quick walkthrough.
Best,
Pierre
✅ Prompt-driven AI plays
- ABM GPT to prep per-account messaging
- RFP GPT to auto-complete vendor questionnaires
- Post-demo GPT to sequence nurturing emails
I even use AI to adapt tone based on DISC personality. Everyone gets a different flavor.
Turn this playbook into your next action.
Steal & apply these 5 moves from Pierre’s playbook today!
Use signals that aren’t overplayed
e.g. job changes, CMS migration, website gaps
Personalize to the person, not just the company
Same school, job style, DISC type
Build a GPT for pre-call prep
Saves time and improves meetings
Use your agency’s learnings
Scalability brought pre-tested sequences and better deliverability
Warm up all touchpoints
Reference emails in LinkedIn, and vice versa