Hey there,
Matteo here from Kinetyca.
I wanted to share a multi-country outbound system we built for a premium mobility services company.
The numbers: €525k in new sales, 48 deals closed, 1,101 qualified leads across Italy, France, Spain, and the UK.
Here is the exact system we built to make that happen.
THE ACTUAL PROBLEM
Most outbound breaks the moment you try to scale it across markets.
The ICP shifts. The data sources change. The messaging that works in one country falls flat in another.
The mistake most teams make is forcing one global playbook onto very different markets.
We did the opposite.
STEP 1: MARKET DEFINITION BY COUNTRY
Before a single message was sent, each country was defined as its own market.
- Separate ICP logic per country
- Separate buyer roles and decision-maker mapping
- Separate data constraints and sourcing strategy
Italy, France, Spain, and the UK each had their own starting point. Nothing was assumed to translate.
STEP 2: DATA SOURCING AND ENRICHMENT PER MARKET
A dedicated database was built for each country.
- Company sourcing via Apollo and manual research
- List building and scraping via PhantomBuster
- Enrichment, classification, and custom fields via Clay
Every record was validated and cleaned before it touched the outreach layer.
STEP 3: SENDING INFRASTRUCTURE
Delivery was built before volume.
- 76 inboxes across 26 domains
- Deliverability rotations and warmup sequences
- International targeting workflows configured per market
Email via Instantly.ai ran in parallel with LinkedIn flows to reach multiple buyer types within the same account.
STEP 4: 16 SECTOR INITIATIVES
Instead of one broad campaign, 16 sector-specific initiatives were launched.
Each one had its own angle, messaging, and tracking. Underperformers were paused fast. Winners were scaled.
This is how you learn quickly without burning your entire pipeline.
STEP 5: AI FOR PERSONALISATION AND QUALIFICATION
AI handled the bottlenecks, not the decisions.
- First-line personalisation and company research via Clay
- Messaging variations generated dynamically at scale
- Company and response classification automated
Every contact received contextually relevant messaging. No manual research per record.
STEP 6: REPLY ROUTING AND SALES HANDOFF
Replies were classified in real time.
- Positive responses pushed directly into HubSpot
- Tasks created automatically
- Slack notifications triggered instantly
Sales never touched an inbox. They only worked active, qualified conversations.
STEP 7: WEEKLY ITERATION
The system was reviewed every week.
- Performance compared by country and sector
- Messaging adjusted based on reply data
- Weak initiatives refined or cut
Nothing was rebuilt from scratch. Everything improved in place.
THE RESULTS
- €525k in new sales
- 48 deals closed
- 1,101 qualified leads
- 4 countries live
- 16 sector initiatives tested
This is what happens when data, infrastructure, AI, and sales operations are designed to work together from the start.
If you want to see how a system like this could work for your market, book a call with us.
Lawyer by training, then operations at Amazon. Runs delivery: process, documentation and the detail corporates expect.
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