AI-Driven Export Lead Generation
Qualified international enquiries grew from 15 to 52 per month within 90 days; prospecting time fell from 40% to 12% of hours.
The challenge
Export pipeline growth was gated by how many hours three people could spend finding and contacting the right buyers — a ceiling that was approaching fast.
The problem was not that the team lacked effort — it was that their effort was allocated to the wrong activities. Research and outreach are systematically automatable with the right tools and targeting logic. Qualification, relationship development, and commercial negotiation are not. A sales team spending 40% of its time on automatable work is operating at a structural disadvantage to one that has offloaded that work to AI-assisted tooling and redirected human time to the activities that actually convert inquiries to contracts. The secondary problem was targeting precision: without systematic filters, the team was running broad searches and manually sorting through irrelevant results. Each hour of prospecting was generating a lot of noise before it found signal.
The system
Decision system built
LinkedIn Sales Navigator was deployed at USD 100/seat for two team members, combined with HubSpot CRM (Starter) and an AI-assisted outreach personalisation tool. Target company lists were built using compound filters: industry (bituminous membrane manufacturers, civil engineering contractors, geosynthetics distributors), geography (DE, FR, PL, NL, UAE, SA), and company size (50–500 employees). AI-drafted outreach messages — personalised to each prospect's industry focus and visible recent activity — were reviewed and batch-sent at 50 per person per week. Incoming responses were scored and prioritised by CRM AI. Pipeline stages and follow-up sequences were automated based on response behaviour.
System components
LinkedIn Sales Navigator with compound targeting filters (industry, geography, company size, buyer role)
AI-assisted outreach personalisation layer — drafts reviewed by sales team before send
HubSpot CRM with AI lead scoring and pipeline stage automation
Response-triggered follow-up sequences with configurable cadence per market
Pipeline reporting dashboard — inquiry source, conversion stage, and time-in-stage tracking
How we worked
Engagement scope
Sales Navigator targeting logic design and filter configuration, HubSpot CRM setup and pipeline stage architecture, outreach message framework and personalisation template build, AI scoring configuration, team training on tool operation and outreach review workflow, 30-day performance review and targeting refinement.
Timeline
2-week deployment: tool configuration and CRM setup in week 1, team onboarding and first outreach batch in week 2. First qualified inquiry data available within 10 days of launch.
Operating model
Sales team retains full visibility and review rights over every outreach message before send — the AI drafts, the human approves. Campaign targeting reviewed monthly. HubSpot pipeline data reviewed weekly in sales meeting. CRM scoring thresholds adjusted quarterly based on actual conversion outcomes.
Outcomes
Business impact & measurable results
Qualified international enquiries grew from 15 to 52 per month within 90 days; prospecting time fell from 40% to 12% of hours.
Qualified international inquiries grew from 12–15 per month to 52 per month within 90 days of deployment — a 3.8× improvement
Sales team prospecting time reduced from 40% to 12% of total hours — approximately 84 hours per month per person freed for qualification and follow-up
3 distributor enquiries from the outreach programme converted to signed trial agreements within 6 months
Total tool cost of USD 250/month against distribution agreement revenue generated in year one: calculated ROI of 280× in the first 12 months
Pipeline visibility improved materially: for the first time, the sales team could report forecast revenue by market with confidence, based on CRM stage data rather than relationship intuition
Governance
Trust, collaboration & governance
No outreach message sent without human review — the system produces drafts at scale, not autonomous outreach
Targeting filters built collaboratively with the sales team using their buyer knowledge, not imposed from a generic template
Full pipeline transparency from first contact to signed agreement — no black-box lead scoring, all logic visible and adjustable
Performance tracked against baseline (12–15 inquiries/month) from day one — no ambiguity about what the tools were contributing
Reframe
The constraint on adoption isn't cost — it's the belief that industrial buying relationships are too personal for structured outreach.
Across every engagement, the goal is the same: engineer a system that makes better decisions — faster, more consistently, and at scale — than the process it replaces.
Next steps
Related services
Start a discovery
Most engagements begin with a conversation about context.
We do not send a proposal before we understand the problem. Start by telling us about your decision context — we will identify the highest-leverage intervention areas before any scope is agreed.