LendTech scale-up (anonymised)
Regionalised ABM strategy for a LendTech firm
Account-based campaigns with automated regionalised content lifted click-through rates by around 70% and automated most of the manual campaign operations behind them.

The challenge
Generic global campaigns were underperforming across very different regional markets, and producing regionalised content manually could not scale.
What I did
- Paid media
- Automation and AI
- Marketing strategy
The outcome
+70% click-through rate uplift from account-based campaigns.
Context
A lending-technology company selling to banks across the Middle East, Africa and Asia was running broadly identical campaigns into every market:
- bankers in Nairobi, Riyadh and Kuala Lumpur saw the same message, examples and references;
- engagement was flat;
- the content team could not realistically produce localised variants for every region and segment.
Challenge
Account-based marketing lives or dies on relevance. The firm needed regionally specific:
- messaging,
- examples,
- regulatory references, and
- case studies
for each target-account cluster — without multiplying the content team’s workload by the number of regions.
Constraints
- A small marketing team.
- Long enterprise sales cycles.
- Strict brand and compliance review requirements.
- A stack centred on HubSpot, with LinkedIn and Google as the primary paid channels.
Strategy
- Segment target accounts by region and regulatory context.
- Build an automation pipeline that produces regionalised content drafts systematically instead of manually.
- Keep humans in the approval loop for every asset.
- Rebuild the campaign structure around account lists and regional clusters, not broad targeting.
Implementation
Content engine. An n8n workflow takes campaign inputs (keywords, region, country, structure) and produces structured drafts:
- titles and introductions,
- chapters with regional references,
- conclusions,
- all validated for completeness before anyone spends time reviewing them.
Drafts land in the CMS as password-protected drafts, with notifications to the marketing team.
Campaign engine. LinkedIn and Google were rebuilt around regional account clusters, with landing pages and ad copy drawing on the regionalised content library. Reporting connected campaign engagement back to target-account activity in the CRM.
Results
- ~70% higher click-through rate than the previous generic approach.
- ~80% of repetitive campaign operations automated.
- Deeper commercial outcomes are confidential, but the approach became the standard operating model for regional campaigns.
Lessons
Relevance scales through systems, not headcount. The combination that worked was narrow:
- automation produces drafts,
- structure validation catches failures early,
- human editors spend their time on judgement, not first drafts.
Technology stack
- LinkedIn Ads
- Google Ads
- n8n
- HubSpot
- OpenAI API
The regional programme changed how we go to market. Relevance stopped being a bottleneck, and the team finally spends its time on judgement instead of first drafts.
Services behind this project
Paid media
Paid campaigns measured to pipeline, optimised on lead quality, and governed by explicit budget rules.
Google and LinkedIn campaigns run with tracking readiness, honest reporting and lead quality analysis, not vanity metrics.
- Google Ads
- LinkedIn Ads
- Meta Ads
- TikTok Ads
Automation and AI
Documented, monitored automation that gives the team hours back and makes processes reliable.
n8n workflows and AI-assisted systems that remove repetitive marketing work, connect your tools and keep humans in control of what ships.
- n8n
- Zapier
- Make
- OpenAI API
Marketing strategy
A clear positioning, channel plan and KPI framework that the whole organisation can execute against.
Market analysis, positioning and a growth plan your team can actually execute, built by someone who also implements the systems behind it.
- GA4
- Semrush
- HubSpot
- Looker Studio
Next move
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