Cold outreach is still one of the most reliable channels for generating a steady flow of qualified leads in B2B. The catch is that most cold emails look exactly the same: "Hope you're doing well," a generic value prop, and a calendar link. Recipients can spot a template within five seconds, and that's where your reply rates die.
What actually gets replies is personalization that shows you did the work — you looked into the company's growth trajectory, you noticed the recipient's career path, you understand the specific pain that comes with their role. Not "I see you're in fintech," but "you doubled revenue to SAR 333M last quarter, and at that volume, device recovery becomes a material line item."
We're getsally.io, a B2B lead generation agency focused on US & EU markets. We've sent hundreds of thousands of cold emails and consistently generate 500+ qualified leads per month for our clients.
Over time, we cracked what makes deep personalization work at scale and systematized every piece of it: how to research, how to score what you find, how to pick the right hook, how to rotate angles across a sequence so each follow-up feels like a fresh reason to reply.
Here's what replies to good cold emails might look like:
We packaged this methodology into a skill file for Claude Code, so you can use the same approach on your own campaigns. Below is how to set it up.
You give Claude Code a list of contacts (first name, last name, company) in any format — CSV, plain text, CRM connector — and it:
---
CONTACT: Peter Parker | CEO & Co-Founder | Company name
TIER: person
MULTI-ANGLE: yes
QUALITY: person=2 company=3
HOOK (E1): career_path — Saudi Central Bank → серийный предприниматель → unicorn CEO
HOOK (E2): concrete_number — $2.4B Goldman Sachs facility, выручка ×2 до SAR 333M за квартал
SUBJECT 1: MJ, quick on device recovery at [Company name]
SUBJECT 1B: MJ, the default math at [Company name]
EMAIL 1:
MJ, you went from the Saudi Central Bank to building X into the first Saudi fintech unicorn — which means you've thought through every risk vector in consumer credit. Curious if device recovery is one of the ones keeping your risk team busy.
When BNPL customers default on a phone purchase, most lenders lose the device entirely. [Your company name] remotely locks and recovers those devices — cutting loss rates by 10%+ and boosting recovery by 40%+.
15 minutes to see if it fits [Company name] risk stack?
EMAIL 2:
Different angle — with $2.4B in fresh financing from Goldman Sachs and revenue doubling to SAR 333M last quarter, [Company name] loan book is growing fast. More BNPL volume means more devices in the field — and proportionally bigger exposure if recovery doesn't scale with it.
Most BNPL lenders at your scale still rely on collections calls and manual repossession. GetMobi replaces that:
- Remote lock the moment a payment is missed
- SIM-based lock that works even without internet
- Zero-touch enrollment — activate devices without opening boxes
Worth 15 minutes?
EMAIL 3:
Lenders using [Your Company name] see 10%+ reduction in device loss and 40%+ improvement in recovery within the first quarter — without adding headcount to collections.
For a BNPL book doing thousands of device transactions monthly, that's a material improvement to your credit loss ratio.
Happy to size the impact against [Company name] current device volume?
deep-personalization.md (attached below)..claude/skills/ folder at the root of your project. Create the folder if it doesn't exist.