What We Were Solving
How We Built It
Built a scoring engine that evaluates companies across 15+ criteria (industry, size, location, revenue signals, technology stack). System learns from past sales data. Real-time scoring when a prospect enters the funnel.Manual ICP Matching. Hours Wasted. Misses Everywhere.
B2B sales teams have a clear ideal customer profile. Specific company sizes, industries, geographies, revenue ranges. They have contact lists in the thousands or millions. Manually matching one against the other is impossible. Most teams either ignore it and spray broadly, or spend hours manually reviewing leads against the criteria. They miss good matches. They can't scale across markets.
The real cost isn't just the hours spent. It's the leads left in the database that should have been hot prospects. It's sales teams chasing the wrong accounts. It's the inconsistency across regions when different people do the matching. When you're scaling into multiple markets like USA, UK, Germany, South Africa, you can't manually match contact data against your ICP across all of them. You need a system.
We built this tool for ourselves first. We needed to match our own ideal customer profiles against our contact database across multiple geographies. Once we had it working for us, we realised it solved a real problem for other B2B sales organisations.
- Thousands or millions of contacts. Manual matching is impossible.
- No scoring system. All leads treated the same regardless of fit.
- Inconsistency across teams and markets. Different people, different results.
- Good leads get missed because they're buried in a huge list.
- No way to scale the process across multiple geographies.
AI-Powered ICP Matching at Scale
The tool takes your ICP criteria and runs it against your contact database. It works at three levels. Company level. Brand level. Individual contact level. You define your ICP criteria. The engine matches every contact against those criteria and scores them.
Three scoring tiers. Hot leads match your ICP closely. Warm leads have some overlap but aren't perfect fits. Cold leads fall outside your criteria. The output is ready for CRM. You can export by tier, by market, by account. Sales teams get a ranked list of actual prospects instead of a huge database.
Multi-market support is built in. Define your ICP once. Run it against USA contacts, UK contacts, Germany, South Africa, or anywhere else. The scoring adapts to market differences. Company registration, industry classifications, market-specific contact data. All of it gets factored in.
ICP List Matching
Define your ideal customer criteria. Upload contact database. Engine matches each contact against your full ICP. Instant scoring across all records. No manual review.
3-Tier Segmentation
Leads scored into hot, warm, cold tiers. Works at company level, brand level, and individual contact level. Clear ranking of who to pursue first. Actionable prioritisation.
Multi-Market Support
USA, UK, Germany, South Africa, and more. ICP matching adapts to local company registration, industry codes, market data. One setup. Multiple geographies.
Export and CRM Ready
Output exports by tier and market. Formatted for direct CRM import. Instant delivery. No back-and-forth. Leads in your sales pipeline immediately.
Development focused on accuracy and speed. Building matching logic that works across different data structures and market regulations. Creating scoring algorithms that prioritise true fit over superficial matches. Testing across real contact databases to ensure the output actually converts.
Built for Sales Teams That Scale
- ICP list matching and instant lead scoring across entire contact database
- Three-tier segmentation system based on fit alignment
- Company-level, brand-level, and individual contact-level matching
- Multi-market support with localised matching logic
- CRM-ready export functionality for immediate sales action
- Instant turnaround from upload to scored results
- Repeatable process for continuous lead qualification