How matching works
The matching engine compares your product, your target-market profile, the prospect's business profile, available buying signals, decision-maker relevance, location and size suitability, your exclusions, and the quality and freshness of the data.
You describe what you sell. The analysis step turns that into problems solved, likely buyers and recommended search criteria for your approval.
Industries, sub-industries, global locations, size, technology, decision-maker roles, keywords and exclusions form the profile that discovery and scoring both use.
The provider layer returns businesses matching your filters, with company profile, decision-maker and data-source details.
Expansion, funding, tenders, technology changes and industry-specific events are recorded with a source, date, confidence level and evidence type.
Seven weighted components produce a 0–100 score, a category and a written explanation of why the business matched.
Your team approves, rejects, tags or suppresses each business before anything is added to a campaign.
Drafts reference the real signal, the real benefit and the reason for the match. A person approves before the first launch.
Replies are classified, opportunities move through the pipeline and every change is recorded in the activity log.
We never claim a business is “actively looking” unless there is direct evidence. Instead we use:
Likely to need
Used when the profile and signals point towards a requirement.
Potential requirement
Used when evidence is partial or indirect.
Relevant buying signal
Used when a recorded event relates to your product area.
Suitable prospect
Used when the business fits the selected target market.
Strong product fit
Used when several components score highly together.