This article explains how to use properties in FirstQuadrant to structure contact and company data, segment audiences, and enable AI-powered enrichment. It covers the creation of custom properties, enrichment options using Perplexity or internal data, and best practices for managing and testing property-based data workflows.
Latest funding round
, Y Combinator funded
, or Lost reason
.
Next to the name, you’ll see an icon to control visibility. By default, the property is shown in the context panel. You can toggle it to keep it hidden.
Info: Only properties with a value are shown in the context panel. If a property is empty for a specific contact or company, it won’t appear.
Latest funding round
, you may want to enrich this only for VC-backed companies, as others are unlikely to have this data.
Tip: Before running a large enrichment, test Perplexity manually: Go to perplexity.ai. Ask: _“What was the latest funding round of [company name]?”. _Try this with 2–3 companies. If results are accurate, you can proceed to enrich in FirstQuadrant.
Tip: To ensure enrichment logic is working as expected before using it broadly, you can alternatively create a small test view with just a few records and apply the enrichment to that view first. This allows you to verify the results and avoid wasting AI credits on a full dataset if something doesn’t work as intended.
Lost reason
(as multi- or single-select). When someone declines to work with you, you send a follow-up email asking for the reason. Once the prospect replies, FirstQuadrant can automatically extract the answer and populate the property.
Example 2: Interest in a feature
Let’s say some leads have expressed interest in an upcoming feature. You may have recorded that in meeting notes or emails. You can:
Interested in Feature A