A step-by-step look at Demand Verity’s workflow.
DV gathers data the instant demand arrives: form fields, UTM tags, referral pages, and how the form was filled. It also uses the visitor’s earlier visits to your site when they are available. Submissions can come from the DV script on your forms or from your own backend through the DV API.
The engine maps the origin, reconstructs the journey, calculates intent maturity, and checks trust signals, including email, phone, IP and company verification. This produces detailed evidence and flags, such as high interest or bot-like behavior.
Based on the evidence profile, DV’s decision engine reaches one of three decisions. The decision is sent to your systems through the API or webhook (for example, “tag this lead as ACT”), with a short operational note. You can also view it in the DV dashboard.
When a lead converts, qualifies, books or completes a meeting, goes unqualified, doesn’t respond, turns out to be spam, or no-shows, DV takes in that outcome through your CRM or spreadsheet connection. It uses recorded outcomes to evaluate signal reliability and source trust. Scoring-weight changes require a separately versioned configuration, so every change is deliberate and traceable.
DV runs a queue-based pipeline: events are validated and stored, scoring runs in background workers, and every verdict is versioned and traceable from raw event to external sync. The app is built on Next.js and Fastify with PostgreSQL and Redis.
Book a demo and see the four steps run on a real submission from your own site.