Definitions for common terms in lead validation, bot detection, ad fraud, and CRM data quality.
An organized operation that employs low-wage workers or automated systems to generate large volumes of fake clicks, form submissions, or social media engagement.
The practice of artificially inflating the number of clicks on a pay-per-click ad. Perpetrated by competitors, bots, or click farms to drain an advertiser's budget without generating legitimate interest.
The average cost of acquiring a single lead through marketing channels. Calculated as total campaign spend divided by the number of leads generated. Inflated by invalid leads.
The accuracy, completeness, and reliability of contact and lead data stored in a Customer Relationship Management system. Poor data quality wastes sales time and corrupts pipeline forecasts.
An IP address assigned to a server in a commercial data center rather than a residential internet connection. Often associated with bot traffic, VPN services, and automated scripts.
A temporary email address from services like Guerrilla Mail or Temp Mail that self-destructs after minutes or hours. Used to avoid spam but also to submit fake leads with no intention of engagement.
The practice of analyzing an email's domain for signals like MX record validity, domain age, registration patterns, and whether it belongs to a known disposable email provider.
Web traffic that doesn't come from genuine human users with real interest. Includes bot traffic, click fraud, accidental clicks, and incentivized traffic. Divided into General IVT (GIVT) and Sophisticated IVT (SIVT).
A risk score assigned to an IP address based on its history of malicious activity, association with botnets, proxy/VPN usage, datacenter hosting, and past abuse reports.
A numerical value assigned to each lead indicating the likelihood that it represents a genuine, qualified prospect. Based on identity verification, behavioral analysis, and network intelligence signals.
The process of assigning values to leads based on various attributes — demographic, firmographic, behavioral, and technical — to prioritize sales follow-up. Modern lead scoring includes identity and authenticity verification.
The process of verifying that a lead submission is from a real person with valid contact information. Includes email verification, phone validation, IP checks, and behavioral analysis.
A lead that marketing has determined meets certain criteria and is ready for sales engagement. Quality of MQLs is severely impacted when bot traffic and fake submissions aren't filtered.
A DNS record that specifies the mail server responsible for accepting email for a domain. Checking MX records validates that an email domain can actually receive messages.
A proxy server that routes traffic through real residential IP addresses, making bot traffic appear to come from legitimate home internet connections. Used by sophisticated bots to evade IP-based detection.
A marketing metric measuring revenue generated per dollar of ad spend. ROAS calculations are distorted when invalid traffic inflates lead counts without generating real customers.
An individual data point or check used in lead scoring. Examples include IP reputation, email domain age, typing speed, mouse movement patterns, and form completion time. Multiple signals combine into a composite score.
A lead that sales has accepted as worthy of direct follow-up based on meeting qualification criteria. Junk leads that become SQLs waste sales resources and lower conversion rates.
Monitoring the rate of form submissions from a single source (IP, device, email pattern) over time. Abnormally high submission velocity indicates automated or abusive behavior.
The classification assigned to a lead after scoring: typically Legitimate, Suspicious, Likely Bot, or Definite Bot. Determines how the lead is routed — approved, queued for review, or rejected.
The ability to identify when a visitor is using a Virtual Private Network to mask their real IP address and location. VPN usage on form submissions may indicate an attempt to hide identity.
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