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False Positive Rate

False positive rate measures how often a system incorrectly flags something as true or problematic when it is not. It is widely used in security, fraud detection, machine learning models, and analytics accuracy checks. A lower false positive rate means fewer incorrect alerts, improving trust and reducing unnecessary action. High rates can create noise, wasted effort, and user frustration.

Picture an antivirus tool wrongly blocking safe software or a fraud system flagging genuine transactions. Teams monitor this metric alongside precision and recall to balance protection with user experience. Reducing these errors often requires better data, tuning detection rules, and continuous testing.

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Funnel Testing

Funnel testing involves experimenting with different funnel steps to identify changes that improve performance.

Marketers test variations in design, content, or process at specific points in the funnel. Results show which version keeps more users engaged and moving forward toward conversion.

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Funnel Analysis

Funnel analysis is the practice of reviewing each step in a funnel to see where users drop off. It measures conversion rates between stages, helping identify weak points.

By analyzing funnels, marketers pinpoint bottlenecks and learn which steps require adjustments to improve the customer journey.

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Funnel

A funnel in marketing is a visual or conceptual model showing steps a user takes from first awareness to a final action like a purchase or sign-up.

Common stages include awareness, consideration, and conversion.

Funnels help marketers map user journeys and measure how many complete each step.

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Friction

In marketing, friction refers to obstacles that make it harder for users to complete desired actions. It may be a slow-loading page, unnecessary form fields, or unclear instructions. Friction interrupts the user journey, lowers engagement, and often results in abandoned purchases or incomplete sign-ups.

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Form Testing

Form testing involves experimenting with variations of online forms to see which performs better. Using methods like A/B or multivariate testing, marketers compare versions with different layouts, field orders, or call-to-action buttons. The aim is to discover which version encourages more users to complete the form.

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Form Analytics

Form analytics is the process of tracking how users interact with online forms. It records metrics such as time spent on each field, hesitation, refill rate, and abandonment. The goal is to understand user behavior, identify confusing sections, and improve completion rates by optimizing the overall form experience.

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