Cognifyd

Detect cart abandonment intent through cursor velocity.

Query the user's psychological profile for 'Loss Aversion' sensitivity.

Trigger a dynamic 'Stock Low' nudge for items in the cart.

Measure conversion uplift against a neutral control group.

Analyze usage patterns to identify 'Power User' behavior.

Deploy 'Social Proof' nudges showing similar companies using the Pro features.

A/B test the timing of the nudge to occur during high-value task completion.

Automate the upgrade flow based on intent-triggered API calls.

Assess user's cognitive style (skimmer vs. deep reader).

Adapt the content recommendation layout (visual vs. text-heavy).

Use 'Curiosity Gap' headlines for recommended articles tailored to specific interests.

Track time-on-site increase as a primary KPI.

Monitor hesitation and correction frequency in form fields.

Flag behavioral anomalies associated with non-standard intent.

Route high-anxiety users to a human-assisted chat window.

Improve data accuracy by simplifying fields for frustrated users.

Evaluate real-time demand and individual price sensitivity signals.

Apply 'Anchoring' techniques to highlight value-tier comparisons.

Offer personalized, time-sensitive discounts to price-sensitive segments.

Ensure pricing stays within ethical and brand-approved bounds.

Detect 'Choice Overload' signals in the browsing session.

Dynamically reduce the number of visible options to 'Top 3' curated picks.

Apply 'Authority' badges from recognized travel experts.

Increase booking velocity by streamlining the decision path.

Implement 'Endowed Progress' visual markers (showing partial completion).

Break down complex questions into bite-sized behavioral micro-steps.

Trigger empathetic support nudges when users pause for >15 seconds on a field.

Measure the reduction in form drop-off rates.