AI platform for optimizing creative ad strategies. It analyzes metrics like click-through rates and ad recall to enhance brand performance. Users can pretest ads and adjust for better results.
AI technology that learns what enhances or damages your brand, providing insight for optimizing every creative project.
Tools that provide data on metrics like click-through rate, ad recall, brand association, and text saliency to understand what works in your ads.
Uses neuroscience to analyze advertising content and predict its effectiveness.
Offers suggestions to improve ad content based on data-driven insights.
Provides a comprehensive dashboard for quick insights into ad performances.
Optimize your creative advertisements rapidly to improve performance metrics like branding and conversion.
Compatible with platforms such as TikTok, Meta, Instagram, YouTube, Amazon, TVC, and Out-of-home.
Evaluates creative elements like background, actions, people, text, and audio to determine impact on each channel.
Assesses cognitive factors such as content complexity, emotions, and context to understand performance drivers.
Provides insights into what works in your ads on each channel, identifying successful and unsuccessful elements.
Optimize ad attention to keep users engaged and ensure the message gets through effectively in digital spaces.
Use AI models to optimize memorability, distinctiveness, authenticity, and cognitive metrics to enhance audience perception.
Analyze data to understand ad success and predict performance, aiding in strategic optimization.
Collect millions of reactions to image and video ads to improve content impact.
Train models to predict cognitive impacts of ads based on collected human reaction data.
Evaluate AI models' predictions by testing them against actual human behavior to ensure accuracy.
Low-performing creatives harm the KPIs on your platform. This feature helps level up the ads to unlock your true marketing potential.
Provides clients access to data on what creative strategies drive more impact, helping them to boost performance and improve.
Trains out-of-maker AI models to allow clients to build impactful ads with no production costs.
Offers pre-launch predictions for ad performance by utilizing advanced machine-learning models and historical data to estimate the effectiveness of campaigns. This allows users to optimize and tailor ads for better engagement and reach.
Provides suggestions on how to optimize creative elements in ads. The system analyzes various visual and textual aspects of the ad to enhance its appeal and effectiveness, leading to higher engagement rates.
Memorable provides AI-powered pretesting capabilities that help clients optimize ad creatives before launching campaigns. This improves click-through rates and reduces cost-per-click.
Helps choose the best key visual among multiple alternatives by evaluating their branding and conversion impact effectively.
Provides insights into how the chosen key visual performs, assisting in data-driven decision making to improve branding and conversion rates.
This approach emphasizes focusing on a clear, simple message to convey the product's strength effectively through emotions like disgust and anger, creating memorable impressions.
Integrates brand presence with high-impact moments to ensure the brand information is transmitted clearly, making sure the brand is not just seen but remembered.
The ad design uses simplicity and clarity to ensure that the brain processes the message easily, resulting in more effective memory retention.
Utilizes relatable and organic elements through user-generated content and storytelling, which increases viewer engagement and builds a connection with the audience.
The research introduces 'Modular Memorability: Tiered Representations for Video Memorability Prediction', a framework for analyzing factors that impact memorability with a novel prediction model.
Develops a memorability model that combines information from different feature tiers and contextual data, surpassing existing video memorability datasets.
Analyzes the model part by part to understand how its modules offer different cognitive insights, extracting predictive insights on different cognitive levels.