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Xpln.ai

Xpln.ai provides AI-driven solutions that utilize eye-tracking data and machine learning to measure and optimize ad effectiveness based on attention metrics, rather than traditional viewability standards. This approach addresses the issue of wasted media spend by ensuring that advertising dollars are focused on ads that genuinely engage audiences and drive measurable business outcomes.

Updated 2 months ago

Funding

$9.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Traditional advertising metrics like viewability and completion rates often fail to accurately measure audience engagement, leading to wasted ad spend on ads that are viewable but not actually watched. This disconnect between ad exposure and genuine attention makes it difficult for advertisers to optimize campaigns for brand perception and business outcomes.

Solution

Xpln.ai provides an AI-driven platform that uses eye-tracking data and machine learning to measure and optimize ad effectiveness based on real-time attention metrics. By analyzing a comprehensive dataset of quality variables, including ad position, page context, and traffic source, Xpln.ai delivers actionable insights into how ads are truly engaging audiences. The platform's goal is to identify the optimal level of attention needed to drive better results and help brands implement this across their media plan. This approach ensures that advertising dollars are focused on ads that genuinely capture attention and drive measurable business outcomes, moving beyond traditional viewability standards.

Target Audience

The primary customers are advertisers, agencies, marketplaces, adtech companies, publishers, and sales houses seeking to optimize ad spend and improve campaign effectiveness by focusing on attention-based metrics.

Features

  • Analysis of ad performance using eye-tracking data combined with machine learning
  • Measurement of attention based on quality variables such as ad position, surface area, and page context
  • Coverage of a wide range of ad inventory, including social media, walled gardens, CTV, and streaming platforms
  • Transparent dashboards providing clear access to data, without opaque indexes or black-boxed scores
  • Identification of the optimal attention level needed to drive specific business results
  • Integration that can be set up quickly, providing actionable insights within 24 hours
This profile is AI-generated and may contain inaccuracies.