Social Listening Beyond Post Titles, Descriptions, and APIs - Part 3

In Part 2: Why Analyzing Titles and Descriptions Isn’t Enough, we discussed how traditional monitoring methods fail to capture the full scope of brand mentions, missing crucial insights hidden within video transcripts, image content, and audio dialogue. But even when you recognize the need to track beyond metadata, the next challenge arises—how do you actually access and analyze this data at scale?

In Part 3, we’ll dive into the complexities of data discovery on modern platforms, explain why APIs alone aren’t sufficient, and show how Pendulum’s proprietary AI-driven methods uncover the brand and topic mentions that truly matter.

The Challenge of Data Discovery on Modern Platforms

In our previous posts, we established the importance of tracking brand and topic mentions beyond Twitter (X) and onto platforms like YouTube, TikTok, and Instagram, where video, audio, and image content dominate. However, the challenge lies in obtaining this data—these platforms do not offer APIs that enable straightforward discovery of brand and topic mentions using Boolean keyword searches.

At Pendulum, we employ proprietary social intelligence solutions to help users uncover brand and topic mentions not just in metadata but also within the actual transcripts and visual content of posts. This approach ensures a more comprehensive and effective monitoring solution.

Title and Description Matches Are Not Enough

A common yet incomplete method for tracking brand and topic mentions is to manually search a platform’s native search function or use Google Search to find keyword-relevant posts. While this approach can be automated, it only scratches the surface of brand and topic mentions.

For video platforms like YouTube, transcript analysis is critical. Our research on a dataset of 20 randomly selected Fortune 500 companies found that over 75% of brand mentions appeared in transcripts rather than in titles or descriptions. Similarly, for image-based platforms like Instagram, identifying logos and topics within images is key. Our study found that 66% of brand mentions on Instagram came from AI-generated image captions or OCR-based analysis rather than from text-based metadata.

Despite this, many competitors in the social media monitoring space rely only on title and description searches, missing a vast amount of valuable content.

Discovering the Deeper Matches That Matter

Given the limitations of traditional search-based methods, Pendulum takes a creative and scalable approach to identifying relevant posts.

Consider YouTube, which saw over 14 billion video uploads in 2024 alone. With over 200 million channels, processing all of YouTube’s content is computationally infeasible for any monitoring company. The same challenge applies to TikTok, Instagram, and other content-rich platforms.

Fortunately, it’s unnecessary to analyze every post. A significant portion of content is irrelevant—ranging from pet videos to low-engagement posts that never reach a meaningful audience. Instead of brute-force ingestion, we employ a strategic data acquisition method:

• Identifying title and description matches: As mentioned above, although insufficient as a primary content discovery strategy, we still use search methods to ensure our content discovery system identifies all posts that can be found manually.
  
• Tracking top creators: We ensure our users never miss a single mention from influential content creators by ingesting and processing all content from top creators (transcripts, image captions, etc.).

• Predictive AI-driven ingestion: Most importantly, we use a proprietary AI model to identify millions of smaller but still important creators likely to discuss brands and topics of interest to our users, allowing us to significantly expand coverage while maintaining efficiency.

By leveraging this approach, we maximize the relevance of social data while avoiding unnecessary computational costs, ensuring our users get the insights that matter most.

Ethical Data Collection: Following the Rules

Unlike some competitors, our methods adhere strictly to each platform’s terms of service. We rely on publicly available data and do not engage in questionable tactics, such as creating bot accounts to scrape private content.

Our users can be confident that our social listening and intelligence solutions are effective and legally and ethically sound, providing peace of mind amid increasing scrutiny of data collection practices.

By going beyond traditional search capabilities and leveraging innovative AI-driven discovery methods, Pendulum ensures that brands can track and analyze mentions where they truly matter—within the content itself.

Uncovering What Truly Matters: The Next Step in AI-Powered Brand MonitoringEmpty heading

Extracting meaningful brand insights from video, audio, and image-based content requires more than basic search methods. As we’ve explored, traditional monitoring tools fall short, missing critical brand mentions hidden within transcripts, visuals, and non-text metadata. Pendulum bridges this gap with advanced AI-driven social discovery, ensuring you never miss an important conversation about your brand.

In Part 4, we’ll break down why Twitter’s content ecosystem is fundamentally different from YouTube, TikTok, and Instagram. Using real-world data, we’ll analyze how brand mentions, consumer discussions, and movements like boycotts vary across platforms—and why relying on Twitter alone can lead to misguided insights.

Want to see this technology in action? Request a Pendulum demo today and gain a competitive edge with next-level brand monitoring.

‍