Dig vs Tubular Labs: Which Is Better? (2026 Comparison)

Content Discovery and Brand Detection

When it comes to finding where your brand appears in the social video landscape, Dig and Tubular Labs take different approaches. Dig is a leader in Brand Mention Detection (5/5) because it doesn't just look at text; its proprietary LLM stack analyzes the audio and visual content of videos to identify narratives. This makes it exceptional for finding sentiment that traditional tools miss. Tubular Labs, while having a larger database, scores slightly lower in specific brand mention accuracy (3/5) as it focuses more on high-level channel performance and category trends. However, neither tool is perfectly optimized for the messy world of user-generated content compared to more specialized Archive alternatives.

Video Tracking and Metrics

Tubular Labs is often considered the "gold standard" for video metrics. With over 10 years of historical data and 15 billion videos indexed, it provides Standardized Video Ratings that allow broadcasters and publishers to compare performance across YouTube, Facebook, TikTok, and Twitch. In our comparison, Tubular scores a 4/5 for Multi-Platform Support. Dig, being younger, focuses heavily on the "why" behind the video rather than just the "how many views." Dig’s Short-Form Video Tracking (5/5) is highly sophisticated, using AI to cluster narratives across thousands of clips on TikTok and Reels. For a deeper look at how these compare to other listening tools, see our Brandwatch vs Dig analysis.

Creator Intelligence

If your primary goal is finding and vetting creators, Tubular Labs is the clear winner with a 5/5 for Creator Analytics. They track over 40 million creator accounts, providing deep audience demographics and behavioral models. Dig scores a 3/5 here; while it can evaluate influencers based on the narratives they promote, it lacks the massive, searchable database of creators that Tubular has built since 2012. Users often find that the Tubular Labs alternative landscape varies significantly depending on whether you need historical data or real-time campaign tracking.

AI Capabilities and Integration

Dig is a "video-first" AI platform, backed by the Google AI Startups Fund. Its AI Content Tagging (5/5) is built to understand natural language briefs, making it more intuitive for research teams than traditional Boolean searches. Tubular Labs matches this with its ContentGraph AI (5/5), which classifies content into over 1 million categories. Where both tools struggle is in technical accessibility; both receive a 1/5 for API Access in their basic configurations, often requiring high-tier enterprise contracts for programmatic data. For those needing better integration, checking out all ShortsIntel comparisons may reveal more flexible options.

Usability and Reporting

Both platforms are built for power users, resulting in an Ease of Use score of 2/5. The learning curve is steep, and both usually require a managed onboarding process. Tubular Labs offers more robust Reporting Dashboards (4/5) for executive summaries, whereas Dig’s strengths lie in its Narrative Clustering, which is better for research teams than for quick performance snapshots. You can see how this complexity compares in our ShortsIntel vs Dig breakdown.