Clayface listens and sees, picking up what is spoken aloud, what appears as on screen text and what is shown in frame, then tying every mention to the products, creators and competitors it is actually about.










Spoken audio, on screen text and products in frame are captured and tied to your product codes, so a mention counts when nobody types the brand.
See it on your own videosOne creator pulled out of the wider conversation and scored on the sentiment they moved, including the sponsored posts they run for your competitors.
Walk through a creator reportYou name the rival set, including comparables chosen for business model rather than category, and everything is measured on the same posts and the same period.
Compare your rival set live





475M+
creators database
25+
platforms covered in a single view
3x
more mentions surfaced from video
A leading powersports brand tracks twenty motorcycle forums and private Facebook groups alongside social, so owner conversation about accessories and fit surfaces in the same view as everything else.
“We named the Facebook groups on a Tuesday and had them running by Thursday. Everywhere else that has been a month long exercise that does not always end up working."

A leading beauty brand analyses every ambassador post as full video, so screen time, spoken claims and on screen products are measured rather than guessed from captions.
“It goes deeper on tone, voice and performance than anything else we evaluated, and it breaks a single video down rather than reading the caption around it.”

Clayface social intelligence runs on the Phyllo data layer, built on full video capture, creator level attribution and your own product taxonomy, so sentiment, creators, competitors, channels, themes and sources are all analysed.
A full breakdown of every video covering brand mentions, screen time, on screen objects, spoken claims, brand safety risk and sentiment, resolved to your own product codes.
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A standing list of the creators in your category, updated as they post, showing what each one contributed to sentiment and which of them are posting for competitors.
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Your named rival set, monitored on the same posts and the same period as your own brand, and it holds together when a competitor is added mid period.
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TikTok, Meta, Google and YouTube as one picture. Which channels drive awareness, which drive conversion, and how awareness spend lands one to two months later.
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Conversation grouped by flavour, format, occasion, model or finish. An educational mention is separated from a complaint instead of both counting as negative.
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Book a walkthrough to see how video capture, creator attribution and your own taxonomy work together to show where a category is heading before it gets there.
Social listening counts mentions that match text. Social intelligence adds everything the text never contains: spoken audio, on screen text, products in frame, the creator behind the post and the SKU being discussed. Listening tells you volume moved. Social intelligence tells you which product and which creator moved it.
Clayface transcribes spoken audio, captures on screen text and detects products in frame, then resolves each signal to your own product codes. Every video returns brand mentions, screen time, on screen objects, spoken claims, brand safety risk and sentiment, so a mention counts when nobody types the brand name.
Clayface scores a creator on the sentiment they moved rather than the impressions they delivered. Any creator can be pulled cleanly out of the wider conversation, including the sponsored posts they run for competitors, and campaign results report as sentiment change and product mentions rather than views.
You define the rival set, including comparables chosen for business model rather than category. Every brand is analysed from the same posts over the same period, so share of voice holds when a competitor is added mid quarter and the comparison works at brand, product and campaign level.
Clayface connects to Tableau, SQL, Google Analytics and platform APIs including TikTok, so internal performance data sits alongside the external conversation. Your product families, models and topics are ingested as they are, and every output is cut to your structure rather than a vendor category tree.