New Tubular Tools Link Amazon Shopping, Social Video Views for Creators and Brands

Tubular Labs today launched a set of marketing tools that enable influencers, agencies, brands and others to better understand the products people are buying and buying on Amazon after watching their video content on social media sites.

The Tubular Consumer Insights product launched today after operating in early access beta mode for the past few months, said CMO Josh Schmiesing. The tool connects Amazon’s purchase data with the company’s existing in-depth data and ratings on audiences for approximately 10 billion videos on Facebook, Instagram, YouTube, Twitter and Twitch.


This marks another step forward in so-called attribution, linking the impact of social media (in this case, video material from around 250,000 creators) to the audience’s actual buying behavior and propensity to buy. and buy other types of products, Schmiesing said.

“It’s really another insight that lies beneath” Tubular’s existing viewership ratings for viewership of creator content on major social video platforms, Schmiesing said.

“So we can take that same audience and then have buying behaviors, whether it’s buying or browsing,” Schmiesing said. “And what’s interesting is that it’s based on Amazon’s categorization, so you can work your way up from something as high (level) as ‘consumer electronics’ , down to something as specific as, say, “soundbar” and look for matches and engagement with that audience, between creators and publishers.”

The company expects two primary use cases for the information, Schmiesing said.

One is for publishers, influencers, media companies, and similar content creators to better understand what their own audience is looking for and buying after watching their programming. It can help inform content creation decisions, Schmiesing said, and can also suggest potential brands and product areas that might be interested in partnering with content creators as advertisers or sponsors.


“We can take the creators themselves, whether it’s MTV or MrBeast, and I could tell you what those audiences are buying,” Schmiesing said. “We can also take, say, a category like the Olympics, and I can tell you (what) audience (buys) that watches Olympic content from all kinds of creators, whether it’s NBC or somebody else, I can tell you what people watching this content are buying or should I say (what they are buying).

The other use case is for brand marketers, agencies, and other advertisers, who can use the data to find sites and creators they want to advertise on, especially those whose audiences over-indexes for their products. Businesses and agencies can also use the data to find influencers they’d like to sign sponsorships and other partnerships with, to dive even deeper into those audiences.

The data reveals sometimes surprising connections and correlations. As an example, Schmiesing said viewers of content on Netflix’s hit Korean horror series squid game are also fans of dance competitions, Pepsi and singer Adele. Barstool Sports viewers not only over-index for video games (4.1 times baseline affinity) and electronics (2.2 times baseline), but also for clothing (1.5 times middle level).


About 30% of Olympic Games viewers shop for home and food items on Amazon. And people who watch home automation videos are 36 times more likely to buy cleaning products on Amazon, according to early product results.

Product categories with the highest percentage of social video audiences in the last quarter include: Electronics (19%), Computers & Accessories (14%), Home & Kitchen (13%) and clothing, footwear and jewelry (12%).

Metrics include “purchase affinity,” the likelihood that an audience will purchase a specific product or category; “Audience Share” means the percentage of viewers who purchased a product or category within 30 days of viewing; “Market Share” means the percentage of shoppers in a category who also viewed that creator or category; and “Relevance Score”, which normalizes shopping affinity scores for smaller audiences.


Comments are closed.