Conviva Makes the Transition from Video Analytics to Bidstream Data with Its First Ad Tech Partnership

Conviva, a streaming analytics startup, launched its first ad tech product on Thursday, contextual data integration with The Trade Desk.

Conviva embeds a sensor in the videos or streaming material of publishers and programmers. The sensor is not a third-party data collector in the same way that a cookie or SDK is. Instead, according to Conviva CEO Keith Zubchevich, it is the tool that publishers use in their video players to monitor video quality and engagement, such as buffering rates or overall watch time.

“In the last couple of years, we began to collect extremely extensive content information, since there is no limit to what you can send through the sensor that sits in the video player, including contextual ad data and even IDs,” Zubchevich said.

The new Conviva bidstream connections, for example, may notify buyers whether a certain video spot is a short-form video, the length of a TV episode, or a complete movie, and can also provide contextual data about the kind of content that will play during that viewing session, according to Zubchevich.

According to Josh Sharma, VP of ad partnerships at Local Now, local weather and content streaming service and a pilot partner for Conviva’s data partnership, contextual advertising data for streaming video are frequently cobbled together from site pixels, mobile app SDKs, ad verification tech vendors, and aggregated third-party data sets, which monitor the page but aren’t embedded in the video player.

“For a long time, it’s been a source of frustration among our DSP partners that they do not see the context of the content itself,” Sharma said.

Aside from factors such as video length – is it a bite-size video or a full-length show? – he stated that Local Now, a subsidiary of Entertainment Studios (owner of The Weather Group and local affiliate stations), can use the Conviva bidstream integration to pass data about specific content adjacency.

Buyers can place more value on inventory if the context is precise. For example, some companies could be willing to pay extra for an ad spot during a kids cartoon if their buying platform allows them to target ad units following a sports-related scene rather than simply general family-friendly content.

According to him, the data could also assist advertisers in targeting users depending on session watch length. For example, suppose someone has been engaged and viewing videos with Local Now for the last hour, and that information can be conveyed in the bidstream. In that case, advertisers can bid more confidently on that impression.

According to Sharma, targeting relevant neighboring material during a movie, show, or news program is commonplace for linear TV advertisers. Bringing such capacity to CTV will help “bridge the gap” for television budgets, he says, since ad revenues are shifting to streaming content at a far slower rate than consumers’ viewing habits have changed.

According to Zubchevich, the Trade Desk was the natural starting point for this contextual data play. Conviva polled its publishing and broadcast partners, and The Trade Desk was a major source of demand across the board. However, he said that the company intends to expand to other DSPs and ad platforms.