Ethen Yao, Co-founder and CFORenowned American management consultant Peter Drucker once said, “If you can’t measure it, you can’t manage it.” This statement rings true in today’s business arena, especially in the digital marketing world, where tracking key metrics gives brands an accurate view of how they are doing, what channels are effective, and where their efforts need improvement. In other words, metrics provide a means for businesses to assess progress, demonstrate accountability, and allow marketers to better know, act upon, align efforts, and reduce market exposure.
However, within the complex landscape of video streaming and OTT, it is harder than ever for marketers to get a solid grip on their on-screen exposure and how their ads are performing. Why? The primary reason is that marketers still rely on outdated measurement methodologies to gain insight into modern consumption habits. Furthermore, brands have to partner with multiple measurement services and attempt to combine those in order to derive a return on investment from streaming advertising, which adds to the complexity.
Stream Engine, a California-based firm, is now changing this status quo with its AI platform designed for an evolving market. Founded by partnerships between leaders in the industries of sports, marketing, media, and technology, Stream Engine offers comprehensive AI services to measure and analyze brand recognition and sentiment across streaming and digital platforms. “Utilizing our breakthrough technology and machine-learning algorithms, we modernize how brands derive true value from advertising and on-screen exposure,” states Ethen Yao, co-founder and CFO, Stream Engine.
The platform was initially developed as a vision, voice, and chat sentiment analysis technology for customer-facing products. However, the pandemic led the company to steer in a new direction. “We decided to shift our focus to the enterprise side of things, and utilize the same technology to help media agencies, broadcast companies, and brand sponsors understand their media stance through a data-driven approach,” remarks Yao.
Utilizing our breakthrough technology and machine-learning algorithms, we modernize how brands derive true value from advertising and on-screen exposure
The firm’s complex vision, voice detection, and chat sentiment tools actively monitor and analyze audio and visual brand impressions, as well as brand sentiment, across the universe of streaming and OTT platforms. Stream Engine also t racks verbal mentions and calculates impressions, engagement, and attribution on the streaming platform and provides brands with accurate, real-time data and analysis, empowering them to make informed decisions faster than ever before. What’s more? The platform’s natural language processing technology offers the ability to translate multilingual streams, enabling companies to easily track global performance.
Talking about the aspects that differentiate the company in the digital marketing space, Yao informs, “By providing everything under one roof—the vision, voice, and chat component—and allowing for real-time data and analysis delivered via a user-friendly dashboard, we save clients from the complexity of dealing with multiple vendors.” Besides, Stream Engine’s delivery cadence and reporting turnaround time is significantly faster than the majority of the incumbents. While others deliver the post-event reporting typically three to eight weeks after an event, Stream Engine updates analytics and measurement on a near real-time basis. In terms of pricing, what Stream Engine extends is not a cheaper price but a competitive one. “We are able to utilize the machine rather than human labor to scale indefinitely and cover more digital media through all channels,” asserts Yao. “We do more. We do it better. And, we do it faster.”
When it comes to client onboarding, Stream Engine adopts a bottom-up approach. “We usually transition from the initial pitch of the product to their analytics department where we work directly with their analytics team and find out the kind of KPIs or metrics they want to measure and track, gather the requirements, then feed it through our algorithm,” he explains. The post-event report is delivered a few days after to the client’s executive team.
The majority of the technology stack of Stream Engine has already been developed. The firm seeks to continue driving innovation and investing in research and development. In that quest, the team is planning to integrate additional features to its platform. This includes White Space Tech, which will help calculate how much a specific area in the broadcast is worth (digital or physical) and Predictive Media Value that will calculate precise media value and optimal placement based on viewership pipeline. “The distribution of live and recorded content is no longer centralized as consumers continue to customize their engagement through OTT subscriptions and streaming services. Our unique formula design evolves with the ever-changing consumer and digital landscape,” concludes Yao.