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C-Level Interview: Diane Strutner, CEO, Datazoom
All too often, the online video industry conflates "data" and "metrics." Datazoom's Diane Strutner breaks down the difference, and proposes new ways to handle data, metrcis, and analytics.
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Each issue, Streaming Media sits down with leading executives in online video to get their insights into the problems, challenges, and opportunities facing the industry. In this kickoff interview, we spoke with Diane Strutner, CEO of Datazoom, a company founded in 2017 with the goal of making data more accessible and more useful to online video publishers. 

Q: “Data” is one of the biggest buzzwords in streaming video right now. What are the kinds of data points that streaming video publishers and OTT services need to be looking at?

Diane Strutner: Let’s start by defining “data.” A data point is non-negotiable, raw information that can act as a point of truth. Unfortunately, I believe our industry suffers by conflating “data” and “metrics.” Metrics are formed by bringing many raw data points together. Although there’s been movement toward standardizing these calculations, most vendors calculate metrics differently, and thus we cannot use cross-vendor metrics for comparison purposes.

I believe the industry has been sold on a world of metrics creating vs. data gathering, and so the overwhelming majority of content distributors don’t capture any of their own data, nor do they have access to it or control who does. Post-processed data or metric measurements are stored in silos by third-party tools, and are only made available minutes, hours, or days later.

Q: How does Datazoom approach data and analytics differently?

To start, Datazoom views the functions of capturing data and analytics as separate things.

Data falls into two categories. We can call the first Functional—data used to power critical services—and the second Feedback—data that lets us know how things are performing. The VAST events exchanged between a player and an ad server are Functional data, whereas throughput or bitrate measurements today are Feedback data, as they aren’t critical to performance.

Datazoom is building the first data capture library of every data point, produced by any service, that can be captured on any player, platform, or device in video. Since every platform is different, we have many data libraries. Datazoom is focused on data capture, management, and routing, enabling customers to not only capture any and all data (without duplication), but also send it wherever it needs to go. Our ecosystem of “Connectors” currently includes analytics (both video-specific and generic tools) and data warehouses, and will later include ad servers, CDNs, and other services that rely on Functional data. We want to move the industry away from using many third-party SDKs, which bloat the video player, over to a single SDK for improved collection and control of data.

Q: With “zoom” in the name, presumably speed is central to what Datazoom does? How do you achieve data reporting and analytics at high speeds?

Since the world of video streaming operates on a second-to-second basis, data should be held to the same standard. We guarantee sub-second latency on data retrieval using our patent-pending platform and Data Delivery Network over the public cloud. Speed is (literally) built into our platform.

Q: How easy is it for publishers to integrate the Datazoom solution into their workflows?

Our demo will take you through the integration process. It takes five minutes. We have a one-time, one-line-of-code, copy-and-paste integration that collects video player data, called a“Collector.” Next, inside our interface you set the data points you want to capture (metadata, events, or FluxData), and capture frequency, down to once per second. Last, you select the tools and input
the account identifier(s) for each tool you want to send data to—called
“Connectors”—and you’re done! You’ll start seeing your data, in different analytics systems, in seconds.

Q: What’s on the horizon for data and video? What’s next?

If you think about it, we’ve not been able to use data in a meaningful way on a per-stream basis. We pump data into analytics systems, where people look at screens and try to take action on big issues. People are the intelligence and optimization behind video. But since video streaming happens on a second-to-second basis, people often cannot react to a change in the time required to be impactful, and can only take on one issue at a time.

In the future all data will be Functional data. Technologies like machine learning and AI can handle the volume, variety, and velocity of data created by video, and can be rolled out at scale to make changes on a per-stream basis. But these platforms require data. Fast data.


Diane Strutner is a proven corporate leader. She was previously the VP of Global Sales and Business Development at NicePeopleAtWork. She played a pivotal role at the company in both sales and business development, shifting the company focus from several products to their budding QoE Video Analytics platform. Before NPAW she was the Director of Business Development at GetApp (Acquired by Gartner). A California native, she is a graduate from Manhattan College where she earned a Bachelors of Science in Marketing and was a Division 1 scholarship athlete who competed and served as team captain on the indoor volleyball team.

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