Building A Scalable Strategy for Video Delivery

A Guide for Building a Data Architecture ready for Real-Time Decisioning and Automation

Originally posted to LinkedIn | June 8, 2018

Over the course of the nearly twenty-three years since the dawn of the streaming media space, beginning with that fateful Yankees-Mariners game in 1995, the industry has grown substantially, evolved its strategic approaches and technologies utilized, and then re-evolved accordingly to keep pace with the demands of the next generation. Today, online video commands 20% of total streaming hours, and counting.

What was once a concerted fight for legitimacy, the streaming media industry has transitioned into a quest for efficient and effective business development — with the biggest challenge now shifting from distribution to achieving sustainable margins. Thanks to advances in technology, audiences have benefited from a wider range of content, available to them at any time, in any place, and on any device. Although this has led to a paradigm shift in consumer expectations and the disruption of the linear television market, the business of streaming media has not caught up to its predecessors, with streamers struggling to monetize their content.

The challenge is two-sided: Content distributors need to increase demand for their content and grow earnings coming from online distribution (revenue), while at the same time they need to get more from less, and build greater efficiency and stability into the resources they are working with today (COGS). Despite falling price points for some key systems (like CDN), we have not evolved how we handle the dependencies, fail-overs and trigger points for how critical infrastructure and peripheral systems should work together to maximize potential.

We’ve reached a point where solving the latter challenge actually helps us kill two birds with one stone. If we want to build more profitable streaming businesses, we need to upgrade our core infrastructure technologies, not by replacing any one system but by creating technology glue that holds all of these systems together. Video distributors need a fundamentally different approach for harmonizing interactions between services, providing greater flexibility and ability to self-heal when failures are detected.

What is Adaptive Video Logistics?

Adaptive Video Logistics (AVL), is a new category of software for the streaming media industry, offering better data collection pipelines and integration for content distributors. Datazoom is pioneering this software category, with our patent-pending technology that is uniquely able to pull data from any software delivered environment (i.g. a webpage or video player framework) using “Collectors” — and push high-frequency, sub-second data to various software tools and destination(s) — what we call “Connectors”. We worked with some awesome companies to join our growing ecosystem at Datazoom.

So far we’ve built Collectors for iOS, Android, Anvato, Brightcove , HTML5, JWPlayer, & THEOPlayer. We’ve completed Connectors for Amplitude Analytics, Google Analytics, Heap Analytics, YOUBORA Analytics, Adobe Analytics (Omniture), New Relic Insights, Google BigQuery, Amazon Kinesis Data Streams, Datadog, Keen IO, and Mixpanel. New integrations are released every 1–2 weeks.

From Datazoom, which acts as an integration mission control, you can manage pipelines of data moving between Collectors to Connectors without needing developers to deploy new code. In addition, our platform is redefining real-time when it comes to data: we operate with sub-second latency, enhancing the usability of the metrics output by other platforms. But the true value of Datazoom is found in its strategic utilizations.

Three Pillars of Data for Adaptive Video Logistics

1. Efficiency — Simplified Data Collection

Most content distributors use several analytics tools, each of which requires a separate SDK to capture data. There are several consequences for using multiple SDKs: The added weight caused by each script has led to what is now known in the industry as “player bloat.” Furthermore, data collected for each tool not only ends up in silos but adds weight to the payload. But the real implication is the damage to the overall usefulness of data — any attempt to unify data gathered from disparate sources would have to face the challenges of data inconsistency, variability and duplication.

As a solution, the Datazoom SDK ensures efficient and consistent data collection and creates a single source for any data to be routed out, maximizing data utility.

2. Latency — Sub-Second Latency

Real-time seems to have a variety of definitions these days… in video streaming conditions aren’t changing hour-to-hour or minute-to-minute, but second-to-second. And the stakes are high — 2 seconds is all it takes to lose a viewer. For an industry whose conditions can change so abruptly (with significant potential consequences) why do we permit our data to be minutes or even hours behind?

Datazoom is laying the groundwork (specifically the data pipelines) required to usher in a new era of video operations, and can enable content distributors to adapt the ability to make decisions as changes occur, and leverage the limitless scale of AI and Machine Learning to power better video experiences — Automation. However, the strength of a decision (whether made by man or machine) is only as good as the information it’s given. We must begin to see that the value of our data is indirectly correlated with latency — the greater the latency the smaller the value.

We should begin to shift our focus not to only ensuring we have access to the data we need, but with the least delay as possible so decisions can be made as soon as changes occur. We’ve built Datazoom to capture data in less than a second. In fact, we guarantee it under our SLA. We know that this is what will be required to grow the business of online video, and match the experience of traditional television.

3. Utility — Creating the Data Feedback Loop

With a unified dataset being updated in real-time, video operations departments are in a better position than ever to receive meaningful feedback from distributed video. But the utility of data doesn’t stop there — the effort of video delivery requires alignment with critical, external services along the video delivery path, from Encode to Device. Data collected from the video player can be used to improve the hand-offs between these systems that ultimately impact the user experience and business of video.

Datazoom enables content distributors to provision access and distribute data in a way that create a sub-second latency feedback loop for key providers. Since Datazoom can segment data and parse it into various intervals, we ensure that the data we capture can be fit the unique backends of any system, increasing the total utility of data.

Broadcaster, Content Owner, OTT Platform Operator

Hallmark Media Family Networks is the team behind Hallmark’s wildly popular 24-hour cable networks: Hallmark Channel, Hallmark Drama, and Hallmark Movies and Mysteries.

They oversee content distribution across ten web, mobile, and OTT platforms with successful content offerings such as Home & Family, The Good Witch film franchise, and the historic Hallmark Hall of Fame their wildly successful original Christmas movies — more than 80 million people flock to their televisions to revel in the merriment of the season (which starts as early as September!).

Highlights

• Real-time analytics and reporting stack available company wide

• Consolidated multiple analytics and reporting solutions into a single platform

• Re-invest costs associated with multiple analytics solutions to other parts of the business

Challenges

With the consolidation of teams and platforms, Hallmark Media wanted to leverage the opportunity to improve their OTT streaming stack. During this time, they realized that part and parcel to improved streaming was the need to embark on a company-wide initiative to restructure their data strategy. Even with previously-approved implementations of their analytics providers, the conflict of expectations and support imposed a constant drain on development resources and budgets that were needed for other projects.

• Reduce the number of reporting and analytics solutions in use across the different media properties

• Eliminate the need for constant development resources needed to optimize and configure different analytics solutions

Solution

Knowing that they’d be looking to do more with BigQuery & Google Analytics than they’d previously explored, Hallmark looked to Infotrust to help them define and deliver a video analytics solution leveraging Datazoom as a source of video data. Infotrust began with an audit of Hallmark’s current analytics implementations to better understand how they were being used and by what teams, where shortcomings existed, additional things they wanted to accomplish with their new analytics stack. The Infotrust analytics consulting team provided a detailed breakdown of all the requirements, as well as how data should flow to both BigQuery & Google Analytics to meet those requirements. Then Infotrust got to work, partnering and coordinating with Hallmark Media and Datazoom’s team to build metrics, dashboards and reports to monitor Audience, Content, Advertising and core video KPIs. This then translated into defining what events, metadata fluxdata and custom events/metadata were needed to generate the required insights. Infotrust, Datazoom and Hallmark Media met regularly to ensure that the schedule was being kept, and deliverables met expectations.

Results

Infotrust ensured that by the end of the engagement, Hallmark Media had a more powerful, reliable, real-time reporting and analytics stack. By implementing Datazoom as their Data-as-a-Service platform, they now have a developer friendly solution that helped them reduce the number of analytics solutions used, and reduced the complexity of maintaining multiple solutions. The overall engagement with Infotrust and Datazoom has allowed their team to re-invest both resources and analytics cost savings into other areas of their business.

With the consolidation of teams and platforms, Hallmark Media wanted to leverage the opportunity to improve their OTT streaming stack. During this time, they realized that part and parcel to improved streaming was the need to embark on a company-wide initiative to restructure their data strategy. Even with previously-approved implementations of their analytics providers, the conflict of expectations and support imposed a constant drain on development resources and budgets that were needed for other projects.

• Reduction in number of analytics and reporting solutions

• Cost-savings related to licensing and maintenance of multiple analytics and reporting services

• Improved agility and flexibility to configure future analytics and reporting requiremetns

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Datazoom’s DaaS platform was the only solution on the market which could consolidate data collection across multiple end devices, replacing a number of incumbent analytics and reporting integrations. While enabling this consolidation to a single data collection SDK, the DataZoom platform also provided a low-code means to configuring, optimizing, and building future data pipes. This reduced the amount of development and capital resources required to support the existing analytics and reporting stack, allowing Crown Media to divert those resources to other priority projects without undermining the collection and delivery of data to business units across the organization.

Content Owner, OTT Platform Operator

Company

Canela Media is a leading, certified minority-owned technology driven media company offering brands a complete ecosystem to connect with multicultural audiences starting with its free streaming platform service, Canela.TV enriching the new generation of U.S. Latinos with free access to unique, culturally relevant content which includes a unique blend of music programming through Canela Music featuring emerging and established Latino artists, Spanish-language Children’s content through Canela Kids and sports content through Canela Deportes.    As part of Canela Media’s proprietary data solution offering, Canela Connect is centered on an OTT first approach that helps identify U.S. Hispanic audiences in English and Spanish language OTT platforms providing unprecedented OTT scale for advertisers to reach U.S. Hispanics. Moreover, Canela Media’s large scale in premium Spanish-language sites, combined with the company’s proprietary data, provides in-depth knowledge and understanding of how to establish meaningful and culturally relevant connections with the new mainstream Hispanics across the U.S. and Latin America. 

Solution

• Consolidated data pipelines across the company onto a single platform

• Integrated data stream with existing toolchains increasing the speed of data insights

• Addressed all devices through a single SDK for data collection

Results

By leveraging the Datazoom platform, Canela Media is able to leverage a single, cost-scalable solution to power a broad scope of analytics requirements to support product, engineering, ad sales and ad ops teams. Canela Media has the flexibility to route data to new endpoints and dashboards, in order to remain in control of their data and analytics journey.

• Consolidate data capture needs across business units into a single platform

• Improved insight into how users engage with content

• Able to leverage existing investment in data analysis and visualization tools

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As a turnkey Data-as-a-Service platform, we were able to get up and running very quickly. By implementing just a single element into our video player (the DataZoom SDK), we could build a variety of different data pipes to deliver metrics to business units across the organization. This allowed us to get up and running quickly to better understand how viewers engage with our content and streaming platform while providing a means to maximize views and revenue.