Video services are seeking ways to optimize the performance of their businesses in as many dimensions as possible. Data, insights, and actions enabled by the application of artificial intelligence (AI) and machine learning (ML) can maximize their abilities to compete and thrive in the current high-pressure streaming video landscape. In today’s competitive landscape, video service providers need to be attuned to the wants, needs, and preferences of their subscribers. Often, subscriber goodwill is lost via the customer experience (CX), which can be a conglomeration of multiple facets of the customer journey.
Content personalization is perhaps the most common example of applying AI to improving the customer experience. Beyond content personalization, there are numerous use cases for which AI-enabled insights can improve different aspects of the customer experience. AI can ingest and analyze any number of sources of subscriber data to gain a more broadly informed, in-depth understanding of a subscriber’s wants, needs, and behavior. This deeper understanding of the subscriber can then drive more precise and effective personalization of content offerings, advertising, dynamic pricing, product and service offers, and more.
Revenue optimization
For companies in the OTT video services market, the concept of optimizing revenue can be a daunting task, especially given the effort needed to analyze and derive insights from multiple sources of big data. For services, AI solutions can automate the process of driving optimal revenue through several business aspects of video distribution and/or service provision - such as driving smarter recommendations, reducing churn, creating more advanced subscriber segmentation, optimizing content, increasing trial conversions, and reducing customer acquisition cost. For content distributors, AI can speed and ease the processes of tracking, analyzing, reporting, and auditing license-based revenue. Solutions that utilize AI-enhanced data can maximize revenue generation for either business perspective by reducing the speed and overhead costs of data analysis and minimizing revenue loss
Content optimization
When it comes to retention; subscriber satisfaction is key. A vital factor in maintaining satisfaction is having a fresh and constant supply of individually relevant content. AI and ML can facilitate the identification of content most relevant to both individual subscribers and segments of the larger subscriber base. AI can also aid in predicting and driving the content suggestions that are likely to generate maximal revenue for individuals and customer segments. It can personalize recommendations to fit each individual user, across multiple segments, and improve recommendations over time as it acquires and digests more data. A service that delivers highly relevant content to each subscriber will be “stickier” with its consumers than one reliant on a more self-service content search and discovery experience.
Audience analysis
With the variability of the current OTT video landscape, including evolving streaming video consumption behaviors among different age groups, potential changes between pre- and post-pandemic video consumption and subscription behavior, and ever-escalating competition, services must be able to analyze their audience and detect patterns and anomalies to correct potential problems or capitalize on new opportunities quickly.
Parks Associates data uncovered interesting trends when pre- and post-pandemic video consumption was examined by age group. Video consumption levels since 2019 have trended very differently for the 18-24 and 45- 54 age groups in the US, and these distinct shifts represent opportunities that may or may not have been fully capitalized upon by OTT service providers. The ability to be alerted to, and to understand, the interrelated causes and effects of these trends as they are occurring would be invaluable to companies’ decision-making processes. AI solutions can identify patterns and relationships in data and, when augmented with unsupervised ML capabilities, uncover “hidden” opportunities to optimize a service’s strategies.
Timely and insightful data is crucial to making faster and more effective business decisions than one’s competitors – a vital edge in today’s increasingly-crowded and competitive OTT video landscape AI and ML can significantly enhance the quality, relevance, and impact of the data collected and the resulting insight. AI-enhanced data empowers video services and content owners to efficiently optimize their businesses and more quickly formulate effective strategies to serve their customers.
Download Parks Associates’ and Symphony MediaAI’s complimentary whitepaper for more research on the drivers and use cases for artificial intelligence (AI) and machine learning (ML) - enabled data in the video services market.
Paul Erickson is a senior analyst at Parks Associates with more than 20 years of technology industry experience. Erickson’s coverage has spanned connected consumer electronics, pay & broadcast TV, digital & physical media, streaming devices and services, home and pro AV, smart home, user interface technologies and digital rights management.
Industry Voices are opinion columns written by outside contributors—often industry experts or analysts—who are invited to the conversation by Fierce Video staff. They do not represent the opinions of Fierce Video.