The media and entertainment industry is undergoing significant changes, including viewership habits, rapidly changing industry standards, and increased scrutiny around data use and consumer privacy. But an effective compass is available to navigate these changes: media analytics. Let’s examine the benefits media companies are experiencing using analytics and the key capabilities that will maximize these benefits.
Benefits of Media Analytics
Media analytics is a specialized form of analytics that tracks audience engagement, content usage, and other meaningful metrics to provide media companies with the insights they need to attract new customers, retain existing customers, and improve advertising offerings. Here’s how implementing a modern media analytics program can help both traditional and OTT media companies to thrive.
Enhance content development, acquisition, and monetization
Understanding the types of content users want to consume is an essential ingredient for growth. Without an accurate view of consumer preferences, media companies are left operating on hunches and gut instincts. Media analytics can uncover emerging trends in viewing or listening habits. Staying attuned to shifts in consumer preferences helps guide content development, making it easier to acquire new viewers, and helps media executives make better decisions about how to most effectively monetize content.
Improve content personalization and optimize recommendation engines
Today’s consumers expect a tailored experience that makes it easy for them to find the content they enjoy. Media analytics makes it possible to serve up highly personalized content suggestions to individual users based on their unique patterns of consumption and content preferences. Data gathered on the types of videos, podcasts, or music individual consumers choose to access can be fed to recommendation engines that suggest additional content that better reflects those interests. Data including preferred content length, format, specific content creators, and niche topics can all be used to recommend additional content that the consumer is likely to value but would otherwise be unaware of.
Optimize programming and scheduling
Analyzing customer data can help media companies to better optimize their program offerings and improve content scheduling. Knowing which content is the most popular and when audiences prefer to view various types of content can help to maximize viewership. As the popularity of certain content offerings grows or diminishes over time, platform analytics helps media companies optimize their content scheduling.
Improve advertising effectiveness
Accurately tracking ad campaign performance is a critical capability for achieving strong ROI. Media analytics allows advertisers to see which sources and which messages are driving the highest rates of conversion. Customer data from on-platform and third-party sources can also be analyzed to better understand customer sentiment about current content offerings, pricing and subscription models, and the accuracy of content personalization engines. These insights can be used to better understand what is working well and where improvements are needed in advertising.
Key Capabilities for Media Analytics
Gleaning the data-driven insights needed to expand viewership and boost ad revenue requires certain capabilities. Here’s what’s required for a successful media analytics initiative.
Access to relevant data
Data to power actionable insights can be found in your own platform data and in third-party data sources that provide a complete picture of customer behavior. Supplementing internal data sources with live, ready-to-query data sets from providers such as Snowflake Marketplace offers a more comprehensive view of consumer needs and preferences.
Securely share and combine consumer data across multiple clouds with limited copies and movement
Recommendation engines and other valuable analytics use cases require near real-time data to be effective. For this reason, you must be able to quickly get relevant data where you need it—without relying on traditional ETL or APIs.
To fully benefit from media analytics, you’ll need the ability to create unified profiles of viewers across devices and platforms. These profiles can be augmented with third-party data for a complete view of the customer. For example, Experian Identity Resolution is an identity service that provides access to Experian’s rich referential identity data. By matching separate identification data sets that could otherwise not be matched, it safely delivers opportunities that can be shared with partners and other key internal or external stakeholders.
Easily manage security administration with data clean rooms and auditability features
Data clean rooms make it possible to share data in real time with outside partners in a way that maintains the highest levels of data security by anonymizing the identity of individual customers. This technology enables organizations to match their data with other organizations’, making it possible to see the overlap between data sets. Data clean rooms can assist media companies with identifying high-value targets, lapsing customers, and opportunities to gain new business.
Handle any data format at scale
Every action on a media platform, website, or app represents a potential opportunity for customizing content and advertising messages to better meet the needs of the individual. This data is generated in a variety of semi-structured and unstructured formats. As the volume of available data continues to grow, it’s crucial to have a data platform with scalable storage and compute power with built-in features that facilitate speedy ingestion and processing.
Examples of Media Analytics in Action
Let’s look now at concrete examples to see how today’s media companies are using analytics to engage customers and boost advertising sales.
Disney Advertising Sales’ data clean room
Disney Advertising Sales is the entity responsible for the advertising sales and integrated marketing efforts of The Walt Disney Company’s sports and entertainment offerings. This organization uses a data clean room to provide advertisers on Disney-branded media properties with access to Disney Select, a first-party data solution. Through Disney’s data clean room, advertisers have access to over a thousand user segments they can use for their own ad targeting and analytics applications while advertising on one or more of Disney’s media holdings.
Read more about how Disney Advertising Sales is using its data clean room to raise the value of its advertising opportunities.
Simon Data’s differentiated ad products
Simon Data is an enterprise customer data platform (CDP) that leverages enterprise-scale big data and machine learning capabilities to enable brands to deliver data-driven, personalized customer experiences. Simon’s model allows brands to develop and deliver personalization capabilities without the need to construct and maintain their own massive bespoke data infrastructure.
Read more about how Simon Data’s enterprise customer data platform delivers personalized customer experiences.
Snowflake for Media Analytics
The Snowflake Media Data Cloud is specifically designed to help media companies implement powerful analytics programs to prosper in today’s increasingly competitive media and entertainment landscape. It empowers organizations to easily share consumer data with minimal copies and movement, all while maintaining privacy and data governance. Additionally, Snowflake Data Marketplace offers media companies seamless access to turnkey data products from over 175 third-party data partners for deeper insights.
See Snowflake’s capabilities for yourself. To give it a test drive, sign up for a free trial.