Predict and identify patterns in audience behavior.
How SAS Delivers Superior Audience Analytics
Our integrated audience analytics framework relies on actual viewership data and incorporates data management, big data visualization and advanced analytics – including data mining and forecasting – to reliably predict future audience behavior and content performance.
- Forecast the viewing behavior of audience segments using seasonality, causal factors and events to increase accuracy. Use historical audience measurement data to perform lookalike modeling on new content.
- Discover why audience segments tune in and out using vast volumes of audience data combined with historical measurements – e.g., clickstream, ad server, set-top-box, ComScore or Nielsen.
- Easily perform likely outcome analysis of various programming scenarios or viewership levels to drive critical business decisions to strengthen your brand.
Media campaign stewardship
- Reduce liability and increase monetization using SAS data management, forecasting and optimization technologies.
- Ensure accurate and timely campaign stewardship across all platforms by enabling faster decision making in response to rapidly changing audience and inventory levels.
- Automate cumbersome data engineering processes e.g., cleansing, standardizing, deduplicating, merging and applying business rules – to make data available for business use quickly.
- Incorporate viewership patterns, device preferences, and demographic, geographic and psychographic characteristics into advanced clustering algorithms to find out which audience segments are most valuable to your business.
- Increase revenue and viewership using analytically derived audience segments to enhance your advanced advertising and targeted marketing platforms.
- Use AI and machine learning to derive recommendations based on historical viewership, consumer behavior and contextual factors (location, time of day, holidays, etc.).
- Harvest social and other unstructured data to determine trending content in real time.
- Incorporate business objectives and constraints to optimize available content and maximize profits.
AI for video analytics
- Apply market-leading deep learning and natural language processing techniques to detect objects, scenery, expressions and sentiment in movies, TV shows, commercials and promos, creating extensive frame-by-frame metadata to support causal factor analysis for viewer retention and drop-off.
- Use rich metadata to empower the consumer with wide-ranging search capabilities.
Why do TMT companies choose SAS® for audience analytics?
SAS provides a breadth of analytic capabilities – audience forecasting, AI/ML for content personalization, text analytics for surveys and social media, etc. – to address your most pressing challenges, and scalability to quickly process large volumes of granular audience data. In addition, SAS can be used by a variety of users with varying skill sets, including media executives, researchers, ad sales reps, finance personnel, business analysts and data scientists.
Analyze audience data of all types, sizes and complexity, quickly and easily
SAS integrates with the most common data sources, including ad serving, sales and ad trafficking, audience measurement, social media and surveys. In-memory analytics requires less data movement, enabling you to analyze audience data on the fly. Plus, you can analyze all your data instead of just samples.
Perform large-scale, automatic audience modeling
Forecast audiences quickly and at scale by generating millions of highly accurate forecasts for each program and audience segment across all platforms in minutes. SAS can automate the process for training forecast models to minimize the amount of coding required while giving you the flexibility to override and customize your forecasting algorithms.
Take action in real time while data is still in motion
Take next-best actions in real time while accounting for network performance, current content consumption, website activity and other variables. High-volume event stream processing at millions of events per second results in low-latency response times.
Extend your open systems environment with a centralized analytics framework
Combine the benefits of SAS and open systems within your organization. Centrally manage the analytics life cycle while taking data prep and deployment, speed and support, and performance and scalability into consideration.
SAS helps Viacom perform segmentation based on TV viewing behavior along with audience demographics, psychographics, social media chatter and purchasing propensity. Fabbio Luzzi Vice President, Advanced Analytics & Data Science Viacom
How does a global media company develop better plans for advertising shows and optimize promo placements across all its brands on a regular basis, for new or existing content?
SAS helped Viacom Media Networks:
- Group TV viewers into segments based on consumption of hundreds of shows, different types of profiles and purchasing behavior, then use machine learning and data mining techniques to process multidimensional data points in parallel.
- Build audience segmentation models based on viewing data, demographic and psychographic profiles, purchasing behavior data and more.
- Mine Nielsen’s all-minute respondents to identify audience segments, then design and implement strategies to target them.
- Track the effectiveness of its marketing plans, ensuring they deliver maximum conversion and rating lift.
Improve media sales with AI and machine learning
Find out how analytics with embedded AI provides insights for targeting the right customer microsegments to turn data into revenue.
Harness audience data to minimize churn, grow content viewership and boost ad revenue
Learn how you can gain insights into how customers consume content and find new ways to increase engagement and retention.
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