| Case Studies
Human-Centered Workforce Transformation
Optimum’s Product Development was good, but the business needed it to be great. So we banded together to define what great looks like and how to achieve it by putting people first. [see more]
Accelerating Acquisition
While organic and paid acquisition was steadily adding customers to Discovery’s direct-to-consumer subscription product, they were not growing fast enough to offset the pay TV subscriber losses.
To accelerate subscriber growth an automated identity federation and entitlements solution was created to enable partners to sell Discovery+ to consumers as well as operate the billing and payments for the subscriptions. [see more]
Growing Audience
Exploration of location as a more effective content discovery approach than standard carousel and grid design patterns to reduce bounce rate. [see more]
Increasing Engagement
Connected TV app purpose-built for the needs of Investigation Discovery viewers to lift total viewing time with a low friction video-first experience. [see more]
Improving Outcomes
Machine learning models that continuously infer the acquisition of knowledge as people interact with Codecademy to improve the likelihood of mastering new tech skills.
Customer Obsession
Going beyond surveys, interviews, and usability studies the FiOS TV product team employed multiple capabilities to continuously interact with thousands of customers every month, using the data to drive the category’s highest satisfaction scores.
Five 9s Quality
Using data to find and fix issues anywhere in the customer experience, the Five 9s program helped Optimum Fiber win Ookla’s awards for fastest speeds, lowest latency, and best gaming across the Tri-State area – #1 for two years and counting.
Data-driven operations
In order to improve the application of data to decision support, ad sales, and the end-user experience Discovery’s platform engineering team developed a solution to capture data from front ends and APIs and enrich it for delivery to downstream systems, which resulted in decreased levels of effort to develop new features while increasing data integrity. [see more]
