Pluggability

As video services mature, relying on an off-the-shelf recommendation engine alone can prevent platforms from delivering the personalized, relevant experiences necessary to stand out in a competitive marketplace.

From shifting user preferences to changing seasonal trends and the complexities of managing extensive content catalogs, maintaining flexibility in curation and personalization is crucial.

Editorial teams need the ability to adapt rapidly, integrate multiple data sources, and experiment with new recommendation strategies.

The growing demand for customization and adaptability leads to the need for a solution that can evolve alongside a platform’s growth and complexity.

Integrating Custom Models with UX Engine Pluggability

UX Engine Pluggability addresses the need for flexibility by allowing operators to incorporate bespoke recommendation models tailored to their unique business needs.

Rather than being restricted to off-the-shelf algorithms, operators can adopt bespoke AI/ML models, whether built from internal efforts, our customer success team, or partners.

Pluggability empowers teams to seamlessly integrate these models into the existing UX Engine framework, making it a versatile tool for content personalization.

Whether working with proprietary data, third-party datasets, or a mix of both, this feature enables experimentation and optimization.

The models can be seamlessly plugged into the engine, tested, iterated, and adjusted according to changing business goals or user behavior.

By supporting custom AI models, Pluggability opens the door for editorial teams to enhance discovery experiences in ways that align with their vision.

Customization, Experimentation, and Improved Outcomes

The primary benefit of Pluggability is the unparalleled flexibility it offers.

 Editorial teams can tailor content recommendation strategies to their specific objectives—whether it’s driving click-through rates, increasing content discovery, or improving user engagement. 

This feature encourages a culture of experimentation and continuous improvement by empowering teams to deploy custom models within the UX Engine. 

As business needs shift, models can be updated or swapped out without disrupting the overall user experience. 

Pluggability ensures that operators are never locked into a single recommendation strategy, allowing them to dynamically respond to user behavior, market trends, or new business opportunities. 

This adaptability enhances the user experience by offering personalized and relevant content and provides editorial teams with the tools they need to succeed in a competitive environment.