Norsk Hydro uses AI recommendations to act on unique interests

Renewable recommendations

Norsk Hydro ASA is a Norwegian aluminium and renewable energy company, headquartered in Oslo. It is one of the largest aluminium companies worldwide operating in 50 countries on all continents and employing over 30,000 people. The organization is committed to leading the way towards a more sustainable future, creating more viable societies by developing natural resources into products and solutions in innovative and efficient ways.

Norsk Hydro needed an automated and intelligent content strategy to help build a website with personalized content by region and persona. Having used outdated automated translation and personalization content tools in the past, the team was keen to find a solution that benefits the site visitor and is easy to navigate from the backend, by the digital team by removing arduous manual processes.

Personalizing the story to a greater extent

Optimizely’s Web Content Recommendations was the perfect tool for Norsk Hyrdo’s project. AI-powered recommendations act upon the unique interests of each visitor in real-time to help Norsk Hydro deliver personalization with minimal manual effort and serve each visitor the most relevant content automatically.

AI-powered interest profiling technology generates first-party intent data profiles for all visitors, even if the visitor is anonymous. This real-time interest profile at the individual level serves as the foundation for 1:1 recommendations.

Norsk Hydro now has a fully automated process in place. Optimizely’s Web Content Recommendations enable the business to maximize the relevance of its content for each visitor to encourage deeper engagement with recommendations powered by real-time. The team is able to filter relevant content from a reliable source that allows the website to drive high value personalized content. The machine learning algorithm does the heavy lifting of choosing who gets what content without bogging the team down with endless "if/else" rules, yet allows for manual interaction if required to empower local editors. The team can now easily measure uplift and results with the built-in dashboard which provides clear metrics on the uplift from recommendations enabling them to quantify the value of personalization.