Personalised Content Recommendations

Problem

Customers expect highly personalised content based on their preferences and needs. As a traditional way, marketers and media professionals create and deliver segment-based content based on historical data. Unfortunately, this approach is based on broad segmentation or manual preference selection, which leads to low click through and conversion rates. For example, a media website page with generic information fails to increase content consumption, a marketing email with generic messages and offering has low conversion rate.

How can TurinTech help? 

With TurinTech, you can create accurate models to understand customers’ interests and predict their preference based on their real-time behaviors, such as current browsing contents, prior clicks and purchases. In addition, AI can be used to dynamically select 1:1 personalised content (e.g., news, emails, articles) that match a given customer at the right time. These personalised content recommendations significantly increase the chances of a customer consuming more content than generic recommendations, which are based on outdated insights or broad segments.

Benefits
  • Personalised content at scale: provide a one-to-one personalised content for every customer quickly and at scale.​
  • Increase content consumption and conversion: faster with more relevant content recommendations.​
  • Boost customer experience: personalised customers’ journey to improve experience.
This is a staging enviroment