Personalising

Personalising, or personalizing in American English, is the process of tailoring products, services, or content to the individual preferences, behaviors, or context of a user. It relies on data about the user and automated decision-making to present a more relevant experience. Personalisation is often contrasted with customization, where users manually select settings; personalisation aims to adjust automatically.

Applications include digital marketing, e-commerce, media streaming, and website or app design, as well as education and health care. Common examples are product recommendations, personalised emails, adaptive learning paths, and dynamically adjusted interfaces that reflect a user’s language, region, or previous interactions.

Techniques used include data collection with consent, user profiling, behavioral analytics, and machine-learning algorithms such as collaborative filtering and content-based recommendations. Content and interfaces may be dynamically adjusted in real time based on context like location, time, device, or recent activity. A/B testing and experimentation are used to measure impact.

Benefits may include increased relevance, engagement, and conversion, improved user satisfaction, and more efficient information retrieval. Drawbacks include privacy concerns, data quality issues, bias or overfitting, filter bubbles, and the risk of over-personalisation reducing serendipity or autonomy. Transparency and user control are often recommended.

Ethical and regulatory considerations cover consent, data minimisation, purpose limitation, security, and the need to provide explanations for why certain content is shown. Regulations such as the General Data Protection Regulation and the California Consumer Privacy Act govern data handling and user rights.

Future trends include privacy-preserving approaches such as on-device or federated learning, and increased emphasis on accessibility and inclusivity to avoid discrimination.