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AI Glossary: AI Personalisation

AI Personalisation uses machine learning to analyse user data and create tailored experiences, content, and recommendations.

Explanation

Imagine a world where everything you interact with online is perfectly tailored to your individual needs and preferences. That’s the promise of AI personalisation.

It uses machine learning to analyse vast amounts of data about you – your browsing history, purchase patterns, social media activity – to create a detailed profile of your interests, behaviours, and goals.

This profile is then used to customise your experiences, from the products you see to the content you consume.

It's like having a digital concierge who anticipates your every need and curates the world to suit you.

AI Personalisation enables us to avoid information overload.

Examples

Consumer Example

Think about your favourite online retailer.

When you visit their website, you see products that are specifically recommended for you based on your past purchases and browsing history.

You also receive personalised email offers and promotions that are relevant to your interests.

It's like having a personal shopper who knows your style and preferences.

Business Example

Imagine a bank using AI personalisation to provide tailored financial advice to its customers.

By analysing a customer's financial history, investment goals, and risk tolerance, the bank can offer personalised recommendations for savings accounts, loans, and investment products.

This improves customer satisfaction, builds loyalty, and increases revenue.

It's like having a personal financial advisor available 24/7.

Frequently Asked Questions

How does AI personalisation affect data privacy?

AI personalisation relies on collecting and analysing user data, which raises concerns about data privacy. It's important to implement robust data security measures and be transparent with users about how their data is being used. Companies must comply with data privacy regulations.

What are the limitations of AI personalisation?

AI personalisation can sometimes create filter bubbles, where users are only exposed to information that confirms their existing beliefs. This can limit their exposure to new ideas and perspectives. It’s important to balance personalisation with serendipity.

How can AI personalisation improve customer loyalty?

By providing tailored experiences and recommendations, AI personalisation can make customers feel valued and understood. This fosters a sense of connection and loyalty, leading to increased customer retention and advocacy.

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