Personalise your website with AI: basics and best practices

Personalising your website to align with visitors’ needs can differentiate your business from the competition. Personalisation helps shape the user experience of your site, and an excellent user experience boosts engagement and even customer retention over the long term.  

In this article, we will show you how you can use artificial intelligence (AI) to personalise your website to tailor your content, products or services to the individual needs and interests of your users. Let’s get started!  

Benefits of website personalisation   

Personalising your website can create a closer connection between your company and your customers, besides improving the user experience. Here’s a few direct benefits you can experience:  

Improved relevance to visitors: Your website or online store visitors feel engaged by content that is relevant to them, which makes them feel understood and valued – for example, with product recommendations based on previous purchases or search queries. 

Boosted metrics: Customised content increases the likelihood that users will stay on your website, interact with the content offered, and ultimately convert. 

Efficient website experience: Personalisation reduces the mental load on users because they no longer have to search for suitable products or information themselves. Everything they need is presented to them directly! 

The role of AI in personalisation  

Websites, apps, and other digital platforms generate huge amounts of data from different sources, including usage analytics, click-through rates, purchase history, demographic information, and social media activity.  

The challenge is to analyse these data in a meaningful way and turn it into action, and it’s exactly in this process that artificial intelligence has a role. 

Advantages of AI over manual personalisation 

1.     Efficiency and scalability  

Manual personalisation requires significant resources as marketers and developers need to segment audiences, customise content, and run tests – all of which are automated and real-time with AI.  

2.     Precision and accuracy 

AI recognises patterns and correlations in data that are often hidden from the human eye. It minimises the error rate that can occur with manual approaches and delivers more precise results by continuously optimising itself. 

3.     Real-time adjustments   

Unlike manual approaches, which often come with delays, AI can react immediately to new information or a change in user behaviour. This allows for dynamic changes to content, for example when a user changes their preferences or clicks on a specific offer. 

4.     Personalisation at the individual level 

While manual personalisation is usually based on broad audiences, AI enables ‘hyper-personalisation’, meaning that content can be customised for each individual person rather than just broad audiences. 

5.     Long term cost savings  

Even though initial AI setup requires some investment, in the long term it can lead to significant cost savings. Companies can work more efficiently because AI takes over many repetitive tasks that would otherwise have to be done manually. 

6.     Continuous improvement 

AI systems learn from every interaction to continuously improve their performance. Manual approaches, on the other hand, require frequent human revisions, which is time-consuming and costly. 

For example, an online-shop could use AI to offer personalised product recommendations based on browsing history and previous purchases. Without AI, a marketing team would have to analyse the data and manually create campaigns – a process that is inefficient and error-prone.  

Fundamentals of AI-powered personalisation  

What is AI personalisation?  

AI personalisation refers to the use of artificial intelligence to create individual user experiences. AI analyses large amounts of data and uses algorithms to tailor content, products, or services to the needs and preferences of individual users.  

AI personalisation concepts 

1. Machine learning
   Machine learning is a field within AI in which algorithms learn from data to improve over time without needing to be specifically updated. It relates to personalisation as machine learning means a system can recognise patterns based on past user behaviour and use them to predict future preferences.

2. Algorithms are decision-making assistants
   Algorithms form the technical heart of AI-supported personalisation. They analyse data, identify relevant information, and make decisions based on it. 

3. Data collection forms the basis
   Personalisation begins with the collection of data. Data can be collected directly, for example when a user searches for something, or indirectly, for example by tracking clicks, time on page or purchases. In addition, information about demographics, location, or seasonal trends are often included.

4. Linking user and product data 
   In order to adapt content in a targeted way, AI combines data about user preferences with product and content attributes. This can include colour and style preferences for fashion products, or genres and ratings for streaming services.

5. Predictive analytics  
   With the help of predictive models, AI can also predict future interests. This makes personalisation not only reactive, but also forward-looking.

How AI uses collected data 

The foundation for AI-powered personalisation is the intelligent use of data. AI algorithms analyse extensive information to recognise patterns and derive personalised experiences from it.  

By linking behaviour, location, demographics and purchase history, a comprehensive user profile is created. This profile is continuously updated, so personalisation is real-time and dynamically adapts to new information.  

The intelligent use of data enables companies to not only better understand users and identify patterns of behaviour, but also to offer them exactly the products and content that really interest them. In addition to satisfaction, this also increases the conversion rate and customer loyalty. 

The process: analysis, segmentation and customisation 

AI-based personalisation goes through a multi-step process from data to action to provide a tailored experience for each user. The most important phases are: 

1. Analysis of the data 

In the first step, the AI collects and analyses the available data from various sources: 

• Behavioural data: Clicks, search queries, time on page, landing pages viewed, products in the shopping cart, etc.   

• Search queries: What do users type into the search bar? 

• Purchase histories: Purchases made, preferences for certain brands or product categories 

• Geolocation: A user’s location data provides helpful insights, such as language or currency selection. 

• Previous purchases: Purchase history provides valuable information about preferences and needs.  

• Demographics: Age, gender, income or marital status help to better understand target groups and make specific recommendations.  

 2. Segmentation

After the analysis, users are divided into groups, or segments, that have similar behaviours or characteristics. For example: 

• Demographic: e.g., age range, gender, or location 

• Behaviour-based: e.g., frequent shoppers, casual shoppers, or bargain hunters 

• Interest-based: e.g., users interested in sporting goods, technology, or fashion 

This segmentation helps deliver personalised content without having to manually edit each individual user profile. 

3. Customisation 

In the last step, AI goes beyond segmentation to customisation. This is done by: 

• Personalised product recommendations: Based on user behaviour and individual customer preferences – e.g., complementary products such as accessories or refills. 

• Dynamic content: The homepage, emails, ads or blog posts are automatically tailored to the individual user. 

• Predictive personalisation: AI predicts future needs or interests and proactively suggests suitable products.  

Example of a process: 

1. Analytics: A user visits an online store and searches for outdoor jackets. The AI recognises that similar users have often also bought hiking boots. 

2. Segmentation: The user is assigned to a group of ‘outdoor enthusiasts’. 

3. Individual customisation: The shop shows hiking jackets and boots on the homepage as well as blog posts about outdoor activities. 

This three-step process enables the AI not only to understand users, but also to serve them individually. The result: a more relevant, efficient, and satisfying interaction that benefits both users and the business.  

Strategies for AI-powered personalisation of your website

Dynamic content 

Dynamic content is a core part of AI-powered personalisation. With AI, it’s possible to adapt the presentation of content on your website in real time to the individual needs and interests of users. This content includes:  

• Product suggestions: Based on a user’s past behaviour, such as products viewed or purchased, similar or complementary items can be recommended. 
• Personalised banners and offers: Special promotions or discounts can be targeted to users who show an increased interest in certain products or categories due to their surfing behaviour. 
• Content customisations: Blog posts, articles, or news can be prioritised or highlighted according to the user’s interests. 

Personalised navigation 

Personalised navigation makes it easier for users to find their way around a website and helps lead them to relevant content more quickly. With AI, the menu navigation or the display of the categories is individually adapted to the preferences and interests of the users. 

Customising the navigation menu or displayed categories  

AI-powered navigation analyses user behaviour and preferences to highlight relevant content and categories. Examples of such adjustments: 

• Menu navigation: Categories or menu items that a user visits frequently are prioritised and put in the foreground. 

• Filter options: Specific filters are suggested based on previous searches or purchases (e.g., sizes, colours, or styles for a fashion store). 

• Recommended categories: Products or content from favourite categories are displayed more prominently to increase the likelihood of clicks. 

Targeted recommendations 

Targeted recommendations are one of the most effective ways to drive personalisation on a website and offer users relevant products, services, or content.

These recommendations are based on users’ interests, behaviour, and preferences and are dynamically generated using AI algorithms. 

Highlighting based on user interests 

AI-powered systems analyse a variety of data points to make targeted recommendations. The most common recommendations are: 

• Product suggestions: Based on the products previously viewed or purchased. 

• Service recommendations: Users who have used a certain service receive appropriate additions or upgrades. 

• Content recommendations: Content based on their previous reading or viewing habits. 

Targeted recommendations add value to users by introducing them to relevant products or content while boosting the visibility of specific offers. 

Chatbots

Chatbots are another powerful tool for AI-powered personalisation. They provide users with immediate, personalised support and can intelligently make recommendations, answer questions, and guide them through the buying process.  

How AI-powered bots can provide users with personalised support 

AI-based chatbots use natural language processing (neurolinguistic programming, NLP for short) to communicate with users and identify their needs. Chatbots can: 

• Give product advice: Chatbots can make tailored product recommendations based on the user’s wishes and requirements. They ask specific questions to learn more about the user’s taste or needs and then suggest products. 

• Answer questions: Bots can provide information on products, prices, availability or order status in real time – perfect customer service. 

• Shopping assistance: Chatbots can accompany the user through the entire purchase process and advise them – from product selection to the shopping cart to checkout. 

• Personalised communication: Bots learn with every interaction to further improve the user experience on future visits. 

Chatbots are a great way to improve the user experience and promote customer satisfaction.  

Dynamic pricing  

Dynamic pricing allows companies to adjust prices in real time. To do this, the AI analyses various factors and personalises prices for products or services. 

User-based personalised pricing

AI-based systems monitor user behaviour and their interactions with the website to create customised price quotes. Some of the key factors that go into dynamic pricing include: 

• User behaviour: Frequent searches for specific products, adding items to the shopping cart, or repeatedly visiting a product page can lead to customised price quotes to entice the user to buy. 

• Demand: If a product is in high demand or availability is limited, the price can be adjusted accordingly to manage demand. 

• Location: Geographical differences can also affect the price. Products or services are often dynamically adjusted based on the user’s location (e.g., price differences by country or region). 

• Time factors: Pricing can also be influenced by the time of day, day of the week, or seasonal conditions, as this allows companies to respond to specific needs or trends. 

By using dynamic pricing, businesses can maximise profitability while providing users with an attractive, personalised offer. This strategy makes it possible to deliver a good price perception to visitors and target them where they are most receptive to offers. 

Integration into existing websites 

To successfully integrate personalisation on your website, you should follow these steps (note that not all steps make sense for every type of personalisation): 

1. Data analysis: Collect and analyse relevant user data to find behavioural patterns and preferences. 

2. Segmentation: Divide your user base into different segments to deliver targeted content to specific groups. 

3. Data integration: Make sure that the chatbot, for example, can access relevant data, such as product catalogues or user profiles. 

4. Adaptation: Develop algorithms that adjust the respective elements (navigation, blog posts, recommendations, prices, etc.) in real time based on the data collected. 

5. Testing and optimisation: Conduct regular A/B tests to verify and continue improving the impact of personalised content. 

A chatbot-specific tip: Train the bot with real user interactions to optimise its responses and improve the user experience. 

Technical integration of AI systems 

Integrating AI-powered personalisation systems into existing websites, for example into WordPress-based websites, is now easier than ever thanks to new tools and platforms. Even if you don’t have extensive technical knowledge, you can still get the benefits of AI.  

There are various strategies and technologies that make it possible to easily integrate AI functions without the need for in-depth programming knowledge. 

1. Easy-to-use platforms and tools: There are many website personalisation platforms and tools that are specifically designed for users without extensive technical knowledge. Tools like Optimisely or Adobe Target offer an intuitive interface that allows you to run tests and personalisation without digging deep into the code.  

2. Use of pre-built chatbots and assistants: If you want to implement an AI chatbot on your website, then you can use platforms like Chatfuel, Tidio or ManyChat to create your own chatbot without any coding knowledge.  

3. Content management systems (CMS) with AI integration: If you’re using a CMS like WordPress, you can add AI-powered features via pre-built integrations or plugins – such as for product recommendations, personalised content, or A/B testing.  

4. Easy API integrations: APIs offer an easy way to integrate AI services into your existing website. There are many API-based AI tools that require little technical knowledge. Providers such as Google’s Dialogflow for chatbots or Clarifai for image recognition offer easy-to-use APIs that you can integrate into your existing infrastructure. 

Personalise your website with AI 

AI-powered personalisation improves the user experience on your website, helping to create long-term business success. Tailored experiences better meet the needs of your users and make interacting with your brand more relevant and exciting. This leads to higher customer satisfaction, stronger customer loyalty, and ultimately a better conversion rate. 

Feel free to be bold and experiment with different approaches, run A/B tests, and optimise your personalised offers with the data you collect. With a personalised website, you can gain a clear competitive advantage in the long term. Good luck testing it out!