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\u201cAI\u201d, \u201cChatGPT\u201d, \u201cprompt\u201d, \u201cBig Data\u201d, \u201cGemini\u201d: Are your LinkedIn feed or water cooler chats filled with discussions on the rise of AI? It’s on everyone\u2019s lips!\u00a0 Artificial intelligence is the talk of the town, from conversations over dinner<\/strong> to TV shows and across all business sectors…<\/p>\n Today, we’ll look at its impact on the online customer experience<\/strong>. From personalised product recommendations to real-time support and user sentiment analysis, AI is transforming how companies interact with their customers.<\/p>\n Below, we share our comprehensive guide to leveraging AI to personalise the customer experience<\/strong>.<\/p>\n <\/p>\n Traditional personalisation and segmentation methods rely on numerous variables:<\/p>\n Manually gathering and thoroughly analysing<\/strong> this data is a time-consuming task<\/strong>.<\/p>\n AI speeds up<\/strong> the process and provides a more in-depth shopping experience by analysing:<\/p>\n 📌 Example<\/strong>: Streaming platforms like Netflix and Prime Video use AI-powered product recommendation systems<\/a> to suggest content based on past user engagement.<\/p>\n Chatbots and AI-driven virtual assistants have significantly improved the quality of customer support. How? By reducing response times<\/strong> and ensuring effective resolution of problems<\/strong> that customers may have.<\/p>\n Thanks to conversational AI<\/a>, bots can now understand and respond to complex queries with near-human precision. What’s more, interactions can be written or spoken, and come in various languages!<\/p>\n Not to mention that AI-powered chatbots are available round-the-clock. Whatever the time of day or night, consumers can get answers to their questions.<\/p>\n Finally, predictive AI allows brands to access statistical analyses<\/strong> so they can anticipate potential problems. Businesses can then proactively find solutions and leverage conversational marketing<\/a>.<\/p>\n 📌 Example<\/strong>: E-shops can now boost their sales thanks to online chats<\/a>. AI-powered chatbots guide users through the buying process, answering their questions and suggesting relevant products in real-time.<\/p>\n E-tail is one of the sectors that has benefited the most from AI to personalise the customer experience.<\/p>\n The arrival of artificial intelligence now makes it possible to recommend products according to an individual’s preferences<\/strong>. It can dynamically adjust prices<\/strong> based on user demand and interest. It means you can personalise marketing campaigns<\/strong> to target each customer.<\/p>\n This means it boosts engagement and improves customer satisfaction, for a smoother user journey.<\/p>\n 📌 Example<\/strong>: E-shops now offer AI-powered virtual<\/a> fittings<\/a>, real-time product recommendations, and virtual sales assistants<\/a>.<\/p>\n As mentioned above, predictive analytics has led to notable advances in improving the customer experience. Because it allows businesses to anticipate customers’ needs before they arise<\/strong>.<\/p>\n This is particularly useful in sectors such as:<\/p>\n 📌Example<\/strong>: Some hotels use AI to enhance their guests’ experience, such as factoring in room requirements and suggesting personalised ideas for nearby activities and restaurants. To do this, they collect data based on guests’ previous stays. If Jean-Marc loves jet skiing, the hotel can, for example, offer him a tempting 20% off jet ski hire when he places his next booking.<\/p>\n The power of AI is growing everyday but, while brands can leverage the power of personalisation, they should be aware of how far this goes so as not to compromise privacy<\/strong>.<\/p>\n To do this, we recommend factoring in the following three guiding principles<\/strong>:<\/p>\n 📌 Example<\/strong>: You must state your data privacy policy if your site recommends products based on user searches and previous purchases. For example, you can opt for a clause like: \u201cThese personalised product recommendations are based on criteria such as your browsing and purchase history, customer segmentation, user behaviour and the buying patterns of others like you\u201d.<\/p>\n <\/p>\n Using AI to personalise the customer experience can come with drawbacks.<\/p>\n According to a study, only 51%<\/a> of consumers believe brands secure their personal data and use it responsibly. This figure stresses the importance of having clear data privacy policies in place.<\/p>\nWhy use AI to personalise the customer experience?<\/h2>\n
1. A more in-depth understanding of consumer expectations<\/h3>\n
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2. More helpful real-time interactions<\/h3>\n
3. A hyper-personalised shopping experience<\/h3>\n
4. Anticipating consumer behaviour<\/h3>\n
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5. Striking a balance between personalisation and privacy<\/h3>\n
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The downsides to using AI to personalise the customer experience<\/h2>\n
Data privacy<\/h3>\n
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