Harnessing AI for Value-Based Personalisation: Driving Customer Engagement and Loyalty

Businesses are getting the edge on their competitors through forging deeper, stronger bonds with customers - thanks to technology

Brands are constantly striving to differentiate themselves in today's hyper-competitive landscape: one of the most important ways for businesses to achieve this is through personalising messages early and often to beat the competition. Traditional marketing is still reliant on generic marketing, but there is a fast-growing industry based around meeting the expectations of customers who want experiences that cater to their individual needs and preferences.

Artificial Intelligence (AI) is playing a crucial role in enabling the kind of personalisation that generates more sales and loyal customers, a strategy that focuses on delivering experiences that resonate with a customer's perceived value. In this article we will look at how AI plays this role, dynamic content personalisation and using predictive analytics powered by AI.

How AI plays a crucial role in enabling value-based personalisation

Value-based personalisation involves customising interactions based on what customers value most. This goes beyond demographic or transactional data, focusing instead on aligning brand messaging and experiences with the values and preferences of each customer.

AI empowers businesses to personalise customer interactions in profound ways, closing in on the goal of offering bespoke experiences at scale.

Here's how:

• Data Analysis and Insights: AI can analyse vast amounts of customer data, including purchase history, browsing behaviour, demographics, and sentiment. By using machine learning algorithms, AI can identify patterns and preferences, uncovering hidden insights into customer needs and motivations. This empowers brands to tailor their offerings and communications to resonate with specific customer segments and individuals. For example, streaming services such as Luna leverage AI to create a personalised gaming experience. By analysing playing history and even the device used, AI can identify patterns and preferences, recommending content that aligns with customer values. This data-driven approach ensures Luna caters to each player’s unique viewing habits.

• Real-time Personalisation: AI enables real-time tailoring of content and experiences based on a customer's current behaviour and context. For instance, an e-commerce website may recommend products based on a customer's browsing activity, or a travel platform may suggest personalised itineraries based on a user's preferences and past travel history. These companies could go a step further: families with teenagers won’t want the same facilities as families with young children, for example.

• Predictive Modelling: AI-powered predictive analytics can anticipate a customer's future needs and wants. By analysing past behaviour and market trends, AI can recommend products or services that a customer is likely to be interested in, even before they realise it themselves: recommending a new series on a streaming service, for example, or offering a money off deal for laundry detergent before it runs out. This proactive approach fosters customer loyalty and satisfaction with a feeling that the company is looking out for their interests.

• Personalisation at Scale: AI allows businesses to personalise experiences at scale, even with a large customer base. Through automation and machine learning, AI can handle the heavy lifting of data analysis and personalisation, enabling brands to cater to each customer individually without the limitations imposed by having to carry out personalisation manually.

Dynamic Content Personalisation

Personalisation is no longer about first/last name; dynamic content personalisation is a powerful application of AI that allows brands to tailor website content, marketing messages, and product recommendations in real-time based on individual customer data. In short, relevance is king - and AI will help you achieve it.

In practice, this is how it works:

• A clothing retailer can display personalised product recommendations for a customer based on their recent browsing history and past purchases. If a customer has recently viewed a specific style of dress, the website might showcase complementary items such as shoes, jewellery, or handbags.

• A streaming service can curate personalised video recommendations for each user based on their viewing history and viewing preferences. If a user has been binge-watching sci-fi movies, the platform can suggest similar options or movies featuring the same actors or directors.

• A news website can dynamically adjust the content displayed to each user based on their location, browsing history and interests. A user interested in sports might see headlines about local sports teams, while a user focused on politics might see articles on current political events.

These are just a few examples – the possibilities for dynamic content personalisation are limited only by imagination. By tailoring content to individual needs, targeted marketing efforts result in higher conversion rates and a better return on investment. As AI technology continues to evolve, and more possibilities for the technology are realised, we can expect even more sophisticated and nuanced value-based personalisation strategies to emerge.

Using predictive analytics powered by AI

Predictive analytics powered by AIallows brands to anticipate customer needs and behaviour before they even occur. Here's how it works:

• Identifying churn risk: AI can analyse customer behaviour patterns to identify customers at risk of churning (that is, cancelling their subscription or service). This allows businesses to proactively engage with these customers and offer solutions to retain their loyalty.

• Next-purchase prediction: AI can predict what a customer is likely to buy next based on their past purchases and browsing activity. This empowers brands to recommend relevant products, leading to increased sales and customer satisfaction.

• Personalised product development: AI can analyse customer feedback and social media sentiment to identify emerging trends and predict future product needs. This empowers brands to develop products that resonate with their target audience and fill real needs in the market.

Real-world applications of AI-driven value-based personalisation

Several companies are already harnessing AI for value-based personalisation with impressive results:

• Spotify: The music streaming platform uses AI to personalise playlists for each user based on their listening history, mood, and time of day. This helps users discover new music and keeps them engaged with the platform.

• Amazon: The e-commerce giant utilises AI for extensive personalisation across its platform. From product recommendations to dynamic search results, Amazon tailors the customer experience based on individual preferences and past behaviour, leading to a highly successful customer-centric approach.

• Netflix: The streaming service leverages AI-powered algorithms for personalised recommendations. By using data about viewing history and ratings, Netflix suggests shows and movies that are likely to appeal to each user's taste,leading to increased user satisfaction and reduced churn.

These examples showcase the real-world impact of AI-driven value-based personalisation. By understanding their customer base and delivering value-relevant experiences, brands can forge stronger relationships with their customers.

Value-based personalisation, powered by AI, offers a range of powerful ways for companies to connect with their customers on a deeper level at ever-more granular levels. By understanding and aligning with customer values, brands can create more meaningful and resonant experiences that not only enhance customer engagement and loyalty but also drive long-term business success. In the current landscape, companies that embrace AI-driven value-based personalisation will have the edge on their competitors.

Want to learn more about how AI can drive customer engagement and loyalty? Join us at the Personalisation Summit - where consumer brand leaders explore best practices and innovations in leveraging customer data for personalised consumer journeys that build loyalty and drive business growth. Sound of interest? Download the event agenda here

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