How to boost personalised marketing with AI

How to boost personalised marketing with AI
10
May 23

Bradley Kronson

AI in digital marketing has completely revolutionised how businesses interact with their customers. By leveraging AI, businesses can now offer personalised experiences that result in higher engagement and conversions.

From AI-powered chatbots to personalised product recommendations, this technology has opened up new doors for businesses looking to enhance customer satisfaction and retention.

Customised experiences = higher engagement and conversions

Providing relevant product recommendations is a crucial aspect of a successful e-commerce business. According to a report by Accenture, 91% of consumers are more likely to shop with brands that offer personalised recommendations. This is where AI comes in. By leveraging AI algorithms, businesses can analyse customer data and provide personalised product recommendations based on individual preferences and behaviours. This improves the customer experience and increases the likelihood of conversion and customer loyalty.

Improve audience targeting

AI-powered data analysis can help businesses better understand their target audience and create personalised digital marketing campaigns. By identifying patterns and behaviours in customer data, businesses can create targeted campaigns that resonate with their audience.

According to a study by Epsilon, personalised emails have an open rate of 29%, compared to non-personalised emails, with an open rate of only 18%. This highlights the significant impact that personalisation can have on email marketing campaigns. With the help of AI, businesses can easily leverage data-driven personalisation to improve their return on investment and build stronger relationships with their customers.

Predictive analytics for customer behaviour

One of the most significant benefits of AI in marketing is its ability to anticipate customer behaviour and preferences. By analysing data and identifying patterns, AI can help businesses create targeted campaigns that are more likely to resonate with their audience.

Through predictive analytics, businesses can identify opportunities to upsell or cross-sell products or services to their customers, resulting in improved sales and revenue. This technology can also help businesses stay ahead of their competitors by understanding their customers' changing needs and preferences and adapting their digital marketing strategies accordingly.

Chatbots informed by natural language processing

Chatbots have become increasingly popular in the customer service industry, offering a more efficient and cost-effective way for businesses to handle customer queries. According to IBM, chatbots can reduce customer service costs by up to 30% by answering 80% of routine questions and speeding up response times. This means businesses can redirect resources to more complex customer queries and reduce the workload on their customer service teams.

One key factor that sets chatbots apart from traditional customer service methods is their ability to understand and respond to natural language queries. Chatbots can comprehend and interpret customers' queries using natural language processing (NLP) technology, providing a more personalised and human-like interaction. This improves the customer experience, helping businesses build stronger relationships with their customers and increase customer loyalty.

Machine learning for personalised marketing

Machine learning is a powerful tool that businesses can use to analyse customer data and personalise digital marketing campaigns accordingly. By leveraging AI-powered machine learning algorithms, businesses can identify customer behaviour patterns and provide recommendations tailored to each individual's preferences and behaviour.

For example, machine learning algorithms can analyse a customer's purchase history and recommend products or services they are likely to be interested in. This personalised approach can help businesses increase customer loyalty and revenue while improving the customer experience.

Personalised e-commerce recommendations

The use of AI in e-commerce personalisation has been proven to be highly effective, as seen in the case of Amazon. The company relies on AI to power its recommendation engine, which is responsible for a significant 35% of its revenue, according to McKinsey & Company.

The AI algorithm analyses vast amounts of customer data, including purchase history, browsing behaviour and search queries, to provide highly personalised product recommendations to each individual. This leads to increased customer engagement, loyalty and, ultimately, revenue for the business. AI’s ability to understand and analyse customer behaviour, preferences and patterns makes it a valuable tool for e-commerce businesses looking to maximise their sales and improve customer satisfaction.

At League, we leverage automation and data analytics to provide a growth-driven customer experience solution. Our digital marketing solutions can help you develop and manage campaigns that provide truly personalised experiences to your customers.

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