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Generative AI

How to achieve personalisation using generative AI?

Constant connectivity is one of the defining features of the world today. If brands want to stand out from the constant chatter online, they have to work on personalising every interaction they have with their customers. The troves of data available can make this happen if businesses use the right tools to leverage data and get personalised insights into every customer.

AI for business offers a powerful suite of tools and solutions to help achieve personalisation at every stage of the customer lifecycle, from marketing communication to service offerings tailored to the specific needs and expectations of individual customers.


Achieving new levels of personalisation with AI for business

Personalisation in customer service is not a new trend, but it has come a long way. From greeting customers with their first names in emails, personalisation in marketing has evolved to leveraging data to understand customers' individual preferences and behaviours to tailor every multi-channel interaction. This has taken personalisation to a new level, with AI leveraging data beyond the name and location of the customers to create a "hyper-personalised" experience every time customers interact with a brand.

Data and advanced analytics techniques – like machine learning and artificial intelligence – are at the heart of such AI personalisation, where a deep understanding of customer behaviours, needs, and preferences tailors a unique customer experience. AI tools can leverage real-time data to tailor highly contextual interactions, while generative AI in personalisation marketing makes these interactions conversational and “human”. Furthermore, AI algorithms can continue to learn from these interactions, readjusting customer profiles and creating unique customer experiences in real time.


Achieving AI personalisation in marketing

A recent survey revealed that 72% of global customers believe generative AI will improve their interactions and experience with a brand. But how can businesses use AI personalisation responsibly—create a unique experience without seeming intrusive? The answer lies in understanding the key components contributing to hyper-personalisation and the key behavioural attributes to focus on.

The key elements you need to focus on when utilising generative AI for personalisation in marketing include:


Customer journey mapping

The first thing you need to do is understand and map a customer’s journey – from awareness to post-purchase support. This can help you identify different stages and touchpoints where customers interact with your brand and identify the data points you need to analyse to provide a personalised experience.


Data collection

Once you have the data points you need to focus on, the next—and perhaps the most important step—is to collect detailed data about your customers. Depending on your personalisation goals, this can include anything from demographic data, purchase history, and transaction history to social media activity and sentiment analysis.


Data analysis using AI and machine learning algorithms

Once you have collected and organised customer data, the next step is data analysis to extract meaningful and actionable insights. AI and machine learning tools come into the picture at this stage, allowing you to analyse large amounts of data, predict customer interactions, and personalise customer experience. Generative AI takes one step further, allowing you to input raw data to generate deep insights into customer behaviour and generate content tailored to each individual customer.


Real-time decision-making

Now, you can use the collected data and generated insights to facilitate real-time decision-making. This can be as simple as offering personalised product recommendations as customers navigate your website or app or as complex as providing a completely dynamic user experience for everyone.


Data security and privacy

Since generative AI deals with large amounts of personal and sensitive data, you have to focus on using the data responsibly and ensuring regulatory compliance for data security and privacy.


Testing and optimisation

The last step is continuous learning, an integral part of AI algorithms, via continuous testing and optimisation. With this, you can continue to update customer profiles and offer personalised experiences to everyone.
Different data attributes, including demographics, psychographics, behavioural data, transaction history, and interaction data, can support the sentiment and predictive analytics essential for leveraging AI for personalisation. Once you have a handle on these data attributes, you can use AI to personalise your marketing communication across multiple channels, including email, SMS, social media, chatbots, and more.


Benefits and challenges of hyper-personalisation with AI

Effectively utilising AI for business to personalise customer interactions can help you improve customer lifetime value and achieve a greater marketing ROI. Here are some key hyper-personalisation benefits that make it possible:

  • Improved customer experience and satisfaction
  • Increased conversion rates
  • Enhanced customer loyalty

However, you also have to be mindful of critical challenges that could spell disaster for your personalisation efforts, including:

  • Data privacy and security concerns
  • Effectively balancing personalisation and intrusiveness
  • Complexities associated with data integration, analysis, and implementation
  • Infrastructure needs for real-time processing capabilities and scalability
  • Access to AI and machine learning expertise

Although the challenges may seem daunting, you can overcome them with meticulous planning and use AI to personalise your marketing efforts.


How can Infosys BPM help?

Leveraging AI for business is no longer a luxury but a necessity if you want to survive and stay competitive in today’s data-driven world. Infosys BPM generative AI business operations platform can help you harness the prowess of data as you reimagine your business operations and drive AI-first digital growth. Infosys BPM can help you generate customer insights, implement self-service abilities, expedite resolution management, and leverage AI for personalisation in your marketing efforts.


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