Hyper-personalisation of Customer Experience Using Data
Pressure on the bottom line, shorter strategy implementation cycles and increased customer expectations require the introduction of solutions based on the latest technology to streamline the purchasing process and improve the overall customer experience. Artificial Intelligence supported by data analytics is increasingly used by companies and is key in addressing the challenge of competitiveness. So, does implementing AI-based solutions lead to building stronger consumer-brand relationships?
The customers no longer base their loyalty on price or product alone. Instead, they remain loyal to companies because of the experience they receive. Artificial intelligence and machine learning are changing the way companies interact with customers. They help to personalise the services and product recommendations by processing previous purchases, interactions with the communication, customer preferences and combining them with a range of other data collected, as well as with analysis of people who have chosen similar patterns.
A customer who is no longer anonymous is worth up to 18 times more to the retailers than the average consumer. This is possible thanks to the advanced personalisation achieved based on contextual and behavioural data. The marketers are choosing to use AI technology to build authentic interactions with customers in real time.
Micro-segmentation and Hyper-personalisation
The concept of segmentation is currently undergoing a transformation. Given the new criteria, and in particular the behavioural data, the companies can now better understand that their existing and potential customers may be very different in terms of their consumption habits. AI allows you to use behavioural segmentation at the micro level. Instead of dividing potential customers into rigid segments, you can define consumer behaviour taking into account even seemingly small differences, at the level of small groups or even individuals.
Over the past few years, the companies have managed to collect huge amounts of customer data, and this allows marketers to take a highly personalised approach, for example by adding more and more criteria to describe the customer. New segmentation techniques focus on supplementing the core data set with complex elements such as behavioural information, psychographic information, data from external sources to understand consumers and predict what they want before they even interact directly with the product. Further refinement leads to personalisation, where each consumer is a distinct segment.
More and more companies are adopting deep personalisation of services — from product design through pricing to creating consumer experiences — which creates a steady rise in expectations among consumers in this context. With machine learning applications such as social media mining, sentiment analysis and customer churn prevention, you can be tremendously efficient in processing large and unstructured data in real-time, and generating accurate predictions to help make marketing decisions.
Hyper-personalisation of marketing activities is the advanced real-time customisation of offerings, content, and customer experiences on an individual level. This reflects a shift in marketing, which was previously product-centric and has now become customer-centric. With micro-segmentation and hyper-personalisation, you can plan effective communication activities in an automated way. With artificial intelligence and machine learning, it is possible to generate qualitative real-time recommendations that allow for better detection of trends in the data acquired, recommendations for working with segments and program mechanics and overall recommendation support in the way the personalisation is done.
On the one hand, artificial intelligence and automation are saving time and costs for the company, while on the other hand, they offer greater customer benefits based on improving the customer experience. The Deloitte study, Connecting with meaning – Hyper-personalising the customer experience using data, analytic, and AI (deloitte.com) shows that hyper-personalisation, when done well, can deliver ROI of up to 800% on marketing spend. Additionally, it can also increase sales by at least 10%.
With hyper-personalisation, the companies can send contextual communications to specific people at the right place, at the right time, and through the right channel. Hyper-personalised marketing offers the opportunity to build meaningful customer engagement, deepen existing relationships and build new ones, and improve the customer experience. Implementing this type of strategy not only improves customer satisfaction, but also increases brand loyalty, purchase propensity and overall marketing effectiveness.
With the growing amount of data, its sources and new points of contact between consumers and brands, there is a wide range of possibilities for personalisation of services. Loyalty program management platforms are one of the tools that make it possible to effectively use this type of customer data. Artificial intelligence-based tools have a critical advantage — they allow you to act in real time.
The data, analytics, and artificial intelligence are essential tools for developing a hyper-personalised strategy that will allow brands to stand out in the marketplace and gain customer trust. Real-time automation and optimisation are becoming the way of doing things in marketing, and machine learning methods are the best solutions available today that not only improve the customer experience but also increase profit for the company.