Demystifying AI: Understanding Hyper personalisation

The importance and necessity of hyper-personalisation

Recent years have seen an increased focus on hyper personalisation, as companies come to recognise the pivotal role that contouring the experience to individual consumers will play in their future success. Mere personalisation is no longer enough for customers who have come to expect companies to tailor products, services and experiences to their unique needs, rather than being shunted into customer segments based on broad categories needs and generic profiles.

Research shows that customers value a more personal and individualised approach rather than ‘mass- personalised’ experiences and are likely to react positively and respond to campaigns that are directly targeted to them. Consumers are becoming increasingly decisive and demanding, and expect brands to accommodate and cater to those demands. The time in which companies can rely on old-school methods of mass marketing and arbitrary segmentation are coming to an end. Brands have long been coaching consumers to embrace their uniqueness and in one way or another, have it their way. Now consumers are becoming to expect and feel entitled to this new era of personalisation; hyper-personalisation. Brands that fail to identify, anticipate and personalise will quickly find themselves left out in the cold.

So what exactly is hyper personalisation and how does it work?

Hyper personalisation utilises and analyses historical and real-time data relating to customer behaviour and actions to infer intent, needs and wants and subsequently inform how brands engage and communicate with customers in order to provide a more personalised experience. This in turn can create better customer loyalty and engagement with customers [1]. Data points such as location, demographics, browsing history and purchase decisions can inform the creation of unique customer profiles that consider individual wants, needs and pain points to guide the hyper-personalisation of advertising, content, product recommendations and offers based on those unique preferences.

How is hyper-personalisation being used?

Depending on your industry and the accessible data, there are many potential opportunities and approaches to leverage hyper personalisation across various customer touch points. A high profile use-case for most customers will be personalising recommendations to customers using their unique browsing patterns and search history. Many industries have already begun to use hyper personalised recommendations to satisfy their customers needs and increase engagement, including e-commerce retailers, marketing, content producers and even the music industry. These industries are benefiting from using AI to recommend products, services, offers and content to their customers that are shaped by their personal choices and preferences and building a unique customer experience with each individual.

Hyper personalisation is also making an impact in the financial industry, being used by companies who offer credit scoring services to gain a deeper understanding of individuals which allows them to create a more accurate representation of each individual's circumstance, their creditworthiness and their ability to service loan payments [2]. The traditional way of segmenting people into vast impersonal groups resulted in inaccuracy relating to an individual's ability to pay back loans and unfair penalisation which may result in worthy individuals being rejected for loans.

As an industry, Marketing has enthusiastically pursued hyper personalisation and the promise of the ability of having one-to-one conversations and engagements with customers and potential customers as a game-changer. Marketers have been using AI to deliver highly personalised, targeted campaigns to improve communication with prospecting and current customers/clients. They use AI to gather vast amounts of data from individuals' interactions with their site and then use this information to build more authentic relationships through creating retargeting campaigns, sending push notifications, or even offers that cater to the customers desires based on items searched. Marketers also use data to analyse when is the best time to target their customers based on their historical behaviour and purchases by analysing how frequently they use the app and whether there are certain indicators that they are more likely to place an order or interact with their site.
To put it simply hyper personalization allows for marketers to produce highly relevant and contextual communications with customers which in turn leads to increased sales and customer interactions while allowing them to build more meaningful relationships that considers their customers different preferences.

What are you waiting for?

Organisations that adopt hyper personalisation into their business strategy are better equipped to manage the increasing expectations of consumers, whilst also gaining a competitive advantage of those who don’t. The move towards hyper-personalisation is unstoppable; a natural consequence of our obsession with personalisation as both customers and service providers and having the data and technology required to make it achievable at scale. Brands must recognise the key catalyst for hyper personalisation is consumer expectation; a need has been created and consumers will gravitate towards brands that satiate that need. Hyper personalisation may be the next marketing cold war; a battle of brands competing for customers not based on the idea of hegemony and belonging but on the promise of helping customers find and engage with brands, products and experiences that are truly in touch with who they are.

For more information on how Brainpool can assist you start your journey of implementing AI and hyper personalisation please get in touch.


Written by Alana Finnerty

References:

[1] Hgsdigital.com. (2020) ‘How hyper personalization helps build loyal customer relationships’. https://www.hgsdigital.com/blogs/how-hyper-personalization-helps-build-loyal-customer-relationships

[2] Dolgorukov, D. (2018) ‘Lenders bet on Artificial intelligence for credit scoring’ Retrieved from Lending Times: https://lending-times.com/2018/08/15/lenders-bet-on-artificial-intelligence-for-credit-scoring/

[3] Ragotham, R. (2020) ‘AI has changed the way banks interact with their customers’                                                                                                                   Retrieved from Fintechnews.com: https://www.fintechnews.org/ai-has-changed-the-way-banks-interact-with-their-customers/