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Hyper-personalisation: Inducing behaviours through data — how machine learning and automation can help customers make valuable and informed decisions

Author

Listed:
  • Coelho, Luís

    (Celfocus, Portugal)

  • Cachola, Gonçalo

    (Celfocus, Portugal)

Abstract

While personalisation is not an entirely new topic, there is currently massive hype around it. This is because service providers realise that they need to be more cost-effective in engaging with their customers, and also because customers now demand to be treated individually and in a personalised way. Several market trends have been adopted in recent years, bringing service providers to the level where they currently stand. The previous trends were both beneficial and applicable in a particular context; however, today, new approaches are required for service providers to progress, improve and move to the next level. Achieving a hyper degree of personalisation can be challenging — it requires investment, time and the right strategy. Furthermore, it is not a straightforward path, and it is essential to understand the business and technical challenges that service providers must address and overcome to succeed — challenges for which hyper-personalisation is the answer. This paper explores the concept of hyper-personalisation and its potential to induce customer behaviour through datadriven insights. It highlights the importance of knowing customers and leveraging their preferences and habits to deliver valuable and informed decisions. The financial services industry has the significant advantage of having access to a huge installed customer base and its data. In general, it is not a problem of lack of data that these industries face but rather one of how to derive actionable insights from it. The hyper-personalisation approach is bridging data with cognitive and digital capabilities to deliver unique, in-context and highly relevant experiences. With hyper-personalisation, service providers can scale up the personalisation leveraged by artificial intelligence (AI) and machine learning (ML) to deliver experiences and recommendations in real time to individuals, creating a true one-to-one personalisation.

Suggested Citation

  • Coelho, Luís & Cachola, Gonçalo, 2023. "Hyper-personalisation: Inducing behaviours through data — how machine learning and automation can help customers make valuable and informed decisions," Journal of Digital Banking, Henry Stewart Publications, vol. 8(3), pages 198-209, December.
    • Handle: RePEc:aza:jdb000:y:2023:v:8:i:3:p:198-209
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    More about this item

    Keywords

    hyper-personalisation; data; advanced analytics; banking;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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