Overview of hyper-personalisation in fintech
Hyper-personalisation has emerged as a key trend in the European financial sector. However, significant challenges related to technology and scalability need to be addressed before it becomes widespread.
Despite the clear benefits of hyper-personalisation demonstrated in e-commerce and entertainment, most banks are unable to offer a similar level of personalisation. This shortcoming is primarily due to the challenges of managing unsystematized, rapidly growing data and the organizational mindset shift required to prioritize person-centric services. In other words, it is difficult to chart a sure course into the future with so much incoming data.
Hyper-personalisation in e-commerce and entertainment: what attracts customers?
Today’s customers anticipate that their financial institutions will possess a deep understanding of their needs, behaviors, and preferences. This expectation is shaped by their experiences in other fast-growing digital sectors, such as e-commerce and entertainment, where hyper-personalisation has been successfully implemented.
Yet, over nine in 10 banks cannot currently offer customers hyper-personalisation.
This lag is due to the significant technological, regulatory, and infrastructural developments needed to make hyper-personalisation a reality in the European financial sector. Additionally, the field of opportunities is vast and constantly evolving, making it challenging to keep up with the best practices in person-centric services.
Key features in e-commerce and entertainment
Technologies are developing rapidly, and we often learn about their existence from the implemented functionality of applications. As customers, clients, and users, we enjoy being surprised with something new, convenient, and interesting. Here are the main key features in e-commerce and entertainment that attract users through hyper-personalisation:
E-commerce
Personalized product recommendations:
- Based on browsing history: Suggestions tailored to what customers have previously viewed or shown interest in.
- Purchase history: Recommendations based on past purchases, predicting what customers might need next.
- Similar customer preferences: Using data from similar customers to recommend products that might be of interest.
Dynamic pricing:
- Customized offers and discounts: Personalized deals based on customer’s purchasing patterns and loyalty status.
- Price adjustments: Offering competitive pricing for products frequently viewed or added to the cart but not purchased.
Targeted marketing campaigns:
- Email marketing: Sending personalized emails with product recommendations, special offers, and relevant content.
- Social media ads: Using customer data to show personalized advertisements on social media platforms.
Customized shopping experience:
- User interface customization: Altering the homepage layout based on user preferences and past behavior.
- Tailored content: Displaying blog posts, articles, and videos that align with the customer’s interests.
Predictive analytics:
- Inventory management: Predicting which products a customer might buy next to ensure stock availability.
- Sales forecasting: Using customer data to anticipate future sales and plan accordingly.
Entertainment
Personalized content recommendations:
- Streaming services: Suggesting movies, games, TV shows, or music based on viewing or listening history.
- Curated playlists and channels: Creating playlists or channels tailored to the customer’s taste and preferences.
Adaptive UX:
- Customized interfaces: Adjusting the UI to highlight preferred genres, artists, or types of content.
- Interactive features: Offering interactive features like quizzes or polls that adapt based on user responses.
Targeted notifications:
- Content alerts: Sending notifications when new content matching the user’s interests is available.
- Event reminders: Informing users about upcoming live events, premieres, or releases they might be interested in.
Engagement analytics:
- Behavioral analysis: Tracking user interactions to understand and predict content preferences.
- User feedback integration: Incorporating user feedback to refine and enhance content recommendations.
Exclusive content:
- Access to exclusive releases: Providing early or exclusive access to content based on user engagement and preferences.
- Customizable content: Allowing users to personalize aspects of their content experience, such as creating custom watchlists or playlists.
Super apps as the future of fintech
This brings us to the concept of super apps. Super apps represent the next evolution in the digital banking landscape, integrating a multitude of financial services into a single, cohesive platform. This approach aims to meet the diverse and dynamic needs of modern customers, who increasingly demand convenience, efficiency, and a seamless user experience. Here’s a detailed look at how super apps function and their potential impact on the banking sector:
Integration of diverse banking services
Super apps consolidate various banking services into one platform, offering a unified user experience. This includes:
- Shared wallets
- Bill reminders
- Investment options
- Savings accounts
- Loans and credit
- Insurance services
- Budgeting tools
Comprehensive financial services through one user account
The goal of a super app is to provide a comprehensive suite of financial services accessible through a single user account. This approach has several key benefits:
- Seamless user experience
- Enhanced data utilization
- Increased customer loyalty
- Cross-selling opportunities
- Improved financial inclusion
Conclusion
As we delve deeper into the possibilities of hyper-personalization within fintech, it’s clear that the path forward is both promising and complex. For financial institutions, the transition from traditional models to next-generation super apps that offer highly personalized services is not just an innovation but a necessity. Customers’ expectations, shaped by advancements in sectors like e-commerce and entertainment, demand a similar evolution in financial services.
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