The 21st-century consumer wants the brands they associate with to treat them as a unique individual. The growing digital ecosystem is creating a wealth of competition, with businesses pushing to find new ways to attract customers. If the success of Amazon, Facebook or Netflix is anything to go by, those who succeed are providing the best personal services.
In the retail world, it is common to differentiate the customer base to ensure that businesses offer the right products to the right people. Consumers are accustomed to sharing data so far as they optimise their experiences. Imagine if we didn’t let Netflix see what shows we’re streaming. The entire premise of the recommendation system making this media giant succeed would fail, given that it is the main ‘unique selling point’ for millions of subscribers.
The use of personalisation in digital environments creates a problem for more traditional industries operating on legacy systems and infrastructures. Financial services is one sector that has quickly adapted to the new way of doing things, which is, ensuring customers have the experiences they desire.
In this article, we will look at how financial firms are using new technology and data within the hyper-personalised world.
What is hyper-personalisation?
Hyper-personalisation is the provision of more relevant products and services to end-users, using data and technology. At the forefront of the approach is artificial intelligence (AI), which takes data from several sources, often disparate, and builds comprehensive profiles to make decisions accurately. The insights tend to be in the form of predictions or recommendations, as per our Netflix and Amazon examples. Amazon generates 35% of its revenue through recommendations, amounting to over $100 million per day, exemplifying why it is a smart and powerful strategy.
Hyper-personalisation in financial services
In the context of financial services, firms now have access to customer information previously unknown or unavailable. For example, with transactional history, additional tools can help them understand shopping habits, social media use, or about where customers live. All of this extra data drives hyper-personalisation.
Banks, for example, can use hyper-personalisation to ensure their offers are more relevant to their target audience, so to create a more “retail-like” experience. Nearly 40% of customers say they purchase from competing companies when they are overloaded with product choices. Financial firms use hyper-personalisation to tailor what their customers see and improve conversion rates.
The example below from Lemnisk shows how hyper-personalisation works in practice.
Source: https://www.lemnisk.co/hyper-personalisation/
In a 2019 report from HSBC, hyper-personalisation is presented as the dominant trend within the industry for the next decade. As digital banking becomes part of the new normal, banks will continually look to take advantage of technological solutions as a way of organising and analysing customer data. Investing in personalisation tools will help banks engage with consumers and deliver the right products at the right times.
Hyper-personalisation starts with data
Data is a hugely valuable asset to financial firms. They have an abundance of information coming in from transactions and customers every day, creating opportunities for effective hyper-personalisation strategies.
A framework for hyper-personalisation is in the below.
Here, seemingly independent systems work together to deliver the right messages. Data management platforms collect behavioural data from websites, audiences, and third parties. CRM systems collate profiles in a central repository to generate a 360-degree view of customers. A marketing orchestration platform collects millions of data points on customer interactions and uses AI to drive actions.
Much is happening in tandem, but the takeaway is that it all revolves around data. Successful firms will create personalised services, given they efficiently govern their data use, quality and accuracy. Data quality is a subject in itself, but imagine if Netflix started recommending shows you didn’t like, or Amazon showed irrelevant products. Customers would eventually go elsewhere.
Financial firms must work to consolidate their technology and map out a framework for disparate systems to derive the most from their data and hyper-personalisation services.
Use cases for hyper-personalisation in financial services
Hyper-personalisation is not a new concept. Some institutions have already exhibited great success implementing it as a strategy.
Bank of Ireland
The Bank of Ireland uses data as part of its customer experience program to help boost engagement. The firm follows the examples of tech giants in tracking and tagging messages to personalise them and offer tailored in-branch experiences. Bank of Ireland merges both online and offline data, creating singular, comprehensive reviews of customer information. The result is a 278% increase in the number of applications the bank receives from digital channels.
Capital One
The US firm, Capital One, works with the Foursquare analytics platform to better serve its customer base. Foursquare provides a geolocation solution sending out real-time mobile notifications to clients. Capital One works with several partner retailers, where customers can purchase products. By prompting customers when they are near these partners, Capital One enhances the opportunity of upsells, targeting again, the right people at the right time.
HSBC
HSBC is an advocate of AI and uses it to predict how customers might like to redeem credit card points, offering rewards more effectively. The objective is to provide customers with more valuable rewards while competition continues to grow. According to the linked report, around 70% of customers receiving personalized rewards were thrilled with them, and email open rates increased by 40%.
Direct Assurance
Outside of banking, Direct Assurance has an insurance programme known as ‘YouDrive’. A device in the customer’s car records their journey, generating a score for each trip. Various metrics are feeding the score, but overall a higher score equates to a lower insurance premium. Customers benefit from a premium that is personal to them, rather than being part of a generic product.
Summary
Financial services must invest in new technologies and big data to keep up with consumer demand. It is a necessity to deliver real-time, relevant interactions to survive in such a competitive marketplace. While it takes time to deploy technology and make the most of external data sources, financial institutions need to move now.
Disclaimer: The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech and entertainment. Mr. Chalopin is Chairman of Deltec International Group, deltecbankstag.wpengine.com.
The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, deltecbankstag.wpengine.com.
The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.
