Sam Page, CEO of 7DOTS, explores how data can organise data to create great digital experiences.
In today’s digital-first world, financial services brands are sitting on a rich goldmine of data. Yet, many struggle to translate this wealth into digital experiences that meet and exceed customer expectations.
This disconnect isn’t just a missed opportunity; it’s a critical flaw that directly impacts brand perception and loyalty. Recent Salesforce research reveals that 46% of consumers would stick with a financial provider offering exceptional customer experience, even if fees increased.
The challenge lies not simply in gathering data, but in transforming these signals into actionable insights that pinpoint customer pain points and personalised solutions. Yet fully activating this data will deliver immense rewards. Forrester research shows that retail banks utilising customer insights and digital transformation grow more than three times faster than their peers.
Why is it so difficult?
The financial services industry faces particular challenges in bringing its data to life. Financial services brands deal with massive volumes of data daily, including customer transactions, market data, risk assessments, compliance records.
However the financial industry is also heavily regulated, with strict requirements for data privacy, security, and reporting. This includes navigating the complexity of GDPR, PSD2, and other compliance frameworks, impacting the ability to effectively translate customer insights. This is a common theme that has emerged from dozens of conversations I have had with finance leaders over the past year.
The challenge they face is not having a clear, unified view of their data. Yet without this they can’t effectively measure performance, identify areas for improvement, or deliver the personalised experiences customers demand. In short, they’re missing the key ingredient for competitive advantage.
So how to get this right? There’s no one-size-fits-all solution, and each strategy requires a strategic, nuanced approach. A roadmap is crucial for businesses to transform data from a liability into a strategic asset. There are seven steps businesses should undertake.
1) Define clarity
Firstly finance brands need crystal-clear objectives for data utilisation. This provides the road map to where they will want to go. In each case, “defining clarity” means establishing objectives for how data will be used, ensuring compliance, and setting measurable goals.
For example this could be a bank using transaction data to provide personalised loan offers, requiring clarity on targeting criteria, privacy compliance, and conversion goals. Or an insurance firm using customer service interaction data (e.g. call transcripts, chat logs, email correspondence) to improve customer support and personalising future interactions.
2) Ensure accuracy
Secondly finance brands need to implement rigorous data cleansing and validation processes. This includes verifying customer information, regularly updating databases, and implementing checks to identify and correct inconsistencies or errors. Without accurate data, the personalised experience becomes frustrating and ineffective, damaging customer trust.
3) Achieve integration
Once accuracy has been assured it is then crucial to provide a unified customer view by integrating disparate data sources. Achieving this 360-degree customer view requires breaking down data silos, perhaps through a central data warehouse, data clean rooms, Application Programming Interface (APIs), or a Customer Data Platform (CDP). A financial services firm might have customer data spread across Customer Relationship Management (CRM) systems, banking platforms or marketing automation. Without integration, they struggle to understand the customer journey and personalise interactions.
A good example of this principle in action is Cosegic, a compliance consultancy who wanted to fully attribute the impact of its digital marketing activity. The business created a connected ecosystem and full data attribution modelling across multiple data touchpoints, providing a clear view of Return on Investment (ROI) across all activity, from first touchpoint to contract closure. This laid the groundwork for increased conversions and brand visibility. With this level of integrated data comes a critical need for robust governance.
4) Establish governance
It is crucial to build trust in financial services, especially in the digital realm, given the industry’s stringent regulations. Therefore, defining clear rules and responsibilities for data management and protecting customer data is key. It is about a careful balance between security, compliance, and user experience.
However, there is widespread misunderstanding of data capture requirements, particularly within regulations like GDPR. Recent research carried out by 7DOTS found a concerning 43% of finance brands were non-compliant with data protection laws due to accessing browser storage for advertising and/or analytics (e.g., cookies) without obtaining proper user consent. This highlights the urgent need for robust governance and expert oversight.
5) Unlock intelligence
With brands confident in the compliance of their approach, they are then in a position to extract meaningful insights to drive strategic decision-making. It is about the use of the right technology to translate the data. Think of data like a puzzle. The right technology helps to assemble the pieces, revealing a clear picture, the insights, that informs strategic decisions. AI can be critical in extracting the insights at scale, assembling the pieces faster.
Southeast Asia’s largest lender DBS Bank is a good example of a bank that has really invested in big data and generative AI to unlock the treasure trove of data it owns. It has generated more than 100 artificial intelligence and machine learning algorithms to analyse internal data based on 15,000 customer data points which it was then able to extract to enhance personalisation.
6) Drive activation
Once the right data has been extracted, smart financial services brands are able to then realise the value of it to drive performance and create personalised products and services. A retail bank might analyse transaction data to offer personalised budgeting advice and targeted product recommendations. Like Bank of America who use a “Life Plan” tool within its mobile app to provide personalised +financial advice and guidance. It analyses customer spending habits, savings goals, and life events (like buying a house or having a child) to offer tailored recommendations.
Or in the B2B space, a fintech company could use payment processing data to offer businesses insights into customer spending habits, enabling them to optimise pricing strategies and identify new market opportunities.
7) Embrace evolution
Finally it is crucial to create a culture of continuous improvement and adaptation to move from a siloed to an holistic data strategy. An agile strategy allows organisations to quickly react to market changes and customer needs. It’s about being flexible, responsive, and proactive in strategy implementation. Within a rapidly changing digital context, firms need to have the right set up to move at pace and scale.
By embracing these seven steps financial services brands can transform their data into a strategic asset. This transformation is not just about keeping pace with customer expectations. It is a powerful opportunity to develop deeper relationships, building loyalty and competitive advantage.
