Unlocking the potential of digital analytics in finance and banking

Many financial organizations do a great job gathering customer data. But to stand out, they need to anticipate customer expectations better and quickly adapt products and services to changing preferences. 

Banks must ensure that their digital platforms are user-friendly, offering features like easy account management, instant transactions, integrated banking services in mobile apps, responsive customer service through chatbots or other digital tools, and more. Enhancing the overall digital experience can significantly reduce the likelihood of customers switching to competitors. 

Strategically applying analytics is what banks are struggling with today. With this come the challenges of efficiently meeting customer needs, managing compliance, mitigating security risks and effectively applying analytics insights in different areas of business.

In this article, we will explore the challenges financial organizations face in analytics, how they can address them, and ideas for effectively applying analytics in their business.

Challenges of using analytics by financial organizations

Organizations in the finance sector handle large volumes of sensitive data spread across different systems and tools. This generates unique challenges for these organizations in implementing web analytics. 

Regulatory compliance

Financial institutions must navigate a complex landscape of regulations, including data privacy laws such as GDPR. These regulations impose strict requirements on collecting, storing, and processing data. Non-compliance can lead to severe penalties, making it crucial for organizations to ensure that their web analytics tools adhere to these standards.

Data security and privacy

Given the high stakes involved in handling sensitive customer information, financial organizations are particularly vulnerable to data breaches. Third-party web analytics solutions can increase this risk, especially if sensitive data is stored on external servers. Organizations in the finance industry must choose analytics vendors that prioritize data privacy and employ the highest security standards. 

Integrating data from disparate sources

Finance teams need to build a unified data system to effectively collect and store massive amounts of data from their own systems, different departments, and external sources. Many of these organizations struggle with data silos, where information is controlled by one department and isolated from the others. Data is often trapped in legacy systems that do not integrate well with modern analytics tools. This fragmentation makes it challenging to obtain a comprehensive view of customer behavior and limits the effectiveness of analytics. 

Data quality

The effectiveness of web analytics relies heavily on the quality of the data collected. The sheer volume of data financial institutions collect can complicate reporting and analysis, requiring robust data management systems to ensure accuracy and relevance. Access to inaccurate data hampers the ability to effectively use analytics insights in marketing, sales or product development. Low-quality or inconsistent analytics data poses significant challenges for financial organizations, affecting their operational efficiency, decision-making processes, and overall trustworthiness. 

Privacy compliance in finance

The finance industry deals with extremely sensitive data, often including personally identifiable information (PII). Examples include collecting visitors’ details such as names, dates of birth, home addresses, email addresses, demographic information, browsing history, device IDs, IP addresses, and more. 

On top of that, they handle personal financial information (PFI), which includes account passwords, tax information, credit reports, credit card security numbers, and a lot more. Handling such information requires extra caution as any breaches can be particularly dangerous, leading to potential regulatory fines and loss of trust. 

Financial institutions must comply with a large number of regulatory regimes and laws, which include strict sector-related restrictions, such as: 

• The Gramm-Leach-Bliley Act (GLBA),
• The Dodd-Frank Wall Street Reform and Consumer Protection Act,
• The GLBA Safeguards Rule,
• The Sarbanes-Oxley Act (SOX), and many more. 

At the same time, because financial organizations typically handle personal data and/or PII, they may fall under privacy laws governing these types of information, such as GDPR, CCPA, LGPD, and other global or local data protection regimes. 

To align with regulatory requirements and ensure data privacy, financial organizations can employ the following strategies:

• Understand what privacy regulations they must adhere to and continuously monitor their compliance. 
• Choose secure data hosting (e.g., in a dedicated database) in the location of their choice. For example, select an EU-based hosting provider if the institution is located in the EU. 
• Maintain full ownership of data, how it’s used and what third parties it is shared with.
• Integrate analytics with a consent management platform to obtain valid user consent before collecting personal data.
• Communicate data collection practices to users through updated privacy policies.
• Apply data minimization to only collect the necessary data for specific purposes.
• Choose a privacy-conscious analytics provider that follows the privacy by design and privacy by default standards. 
• Ensure their analytics vendor offers robust security features, such as SSL encryption, SSO authorization, access control, and data backups. 

Practical use cases for web analytics in finance

Financial institutions can leverage web analytics to gain deeper insights into customer preferences. By understanding how customers behave across different channels, they can offer personalized financial advice, proactive product recommendations, faster response times, and customized alerts. 

Let’s dive into the most important ways a financial company can practically apply analytics insights to their organization’s operations. 

Personalizing customer experiences

Web analytics helps financial institutions track user interactions on their websites or apps, offering valuable insights into their engagement and interests. For example, they can understand how users navigate the website or app, their actions, and whether they complete funnels for specific goals, such as submitting a loan application or filling out a contact form. 

By integrating analytics with a customer data platform (CDP), organizations can segment customers based on demographics, products or services they purchased, and website or app interactions. This segmentation enables banks to deliver personalized marketing messages and tailored content that resonates with specific customers, enhancing their experiences. 

Improving marketing campaigns

Organizations in the financial sector can effectively use analytics data to improve their marketing campaigns. 

They can measure and track their performance to refine and improve marketing assets and messaging in future campaigns. For example, they can analyze which channels drive the most traffic and engagement, recognize their audiences, and determine the best launch time for increased effectiveness. 

They can also monitor content-related trends based on visitor activity and conversions, using these insights to influence their future content plans. For example, they can analyze page views, clicks, time spent on page, or file downloads.

Optimizing customer journeys

Web analytics also allows companies to identify pain points within the customer journey. With customizable reporting features, financial institutions can track how users navigate their websites or apps and analyze whether they complete the desired journeys. 

One approach focuses on the small steps that users take that make up whole customer journeys, including: 

• Evaluating available account options.
• Opening a bank account and onboarding.
• Making money transfers.
• Checking the account balance. 

By identifying friction points for customers and where they drop off, organizations can address users’ issues and understand which interactions drive users to convert into paying customers. This can ultimately lead to a smoother user experience, increased customer satisfaction, and better business outcomes. 

Reducing churn

Understanding customer behavior through analytics helps financial institutions predict and prevent churn. Financial organizations can establish feedback collection across channels – such as through surveys or social media – to understand the issues behind churn. 

They can spot other signs of dissatisfaction, such as reduced engagement, to proactively reach at-risk customers with personalized retention strategies, including tailored products, incentives, or dedicated support. Additionally, they can regularly monitor KPIs such as customer lifetime value (CLV), churn rates, and satisfaction scores to measure the effectiveness of their retention strategies.

Developing products and services

Analytics insights are essential for continuous product optimization. By tracking metrics such as page views, clicks, conversion rate, or bounce rate, financial institutions can evaluate the performance of product pages and see how well their offers respond to prospects’ needs. They can also regularly analyze customer feedback gathered through surveys to refine their offer and adapt to customer expectations, ensuring their competitive edge.

Predicting trends

With analytics, financial organizations can assess historical data to predict future trends. For example, they can use available data to identify potential customers’ interests, target them with relevant offers at the right time, and optimize cross- and upselling opportunities. They can also make informed decisions regarding loan approvals and customer segmentation by assessing the risk levels using existing data. 

Key features of an analytics platform for finance and banking

When selecting an analytics platform, financial institutions should prioritize several key features to gain access to accurate, integrated data that they can effectively apply to their marketing or sales operations.

Access to actionable data 

Web analytics should provide actionable insights to drive marketing strategies and improve user experiences. Companies need accurate, unsampled data to better understand customer behavior, optimize marketing efforts, and enhance the customer journey. Features like A/B testing, heatmaps, and customer journey mapping can help in identifying strengths and weaknesses in user interactions. 

By combining analytics with customer data platforms (CDPs), organizations can apply the collected insights to create targeted marketing campaigns, provide tailored offers or send personalized emails. 

Real-time data insights

Real-time data analytics is crucial for timely decision-making, risk management and operational efficiency.  It shows how many people are interacting with a website or app, and what goals they are converting. 

Financial institutions can use this data to dynamically manage their marketing content and campaigns. On the other hand, they’re able to monitor transactions and identify anomalies to detect fraudulent activities as they occur. They can customize real-time dashboards to visualize the most critical data and simplify day-to-day data management.

Integration between systems and data

Integrating customer data across different systems and tools is essential for smooth data flow. It also provides access to unified first-party data sets that can be effectively used by other departments, be it marketing, sales or customer service. Working on consistent data reduces the risk of errors and helps enhance the effectiveness of data processes. 

Financial institutions should opt for analytics platforms that offer seamless integration with other tools in their data ecosystems. They can also connect a customer data platform (CDP to integrate data from multiple sources, segment customers based on behavioral or demographic attributes, and activate data to target audiences with relevant marketing campaigns or personalized offers.

Cross-platform analytics

Cross-platform analytics provide insights from different platforms, helping financial institutions create funnels to identify and track users between native mobile app, WebView and website. This is especially vital for banking, where customers have grown accustomed to an omnichannel experience.

Reliable data

Financial organizations need to use an analytics platform that gives them access to accurate data. Analytics vendors often use data sampling, which only shows a subset of data. While sampling may be helpful in certain situations, it can lead to far less accurate reports and hide crucial insights, directly impacting business efficiency. Additionally, financial institutions can benefit from access to raw data, which gives analysts more possibilities for in-depth analysis, exploring data insights and making them actionable.

Dedicated support

Reliable support services from the analytics provider can significantly improve the platform’s effectiveness. Institutions should look for vendors that offer dedicated support services rather than relying solely on automated systems or chatbots. For complex data setups, companies may benefit from access to technical support in implementing their analytics infrastructure. 

Conclusion

As the financial landscape continues to shift, having access to actionable insights will be crucial for maintaining competitiveness and fostering customer loyalty.

By choosing an analytics vendor that prioritizes privacy compliance, data security and access to valuable, actionable data insights, financial organizations can improve their marketing strategies, enhance user experiences, and ultimately drive better business outcomes.

Reach out to us to discover the full potential of Piwik PRO as an integrated analytics platform that satisfies the needs of financial organizations: