How financial services can drive growth with digital analytics

The financial services industry is evolving rapidly. In recent years, consumer expectations of banks and insurance companies have shifted significantly. Customers now expect their financial service providers and their customer service agents to recognize their needs, remember their past transactions and anticipate their future requirements.

 

Traditional banks face increasing competition from emerging fintech companies which threaten their profitability. New methods of lending such as peer lending and microcredit, and new forms of payments such as e-wallets and buy-now-pay-later services, are common. Competition is fierce. As a result, the market for business analytics in fintech has been valued at $3.1 billion globally and is projected to reach $22.9 billion by 2031.

 

To stay ahead, financial services companies need to modernize their total digital analytics processes so they can dig deeper than business metrics and get closer to their customers. However, legacy technology often poses a significant challenge, compounded by vast amounts of unstructured historical data in formats and locations that make it difficult to analyze.

 

 

A robust analytics platform can help financial services companies overcome these challenges by delivering data-driven insights that can transform product and marketing strategies. Traditional analytics tools often focus on sales funnels, but modern solutions go far beyond simple conversion rates. 

 

Advanced behavioral analytics capabilities play a crucial role in financial services innovation. Companies that collect and analyze data on customer behavior, pain points and reactions will be better equipped to develop solutions that address customer needs. They will be able to deliver improved customer service, enhanced user experiences and optimized AI-driven tools such as chatbots. These capabilities enable techniques such as cohort analysis and user journey analytics which provide deeper insights into customer behavior.

 

Cohort analysis enables businesses to see how groups of customers behave and whether that behavior evolves over time. Instead of assuming that a demographic group remains static, organizations can see how users change based on their experiences with a brand. The behavior of an older customer or one in an inner city may change at a different rate or in different ways compared with that of a younger customer or one living in a rural location. These insights can help companies tailor their messaging and user experiences accordingly.

 

User journey analytics further enhance understanding by tracking users across different channels. Businesses can compare the behaviors of customers who convert or drop off anywhere from their first engagement with a piece of marketing content to adopting multiple features in the product. This level of detail helps organizations refine their value propositions, identify pain points, optimize the user journey – and maximize conversions.

 

 

For product teams, deep analytics provide valuable answers to key questions about conversion, customer onboarding and long-term retention.

 

 

Today’s banking and insurance customers expect seamless, multi-channel experiences (71 per cent of private bank clients prefer interactions across multiple touchpoints). Customer segmentation plays a vital role in targeting these users effectively. For example, one mobile banking app achieved a 30 per cent increase in conversion and a 55 per cent reduction in user verification costs by using digital analytics to uncover the right messaging with which to target the right customers. A/B testing can further enhance activation rates by identifying the best-performing strategies.

 

 

Efficient know-your-customer (KYC) processes are essential when new customers are being introduced to a new product. Analyzing where they struggle during onboarding will enable banks to experiment with different process sequences and shortcuts – such as card scanning for payment details – to minimize friction.

 

Key adoption metrics to be examined include KYC completion/abandonment rates and time to activation. Demographic and cohort insights can be generated to inform better (faster, less expensive, more successful, less frustrating) onboarding strategies.

 

A key challenge is converting un-activated users – customers who have completed a company’s KYC process but have not yet engaged with the product to any great extent. It is critical to optimize your processes to make it faster for customers to complete transactions. Detailed reviews of first-time transaction patterns enable strategies to be developed that encourage engagement.

 

 

Understanding user behavior enables banks and insurance companies to personalize experiences effectively. By analyzing the behavior of different customer types, such as newly acquired customers or customers who have recently experienced a significant life event such as marriage or a house move, companies can deliver relevant financial services.

 

In the same way, targeted promotions can be generated for active and satisfied users, with different messages generated for customers who have given poor feedback, who are still in a cooling off period, or have started a process to close an account.

 

 

Compared with many industries, banks and insurance companies often have low profitability levels, especially when interest rates are low. This means they have to focus on long-term retention strategies.

 

Fortunately for the industry, loyalty levels are relatively high in financial services. For example, fintech apps have higher retention rates than other industries, with 27 per cent of users re-engaging after one week and 15 per cent still active after 52 weeks.

 

Despite this advantage, it is still important for banks to understand what drives loyalty. Key retention metrics include retention rates over time, customer lifetime value, repeat product purchase rates, and the relative impact of referral programs and other marketing initiatives. Using this data, product managers and marketing teams can collaborate on feature enhancements and user experience improvements, as well as running A/B tests to drive up retention metrics.

 

 

Financial services companies handle a great deal of sensitive customer data. Privacy and information security are therefore top priorities. A data breach can have severe consequences: the bank may be fined for failing to comply with regulatory requirements and may also experience substantial reputational damage; the customer can experience fraud, theft and even have their account taken over by criminals.

 

Strong analytics play a critical role in enhancing security and privacy within financial services. By using digital analytics that can automatically identify anomalous or suspicious activity, companies can detect fraudulent transactions in real time and mitigate cyber-security threats. Automated analysis of compliance and compliance-related activities further ensures adherence to stringent data protection laws, reducing financial, legal and reputational risks.

 

Differential privacy plays a part here. This is an advanced mathematical technique that helps protect an individual’s data by anonymizing it while still allowing aggregate analysis of the data set to take place. It allows companies to track key events without tying data to specific user IDs, ensuring compliance while delivering valuable insights.

 

 

Mixpanel provides a powerful analytics solution that ties user interactions to business outcomes. Its digital analytics span product usage and marketing engagement and seamlessly integrates with customer data from a CDP or business data from a data warehouse, delivering a complete picture of user behavior and its impact on revenue.

 

Unlike other solutions, Mixpanel combines deep, flexible analysis with an intuitive, easy-to-use interface, enabling teams to make data-driven decisions without relying on specialized data teams.

 

For financial services specifically, Mixpanel tracks customer journeys in granular detail—before, during, and after conversion—while preserving user anonymity. This helps companies optimize web and mobile experiences, improve conversion rates, and streamline critical processes like KYC. With real-time insights, marketing, data, and product teams can act quickly to drive acquisition, engagement, and retention.