When Customer Data Proved Us Wrong: Using Behavioural Analytics to Improve CRM Engagement Across 380,000 Customers
Overview
Between 2021 and 2022, I worked within the Customer Relationship Marketing team of a leading Brazilian financial services company serving more than 380,000 customers across private pension, life insurance, premium bond, and rental guarantee products.
Operating within a highly regulated industry, customer communications required close collaboration between CRM, Customer Experience, Customer Support, Product, Marketing, Compliance, Legal, and external partners. The company managed a large and diverse customer base with varying levels of financial knowledge, product understanding, and engagement.
My role sat at the intersection of CRM analytics, customer engagement, lifecycle marketing, customer education, and reporting. While I was initially responsible for campaign reporting and communication performance analysis, the role evolved into a broader focus on understanding customer behaviour and using data to improve engagement across newsletters, educational content, lifecycle communications, self-service platforms, and customer support journeys.
One of the company's strategic priorities at the time was increasing digital engagement while reducing customer friction. Financial products can be complex, and many customers relied heavily on customer support channels to answer questions, understand product features, or complete routine requests. At the same time, communication performance indicated opportunities to improve engagement, content relevance, and customer education.
What began as an effort to optimise communication performance evolved into a broader behavioural analytics initiative focused on understanding how customers actually interacted with content, what information they valued, and how education could be used to strengthen engagement and long-term customer relationships.
Challenge
The organisation managed hundreds of thousands of customers across multiple financial products, yet communication planning was often influenced by assumptions about what customers wanted to read and how they engaged with information.
Several challenges emerged:
Customer engagement levels were below expectations across newsletters and educational communications.
Communication strategies were largely driven by internal assumptions rather than behavioural evidence.
Many customers relied on call centre support to answer questions that could potentially be resolved through better communication and self-service resources.
Financial literacy gaps made it difficult for some customers to fully understand product benefits, long-term value, and financial planning concepts.
Existing communications focused primarily on delivering information rather than building engagement through behavioural insights and customer education.
Limited understanding existed around which customer segments were most engaged, what content themes generated interest, and how communication could support customer retention.
The key question became:
How could customer behaviour data be used to improve engagement, increase content relevance, strengthen customer education, and support longer-term customer retention?
Solution
What I Analysed
To understand why engagement performance was underperforming, I conducted behavioural analysis across multiple customer and communication data sources rather than focusing solely on campaign-level metrics.
This included analysing:
Newsletter open rates, click rates, and article-level engagement.
Customer demographics and profile characteristics.
Product ownership and customer lifecycle stage.
Content consumption patterns across newsletters, blogs, guides, and educational materials.
Customer feedback surveys and engagement responses.
FAQ search behaviour and recurring customer questions.
Communication performance by day of the week, day of the month, send time, and publication frequency.
Customer participation in onboarding, educational, and lifecycle communication journeys.
The objective was to understand not only which communications performed well, but why customers engaged with certain content and ignored others.
Key Insights
The analysis revealed several important insights that challenged existing assumptions.
First, customer engagement behaviour did not fully align with the audience profiles that had traditionally guided communication planning. The customers who consistently engaged with content were not always the groups the business expected to be most active.
Second, educational content regularly outperformed many product-focused communications. Customers showed stronger engagement with content that helped them understand financial concepts, improve financial planning, or solve practical problems.
One particularly interesting example was an educational article that used football concepts to explain financial topics. The article significantly outperformed expectations and highlighted how customers responded positively to relatable and easy-to-understand educational content.
Third, communication timing had a measurable impact on engagement. Analysis identified specific days of the week, periods of the month, and sending windows that consistently generated stronger open and click performance.
Finally, the existing newsletter structure created content overload. Monthly newsletters often contained multiple articles competing for attention, making it difficult for customers to identify the most relevant content.
What I Changed
Based on these findings, I helped redesign the communication strategy around customer behaviour rather than internal assumptions.
Key changes included:
Optimising send schedules based on behavioural engagement patterns.
Restructuring communications from larger monthly newsletters into more focused and timely communications delivered twice per week.
Reducing content overload by decreasing the number of articles presented within each communication.
Improving content hierarchy and newsletter layouts to make content easier to consume.
Introducing customer feedback surveys to support future content planning.
Expanding financial education initiatives based on demonstrated customer interests.
Creating additional educational content categories designed to improve financial literacy and customer understanding.
Using engagement insights to guide content selection and prioritisation.
Beyond newsletter optimisation, I also supported lifecycle communication initiatives designed to improve onboarding, engagement, and retention.
By analysing customer journey behaviour and engagement trends, I helped identify moments where customers were more likely to become disengaged or question the value of their products. These insights informed targeted communications focused on product understanding, financial education, milestone engagement, and long-term customer retention.
Rather than simply sending more communications, the objective became delivering more relevant communications at the right moment, with content aligned to customer needs, interests, and behavioural patterns.
Results
The combination of behavioural analysis, content optimisation, customer education initiatives, and lifecycle communication improvements delivered significant improvements in customer engagement performance.
Key outcomes included:
Increased newsletter open rates by more than 20 percentage points.
Increased article-level engagement by more than 225%.
Increased total newsletter clicks by more than 150%.
Improved engagement among targeted customer segments.
Increased interaction with educational content and customer learning initiatives.
Strengthened participation in lifecycle communication journeys.
Improved understanding of customer interests, behaviours, and engagement drivers.
Supported more data-driven communication planning and CRM decision-making.
Helped establish customer education as a strategic component of engagement and retention efforts.
More importantly, the project shifted communication planning from assumption-driven decision-making to evidence-based customer engagement strategies built on behavioural insights and real customer needs.
Metrics and selected operational details have been adjusted slightly for confidentiality purposes while preserving the overall business outcomes and learning points.
Key Topics
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