Banco Inter

As Brazil's first 100% digital bank, Banco Inter scaled rapidly — but three years of high growth left its customer data fragmented across six distinct sources and 103 separate streams. Because customers routinely held multiple products (checking accounts, credit cards, investments, insurance), records were duplicated and marketing communications became misaligned with actual customer needs. In the hyper-competitive neobank landscape, where personalization is a core differentiator, irrelevant outreach directly undermines conversion and retention. Without a unified customer profile, Inter's teams had no reliable way to predict what a customer needed next or time offers appropriately — leaving significant commercial value on the table.

Inter deployed Salesforce Data Cloud as the foundation for a unified customer data platform, consolidating profiles from all six sources into a single, deduplicated view. On top of that foundation, Tableau was integrated to analyze customer preferences in real time — tracking webpage visits, behavioral signals, and product engagement — and generate individual engagement scores using machine learning and predictive analytics. Those scores fed an automated segmentation engine that produced over 3,500 distinct audience segments, enabling highly targeted product offers delivered through the right channel at the right moment. Separately, Inter built InterGPT, a generative AI application on Slack, in a matter of days — giving more than 1,000 developers and service employees an internal, compliance-safe AI assistant for code review, knowledge-base search, and customer response generation.

The impact of unified data and predictive segmentation was immediate and measurable. Personalized targeting drove a 35x increase in conversion rates and a 20x improvement in overall ROI — outcomes that reflect compounding gains as relevant offers reached the right customers at scale. Operational efficiency also improved: making customer intelligence instantly accessible eliminated an average of 1.5 hours of meetings per day across teams. The InterGPT deployment added further productivity gains, saving each employee roughly 30 minutes per month and generating $13,000 in monthly cost savings. Taken together, these results demonstrate how data unification compounds its value across both revenue generation and internal operations.

• Data unification precedes personalization: a single, deduplicated customer profile is the prerequisite — not the outcome — of effective AI-driven marketing in financial services.
• Behavioral signals are more predictive than demographics: tracking webpage visits and product engagement to generate engagement scores outperformed static segmentation.
• Scale of segmentation matters: 3,500+ audience segments enabled hyper-relevance that broad targeting cannot achieve; invest in the infrastructure to support it.
• Build AI internally when compliance risk is high: Inter's decision to build InterGPT on Slack rather than permit external tools preserved data privacy while still capturing productivity gains.
• ROI compounds across functions: data cloud investments should be measured holistically — conversion lift, meetings eliminated, and employee productivity savings all flow from the same underlying platform.