Marketing Personalization
Inter's growth spread customer data across six sources and 103 streams, creating duplicate profiles and generic outreach that made it difficult to personalize offers while managing AI security and privacy risk.
Reported impact
Inter dramatically improved conversion and ROI on customer offers, reduced coordination overhead for internal teams, and created a secure path for generative AI adoption across development and service workflows.
Inter uses Data Cloud, Tableau, Slack, and a secure internal generative-AI application called InterGPT to turn fragmented banking data into personalized offers and employee productivity workflows. Data Cloud unifies marketing, sales, website, and mobile-app signals from six sources and 103 streams into a single customer profile so the bank can stop sending duplicate or irrelevant messages. Tableau works with Data Cloud to analyze digital behavior such as the pages customers visit and how often they engage, producing scores and more than 3,500 audience segments that feed better product recommendations and campaign timing. To avoid uncontrolled use of outside GenAI tools, Inter also built InterGPT in Slack, where developers use it for code work and service teams use it to search internal knowledge, draft responses, and translate content without taking data outside governed channels.
Customer behavior and product data from six sources and 103 streams are unified in Data Cloud, scored and segmented with Tableau, and then reused for product recommendations and communications, while internal employees access governed GenAI capabilities through the Slack-based InterGPT application.
By making each experience more personal, Inter increased conversion rates 35x and overall ROI 20x.
In three years of high growth, Inter's customer data started to spread across six different sources and 103 streams.
Now, over 1,000 Inter developers can write and review product code in any development language.
This generates engagement scores for each customer, helping Inter create more than 3,500 new audience segments.
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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