Olist Detects Churn Signals Early w/ 6 Unified Sources

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Olist

Olist used Birdie’s AI platform to uncover the early signals behind customer churn by unifying feedback from cancellation forms, support tickets, NPS, and public reviews. By correlating complaints with customer segments and behavioral data, the company reduced churn analysis time by 90%, identified issues previously invisible in traditional forms, and built a data-driven action plan for product, CX, and communication improvements. With Birdie, Olist now detects risks faster, prioritizes high-impact fixes, and drives a more customer-centric growth strategy.

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Atlas

Atlas Eletrodomésticos is a Brazilian home appliance manufacturer with more than seventy years of experience in the stove industry. Founded in 1950 in Pato Branco, Paraná, the company began with handcrafted wood-burning stoves and evolved into a major national player. With a strong focus on durability, practicality, and continuous improvement, Atlas has grown through decades of product innovation and expanded further with the acquisition of Dako in 2018.

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Tegus

Tegus centralized all of its feedback sources with Birdie’s AI platform, eliminating manual work and transforming scattered inputs from support, sales calls, surveys, and web forms into a unified stream of insights. By automating categorization, filtering noise, and applying a flexible taxonomy, the team reduced analysis time dramatically, saving 27 hours per month and turning 300 hours of conversations into actionable insights in just five hours. This enabled Tegus to double the amount of product insights generated, improve cross-team credibility, and make faster, data-driven decisions across its product lifecycle.

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Agibank

A Agibank, one of Brazil's fastest-growing financial institutions with almost 6 million active customers, faced the challenge of understanding the true drivers of churn amidst 2.4 million conversations and 33 thousand NPS responses per quarter. In partnership with Birdie, the bank built a customer voice intelligence engine that unified data from multiple channels and automatically prioritized 117 opportunities by business impact. The implementation resulted in a 10% reduction in churn in pilot markets, preserving approximately 250 accounts monthly and $60,000 in monthly value, in addition to accelerating feedback analysis by 80% and decision-making by 90%.

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Neon

Neon, one of Brazil's fastest-growing neobanks with about 32 million digital accounts, faced the challenge of maintaining its customer-centric focus amidst rapid growth. With customer data fragmented across multiple channels and high detractor rates on app platforms, Neon needed to transform reactive feedback into predictive intelligence. In partnership with Birdie, the bank unified all customer signals into a single source of truth, making it possible to identify friction patterns 3–4 weeks before they appeared in traditional metrics. The results include a 27% improvement in app ratings, a 53% reduction in Android detractors and 57% in iOS, along with 20x faster validation of product improvements.

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Mercado Bitcoin

Although the Voice of the Customer (VoC) process was in progress, it was hard to access, segment, and work the data, making it nearly impossible to delve into customer pain points in a timely manner and correlate their impact in business metrics. In discussions with the Product and Business teams, it was challenging to defend the importance of solving customer issues without clear evidence of their impact on the KPIs that the executive leadership was interested – NPS, contact rate, and transaction rate.

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