Betting on data has been a key strategy for the growth of e-commerce apps and fintechs. Through detailed analyses of user behavior, brands are able to segment their audience more precisely, personalizing interactions and optimizing the customer experience. This allows not only the acquisition of new users but also the retention and expansion of the existing user base.
According to the study "Top 10 Fintech & Payments Trends 2024," conducted by Juniper Research, companies that utilize advanced analytics observe significant improvements in performance. Data-driven personalization can lead to an increase of up to 5% in sales for companies that implement targeted campaigns. Additionally, by using predictive analytics, applications can optimize marketing expenses, reducing costs and increasing customer acquisition efficiency.
Mariana Leite, Head of Data and BI at Appreach, explains the impact of this approach: "Using data gives us a complete view of the user, enabling real-time adjustments to improve the experience and increase satisfaction. This results in more effective campaigns and an app that evolves according to user needs." Furthermore, real-time data collection and analysis enable the immediate identification of opportunities and problems, ensuring that companies stay ahead of the competition.
Data-driven personalization and retention
Customization is one of the great advantages that the use of data provides. With user behavior analysis, apps can identify browsing, purchasing, and interaction patterns, tailoring their offers according to each customer's profile. This personalized approach increases campaign relevance, resulting in higher conversion and loyalty rates.
The use of specialized tools, such as Appsflyer and Adjust, is essential for monitoring marketing campaigns, while platforms like Sensor Tower provide market insights that help compare performance with competitors. By cross-referencing this data with internal information, it is possible to make informed decisions to enhance growth.
Mariana highlights the impact of this strategy: "With data in hand, we can offer the right recommendation to the right customer at the right time. This elevates the level of engagement and makes the user experience unique, significantly increasing retention chances." By monitoring and interpreting demographic, behavioral, and transnational data, companies can design specific campaigns that keep users active and engaged.
Machine learning and AI technologies accelerate growth
Machine learning (ML) and artificial intelligence (AI) have been playing an increasingly important role in the growth strategy of fintech and e-commerce apps. These technologies enable behavior predictions, marketing automation, and even real-time fraud detection, bringing greater operational efficiency and security to transactions.
"Machine learning tools help us anticipate user actions, such as the likelihood of abandonment or predisposition to purchase. With this, we can act before the customer disengages, offering promotions or personalized recommendations," says Mariana. Furthermore, AI automates marketing processes, quickly and efficiently adjusting campaigns, which reduces costs and maximizes return on investment.
Security and privacy: challenges in data use
Despite the advantages, the use of data in fintech and e-commerce apps also presents challenges related to privacy and security. Since these platforms handle sensitive information, it is essential to ensure that data is protected against leaks and that companies comply with regulations such as LGPD and GDPR, which require strict guidelines on data use and storage.
Mariana emphasizes the importance of compliance with the laws: "The challenge is not just to protect the data, but also to ensure that users understand how their information is used. Transparency is an essential factor in building trust." Careful management of consents and the adoption of robust security practices are essential to ensure data protection and the continued growth of apps.
Balancing data and innovation
Although data analysis is crucial for app growth, it is important to balance quantitative focus with qualitative insights. Excessive data use can sometimes stifle innovation and creativity. Furthermore, incorrect interpretation of data can lead to misguided decisions that do not reflect the reality of the market.
"It is essential to combine data analysis with a deep understanding of user needs. Thus, we are able to make more accurate and innovative decisions," concludes Mariana. Betting on data should be accompanied by a keen eye on consumer behavior, ensuring that strategies are always adaptable to market changes and trends.
