Betting on data has been a key strategy for the growth of e-commerce and fintech applications. Through detailed analysis of user behavior, brands can segment their audience more precisely, customizing interactions and optimizing the customer experience. This allows not only the acquisition of new users, but also the retention and expansion of the existing base.
According to the study ” Top 10 Fintech & Payments Trends 2024″, prepared by Juniper Research, companies using advanced analytics observe significant improvements in performance. Data-driven personalization can lead to an increase of up to 5% in sales for companies implementing targeted campaigns.In addition, by using predictive analytics, applications can optimize marketing spending, reducing costs and increasing customer acquisition efficiency
Mariana Leite, Head of Data and BI at Appreach, explains the impact of this approach: “The use of 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 the needs of the user”.In addition, the collection and analysis of real-time data allows us to identify opportunities and problems immediately, ensuring that companies stay ahead of the competition.
Personalization and retention based on data
Personalization is one of the great advantages that data use provides. With the analysis of user behavior, apps can identify browsing patterns, purchases and interactions, adapting their offers according to the profile of each customer. This personalized approach increases the relevance of campaigns, resulting in higher conversion rates and loyalty.
Using specialized tools such as Appsflyer and Adjust is essential for monitoring marketing campaigns, while platforms such as Sensor Tower offer market insights that help in comparing performance with competitors.By crossing 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 are able to offer the right recommendation to the right customer at the right time.This raises the level of engagement and makes the user experience unique, significantly increasing the chances of” retention. By monitoring and interpreting demographic, behavioral and transnational data, companies are able to design specific campaigns that keep users active and interested.
Machine learning and AI technologies accelerate growth
Machine learning (ML) and artificial intelligence (AI) have played 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 more 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.In addition, AI automates marketing processes, adjusting campaigns quickly and efficiently, 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 brings privacy and security challenges. As these platforms handle sensitive information, it is essential to ensure that data is protected from leaks and that companies follow regulations such as LGPD and GDPR, which require strict guidelines on the use and storage of data.
Mariana stresses the importance of compliance with laws: “The challenge is not only to protect data, but also to ensure that users understand how their information is used. Transparency is an essential factor in building” trust. Careful consent management and the adoption of robust security practices are key to ensuring data protection and continued growth of apps.
Balance between data and innovation
While data analytics is crucial to app growth, it is important to balance quantitative focus with qualitative insights. Excessive data use can sometimes stifle innovation and creativity.In addition, misinterpretation of data can lead to misguided decisions that do not reflect market reality.
“It is essential to combine data analysis with a deep understanding of the needs of users. Thus, we can make more assertive and innovative decisions”, concludes Mariana. The bet on data must be accompanied by a close look at consumer behavior, ensuring that strategies are always adaptable to market changes and trends.
