Betting on data has been a key strategy for the growth of e-commerce and fintech apps. Through detailed analyses of user behavior, brands can segment their audience more accurately, 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 that use advanced analytics see significant improvements in performance. Data-driven personalization can lead to an increase of up to 5% in sales for companies that implement targeted campaigns. Furthermore, when using predictive analytics, apps can optimize marketing expenses, reducing costs and increasing customer acquisition efficiency
Mariana Leite, Head of Data and BI at Appreach, 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 user's needs. Furthermore, the collection and analysis of real-time data allow for immediate identification of opportunities and problems, ensuring that companies stay ahead of the competition
Data-driven personalization and retention
Personalization is one of the great advantages that the use of data provides. With the analysis of user behavior, apps can identify browsing patterns, purchases and interactions, adapting your offers according to each customer's profile. This personalized approach increases the relevance of the campaigns, resulting in higher conversion and loyalty rates
The use of specialized tools, like Appsflyer and Adjust, it is essential to monitor marketing campaigns, while platforms like Sensor Tower provide market insights that help in comparing 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 are able to offer the right recommendation for the right customer, at the right moment. This elevates the level of engagement and makes the user experience unique, significantly increasing retention chances. When monitoring and interpreting demographic data, behavioral and transnational, companies are able to design specific campaigns that keep users active and engaged
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 allow for 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 probability of abandonment or the predisposition to purchase. With that, we can act before the customer disengages, offering promotions or personalized recommendations, Mariana states. Furthermore, AI automates marketing processes, adjusting campaigns quickly and efficiently, what 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 challenges related to privacy and security. How do 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, that require strict guidelines on the use and storage of data
Mariana emphasizes the importance of compliance with the laws: "The challenge is not just to protect the data, but also 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 the growth of apps, it is important to balance quantitative focus with qualitative insights. Excessive data usage can, sometimes, suffocate innovation and creativity. Furthermore, the 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 assertive and innovative decisions, concluded Mariana. The bet on data must be accompanied by a keen eye on consumer behavior, ensuring that the strategies are always adaptable to market changes and trends
