The Rise of Low-Code and Machine Learning in UI Management: A New Era for Avito
February 8, 2025, 5:19 am
In the fast-paced world of technology, the demand for rapid development and deployment is like a roaring river. Companies must navigate its currents to stay afloat. Avito, a leading online marketplace in Russia, has embraced this challenge by integrating low-code solutions and machine learning (ML) into its user interface (UI) management. This article explores how these innovations are reshaping the landscape of UI development and enhancing user experiences.
Low-code platforms are akin to a painter's palette, offering a range of colors that allow developers to create vibrant applications without the need for extensive coding. Avito's Bricks platform exemplifies this approach. It allows developers and non-developers alike to craft UIs using reusable widgets. This democratization of UI design means that even those without a technical background can contribute to the development process. The result? A more agile and responsive platform that can adapt to user feedback in real-time.
The journey begins with a problem. Users reported that the price in listings often blended into the background, making it hard to spot. Traditionally, addressing such issues required a lengthy process: adding tasks to the backlog, modifying code across multiple platforms, and enduring multiple release cycles. This method was cumbersome and slow, leading to frustration for both users and developers.
Enter the Backend-Driven UI (BDUI) approach. By leveraging a backend-driven architecture, Avito can now deliver UI changes across all platforms simultaneously. This is like having a conductor leading an orchestra, ensuring that every instrument plays in harmony. With BDUI, the UI is defined in a JSON format, allowing for quick updates without the need for users to download new app versions. This innovation drastically reduces the time to market (TTM) for new features, enabling Avito to respond swiftly to user needs.
The mechanics of this system are fascinating. Developers describe the UI, which is then translated into a configuration by backend developers. The backend gathers dynamic data and enriches the UI configuration before sending it to the client application. This seamless interaction between frontend and backend is akin to a well-oiled machine, where each part works in unison to deliver a smooth user experience.
But Avito didn’t stop there. They recognized that the success of their platform also depended on the effectiveness of their service providers. Many service providers struggled to attract clients, leading to a high churn rate. To combat this, Avito introduced a machine learning model designed to enhance the visibility of service listings. This model acts like a lighthouse, guiding potential clients to the best service providers.
The ML model analyzes various factors that influence a service provider's success. For instance, it found that quick response times significantly increase the likelihood of securing a deal. By translating these insights into actionable recommendations, Avito empowers service providers to optimize their listings. The results speak for themselves: A/B testing revealed a 13.9% increase in targeted contacts for business services. This boost translates to more deals and happier service providers.
The underlying technology is equally impressive. Avito employs logistic regression, a statistical method that helps predict outcomes based on input variables. By analyzing the characteristics of successful listings, the model identifies key factors that contribute to higher engagement. This process is akin to a detective piecing together clues to solve a mystery. The insights gained are invaluable, allowing Avito to refine its approach continually.
One of the standout features of Avito's ML model is its use of Weight of Evidence (WoE) and Information Value (IV). These metrics help assess the predictive power of different features, enabling the model to focus on the most impactful elements. This analytical rigor ensures that the recommendations provided to service providers are not just educated guesses but data-driven insights.
The implementation of AutoWoE, a library that automates the process of feature selection and binning, further streamlines this workflow. This tool simplifies the complexity of machine learning, allowing Avito's team to focus on refining their models rather than getting bogged down in technical details. It’s like having a skilled assistant who handles the heavy lifting, freeing up time for creative problem-solving.
As Avito continues to innovate, the integration of low-code platforms and machine learning represents a significant leap forward. These technologies enable the company to respond to user feedback swiftly, adapt to market changes, and enhance the overall user experience. The result is a more dynamic platform that meets the needs of both buyers and sellers.
In conclusion, Avito's journey into low-code and machine learning is a testament to the power of innovation. By embracing these technologies, the company is not just keeping pace with the competition; it is setting the standard for what a modern online marketplace can achieve. As the river of technology continues to flow, Avito is well-positioned to navigate its currents, ensuring that it remains a leader in the digital marketplace. The future is bright, and the possibilities are endless.
Low-code platforms are akin to a painter's palette, offering a range of colors that allow developers to create vibrant applications without the need for extensive coding. Avito's Bricks platform exemplifies this approach. It allows developers and non-developers alike to craft UIs using reusable widgets. This democratization of UI design means that even those without a technical background can contribute to the development process. The result? A more agile and responsive platform that can adapt to user feedback in real-time.
The journey begins with a problem. Users reported that the price in listings often blended into the background, making it hard to spot. Traditionally, addressing such issues required a lengthy process: adding tasks to the backlog, modifying code across multiple platforms, and enduring multiple release cycles. This method was cumbersome and slow, leading to frustration for both users and developers.
Enter the Backend-Driven UI (BDUI) approach. By leveraging a backend-driven architecture, Avito can now deliver UI changes across all platforms simultaneously. This is like having a conductor leading an orchestra, ensuring that every instrument plays in harmony. With BDUI, the UI is defined in a JSON format, allowing for quick updates without the need for users to download new app versions. This innovation drastically reduces the time to market (TTM) for new features, enabling Avito to respond swiftly to user needs.
The mechanics of this system are fascinating. Developers describe the UI, which is then translated into a configuration by backend developers. The backend gathers dynamic data and enriches the UI configuration before sending it to the client application. This seamless interaction between frontend and backend is akin to a well-oiled machine, where each part works in unison to deliver a smooth user experience.
But Avito didn’t stop there. They recognized that the success of their platform also depended on the effectiveness of their service providers. Many service providers struggled to attract clients, leading to a high churn rate. To combat this, Avito introduced a machine learning model designed to enhance the visibility of service listings. This model acts like a lighthouse, guiding potential clients to the best service providers.
The ML model analyzes various factors that influence a service provider's success. For instance, it found that quick response times significantly increase the likelihood of securing a deal. By translating these insights into actionable recommendations, Avito empowers service providers to optimize their listings. The results speak for themselves: A/B testing revealed a 13.9% increase in targeted contacts for business services. This boost translates to more deals and happier service providers.
The underlying technology is equally impressive. Avito employs logistic regression, a statistical method that helps predict outcomes based on input variables. By analyzing the characteristics of successful listings, the model identifies key factors that contribute to higher engagement. This process is akin to a detective piecing together clues to solve a mystery. The insights gained are invaluable, allowing Avito to refine its approach continually.
One of the standout features of Avito's ML model is its use of Weight of Evidence (WoE) and Information Value (IV). These metrics help assess the predictive power of different features, enabling the model to focus on the most impactful elements. This analytical rigor ensures that the recommendations provided to service providers are not just educated guesses but data-driven insights.
The implementation of AutoWoE, a library that automates the process of feature selection and binning, further streamlines this workflow. This tool simplifies the complexity of machine learning, allowing Avito's team to focus on refining their models rather than getting bogged down in technical details. It’s like having a skilled assistant who handles the heavy lifting, freeing up time for creative problem-solving.
As Avito continues to innovate, the integration of low-code platforms and machine learning represents a significant leap forward. These technologies enable the company to respond to user feedback swiftly, adapt to market changes, and enhance the overall user experience. The result is a more dynamic platform that meets the needs of both buyers and sellers.
In conclusion, Avito's journey into low-code and machine learning is a testament to the power of innovation. By embracing these technologies, the company is not just keeping pace with the competition; it is setting the standard for what a modern online marketplace can achieve. As the river of technology continues to flow, Avito is well-positioned to navigate its currents, ensuring that it remains a leader in the digital marketplace. The future is bright, and the possibilities are endless.