How to Leveraging Mobile App Scraping for Retail Success?

Mobile apps have become a vital consumer shopping channel in today's post-pandemic world. With smartphone users spending an average of over 3 hours on their phones daily, it's clear that mobile apps are increasingly preferred over traditional eCommerce apps. Recognizing this shift, Mobile App Scraping has introduced an innovative mobile app scraping solution to complement its successful eCommerce app scraping technology. This advanced solution is designed to help businesses thrive in the evolving retail landscape.

Let's dive deeper into the process and technology behind mobile app scraping, which can be approached in two ways:

Scenario 1:

When composite APIs are open (e.g., Amazon) - In such cases, the scraping process is similar to standard app scraping, with some initial setup required. Mobile App Scraping can utilize the available APIs of platforms like Amazon to access and extract the desired data. The process involves making API requests, handling responses, and parsing the retrieved data.

Scenario 2:

Whenever composite APIs get encrypted (e.g., Dollar General, HEB, Target, Stop & Shop, etc.) - This scenario presents a more complex challenge. Mobile App Scraping employs specialized techniques such as mobile device extraction, OCR (Optical Character Recognition), as well as other machine learning methods to overcome the encryption and extract data from these apps. Mobile App Scraping leverages advanced technologies to navigate the encrypted APIs and interfaces, ensuring accurate and reliable data extraction.

In both scenarios, Mobile App Scraping utilizes its expertise and advanced methodologies to scrape mobile apps efficiently and effectively, providing businesses with valuable data insights to enhance their operations and decision-making processes.

Methodology

Step 1: Recording a mobile session/navigation using unique visual navigation scrapers Technology consideration

Mobile App Scraping employs a virtual device cloud infrastructure to ensure scalability and efficiency. It utilizes an emulated cluster of devices that connect through an intelligent proxy network.

In the first step of the methodology, special visual navigation scrapers are utilized to record mobile sessions and navigation. These scrapers interact with the mobile app interface, mimicking user actions and capturing the relevant data. This approach allows Mobile App Scraping to navigate the app, access different screens, and interact with various elements to gather the desired information.

To achieve scalability, a virtual device cloud infrastructure is employed. This infrastructure emulates a cluster of devices, ensuring that the scraping process can be performed at scale. Additionally, an intelligent proxy network handles communication between the devices and the app, ensuring efficient data retrieval.

By combining special visual navigation scrapers, an actual device cloud, and an intelligent proxy network, Mobile App Scraping ensures a robust and scalable approach to recording mobile sessions and navigating through mobile apps for data scraping purposes.

Step 2: Identify product ROI (Region of Interest)

To accurately scrape text for each product, Mobile App Scraping utilizes an Object Detection algorithm to identify the ROI of individual products within a frame, regardless of the number of products present.

The input files are passed through a custom fine-tuned version of the YOLOv5 (You Only Look Once) architecture, which excels in fast and accurate inference. YOLOv5 can swiftly detect and localize each product's ROI within the frame.

Since a video typically consists of multiple frames per second, the exact product ROIs are possible. To address this, a deduplication stage is introduced. This stage eliminates identical product ROIs, allowing faster and more efficient data processing. The resulting ROIs from the video frames are then cached as images, ready for further analysis and extraction.

By utilizing the Object Detection capabilities of YOLOv5 and implementing deduplication techniques, Mobile App Scraping ensures the accurate identification and localization of product ROIs, laying the foundation for subsequent data processing and extraction.

Step 3: Identify product components

In this stage, Mobile App Scraping focuses on identifying specific components of the products, such as price, product information, product image, and more. The same components to be identified may vary based on the specific mobile app being scraped.

To achieve precise component identification, Mobile App Scraping applies YOLOv5 again, but with a different instance or configuration compared to Step 2. This allows for more granular consideration in detecting and localizing the desired components within the product ROIs.

By leveraging YOLOv5's capabilities, Mobile App Scraping ensures accurate and reliable identification of various product components, enabling the extraction of crucial information such as prices, descriptions, and images. This stage is critical in gathering the specific data elements needed for further analysis and utilization.

Step 4: Extract components with OCR

In this stage, Mobile App Scraping completes the textual extraction process now that all details of the products have been identified. A custom-trained OCR (Optical Character Recognition) framework is deployed to achieve this.

The OCR framework is specifically trained to recognize and extract text from the identified components of the products. It utilizes advanced algorithms and machine learning techniques to accurately extract textual information such as product names, prices, descriptions, and other relevant details.

Mobile App Scraping ensures precise and reliable textual data extraction from the identified product components by deploying a custom-trained OCR framework. This stage is crucial in capturing the detailed information needed for further analysis, processing, or integration with other systems.

Step 5: Accessing the final output

In the final stage, the text extraction output and relevant metadata are stored in a database. Mobile App Scraping applies unit tests and quality checks to ensure the accuracy and integrity of the extracted data.

Once the data is verified and validated, it is transformed into the desired format suitable for the client's needs. This transformation process ensures the information is structured appropriately and ready to be accessed, sent, uploaded, or requested via API (Application Programming Interface).

By storing the data in a database and applying rigorous quality checks, Mobile App Scraping guarantees the reliability and usability of the extracted information. The transformed data can now be seamlessly integrated into the client's systems or applications, empowering them with valuable insights from mobile app scraping.

Conclusion

In conclusion, as the retail landscape evolves with the rise of mobile and social commerce and the emergence of the metaverse, the need for advanced AI and analytics becomes paramount. Mobile App Scraping recognizes this need and is dedicated to providing retailers and brands with sophisticated and accurate analytics across the retail ecosystem. They have developed an cutting-edge mobile app scraping solution to cater to the evolving needs of the retail industry.

Moreover, Mobile App Scraping has extended its proprietary technology to the metaverse, enabling the scraping of retail stores in virtual platforms like Decentraland, Roblox, Sandbox, Meta, and more. This expansion reflects their commitment to staying at the forefront of technological advancements and ensuring that retailers have access to critical data and insights across multiple platforms.

With the growing popularity of mobile commerce and the increasing competition in the retail space, mobile app scraping has become essential for maintaining competitive prices, assortments, and digital shelf ranking. By leveraging Mobile App Scraping's cutting-edge solutions, retailers can stay ahead of the curve and make informed decisions based on accurate and real-time data.

In summary, Mobile App Scraping offers innovative mobile app scraping solutions alongside their established eCommerce app scraping technology, empowering retailers to thrive in the dynamic retail landscape and meet the demands of modern consumers.