TextInsights Analyzer is a data intelligence and analytics solution that aims to transform massive volumes of unstructured textual data into actionable business intelligence through advanced natural language processing. This platform serves as a critical bridge between raw information and strategic decision-making, allowing organizations to uncover hidden patterns and trends within their text-based assets.
SERVICE
Verify Trusted
An online reputation management service
Client
Confidential
Duration
1.5 months
Category
Blockchain
Year
2024
Technology
Python, Django, NextJS, PostgreSQL, Gitlab CI, AWS
Introduction
Verify Trusted is a service that aims to consolidate and showcase a business’s online reputation by combining reviews from various platforms into a single, optimized profile, thereby enhancing trust and online visibility
Challenges
Verify Trusted aims to consolidate and showcase online reviews from multiple platforms to enhance a business’s online reputation and search engine visibility. However, several challenges stood in the way of achieving this goal:
– Data aggregation and normalization: A complex task involved collecting and standardizing review data from various sources like Facebook, Google My Business, and Yelp. Each platform presented unique APIs, data formats, and rate limits, making it difficult to ensure consistency and accuracy across all information.
– Scalability and performance for high-volume data: Designing a system capable of handling a massive and continuously increasing volume of review data was a significant hurdle. Performance needed to remain optimal even as the user base and the number of integrated business and review platforms expanded.
– Real-time data synchronization: Keeping review profiles consistently up-to-date required near real-time synchronization with diverse review platforms. This process was technically intricate due to varying API limitations and rate limits across different sources.
Solutions
To overcome the challenges, Hola Tech adhered to the best practices. Key components of the solution included:
– Data aggregation and normalization: To address the complexities of collecting and standardizing diverse review data, a robust backend system will be developed using Python and Django. This system will incorporate custom parsers and adapters for each review platform’s API, handling varying data formats and rate limits. Data normalization will be achieved through a standardized schema in PostgreSQL, ensuring consistency across all aggregated information.
– Scalability and performance for high-volume data: To manage a massive and growing volume of review data without slowing down, the system will be built to grow easily. The Django backend will run on AWS, automatically scaling application copies based on traffic to keep up with demand
– Real-time data synchronization: To keep review profiles consistently current, a real-time data synchronization system will be put in place. Django Channels will enable instant updates to the Next.js frontend via WebSocket communication, providing immediate feedback.
Featured numbers
– Processed over 100,000 individual review entries
– Integrated with 100+ unique business websites
Results
The implemented Verify Trusted system successfully met businesses’ requirements for consolidating and showcasing their online reputation. The platform has significantly enhanced the visibility of positive customer feedback, attracting over 100 businesses to create their unified review profiles. Verify Trusted has empowered these businesses to prominently display their accumulated trust from across the internet, with an average increase in their organic search visibility for reputation-related queries. This demonstrates Verify Trusted’s success in providing a seamless and highly effective solution for managing and leveraging online reviews for improved brand credibility and search engine performance.
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