Highlights
- Partnering with a Global B2B Company Serving 2000+ Enterprise Clients: fruitful collaboration with a data research and analytics company serving prominent Fortune 500 corporations.
- Leveraging our AI/ML Development Expertise for Automated Social Media Data Analytics: developing a cutting-edge tool for calculating the metrics on the company’s image based on mentions on the most popular social media platforms.
Client
The client is a global B2B thought leadership and marketing agency that provides market research, business intelligence, data analytics, and consulting services for companies across various business verticals. The company prioritizes delivering deeply customized research solutions to cater to each customer’s needs. The client operates in two dozen industries, serving the world’s business leaders including Phillips, Capgemini, and Accenture.
Product
The product is an AI-powered tool for automating the data collection process for the client. In particular, the tool collects data about the customer’s company in social media and calculates the main metrics about their media image. The main data sources include Twitter, Reddit, and the News API. The product is for client’s usage only, serving its internal analytics team, and has a data loading and processing pipeline as its main components.
Goals and objectives
- Automate the Process of Data Collection and Metrics Calculation: Developing a software solution that automatically gathers data from various sources and calculates relevant metrics, ensuring compatibility with different data formats and structures.
- Reduce Human Time on Data Collection and Processing: Eliminating human intervention in data collection and processing where possible, minimizing time and effort for the client’s analytics team, and letting it focus on more strategic and business-critical tasks.
Project challenge
- Lack of Documentation: understand thefull capabilities and limitations of the 3rd-party APIs without having complete documentation and particular examples for this use case. Contact API providers for additional support when necessary.
- Poor Performance of the 3rd-Party APIs: deal with slow response times that harm the overall performance of the product by implementing caching and fallback mechanisms for frequently accessed data to reduce reliance on API calls.
Solution
To take on this project, we assembled a team of two experienced Machine Learning Engineers and a Project Manager. Since the client is partnering with nearly 2,000 industry leaders who created thousands of social media mentions of the company, we had an enormous amount of data to work with. Collecting and analyzing this data was not only very challenging and time-consuming but also prone to errors, so introducing a solution powered by Artificial Intelligence and Machine Learning was an effective solution to this problem.
Our team decided to build a pipeline that could automatically collect data from social media posts and publications of particular companies to evaluate critical metrics about their internet image and media presence. Based on our experience, Python was selected as the most optimal choice for this project, due to its ease of use and the wide range of powerful libraries available.
Additionally, we decided to implement a message queue system to effectively manage data flow and ensure smooth processing across the solution.
Tech Stack
- Python
- Reddit API
- News API
- Meltwater API
Our results
We have successfully delivered all planned functionality, presenting a custom-built tool that leverages the capabilities of Machine Learning and Natural Language Processing to improve the core business functionality for our client.
- 100% Automation of Media Image Metrics Calculation: The development of a tool that takes on data collection, processing, and metrics calculation, saving countless hours of human labor, while also improving precision compared to manual way of conducting this task. We transformed the way our client handles data, improving overall operational efficiency for the company.
- AI Tool Performance Tuning: Our experts continually monitored the performance of our solution, making timely updates and adjustments to maximize the outputs in handling complex data flows, and delivering full value for the client.
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