Executive Summary
A leading New York-based social media insights company sought to gain a deeper understanding of audience sentiment and behavior across multiple platforms.
They partnered with Elastiq to build a social media intelligence platform capable of ingesting, processing, and analyzing billions of messages daily.
We enabled the client to identify and analyze audience segments based on their interests, demographics, and behavior.
This allowed them to tailor content to specific audiences, forecast content performance, and make data-driven decisions by harnessing the full potential of social media data.
Client Profile
Our client is a prominent social media insights company dedicated to providing comprehensive solutions for understanding audience sentiment and behavior. They serve a diverse range of clients, including media companies, brands, and political campaigns.
Business Problem
The client faced several challenges in their quest to gain actionable insights from social media data:
- The sheer volume of social media data (both the content itself and the comments on the content) posed a significant challenge in terms of ingestion and processing.
- Identifying and connecting users across different platforms, even without explicit identifiers, was crucial for accurate audience segmentation.
- The client required sophisticated analytics capabilities, including sentiment analysis, topic modeling, and audience segmentation.
- Including sentiment analysis, topic modeling, and audience segmentation.
Elastiq Solution
Elastiq addressed these challenges by designing and implementing a comprehensive social media intelligence platform. Key components of the solution include:
- High-Throughput Data Ingestion Pipeline on Google Cloud: We developed a scalable pipeline to ingest data from multiple social media platforms, including Twitter (X), Facebook, Instagram, LinkedIn, Reddit, Twitch, and YouTube.
- Data Processing Pipeline: We built a scalable data processing pipeline that ran on Google Cloud Dataflow. The pipeline called various APIs and models for entity extraction, entity resolution, topic modeling, and sentiment analysis, to enrich the data with valuable insights.
- Audience Segmentation: To identify and classify the audience based on their interest, behavior and demographic distribution, we developed a number of Machine Learning Models, using Google Cloud Vertex AI, including Age and Gender prediction, content and collaborative filtering (adapted for the use-case), and clustering based on key features that were engineered.
- Identity Resolution: We implemented identity resolution to identify and connect users across different social media platforms, even in the absence of explicit identifiers like email addresses or phone numbers. This was done by calculating the similarity scores on engineered user features using statistical algorithms like Soundex, Levenstein Distance, and Machine Learning algorithms like the cosine similarity of embeddings using an NLP model.
- Custom Dashboards: We developed custom dashboards on Looker Studio to visualize key metrics and trends, empowering the client to make data-driven decisions.
Results and Highlights
The Elastiq solution delivered impressive results:
- Massive Data Ingestion: We successfully ingested and processed over 5 billion messages per day at peak load.
- Audience Segmentation and Forecasting: We successfully segmented audiences based on their interests, demographics, and behavior, and predicted content performance for different segments.
- Identity Resolution: Our innovative approach to identity resolution allowed the client to accurately segment audiences and track user behavior across different platforms.
Conclusion
By leveraging Elastiq’s expertise in data engineering and machine learning, the client was able to build a powerful social media intelligence platform. This platform empowers them to gain valuable insights, make data-driven decisions, and stay ahead of the competition.
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