AWS Only
Evaluating The Premier League’s Brand value with Generative AI and Global Fan Sentiment
The Premier League sought to validate its claim as the most competitive and compelling sports league globally, using real-world fan sentiment. To address this challenge, Firemind developed a generative AI platform powered by AWS, analysing user-generated data from social media. This solution provided deep insights into fan perceptions, benchmarking the league against global sports competitors.
AWS ONLY ·
Evaluating The Premier League’s Brand value with Generative AI and Global Fan Sentiment
The Premier League sought to validate its claim as the most competitive and compelling sports league globally, using real-world fan sentiment. To address this challenge, Firemind developed a generative AI platform powered by AWS, analysing user-generated data from social media. This solution provided deep insights into fan perceptions, benchmarking the league against global sports competitors.
At a glance
The Premier League is one of the world's most prestigious football leagues, renowned for its high level of competition and global fan base. It manages the top professional football clubs in England, driving global sports entertainment.
Challenge
The Premier League wanted to verify its claim as one of the world's most competitive sports leagues, with a high tier of brand value from fans. To achieve this, it required a solution that could analyse global fan sentiment across various sports, leveraging advanced data and AI-driven insights.
Solution
Firemind deployed a generative AI platform on AWS, utilising Anthropic's Claude 3 LLM to analyse global fan sentiment from social media. The solution combined AI with quantitative insights, enabling the Premier League to validate its competitiveness through comprehensive, data-driven analysis.
Services used
Firemind's PULSE
Amazon Bedrock
Amazon QuickSight
AWS Lambda
Outcomes
58% positive sentiment results from social data, compared to other sporting leagues.
2.5x more excitement for the Premier League matches, in comparison to other sports leagues globally.
Business challenges
Validating the Premier League’s global appeal and competitiveness
The primary challenge for the Premier League was to substantiate its claim as the most compelling and competitive football league globally. This assertion requires rigorous validation beyond traditional metrics, as the league’s reputation is influenced by both quantitative data and qualitative perceptions. The complexity arises from the need to analyse vast amounts of user-generated content and sentiment data across diverse platforms, and then synthesise this information to provide a comprehensive view of global perceptions.
Additionally, the challenge extends to understanding how the Premier League compares to other popular sports leagues in key markets such as India, China, and the USA. This involves uncovering nuanced cultural and emotional factors that affect fan engagement and sentiment, which are not easily captured through conventional statistics.
Addressing this challenge required advanced data analytics and generative AI tools to gain deeper insights and validate the Premier League’s position in the global sports landscape.
Enter
Add role
Solution
Leveraging generative AI to validate Premier League’s global impact
To address the challenge of validating the Premier League’s global appeal, we implemented a comprehensive solution utilising AWS services and the Large Language Model (LLM) Anthropic Claude 3 Haiku. The project began with the deployment of Firemind’s generative AI sandbox on AWS, named PULSE, providing a robust and scalable environment designed to handle the extensive volume of user-generated data collected from diverse sources such as Instagram and X.
AWS services played a crucial role in our solution. AWS Step Functions were used to orchestrate the complex workflows involved in data ingestion, transformation, and processing. This service ensured that each step of the data pipeline was executed in a coordinated manner. AWS Lambda functions were utilised for serverless computing tasks, handling real-time data processing without the need for managing servers, thus ensuring scalability and efficiency. Amazon SageMaker was employed to host the LLM Anthropic Claude 3 Haiku, which was key for performing advanced sentiment analysis. The LLM’s capabilities allowed us to derive deep, nuanced insights from the data, uncovering subtle sentiments and perceptions about the Premier League and its competitors that traditional metrics would likley miss.
To present these insights effectively, we leveraged Amazon QuickSight, which provided interactive and visually compelling dashboards. QuickSight enabled us to create intuitive visualisations of the sentiment analysis and other key metrics, making complex data accessible and understandable. Initially the data came from scraping over 15,000 tweets from the social platform X. These data visualisations allowed stakeholders to interact with the data, explore trends, and gain a clear view of fan engagement and perceptions across key markets such as India, China, and the USA.
By combining these advanced technologies, we not only validated the Premier League’s global positioning but also delivered actionable insights and visually engaging reports. This approach equipped the Premier League with a deeper understanding of its impact and provided the necessary tools to refine its marketing strategies and enhance its global fan engagement efforts.
Comprehensive global insight
Delivering a thorough understanding of the Premier League's global appeal by analysing user-generated data from diverse platforms. With advanced sentiment analysis, we captured nuanced perceptions and emotions from key markets like India, China, and the USA. This comprehensive insight helps validate the Premier League’s claim as the most compelling league globally, providing a clear picture of fan sentiment and engagement.
Data-driven decision making
By integrating AWS services and visualising insights through Amazon QuickSight, the project enables data-driven decision-making. QuickSight’s interactive dashboards present complex data in an accessible format, allowing stakeholders to explore trends and make informed decisions. This empowers the Premier League to refine marketing strategies, tailor engagement initiatives, and address any discrepancies between fan perceptions and statistical data.
Scalable and efficient processing
Utilising AWS’s serverless architecture and advanced analytics tools ensured scalable and efficient data processing. Step Functions and Lambda handled the large volumes of data seamlessly, while SageMaker’s deployment of the LLM facilitated rapid and accurate sentiment analysis. This efficient processing infrastructure supports the rapid generation of insights, making it possible to swiftly adapt strategies based on real-time data and emerging trends.
Model Spotlight
Anthropic Claude 3 Haiku
Anthropic Claude 3 Haiku was chosen for this project due to its advanced capabilities in natural language understanding and sentiment analysis. This large language model (LLM) excels at processing and interpreting complex and nuanced text, which is essential for analysing diverse user-generated content from social media and other platforms.
Claude 3 Haiku’s ability to generate deep insights from vast amounts of data makes it ideal for uncovering subtle sentiments and perceptions about the Premier League and its competitors. Its advanced natural language processing features enable the model to detect and interpret intricate emotional cues and contextual nuances that traditional analytics might overlook.
Furthermore, the model’s efficiency in handling large datasets and producing actionable insights quickly aligns well with the project’s need for scalable and rapid analysis. By leveraging Claude 3 Haiku, the project was able to gain a comprehensive understanding of global fan sentiments, validate the Premier League’s claim, and provide detailed, data-driven recommendations for enhancing marketing strategies and fan engagement.
Why Firemind
Firemind was chosen as the AWS partner for this project due to our specialisation in AWS services, particularly in data, machine learning, and generative AI. Our expertise in leveraging AWS tools like SageMaker, Lambda, and Step Functions aligns perfectly with the technical requirements of the project. This specialisation ensures that the project benefits from optimised solutions within the AWS ecosystem.
Firemind’s commitment to innovation is evident in our use of advanced technologies such as generative AI and large language models. This innovative approach is essential for achieving the project’s goal of validating the Premier League’s global appeal through sophisticated data analysis and sentiment insights.
58%
High positive sentiment
The Premier League's sentiment analysis reveals a strong positive sentiment of 58%, significantly higher than other sporting leagues which revealed a positive sentiment averaging 19%. This indicates that fans view the Premier League more favourably compared to other major leagues, highlighting its global appeal and the excitement associated with its matches.
15%
Team focus
The results highlighted a favourable sentiment toward team performance, rather than individual stats on players in other popular leagues.
Added value
The sentiment analysis highlights that while other leagues have their own strengths, such as competitiveness, player culture, or individual superstars, the Premier League stands out for its widespread fan excitement and global engagement. This contrast offers valuable insights into the unique strengths of the Premier League and areas where other leagues might focus to enhance their appeal.
These highlights provide a comprehensive view of the Premier League’s strong market position, the challenges related to officiating perceptions, and its comparative advantages over other sports leagues.
Get in touch
Want to learn more?
Seen a specific case study or insight and want to learn more? Or thinking about your next project? Drop us a message below!