Targeted-Marketing-Using-LLM

Introduction

Our client aimed to soar above competitors in the fast-paced marketing world by embracing targeted strategies. Recognizing the power of personalized marketing, they enlisted our help to create a cutting-edge solution. Our mission? Develop a machine learning application that assesses content alignment and offers real-time insights and recommendations for improvement.

The Challenge

To tackle the challenge, we set out to design a Large Language Model (LLM)-based application, now known as “Contentify.” The key objective was to ensure marketing content resonated perfectly with the identified target persona, considering metrics such as tone, language, cultural sensitivity, clarity, and coherence.

Skills and Tools Used

• Python
• HuggingFace Transformer
• LangChain
• Llama 2
• Market Survey
• Project Management: Notion
• Model Deployment: AWS EC2, S3 bucket and Streamlit
• Soft Skills: Presentation skill, Collaboration, Communication and Leadership

Task Overview (My contribution)

• Persona Research and Model Selection

  Our journey began with thorough persona research, delving into market surveys to understand the audience’s needs, preferences, and perceptions. Armed with valuable data stored in an Excel file, we proceeded to model selection. The decision to use Llama 2, a powerhouse among open-source language models, was made after extensive experimentation.

• App Development

  Leveraging LangChain, an open-source framework tailored for Large Language Models (LLMs), we engineered the “Contentify” app. Prompt engineering was pivotal in obtaining precise responses from LLMs, enhancing interpretative accuracy. Human judgment occurred during the model assessment, ensuring language fluency, coherence, and factual accuracy.

• Dashboard and Deployment

  Our solution culminated in a user-friendly dashboard, seamlessly integrating Llama 2. This not only empowered marketers but also facilitated a dynamic and responsive environment. Deploying on AWS with an EC2 instance and an S3 bucket ensured optimal performance, responsiveness, and accessibility.

The Outcome: “Contentify” Unleashed

Our meticulous process bore fruit in the form of “Contentify.” This LLM-based application promises to revolutionize marketing strategies, saving time and boosting lead conversion rates. Please take a look at the demonstration to witness its power in action.

Recommendations for Future Enhancement

While our project achieved remarkable success, we identified areas for potential improvement:

1. Higher AWS Compute Power: Upgrading to a higher-powered EC2 instance or utilizing GPU resources can enhance application speed.
2. Advanced LLM Models: Exploring variants like Llama 2 13B or 70B can elevate response precision.
3. Fine-tuning: Tailoring the model with relevant data ensures content generation aligns closely with business needs.
4. Integration: Consider integrating the app into platforms like a Chrome extension for real-time insights as marketers craft content.

Ready to unlock the full potential of your data? I’m excited to collaborate and help your business thrive through data-driven insights. Get in touch!