AI-Based Marketing Tool/Product Development MKT-450

Final Project: AI-Based Marketing Tool/Product Development

Overview: The final project for this course entails the development of an AI-based marketing tool or product, implemented using Python with a user interface. The project will be executed in groups, where students have the freedom to choose any topic related to AI in marketing. Potential project ideas include a website running on recommender systems, a chatbot with Large Language Model (LLM) functionality for customer relationship management (CRM), or a dynamic market campaign creation tool based on user preferences and behavior.

Project Timeline:

• Project Prototype Presentation: Session-12


• Final Submission Deadline: 15 days after Session-12 (27^th Dec 2024)

Instructions:

1. Group Formation:




• Students will form groups based on their interests and skillsets. Each group should consist of 3-4 members.




2. One-Pager Document Submission:




• Each group will submit a one-page document outlining their chosen project topic and a brief description of their proposed AI-based marketing tool/product.


• The document should include:




• Project Title


• Project Description


• Overview of the AI techniques to be used


• Expected outcomes and potential impact


• Group members' names and roles






3. Project Development:




• Groups will commence development of their AI-based marketing tool/product using Python.


• The product should include a user interface for ease of interaction.


• Students can utilize libraries and frameworks such as TensorFlow, PyTorch, Flask, Django, etc., as per the project requirements.

4.Documentation and Submission:

• Each group will prepare comprehensive documentation for their project, including:




• Detailed report documenting the project's objectives, methodology, implementation, and results.


• Code repository containing the Python code for the project, properly commented and structured.


• Data used for training and testing the model, if applicable.


• Relevant software required to run the code, along with an installation procedure document.


• Presentation slides for the project presentation in Session-12.




• All submissions should adhere to the formatting and submission guidelines provided by the instructor.

5.Project Presentation:

• Groups will present their projects prototype in Session-12, demonstrating the functionality and effectiveness of their AI-based marketing tool/product.


• Presentations should cover key aspects such as project objectives, methodology, implementation details, results, and potential applications.

6.Final Submission:

Evaluation Criteria:

• Originality and creativity of the project idea.


• Depth and clarity of documentation.


• Implementation quality and functionality of the AI-based marketing tool/product.


• Effectiveness in addressing the stated objectives and solving the targeted marketing problem.


• Presentation quality and ability to effectively communicate key insights and findings.

Note: Students are encouraged to seek guidance from the instructor and leverage resources available online to successfully complete their projects. Collaboration, innovation, and attention to detail are key to achieving success in this final project.

Some Suggestions but you open to take any topic of your choice

1. Personalized Product Recommendation System

• Description: Build a website or app that provides personalized product recommendations based on user preferences, browsing history, and purchase behavior.


• AI Techniques: Collaborative filtering, content-based filtering, hybrid recommendation systems.


• Potential Impact: Enhances user experience and increases sales conversion rates.

2. AI-Powered Chatbot for CRM

• Description: Develop a chatbot integrated with an LLM for customer relationship management to handle FAQs, support queries, and product recommendations.


• AI Techniques: Natural Language Processing (NLP), sentiment analysis, LLMs (like OpenAI GPT or BERT).


• Potential Impact: Improves customer satisfaction and reduces response time.

3. Dynamic Marketing Campaign Generator

• Description: Create a tool that generates personalized marketing campaigns based on user demographics, preferences, and behavioral data.


• AI Techniques: User profiling, clustering, and text generation with NLP.


• Potential Impact: Increases campaign effectiveness and customer engagement.

4. Social Media Trend Analyzer

• Description: Build an AI tool to analyze trending topics on social media and suggest marketing strategies aligned with current trends.


• AI Techniques: Sentiment analysis, trend prediction using time-series analysis, topic modeling.


• Potential Impact: Helps brands stay relevant and capitalize on viral trends.

5. Ad Performance Prediction Tool

• Description: Develop a tool to predict the success of ad campaigns using historical data and suggest optimizations.


• AI Techniques: Regression models, classification algorithms, and A/B testing simulations.


• Potential Impact: Improves ROI on ad spends by optimizing ad placements and content.

6. Customer Segmentation Tool

• Description: Create an AI system to segment customers into distinct groups based on purchasing behavior, preferences, and demographics.


• AI Techniques: Clustering (K-Means, DBSCAN), classification models.


• Potential Impact: Enables targeted marketing and better resource allocation.

7. AI-Based Influencer Marketing Tool

• Description: Build a tool that identifies and ranks potential influencers for a brand based on their relevance, engagement, and audience.


• AI Techniques: Social media data scraping, graph-based algorithms, and sentiment analysis.


• Potential Impact: Enhances the effectiveness of influencer collaborations.

8. Dynamic Pricing Optimization System

• Description: Develop a pricing tool that adjusts product prices dynamically based on demand, competition, and customer behavior.


• AI Techniques: Reinforcement learning, regression models.


• Potential Impact: Maximizes revenue and improves market competitiveness.

9. Visual Content Analyzer for Marketing

• Description: Create an AI tool to analyze the effectiveness of visual marketing materials (e.g., images and videos) and suggest improvements.


• AI Techniques: Computer vision, image recognition, and sentiment analysis.


• Potential Impact: Improves the appeal and impact of marketing materials.

10. Lead Scoring and Conversion Prediction Tool

• Description: Develop a system to score leads and predict conversion probabilities based on CRM data and user interactions.


• AI Techniques: Predictive modeling, classification algorithms, feature engineering.


• Potential Impact: Helps prioritize high-potential leads and improves sales efficiency.