Goal (Generalized)

Apply data science and analytics to understand user behavior, segment audiences, and gather actionable insights that inform the marketing strategy and guide the design of the upcoming Curly Lifestyles mobile app.

Project Overview & Objective Statement

Overview:

Curly Lifestyles is preparing to launch a mobile app focused on the curly hair community. This project will use existing engagement and marketing data to understand user behaviors, preferences, and content interactions. Interns will translate this data into user insights, marketing strategies, and UX recommendations.

Objective:

To deliver data-driven insights that inform app development, marketing approaches, and overall user experience strategies.

Data Summary & Preprocessing

Data Description:

• User engagement metrics (web, social, email)
• Demographic data (where available)
• Content performance analytics
• Survey results or qualitative user feedback

Cleaning & Preparation:

• Standardize and unify datasets (formatting, timestamps, user IDs)
• Handle missing or inconsistent entries
• Perform basic aggregation (e.g., sessions per user, click-through rates)

Preprocessing Notes:

• Convert timestamps to usable formats for time-series analysis
• Tag and classify content categories (e.g., tutorials, product reviews, community stories)

Analysis or Modeling Output

Segmentation/Classification Logic:

• Use clustering algorithms (e.g., K-Means) or rule-based profiling to identify core user segments
• Classify high-engagement content and user types

KPI Dashboard or Time-Series Analysis:

• Create interactive dashboards using Tableau, Power BI, or Looker Studio
• Visualize engagement trends over time (e.g., peak times, seasonal usage)
• Identify drop-off points or spikes in interaction

Tools:

• Python (Pandas, Matplotlib, Seaborn)
• SQL
• Tableau or Power BI
• Google Analytics and social media metrics

Insights Report

Key Findings:

• Identification of top-performing content categories
• Discovery of behavioral patterns (e.g., product-focused users vs. community-focused users)
• Peak engagement times and channels (e.g., Instagram Stories drive traffic mid-week)

Visualizations:

• User segmentation charts
• Content popularity heatmaps
• Time-based usage graphs
• Funnel visualizations for user engagement paths

Trends & Anomalies:

• Seasonal drops in engagement
• Unexpected content surges (e.g., viral posts or influencer boosts)

Recommendations

Marketing:

• Focus campaign timing based on high engagement windows
• Tailor content based on identified user segments (e.g., “Beginner Curl Journey” vs. “Product Aficionados”)

Mobile App Development:

• Prioritize content types and features (e.g., tutorial video hub, product tracker, or community Q&A)
• Plan for push notification timing and personalization
• Highlight must-have features based on usage gaps (e.g., personalized hair routines)

Final Deliverables

1. User Profile Report – Segmented personas based on current data
2. Content Engagement Report – Analysis of trends, formats, and interaction behavior
3. Interactive Dashboard – Visual summary of user activity and trends
4. App Research Brief – Summary of user needs, top features, and UX recommendations
5. Stakeholder Presentation – Summary deck for leadership and development teams
6. Learning Reflection – Individual or team-written process documentation