Skincare & Beauty Trends Analytics Dashboard

As someone who has followed the skincare industry for years — testing products, tracking ingredient innovations, and watching trends emerge on TikTok and Reddit before they hit store shelves — I wanted to apply my analytical skills to the space I know best. I remember noticing ceramides appearing everywhere in late 2022 and thinking, “this is going to be huge”— months before CeraVe and other brands launched their ceramide-focused lines. That instinct felt like something I could quantify.

This project is the intersection of two things I care about deeply: understanding consumer behavior through data and genuinely wanting to know why certain ingredients take off while others stay niche. Every chart here was built with the same curiosity that drives me to read ingredient lists at Sephora and scroll through r/SkincareAddiction at midnight. The difference is that now I have the SQL queries and the trend data to back up the intuition.

Data is ingested from three sources on a weekly cadence: Google Trends API for search interest, Reddit PRAW for community discussion and sentiment, and web-scraped product launch data from Sephora and Ulta. A Python pipeline normalizes, deduplicates, and loads everything into a SQLite database for downstream analysis.

The normalized schema links ingredients to three data sources through junction tables, enabling flexible queries across Google Trends interest scores, Reddit post sentiment, and product launch timelines.

Curated from personal knowledge, industry reports, and Reddit frequency analysis. Organized by functional category to enable cross-category trend comparison.

Google Trends interest scores (0–100) for the ten most-searched skincare ingredients. Note the dramatic ceramide and snail mucin trajectories versus the stability of established ingredients like retinol and vitamin C.

Compound annual search growth for the fastest-moving ingredients. Snail mucin leads at +180%, though much of that growth is concentrated in a single viral window. Ceramides and peptides show more sustained, structurally driven growth.

Relative monthly search intensity reveals strong seasonal cycles. SPF predictably peaks in summer, while barrier-repair ingredients (hyaluronic acid, ceramides, retinol) dominate winter skincare routines. Niacinamide and vitamin C remain remarkably steady year-round.

One of the most compelling findings: Google Trends demand signals consistently appear 2–3 months before major brand product launches. This suggests that consumer interest is leading brand strategy, not the other way around.

Sentiment classification across 10K+ posts from r/SkincareAddiction and r/AsianBeauty using a fine-tuned VADER model. Hydrators lead in positive sentiment (72%), while acids show the highest negative sentiment (20%) — likely reflecting irritation-related complaints and purging period discussions.

The most discussed categories (Acids, Vitamins) are not necessarily the most positivelydiscussed — Hydrators and Peptides generate fewer total posts but significantly more favorable sentiment, suggesting higher satisfaction rates.

The interactive Streamlit app provides three analysis views, each designed for a different use case. Built with Plotly for rich hover tooltips and responsive zooming.

How beauty brands, retailers, and investors could leverage this type of ingredient-level demand intelligence.