TrendTool – Uncover Consumer Trends Through Keyword Analysis and NLP

Hacker News

Share card

TrendTool – Uncover Consumer Trends Through Keyword Analysis and NLP

Hello, My name is Florian! How are you marketing analysts on Hacker News? I am a digital marketing professional with a background in analytics, data engineering, and consulting. I've always been intrigued by consumer behavior and trends. So, when faced with a market research project, I decided to develop a tool that takes a unique approach to understanding consumer interests. The Google Ads Keyword Planner is a nice little tool in your Google Ads Account that gives us a glimpse into what people are searching for. It makes monthly search volume, CPC and competition index easily accessible. By entering just one keyword, Google creates like 1,000 related and associated keywords - especially the with longtail keywords (those keywords with lower search volume adding up to a quite huge search volume).But what if we could go deeper? What if we could understand not just the volume but the context and trends behind those searches? --> http://trendtool-frontend.geosage.kuwala.io/ I started by using the Keyword Planner to generate over 100,000 associated keywords for the food industry. I then employed NLP techniques using spaCy to develop a Named Entity Recognition (NER) model that categorizes these keywords into dimensions like ingredients for meals, purpose of meal preparation, etc. For the tech stack, I used a budget-friendly VP. I use CapRover to host a PostgreSQL database and Hasura for GraphQL API. The front end is built using React, and visualizations are rendered through Dash.js. You can check out the demo here, which currently supports up to three meal-related queries and is geared towards the German market: http://trendtool-frontend.geosage.kuwala.io/ . Sorry folks that it is steered toward German language - but I am going to fix that soon! My Next Steps are ... - Using Google Trends for weighting absolute search volume to get absolute search volume for the past 15 years. - Expand analysis scope to other domains and languages (and using wiki data as seed keywords and taxonomy). - Enable state-saving on the front end for long-term trend tracking. I'd love to hear your thoughts. Is this tool something you'd find useful? Should I open-source the code? What features would you like to see added?