Problem

We were planning on a Product Hunt launch but needed more upvotes and visibility. Most people we reached out to were inactive or barely used the platform. We wanted to target people who were already active and engaged—users who log in regularly and actually upvote.

Solution

Product Hunt has a page called Streaks, which shows users who’ve been logging in daily. These are the most active users. I used that as the source.

The idea was simple:

  1. Use Instant Data Scraper (a Chrome plugin) to extract usernames and profile URLs from the Streaks page.

  2. Use a Python script in Google Colab to visit each profile and extract social links like Twitter, LinkedIn, personal websites – anything we could use to reach out.

Implementation

Step 1: Scraping the Streaks Page

  • Opened the Streaks page

  • Ran Instant Data Scraper to grab the list of usernames and profile URLs

  • Exported the data to a CSV

Step 2: Getting Social Handles from Profiles

  • Wrote a Python script that:

    • Visits each Product Hunt profile

    • Scrapes name, headline, follower/following count, about section

    • Decodes any base64-encoded links to pull out Twitter, LinkedIn, or personal sites

    • Saves everything into a clean CSV

We could then filter users by follower count, interests, or just collect their social handles to DM them for support.

Get in touch with me to get the full python code.

Results

  • Got data for 3000+ active users in under an hour

  • Found 700+ people with reachable social handles

  • Sent DMs → got real upvotes from real, active users

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