Knowledge GraphDigest

When we were launching KgBase on Product Hunt, we had the advantage of using our own platform itself to maximize our number of upvotes on Launch Day.

How We Did It

The first step is finding a hunter two months in advance. We loaded the entire ProductHunt dataset into KgBase to find which hunter had hunted the most successful products for our space.

For example, we identified active hunters who had a significant number of followers. Then we looked at products he launched in our space to see how they performed.

After analyzing how large his following is in Product Hunt, with over 8000 followers and deemed the number 1 hunter, we decided to go with Kevin William David as our Hunter.

The next step was to identify other products in our space that had launched earlier. The goal was to contact the users that had upvoted these products and reach out well in advance of Launch Date. With KgBase, you can easily see the users connected to each product by focusing on the subject.

We were able to narrow it down to ten products in the data/analytics space. From there, we amassed a list of over 900 ProductHunt users that we knew might have an interest in our product.

Once we had the list, we checked their details to figure out the best way to contact them to check out our demo. Understanding the PH audience base, we reached out to them mostly via Twitter with the message below:

The Results

On the actual day of the launch, we reminded our target users to check out our demo again on ProductHunt. The key is to not ask for an upvote explicitly as that is a ProductHunt violation. We ended up in third place for the day having received over 640 upvotes.

We are now offering KgBase as a tool for all founders launching on ProductHunt!. You can sign up here:

All posts