We finished #2 Product of the Day - thank you! š
Skills Marketplace by Databox launched yesterday (June 30th), and the community pushed it to #2 Product of the Day. Thank you.
Huge thanks to the Databox team and everyone here who upvoted, commented, and gave it a real try. Every download and every piece of feedback told us the same thing: people are done manually pulling metrics together just to answer a simple question about their business.
Some of what stood out to us:
How many people are still stitching together CSV exports every Monday morning just to build the same report
How much excitement there was around skipping that step entirely and getting a report straight from live data
How many people said they'd normally spend an hour just building the report before they could even start analyzing it
We'll keep sharing what we learn as we go.
If you've already downloaded a skill or workflow, tell us what clicked and what didn't.
And if you haven't tried it yet, it's free to get started at https://databox.com/skills-marketplace - pick a skill, connect your data once, and your first report is ready in a few minutes.
Replies
Congrats on reaching #2! š That's a huge achievement. I think the response shows just how tired people are of repetitive reporting work instead of actual analysis.
Databox
@amard_sonalĀ Thanks Amard! And yeah, that's exactly what we kept hearing too - almost nobody said "I want AI analytics," they said some version of "I'm tired of rebuilding the same report every week." The demand for actual analysis was already there, people just didn't have time to get to it.
Databox team is shipping great updates. Probably one of the most actively launching startups on Product Hunt and consistently getting better at distribution and advocacy of the product. Many congrats to you and team, Ziga :)
Databox
@rohanrecommendsĀ Really appreciate that, Rohan - means a lot coming from someone who's watched a lot of launches. We've tried to treat each one as a chance to actually listen, not just ship and move on, so it's good to hear that's coming through.
Congrats on #2! Curious what moved the needle most for you ā was it early comment engagement, an existing audience, or something specific in positioning?
Databox
@deepanshu_garg9Ā Good question. Honestly, it was a mix, but if I had to pick one thing, it was positioning. We led with the actual problem (Monday morning report building, CSV exports) instead of the product itself, and that made the early comments a lot more specific than "cool tool." Existing audience helped get the first wave going, but the positioning is what kept people engaging past the first hour.
@zigapotocnikĀ That tracks ā makes sense that leading with the pain point creates more specific engagement than a feature pitch would. Appreciate you breaking it down, definitely applying that lens to how I'm framing Naxely's launch comments too.
Congrats on #2 Product of the Day. The launch worked because the problem is easy to understand: teams want answers from business data without waiting on a long analytics cycle. One thing Iād keep emphasizing post-launch is trust in the answer: source data, metric definitions, and the assumptions behind each AI-generated report.
Databox
@rahulbhavsarĀ Agreed, and that's a good push to keep emphasizing. That's actually the part we care most about getting right: each skill runs through Databox's metric definitions and live data, not the AI guessing at numbers. It's what makes the report something you can share, not something you have to double check first. Trust in the output matters more long term than the initial download number.
That is the right distinction. If the report is grounded in live data and your metric definitions, it becomes something a team can actually use in a meeting instead of treating it like a first draft. That trust layer is probably the long-term moat for AI analytics.
Databox
@rahulbhavsarĀ Well put, and "long-term moat" is exactly how we think about it internally too. Anyone can wrap a prompt around a metric name. Getting the definitions and the data pipeline right is the harder, less visible work, but it's the reason someone can actually put the output in front of their team.
Databox
@new_user___1802026258df93399c32311Ā Thank you!