Launching today
LinksRF
Branded links that separate humans from bots and previews
18 followers
Branded links that separate humans from bots and previews
18 followers
Create branded campaign links like go.yourbrand.com/offer and understand who actually visited. LinksRF separates likely humans from bots, social previews, automated traffic, and raw requests. Build short links, boards, bio pages, and funnels; manage custom domains and teams; and review campaign analytics from one workspace. Start free, no card required.
honestly the bot filtering is what caught my eye, but it would be super useful if you could export those analytics as a csv or push them to google sheets. right now i can see the split in the dashboard, but i need to combine it with my own ad spend data to figure out what is actually working. a simple zapier hook or a scheduled email report would save me a ton of manual copy pasting.
Congrats on the launch, Abhishek. The thing I like most is how honest the framing is ā "likely human" instead of promising perfect certainty. Most link tools would have oversold that. On the content side we hit the same mess in analytics: preview fetches and bots inflate the numbers and you can't really tell what landed. Curious how you handle a messaging app that fetches the same link a few times for a preview ā does that get filtered, or counted as separate opens?
@saied_alimoradiĀ
Thanks, Saied! Really appreciate that, that was a deliberate choice. We don't think traffic quality is binary, so we'd rather communicate uncertainty than overstate confidence. For messaging apps specifically, preview fetches are treated differently from genuine visits whenever we can distinguish them. We look at a combination of request patterns, headers, interaction signals and subsequent telemetry rather than simply counting every HTTP request as an open. For example, if WhatsApp or another messaging platform fetches the same link multiple times to generate previews, those requests are evaluated as preview traffic and kept separate from likely human visits where there's evidence of an actual browser session and user interaction. It's not perfect, every platform behaves a little differently but the goal is to give users a much more truthful picture than a raw click count. That's exactly why we expose the underlying evidence instead of treating the classification as a black box. Thanks for the great question!