I'm launching Clovia on Product Hunt today: Shopify checkout analytics that show exactly why checkouts get abandoned
I've been building Clovia, a Shopify checkout analytics app that shows merchants exactly why their checkouts get abandoned. Instead of just seeing a drop in revenue, you can look at each abandoned checkout session individually and see the evidence of what the shopper actually did, so you can fix the real problems instead of guessing.
Today I'm launching it on Product Hunt: https://www.producthunt.com/products/clovia?launch=clovia
I'd love any feedback from this community. And if you have a Product Hunt account, an upvote would mean a lot.
This is an interesting approach because aggregate abandonment data often tells you what happened without giving much insight into why. Being able to inspect individual sessions and see the actual behavior could make the data much more actionable.
I’d be curious about privacy and consent as well—especially what shopper-level data merchants can see and how Clovia handles sensitive checkout information.
The biggest question for me would be whether those insights actually translate into measurable improvements in checkout conversion. Would be interesting to see a few before/after case studies.
The core insight is that you're translating a lagging outcome (revenue drop) into signal metrics (session evidence). Most merchants measure the symptom (checkout abandoned) but not the cause mechanism (what the shopper saw, clicked, or felt uncertain about). By showing "evidence of what they actually did", you transform a question mark into a signal that points to a specific fix. That's the difference between a metric that tells you you're losing money and a metric that tells you why.
Have users shown that asking for confirmation at uncertain moments improves trust or outcomes, or does it mainly add friction to workflows they would rather let the agent complete?
The "individual session" framing is the right differentiation. Most checkout analytics tools give you funnel drop-off percentages, which tell you where people leave but not why. Session-level evidence gets you to the actual fix faster — is it a field validation error, a payment method that's missing, a mobile layout issue on a specific device? Good luck launching today.