Stop overpaying for Shopify analytics

We pull COGS directly from your Shopify store. We're also working on a feature that lets you override COGS between specific dates, so you can adjust COGS in Shopify without affecting your historical data.

You can also define COGS for deleted products and variants, ensuring your historical data remains accurate.

Additionally, you can set a fallback COGS percentage to apply when you haven't input a specific COGS.

You can input an average shipping cost per order, or input your full cost matrix from your carrier by defining the cost per weight interval. Kleio then calculates the actual shipping cost based on the weights of each order.

You can also integrate directly with ShipHero to pull your shipping costs automatically.

Kleio has the most flexible variable costs in the game. You can define variable costs per order, per line item, per refund, per refunded line item, as a percentage of sales, as a percentage of COGS, by order weight (in intervals), or by line item quantity (in intervals).

You can also set start and end dates for each variable cost, so you're not locked into the same cost forever.

Variable costs can also be applied to specific countries, products, shipping methods, and more.

99% accurate. Shopify doesn't publish enough data in their API for us to hit 100%, but it's very, very close.

Yes! You're always more than welcome to reach out to me directly at hello@getkleio.com.

Because attribution pretends to be objective — but isn't.

Every attribution model is subjective. It's an opinion baked into code by the developer who built it. They decide what to allocate where. Change those rules, and the story changes. That's not truth — that's storytelling.

We also don't believe in separating optimization from reporting. Your ad platforms optimize using their own data and models, regardless of what an external attribution tool says. So you end up reporting on one version of reality… while optimization happens in another.

Meta is extremely good at what they do. They have more data on this than anyone else on the planet — and that's exactly why their targeting and optimization algorithms perform so well for advertisers. There's no reason to believe a third party attribution tool, with less data and no idea about how Meta's algorithms work, can consistently provide better attribution than the platform itself.

There's also an incentive problem. Attribution software has to justify its price, and the easiest way to do that is to look meaningfully different from the numbers you get for free inside ad platforms. We're not saying anyone is acting in bad faith — but as the saying goes: show me the incentive, and I'll show you the outcome.

We've seen this too many times to ignore: ads get turned off completely, yet attribution tools keep assigning them hundreds of conversions more than a month later. That doesn't sound right. Here's an example of that.

So, instead of building attribution just so we can charge hundreds of dollars a month, we focus on what actually moves the needle, and give it to you at a fair (cheap) price.