by Om RathodAsk ten DTC operators why Peel Insights and Supermetrics ended up on the same shortlist, and most will shrug. They just kept showing up in the same "best ecommerce analytics tools" listicles. But they don't do the same job. Not close.
Peel Insights is a Shopify-native profit and LTV dashboard. Supermetrics is a data connector that moves numbers from ad platforms into a spreadsheet or BI tool. Comparing them head to head only makes sense once you know which decision you're actually making.
The real question isn't "which tool is better." It's: do you want a pre-built dashboard, or do you want raw data piped somewhere so someone can build one? Peel answers the first. Supermetrics hands you the second, and expects you to finish the job.
For brands selling only on Shopify, that's a manageable tradeoff either way. For brands running Amazon and Shopify together, with ad spend split across Meta, Google, and TikTok, neither tool alone covers the full picture, which is where a unified layer like Trivas starts to change the math.
This piece walks through data scope, dashboard depth, AI insight generation, setup effort, and pricing for both tools, then gets specific about where Trivas fits for teams selling across Amazon and Shopify at once.
Peel's strongest feature is also its whole identity: it's built for Shopify, and it shows.
Cohort tracking, LTV curves, repeat purchase rate, all show up out of the box with minimal setup. If your store runs on Shopify and you want to know what a customer acquired in March is worth by September, Peel gets you there without a spreadsheet.
It also bakes in profit dashboards. COGS, shipping costs, transaction fees, all rolled into contribution margin views without needing to bolt on a separate BI tool. For a lot of Shopify-only brands, that's the entire reporting stack solved in one login.
The catch is right there in the name. Peel is Shopify-centric. If you sell on Amazon too, or you're running heavy paid media across Meta, Google, and TikTok, Peel doesn't stitch that in natively. You're back to exporting data elsewhere and reconciling it by hand, which defeats a lot of the point of buying a profit dashboard in the first place.
Supermetrics isn't trying to be a dashboard. It's plumbing, and it's good plumbing.
It pulls raw data from 100+ sources, ad platforms, ecommerce stores, analytics tools, and routes it into Google Sheets, Looker Studio, or a warehouse. If you've already got an analyst who wants clean, structured data without touching an API, this is a fast way to get it.
That flexibility is genuinely useful for teams with the internal skill to do something with the raw feed. You control the model. You control the visualization. Nothing is prescribed for you.
But that's also the limitation. Supermetrics doesn't do profit modeling. It doesn't do cohort analysis. There's no AI insight layer flagging what changed and why. Someone on your team still has to design, build, and maintain the reporting on top of the pipe, and that person's time is a real cost that never shows up on Supermetrics' pricing page.
Laid out feature by feature, the gap between "connector" and "analytics product" gets obvious fast.
Data Scope
Dashboards Out of the Box
AI / Insights Layer
Forecasting
Setup and Maintenance
Best Fit
For a closer look at how Trivas stacks up against Peel specifically, including where Polar Analytics fits into that comparison, see Polar vs Peel vs Trivas.
Both Peel and Supermetrics price around data volume or connector count. That sounds simple until your ad spend climbs or your SKU catalog doubles, and the bill climbs with it in ways that are hard to predict a year out.
Supermetrics has a second, less visible cost. The connector fee is only step one. Someone still has to turn that raw feed into a dashboard people actually check, which means analyst hours or a BI tool license on top. That cost never shows up on the Supermetrics invoice, but it's real, and it's ongoing.
Trivas structures pricing around unified reporting rather than charging per connector, so adding another ad platform or sales channel doesn't multiply your bill the same way. For the specifics, check current pricing rather than taking anyone's word for it, including ours.
If you're Shopify-only, don't sell on Amazon, and just want fast LTV and profit views without building a thing yourself, Peel is the simpler starting point. No argument there.
If you've got an analyst on staff who wants full control over how the data gets modeled and visualized downstream, Supermetrics as a pipeline makes sense. You're paying for flexibility, not a finished product, and that's a fair trade for teams with the headcount to use it.
If you're selling on Amazon and Shopify at once, running paid media across multiple platforms, and you want dashboards plus AI-generated insights without hiring a data team to maintain them, that's the specific gap Trivas is built to close.
If you came into this comparison actually weighing Trivas against Peel directly, the Polar vs Peel vs Trivas breakdown goes deeper on that specific matchup.
Here's the short version. Peel wins on Shopify-first simplicity. Supermetrics wins on raw data flexibility for teams that want to build their own thing. Trivas wins for brands that need Amazon and Shopify in one warehouse with AI insights already built in, not bolted on later.
None of that debate matters as much as seeing your own numbers in the dashboard. If you want to compare Peel Insights vs Supermetrics for your own DTC stack against what Trivas shows for the same data, book a walkthrough and bring your actual Amazon and Shopify accounts.
Or skip the call and see it yourself: start a trial and connect your store directly.
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