NetNet Alternatives for Shopify Profit

This page exists because people search for it, and an evasive answer would be worse than a straight one. Here is where NetNet is the wrong choice.

Our hard limits

Single store. Not a plan restriction — an architectural one. If you run two Shopify stores, or Shopify plus a marketplace, we cannot consolidate them and no upgrade changes that.

Shopify only. No Amazon, no wholesale, no retail, no other platform.

Meta and Google for ad spend. Not TikTok, Snapchat, Bing, Amazon or Pinterest. If a meaningful share of your budget sits elsewhere, your profit-after-advertising figure will be incomplete unless you add that spend manually every month — which stops happening by the third month.

No attribution. No pixel, no multi-touch modelling, no incrementality testing. We measure profit after spend; we do not assign credit for causing a sale.

No custom report builder. Fixed reports plus CSV and Excel export. If you want to define your own metrics and assemble your own views, that is a real requirement we do not meet.

Single account. If several people need access to the same reporting, that is a limitation today.

Which alternative for which problem

You advertise widely → TrueProfit. Six ad platforms against our two, plus a mobile app and multi-store viewing, from $35. On the specific axis of ad coverage it is straightforwardly better than us.

You sell in several places → BeProfit for shops and channels at app pricing; Daasity or Polar Analytics if wholesale, retail or an ERP is involved and the budget supports a platform.

Retention is the question → Lifetimely or Peel. Cohorts, churn and repurchase behaviour are their centre of gravity and a shallow feature of ours.

Attribution is the question → Triple Whale or Northbeam. We do not compete here at all.

You need custom dashboards → Polar Analytics or Daasity.

You want to spend nothing → Shopify’s own profit reports cover gross profit from cost per item. For a store with modest advertising and predictable shipping, that is sometimes genuinely sufficient, and we would rather you established that before paying anyone.

Where we think we are the right choice

One Shopify store, advertising mostly on Meta and Google, where the margin is disappearing somewhere between the sale and the bank — shipping surcharges, gateway fee structures including tax on fees, refunds that need attributing back to the orders that caused them, costs that vary by weight and region.

That is a narrow description on purpose. It is the situation the product was built for, and outside it another tool on this list will serve you better.

How to test any of these fairly

The trial question is the same whichever product you are evaluating, including ours.

Reconcile one fully settled month by hand. Carrier invoices, gateway payouts, ad billing. Calculate net profit yourself, then compare each tool against your figure. Whichever lands closest is modelling your costs correctly, and the differences point at exactly which cost head is misconfigured.

Check the gateway setup against a real payout, including any tax charged on fees.

Sort orders by margin ascending. If the bottom of the list is dominated by orders you can explain — heavy, remote, deeply discounted — the model works. If it is dominated by orders with no cost of goods attached, that is a data problem no product fixes for you.

Count the clicks to the number you would check every Monday. Whichever tool puts it in front of you without configuration is the one still open in six months.

What switching actually costs

Worth knowing in either direction, because it is often underestimated.

Portable: your cost model. Supplier costs with effective dates, shipping rules by weight and region, gateway configuration verified against a real payout, custom cost heads. That work is yours and any tool will need it as input.

Not portable: anything time-accumulated. Cohort curves need months to become meaningful, so moving to or from a retention product resets that clock. Attribution history is similarly difficult to reconstruct.

The practical implication: establish the cost model early wherever you are, because it transfers. Be more careful about switching tools whose value comes from accumulated history.