Plenty of attribution tools will happily take an e-commerce brand’s money. Some were built for lead generation, where the conversion is a form fill and the sale happens weeks later in a CRM. Some were built for mobile apps, where the conversion is an install. Some are general web analytics with an attribution report added. All of them can technically track a Shopify purchase. The question is whether they understand what happened.
In my experience the difference shows up within the first month, in the questions the tool cannot answer. If you run an online store, these are the ones that matter.
New versus returning customers
The most important split in e-commerce marketing barely exists in lead-gen tools. A lead is a lead. An order from a first-time buyer and an order from your fiftieth repeat customer are completely different outcomes, and judging a campaign on blended revenue hides which one it is producing. A tool built for e-commerce reports new-customer ROAS and cost per new customer by channel and campaign by default. A general tool usually makes you rebuild that split yourself, if it can do it at all.
The order is the source of truth
E-commerce attribution should start from your store’s actual orders, with real revenue, discounts, shipping, tax, and refunds, and then work out which marketing touched them. Tools that start from browser events instead tend to drift from your Shopify numbers, double count, or miss orders entirely. Refunds are a good test. Ask a vendor how a refund three weeks later changes the campaign that got credit for the sale. I covered this in how do attribution tools handle refunds and returns?.
Store-specific tracking problems
Online stores have tracking problems other businesses do not. Shopify’s checkout changes have broken scripts that used to work, accelerated checkouts like Shop Pay can skip the pages a generic pixel expects to see, and orders arrive through the Shop app, subscriptions, and point of sale. An e-commerce tool is built and maintained around those paths. A general tool learns about them when your numbers stop matching. See does Shopify checkout extensibility break attribution tracking? and can attribution tools track Shop app and Shop Pay orders?.
Products, codes, and subscriptions
E-commerce decisions are often product decisions. Which products do ads sell? Which discount codes bring in new customers rather than giving margin to existing ones? Do subscription renewals get credited to the campaign that acquired the subscriber? A tool built for stores carries product, SKU, and discount code data through the attribution, so you can ask those questions directly. Lead-gen tools have no concept of a SKU. More on codes in how do attribution tools handle discount and influencer codes?.
Metrics that match how stores are run
E-commerce operators run on MER, new-customer CAC, contribution margin, and payback period. Lead-gen tools run on cost per lead and pipeline. App tools run on installs and retention curves. You can translate between them, but every translation is a spreadsheet someone has to maintain. When the tool’s default reports already use your metrics, the numbers get used rather than exported.
Pricing that fits a store
Even pricing models differ. B2B attribution tools often price on contacts or tracked leads, which means nothing for a store. E-commerce tools usually price on revenue, orders, or traffic, and which one you pick matters as you grow. Revenue-based pricing rises with every price increase and every high-AOV order, while traffic-based pricing tracks how much of your site people use. Model each against your own numbers before signing.
When a general tool is fine
To be fair, there are cases. If most of your revenue comes from wholesale or sales-assisted B2B orders, a CRM-based tool may fit better. If you are a very small store with one ad channel, GA4 and Shopify’s own reports may be all you need for now. The case for an e-commerce tool gets stronger with every channel you add and every month you spend arguing about which numbers to trust.
For a reference point, ThoughtMetric, which sponsors this blog, is built specifically for e-commerce brands, with new-customer metrics, product, SKU, and discount code dimensions, and post-purchase surveys built in, priced on monthly pageviews from $99 a month. My broader checklist is in how to choose an e-commerce attribution tool.
Questions to ask any vendor
- Does it report new-customer ROAS and cost per new customer by campaign by default?
- Does it start from your store’s orders, including refunds?
- How does it handle Shop Pay, the Shop app, subscriptions, and checkout changes?
- Can you break results out by product, SKU, and discount code?
- Is the pricing based on something that makes sense for a store?
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