Ecommerce Advertising Platforms: What They Are and How to Judge One

What is ecommerce advertising, actually?

Ecommerce advertising is paying a platform to put your product in front of a shopper at a moment that's likely to end in a sale. That's it. Everything else — the targeting options, the bid types, the creative formats — is mechanics sitting on top of that one exchange: money for attention.

The confusion isn't the concept, it's the number of places it now happens. A search ad on Google catches someone typing a query. A sponsored product ad on Amazon catches someone already scrolling a category page with a cart. A display ad served through a demand-side platform (DSP) catches someone who isn't searching for anything at all, on a site or app that has nothing to do with your product. Same goal, three completely different jobs.

Most lists of "best ecommerce advertising platforms" are really lists of search engines and social networks with an ad product bolted on. That's fine as a directory. It doesn't tell you which job each one is doing for you, or how to tell if it's working.

The five jobs these platforms actually do

Group platforms by job, not by logo, and the choice gets simpler:

• Search (Google Ads, Bing Ads): captures demand that already exists. Someone typed the query.
• Social (Meta, TikTok, Pinterest): interrupts a scroll to create demand that didn't exist a second ago.
• Marketplace sponsored ads (Amazon Sponsored Products, Walmart Connect): converts a shopper who is already in a buying mindset on that marketplace.
• Programmatic display / DSP (Amazon DSP, StackAdapt, AdRoll): reaches shoppers off the marketplace entirely — retargeting, prospecting, CTV — before or after the search happens.
• Affiliate and creator: borrows someone else's trust to close the sale.

Almost every brand needs the first three. The fourth — DSP — is where most of the confusion in this category lives, because it's the hardest to measure with a last-click report and the easiest to either overrate or dismiss for the wrong reason.

How to judge a platform: a worked example

Don't judge a platform on its headline case study. Judge it on the whole book. Across 30 advertisers reMKTR ran through Amazon DSP in July 2026, the portfolio delivered a 6.04x return on ad spend — measured across every advertiser in that set, not the best line item pulled out to make a slide.

Here's how that number gets built, and why the pieces matter more than the headline: that book ran 78.4 million impressions at a $4.00 CPM, with a blended $1.42 cost-per-click. If you've seen a $0.41 CPC quoted for this category elsewhere, that figure is online-video only — it's real, but it's one format inside a much bigger mix, not the whole book. Blended cost per acquisition came out to $5.49 across 57,137 attributed purchases, and 20.1% of those purchases came from a shopper who had never bought the brand before.

That last figure is the one worth sitting with. A ROAS number tells you the campaign made money. It doesn't tell you whether that money came from people who would have bought anyway. New-to-brand rate is a proxy for incrementality — it's not proof, but it's a lot closer to the real question than ROAS alone.

The mistake almost everyone makes with attribution

The common mistake is running DSP and sponsored ads side by side, then crediting the same purchase to both on a last-click report. Sponsored ads sit closer to the purchase, so last-click hands them the win almost every time — even on purchases the display ad actually put in motion earlier in the week. The DSP campaign looks like it's doing nothing. It gets cut. The brand loses the exact layer that was bringing in new-to-brand shoppers, and nobody notices because the report never separated the two.

We've seen this exact overcounting inside our own book before it got fixed. The fix isn't a smarter attribution model — last-click can't be patched into proving incrementality, because it was never built to answer that question. It can only tell you what touched last, not what would have happened without the ad. The fix is reconciling DSP and sponsored ads in Amazon Marketing Cloud so they stop double-claiming the same purchase, and running holdout tests or matched-control groups where you actually withhold the ad from part of the audience and measure the gap.

When the number you're looking at is bad news

Sometimes the honest read is: this isn't working. Before you cut the channel, check three things in order.

• Is the reporting double-counting? Check whether DSP and sponsored ads are claiming the same purchases in your dashboard. If they are, the real number for either channel alone is lower than what you're looking at, and you don't know which one until you separate them.
• Is the setting already fixing this? Many advertisers assume overlap exclusion or frequency capping is on by default. Check the account, not the assumption.
• Did the fix actually move the number, or just move where the credit lands? Reconciling attribution can make a channel look worse without spend actually being wasted — it's often just correcting a number that was inflated before. That's not a failure, that's the report finally telling the truth.

If after all three the channel genuinely isn't returning, the right move is to reduce it, not defend it. A platform that's wrong for your margin or your audience doesn't become right because you've already spent the budget.