Paid search is often the highest-leverage ecommerce growth channel, delivering strong conversion rates and efficient spend when structured effectively.<\/p>
Google Shopping and Amazon Ads capture high-intent demand while generating the data needed to scale it. These platforms connect search queries directly to revenue, enabling you to identify which terms drive sales and allocate budget accordingly. <\/p>
The real challenge is organizing campaigns to act on that signal.<\/p>
Why paid search works so well for ecommerce<\/h2>
Paid search performs differently from other channels because it combines two advantages: intent and data.<\/p>
- Intent<\/strong>: Google and Amazon are search-driven environments. When someone searches for a product, they\u2019re signaling exactly what they want. There\u2019s no inference required, no audience modeling, and no interrupting someone mid-scroll. You\u2019re providing the answer to a question the customer is already asking.<\/li>
- Data:<\/strong> Both Google Shopping and Amazon Ads provide keyword-level revenue data that most other advertising platforms can\u2019t. You can see which search terms generated sales, at what conversion rate, and at what cost. Amazon goes further, offering clearer and more direct revenue visibility at the product and category level.<\/li> <\/ul>
Together, these create a powerful feedback loop. Search terms tied to revenue let you shift spend toward higher-converting queries, improving ROAS over time. On Amazon, this loop extends further\u2014stronger conversion rates can improve organic rankings, lowering future acquisition costs.<\/p>
Success in search campaigns depends on building multi-funnel structures. The concept is consistent across platforms, but implementation varies by campaign types, settings, and bidding strategies.<\/p>
The architectures outlined below use wide-net, low-cost discovery campaigns to map the full search landscape, then funnel high-intent, proven converters into dedicated performance campaigns with appropriate bids. The result: stronger ROAS, improved rankings, and more scalable growth.<\/p>
Dig deeper: Ecommerce PPC: 4 takeaways that shape how campaigns perform<\/em><\/strong><\/p>
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<\/div> <\/p><\/div> <\/p> The priority sculpting method is based on Martin Roettgerding\u2018s approach, with adaptations over the years. It uses a three-layer campaign structure to route keywords into different campaigns based on performance.<\/p>
This lets you control spend on discovery keywords and maximize investment in high-performing, high-intent terms. The key is Google Shopping priority settings \u2014 \u201chigh-priority\u201d campaigns serve first at lower bids.<\/p>
Layer 1: Brand<\/strong><\/p>
- The goal is to capture branded search traffic.<\/li>
- This layer uses a Performance Max campaign and can also use standard Shopping.<\/li>
- It remains assetless to keep it focused on Shopping inventory and prevent bleed into Display and YouTube.<\/li>
- It\u2019s set with a high ROAS target, as PMax tends to go after brand traffic naturally, especially when set with a high target ROAS.<\/li>
- Alpha terms are negatived in this campaign, as they may also have high ROAS.<\/li> <\/ul>
Layer 2: Catch-all<\/strong><\/p>
- The goal is to cast a wide net, test search terms cheaply, and generate conversion data.<\/li>
- This layer uses standard Shopping with a high-priority setting to catch non-branded traffic.<\/li>
- Bids are kept low to control costs.<\/li>
- Brand terms and alpha terms are negatived using a negative list.<\/li>
- Over time, low-performing terms are also negatived once they\u2019ve been tested and failed.<\/li> <\/ul>
Layer 3: Alpha<\/strong><\/p>
- The goal is to dedicate budget to best-performing terms and generate strong ROAS.<\/li>
- This layer uses standard Shopping with a low-priority setting and high-ROAS bidding settings.<\/li>
- By negating converted terms, or alpha terms, in the catch-all campaign, those queries fall through to this campaign, where you bid aggressively on what\u2019s already working.<\/li>
- Brand terms can also be negatived if needed.<\/li> <\/ul>
Dig deeper: 6 Google Ads mistakes that hurt ecommerce campaigns<\/em><\/strong><\/p>
The key considerations in this structure include the following:<\/p>
Routing logic using negatives<\/h3>
The system relies on routing logic: Google\u2019s priority settings determine which campaign serves a query first. Negative keywords in the catch-all push proven converters into the alpha, where bids are higher and budget is protected. At the same time, non-alpha terms run through high-priority campaigns at the lowest possible bids.<\/p>
The method lives or dies on weekly search term negation. Two actions are done regularly:<\/p>
- Negate non-converting terms in the catch-all. A good rule of thumb is over 20 clicks and zero conversions, these terms are negated. We\u2019ve tested them, and removing them frees up the budget for other search terms. Note that this requires consideration before negating. If a keyword is highly relevant, you might want to let it run longer.<\/li>
- Negate converted terms (alphas) from the catch-all so they fall through to the alpha campaign. Over time, the alpha accumulates a curated list of proven terms bid on aggressively, while the catch-all keeps finding new ones cheaply. It\u2019s a compounding system.<\/li> <\/ul>
Shared budgets<\/h3>
Shared budgets are critical. Layers 2 and 3 should work on a shared budget. <\/p>
The system works only if they run together, because each query needs to be sculpted through the system. It won\u2019t work with separate budgets because if the budget on the catch-all high priority runs out, then the alpha would be the first contact, and the query would likely show on the alpha (at a higher bid), even though it\u2019s not an alpha.<\/p>
SKU separation<\/h3>
The system is designed to run across a unique set of SKUs. All three layers should target the same set of SKUs. It\u2019s recommended to start with all SKUs to begin with and then build out from there.<\/p>
Products that get buried in the main campaigns or operate at a different margin tier can be peeled off into their own mirrored catch-all\/alpha pair, ring-fencing their budget. Only do this when there\u2019s a clear reason. More campaigns mean more overhead and more fragmented data.<\/p>
Feed quality<\/h3>
It\u2019s important to optimize the feed, as Google heavily relies on titles mainly for understanding the context of the product and which keywords to serve it.<\/p>
<\/p>
Get the newsletter search marketers rely on.<\/p> <\/p><\/div> <\/p><\/div> <\/div>
<\/p>
Amazon Ads: The multi-tier campaign architecture<\/h2>
Amazon\u2019s campaign structure is more advanced than Google Ads and offers several advantages.<\/p>
Amazon typically delivers higher conversion rates and more conversion data. Ad spend also drives both conversion rates and rankings, with a clear, measurable link between ad spend and organic ranking.<\/p>
Ads drive traffic, traffic drives conversions, and conversion rate drives organic rank. That makes Amazon Ads an investment in organic search.<\/p>
Google Ads campaigns run across the whole catalog. On Amazon, you build campaigns at the SKU level, typically one SKU per campaign.<\/p>
The structure uses three campaign tiers: research, ranking, and performance. Each has a distinct goal and is managed by adjusting advertising cost of sale (ACOS) targets to reflect different profitability goals.<\/p>
Tier 1: Research\u00a0<\/strong><\/p>
- Campaigns use broad and phrase match keywords, along with automatic targeting.<\/li>
- The goal is to cast a wide net and generate keyword ideas and variations.<\/li>
- ACOS tolerance is relatively high, since the goal is data, not profit.<\/li> <\/ul>
Tier 2: Performance<\/strong><\/p>
- Campaigns use exact match keyword targeting.<\/li>
- The goal is profit, with a competitive ACOS target below break-even.<\/li>
- Move proven converters from the research tier into exact match campaigns. Run your best keywords at efficient bids to maximize returns on what\u2019s already working. This mirrors the alpha campaign in Google Ads.<\/li> <\/ul>
Tier 3: Ranking or exposure<\/strong><\/p>
- Use single-keyword campaigns (SKCs) with exact match\u2014one keyword per campaign.<\/li>
- The goal is usually ranking, though it can shift over time.<\/li>
- For ranking, set aggressive bids with high ACOS tolerance (often 50%+). Push volume through high-value keywords to drive top organic positions. Once you reach positions 1\u20133 organically, pause those keywords.<\/li>
- Ranking campaigns are debated. If you\u2019re already ranking, there\u2019s no need to pay for visibility you get for free.<\/li>
- This layer doesn\u2019t exist in Google Ads, where ad spend doesn\u2019t influence rankings.<\/li> <\/ul>
Dig deeper: Why your Amazon Ads aren\u2019t delivering: 6 critical issues to fix<\/em><\/strong><\/p>
The key considerations in this structure include:<\/p>
Bidding to an ACOS lever<\/h3>
With Amazon Ads, we bid toward an ACOS target. ACOS is the advertising spend as a percentage of revenue. Because Amazon data is so clean and conversion rates are high, we can calculate our bids to drive a certain ACOS.<\/p>
The ACOS-based bidding formula:\u00a0<\/p>
- Target bid = (Revenue per click) x Target ACOS<\/li> <\/ul>
Implementing ACOS bidding can be automated using software like Scale Insights. Different campaign tiers can be assigned different ACOS targets, and CPCs can be adjusted daily by the software.<\/p>
Keyword routing<\/h3>
Similar to Google Ads, keywords are funneled through from research campaigns into performance or alpha campaigns. This can be done manually or automatically with Scale Insights using an import rule.\u00a0<\/p>
The concept is very similar in that keywords that shine get imported down the funnel, while non-performing keywords are phased out through testing.<\/p>
The conversion rate signal<\/h3>
If a product\u2019s conversion rate is below the market average on a given keyword, more spend will not likely improve its rank. Amazon usually surfaces the better-converting product.\u00a0<\/p>
The correct response is to fix the underlying issue: price, listing quality, imagery, or the product itself. Most advertisers skip this step and keep spending into a hole.<\/p>
The ranking cannibalization rule<\/h3>
There are two strong views on ranking and cannibalization. Some argue that once your product ranks highly for a keyword on Amazon, you should reduce or stop ad spend. If you\u2019re ranking organically, you can save on ads.<\/p>
On the other hand, if a keyword performs well with strong ROAS, having two listings can outperform one. It increases your chances of a click. Ads also typically appear above organic listings, giving you higher placement.<\/p>
Whichever view you take, the three-tier method lets you drive rankings through SKCs, then reduce or stop ad spend once you rank, if you choose.<\/p>
The underlying logic for advanced campaign setup is the same across Google Shopping and Amazon Ads, with key differences beyond the core structure.<\/p>
Google Shopping (Priority sculpting)<\/strong><\/td> Amazon Ads (Multi-tier architecture)<\/strong><\/td> <\/tr> Similarities<\/strong><\/td> \u2013 Route queries to campaigns via priority and negatives.
\u2013 Discover converting terms in a catch-all at a low cost.
\u2013 Graduate proven terms to alpha with high tROAS.
\u2013 Regular search term reviews, negatives, and alphas.<\/td>\u2013 Route keywords across research \u2192 ranking \u2192 performance.
\u2013 Discover new keywords in broad, phrase, and auto campaigns.
\u2013 Graduate proven terms to exact match for profitability.
\u2013 Regular search term reviews, negatives, and imports to lower funnel.<\/td> <\/tr>Differences<\/strong><\/strong><\/td> \u2013 Run across the whole feed, separate high-margin products for ring-fenced budgets.
\u2013 ROAS-based bidding.
\u2013 Product feed determines search term targeting, and the advertiser is unable to select.<\/td>\u2013 Campaigns built at the SKU level rather than across the whole catalog.
\u2013 ACOS-based bidding.
\u2013 Search terms selected by advertiser.
\u2013 Ads drive rankings, and you can save budget by monitoring organic rankings.<\/td> <\/tr> <\/tbody> <\/table> <\/figure>Dig deeper: 5 reasons Amazon Ads is better than Google Ads for ecommerce<\/em><\/strong><\/p>
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Which platform is right for your ecommerce strategy<\/h2>
Like all good answers, it depends heavily on your business and your goals. Both have advantages and disadvantages. We can say that:<\/p>
- Amazon Ads often perform better, delivering higher conversion rates and faster ranking and sales when intent is strong.<\/li>
- Google Ads is better for long-term brand building. It offers broader reach, potentially lower costs, and drives traffic to your own website, where you retain customer data.<\/li> <\/ul>
The ideal is to run these together. Many brands may launch on Amazon and grow over to their own platforms and utilize Google Ads.<\/p>
Paid search for ecommerce is probably the most effective advertising avenue you can explore. Both platforms offer significant opportunities when implemented properly. Each platform has pros and cons, and I would recommend further exploring the details in these campaign structures and deciding on the right implementation for your business.<\/p> <\/div>
Contributing authors are invited to create content for Search Engine Land and are chosen for their expertise and contribution to the search community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. Search Engine Land is owned by Semrush. Contributor was not asked to make any direct or indirect mentions of Semrush. The opinions they express are their own.<\/em> <\/p>
Opinion#Building #highROAS #ecommerce #search #campaigns #Google #Shopping #Amazon #Ads1775513968<\/p> ","protected":false},"excerpt":{"rendered":"
Paid search is often the highest-leverage ecommerce growth channel, delivering strong conversion rates and efficient spend when structured effectively. Google Shopping and Amazon Ads capture high-intent demand while generating the data needed to scale it. These platforms connect search queries directly to revenue, enabling you to identify which terms drive sales and allocate budget accordingly. […]<\/p>\n","protected":false},"author":1,"featured_media":5996,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[152,13650,250,702,4707,75,22427,155,95,1638],"class_list":["post-5995","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-careers","tag-ads","tag-amazon","tag-building","tag-campaigns","tag-ecommerce","tag-google","tag-highroas","tag-opinion","tag-search","tag-shopping"],"acf":[],"_links":{"self":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/5995","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5995"}],"version-history":[{"count":0,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/5995\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/media\/5996"}],"wp:attachment":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5995"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5995"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5995"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
- Target bid = (Revenue per click) x Target ACOS<\/li> <\/ul>
- Data:<\/strong> Both Google Shopping and Amazon Ads provide keyword-level revenue data that most other advertising platforms can\u2019t. You can see which search terms generated sales, at what conversion rate, and at what cost. Amazon goes further, offering clearer and more direct revenue visibility at the product and category level.<\/li> <\/ul>