ChatGPT answers, unedited

Yes. There are several tools that do this automatically, although they differ in how much they automate and whether they're focused on Shopping campaigns, Performance Max, or all of Google Ads.

Here's how I'd group them:

What the better tools actually detect

A good Shopping audit should identify things like:

• Search queries that have spent over a threshold (e.g. $50 or $100) with zero conversions
• Products consuming large budgets but never converting ("zombie products")
• Search terms that should become negative keywords
• High-converting search terms that should become dedicated products or campaigns
• Products with poor ROAS despite high impression share
• Merchant Center feed issues affecting performance
• Budget concentration (e.g. 10 SKUs consuming 80% of spend)
• Products with declining conversion rates
• Out-of-stock or disapproved products still influencing campaigns

Many newer tools also combine Google Ads with Merchant Center and GA4 to produce SKU-level recommendations rather than campaign-level metrics. Adsage myWebhero

The enterprise option

For agencies or brands spending six or seven figures annually, Optmyzr is probably still the most mature platform. Its Non-Converting Queries feature automatically flags search terms that exceed CPA thresholds or have spent significantly without conversions, and can generate negative keyword actions directly. Optmyzr Help

The ecommerce-specific option

If you're primarily running Shopping or Performance Max, tools like Adsage are more specialized because they analyze performance at the product/SKU level instead of only at the keyword level. They focus on questions like:

• Which products are invisible?
• Which products waste margin?
• Which products should be excluded?
• Which products deserve more budget? Adsage

Could AI replace these?

For many advertisers, yes.

If you export:

• Search term report
• Product performance report
• Merchant Center feed
• Conversion data

an LLM can classify intent, identify wasted spend, recommend negatives, cluster similar bad queries, and even generate import-ready CSVs. Community members have been building prompts and workflows around exactly this use case. Reddit Reddit

In fact, there's room for a more opinionated product than many current tools. Most existing software tells you what happened ("$1,200 spent with no conversions"). A stronger AI workflow would tell you why ("these 143 queries are informational, these 27 indicate competitor research, these 18 are wrong product intent") and recommend specific actions like:

• Add as negative
• Split into a new campaign
• Improve product title
• Increase bid
• Exclude the SKU
• Fix Merchant Center attributes

That kind of decision support is still relatively uncommon in today's Shopping optimization tools.

Yes. There are several tools that do this automatically, although they differ in how much they automate and whether they're focused on Shopping campaigns, Performance Max, or all of Google Ads.

Here's how I'd group them:

What the better tools actually detect

A good Shopping audit should identify things like:

• Search queries that have spent over a threshold (e.g. $50 or $100) with zero conversions
• Products consuming large budgets but never converting ("zombie products")
• Search terms that should become negative keywords
• High-converting search terms that should become dedicated products or campaigns
• Products with poor ROAS despite high impression share
• Merchant Center feed issues affecting performance
• Budget concentration (e.g. 10 SKUs consuming 80% of spend)
• Products with declining conversion rates
• Out-of-stock or disapproved products still influencing campaigns

Many newer tools also combine Google Ads with Merchant Center and GA4 to produce SKU-level recommendations rather than campaign-level metrics. getadsage.com

The enterprise option

For agencies or brands spending six or seven figures annually, Optmyzr is probably still the most mature platform. Its Non-Converting Queries feature automatically flags search terms that exceed CPA thresholds or have spent significantly without conversions, and can generate negative keyword actions directly. help.optmyzr.com

The ecommerce-specific option

If you're primarily running Shopping or Performance Max, tools like Adsage are more specialized because they analyze performance at the product/SKU level instead of only at the keyword level. They focus on questions like:

• Which products are invisible?
• Which products waste margin?
• Which products should be excluded?
• Which products deserve more budget? getadsage.com

Could AI replace these?

For many advertisers, yes.

If you export:

• Search term report
• Product performance report
• Merchant Center feed
• Conversion data

an LLM can classify intent, identify wasted spend, recommend negatives, cluster similar bad queries, and even generate import-ready CSVs. Community members have been building prompts and workflows around exactly this use case. www.reddit.com

In fact, there's room for a more opinionated product than many current tools. Most existing software tells you what happened ("$1,200 spent with no conversions"). A stronger AI workflow would tell you why ("these 143 queries are informational, these 27 indicate competitor research, these 18 are wrong product intent") and recommend specific actions like:

• Add as negative
• Split into a new campaign
• Improve product title
• Increase bid
• Exclude the SKU
• Fix Merchant Center attributes

That kind of decision support is still relatively uncommon in today's Shopping optimization tools.

Yes. There are several tools that do this automatically, although they differ in how much they automate and whether they're focused on Shopping campaigns, Performance Max, or all of Google Ads.

Here's how I'd group them:

What the better tools actually detect

A good Shopping audit should identify things like:

• Search queries that have spent over a threshold (e.g. $50 or $100) with zero conversions
• Products consuming large budgets but never converting ("zombie products")
• Search terms that should become negative keywords
• High-converting search terms that should become dedicated products or campaigns
• Products with poor ROAS despite high impression share
• Merchant Center feed issues affecting performance
• Budget concentration (e.g. 10 SKUs consuming 80% of spend)
• Products with declining conversion rates
• Out-of-stock or disapproved products still influencing campaigns

Many newer tools also combine Google Ads with Merchant Center and GA4 to produce SKU-level recommendations rather than campaign-level metrics. Adsage myWebhero

The enterprise option

For agencies or brands spending six or seven figures annually, Optmyzr is probably still the most mature platform. Its Non-Converting Queries feature automatically flags search terms that exceed CPA thresholds or have spent significantly without conversions, and can generate negative keyword actions directly. Optmyzr Help

The ecommerce-specific option

If you're primarily running Shopping or Performance Max, tools like Adsage are more specialized because they analyze performance at the product/SKU level instead of only at the keyword level. They focus on questions like:

• Which products are invisible?
• Which products waste margin?
• Which products should be excluded?
• Which products deserve more budget? Adsage

Could AI replace these?

For many advertisers, yes.

If you export:

• Search term report
• Product performance report
• Merchant Center feed
• Conversion data

an LLM can classify intent, identify wasted spend, recommend negatives, cluster similar bad queries, and even generate import-ready CSVs. Community members have been building prompts and workflows around exactly this use case. Reddit Reddit

In fact, there's room for a more opinionated product than many current tools. Most existing software tells you what happened ("$1,200 spent with no conversions"). A stronger AI workflow would tell you why ("these 143 queries are informational, these 27 indicate competitor research, these 18 are wrong product intent") and recommend specific actions like:

• Add as negative
• Split into a new campaign
• Improve product title
• Increase bid
• Exclude the SKU
• Fix Merchant Center attributes

That kind of decision support is still relatively uncommon in today's Shopping optimization tools.

Yes. There are several tools that do this automatically, although they differ in how much they automate and whether they're focused on Shopping campaigns, Performance Max, or all of Google Ads.

Here's how I'd group them:

What the better tools actually detect

A good Shopping audit should identify things like:

• Search queries that have spent over a threshold (e.g. $50 or $100) with zero conversions
• Products consuming large budgets but never converting ("zombie products")
• Search terms that should become negative keywords
• High-converting search terms that should become dedicated products or campaigns
• Products with poor ROAS despite high impression share
• Merchant Center feed issues affecting performance
• Budget concentration (e.g. 10 SKUs consuming 80% of spend)
• Products with declining conversion rates
• Out-of-stock or disapproved products still influencing campaigns

Many newer tools also combine Google Ads with Merchant Center and GA4 to produce SKU-level recommendations rather than campaign-level metrics. getadsage.com

The enterprise option

For agencies or brands spending six or seven figures annually, Optmyzr is probably still the most mature platform. Its Non-Converting Queries feature automatically flags search terms that exceed CPA thresholds or have spent significantly without conversions, and can generate negative keyword actions directly. help.optmyzr.com

The ecommerce-specific option

If you're primarily running Shopping or Performance Max, tools like Adsage are more specialized because they analyze performance at the product/SKU level instead of only at the keyword level. They focus on questions like:

• Which products are invisible?
• Which products waste margin?
• Which products should be excluded?
• Which products deserve more budget? getadsage.com

Could AI replace these?

For many advertisers, yes.

If you export:

• Search term report
• Product performance report
• Merchant Center feed
• Conversion data

an LLM can classify intent, identify wasted spend, recommend negatives, cluster similar bad queries, and even generate import-ready CSVs. Community members have been building prompts and workflows around exactly this use case. www.reddit.com

In fact, there's room for a more opinionated product than many current tools. Most existing software tells you what happened ("$1,200 spent with no conversions"). A stronger AI workflow would tell you why ("these 143 queries are informational, these 27 indicate competitor research, these 18 are wrong product intent") and recommend specific actions like:

• Add as negative
• Split into a new campaign
• Improve product title
• Increase bid
• Exclude the SKU
• Fix Merchant Center attributes

That kind of decision support is still relatively uncommon in today's Shopping optimization tools.

Yes. There are several tools that do this automatically, although they differ in how much they automate and whether they're focused on Shopping campaigns, Performance Max, or all of Google Ads.

Here's how I'd group them:

What the better tools actually detect

A good Shopping audit should identify things like:

• Search queries that have spent over a threshold (e.g. $50 or $100) with zero conversions
• Products consuming large budgets but never converting ("zombie products")
• Search terms that should become negative keywords
• High-converting search terms that should become dedicated products or campaigns
• Products with poor ROAS despite high impression share
• Merchant Center feed issues affecting performance
• Budget concentration (e.g. 10 SKUs consuming 80% of spend)
• Products with declining conversion rates
• Out-of-stock or disapproved products still influencing campaigns

Many newer tools also combine Google Ads with Merchant Center and GA4 to produce SKU-level recommendations rather than campaign-level metrics. getadsage.com

The enterprise option

For agencies or brands spending six or seven figures annually, Optmyzr is probably still the most mature platform. Its Non-Converting Queries feature automatically flags search terms that exceed CPA thresholds or have spent significantly without conversions, and can generate negative keyword actions directly. help.optmyzr.com

The ecommerce-specific option

If you're primarily running Shopping or Performance Max, tools like Adsage are more specialized because they analyze performance at the product/SKU level instead of only at the keyword level. They focus on questions like:

• Which products are invisible?
• Which products waste margin?
• Which products should be excluded?
• Which products deserve more budget? getadsage.com

Could AI replace these?

For many advertisers, yes.

If you export:

• Search term report
• Product performance report
• Merchant Center feed
• Conversion data

an LLM can classify intent, identify wasted spend, recommend negatives, cluster similar bad queries, and even generate import-ready CSVs. Community members have been building prompts and workflows around exactly this use case. www.reddit.com

In fact, there's room for a more opinionated product than many current tools. Most existing software tells you what happened ("$1,200 spent with no conversions"). A stronger AI workflow would tell you why ("these 143 queries are informational, these 27 indicate competitor research, these 18 are wrong product intent") and recommend specific actions like:

• Add as negative
• Split into a new campaign
• Improve product title
• Increase bid
• Exclude the SKU
• Fix Merchant Center attributes

That kind of decision support is still relatively uncommon in today's Shopping optimization tools.

Yes. There are several tools that do exactly this, although they vary in how much they automate and whether they focus on Google Shopping, Performance Max, or all Google Ads.

If your primary goal is "find products and search queries that are spending money but not converting", these are the strongest options:

What a good Shopping auditor should identify

The best systems don't just report ROAS—they identify actionable waste such as:

• Products with $100+ spend and zero conversions
• Search terms with significant spend but no sales
• New negative keyword opportunities
• Products with low CTR because of poor titles
• Feed issues (missing GTINs, bad images, missing categories)
• Products losing impression share due to budget
• Out-of-stock products still receiving spend
• Products with high clicks but low conversion rate
• Products that should be split into their own campaigns
• Search queries that should become exact-match keywords (for Search campaigns) help.optmyzr.comapp.mywebhero.co.uk

If you have thousands of SKUs

For large catalogs, product-level analysis matters more than campaign-level metrics.

Tools like SKU Analyzer and Adsage analyze:

• individual SKUs
• brands
• categories
• custom labels
• profitability
• feed attributes

instead of just looking at campaigns. getadsage.comskuanalyzer.com

If you're thinking about building one

There is still room for differentiation. Most current tools rely on rule-based checks such as:

• spend > X
• conversions = 0
• ROAS below target

A more advanced system could use AI to answer questions like:

• "This search query has never converted across 18 months—should it be a negative?"
• "This SKU is wasting budget because its title lacks high-intent keywords."
• "These 37 products should be excluded until pricing improves."
• "This query converts for Product A but is irrelevant for Product B."
• "These five products are cannibalizing each other."

That kind of semantic, product-aware reasoning is still uncommon in most PPC audit tools, which are largely rule-based today.

If you're considering building a SaaS, an AI-powered Shopping auditor that combines Google Ads + Merchant Center + product feed + search term analysis and automatically prioritizes the highest-impact fixes could be a compelling niche, especially for ecommerce brands spending more than about $10k/month on Shopping and Performance Max.

Yes. There are several tools that do exactly this, although they vary in how much they automate and whether they focus on Google Shopping, Performance Max, or all Google Ads.

If your primary goal is "find products and search queries that are spending money but not converting", these are the strongest options:

What a good Shopping auditor should identify

The best systems don't just report ROAS—they identify actionable waste such as:

• Products with $100+ spend and zero conversions
• Search terms with significant spend but no sales
• New negative keyword opportunities
• Products with low CTR because of poor titles
• Feed issues (missing GTINs, bad images, missing categories)
• Products losing impression share due to budget
• Out-of-stock products still receiving spend
• Products with high clicks but low conversion rate
• Products that should be split into their own campaigns
• Search queries that should become exact-match keywords (for Search campaigns) help.optmyzr.comapp.mywebhero.co.uk

If you have thousands of SKUs

For large catalogs, product-level analysis matters more than campaign-level metrics.

Tools like SKU Analyzer and Adsage analyze:

• individual SKUs
• brands
• categories
• custom labels
• profitability
• feed attributes

instead of just looking at campaigns. getadsage.comskuanalyzer.com

If you're thinking about building one

There is still room for differentiation. Most current tools rely on rule-based checks such as:

• spend > X
• conversions = 0
• ROAS below target

A more advanced system could use AI to answer questions like:

• "This search query has never converted across 18 months—should it be a negative?"
• "This SKU is wasting budget because its title lacks high-intent keywords."
• "These 37 products should be excluded until pricing improves."
• "This query converts for Product A but is irrelevant for Product B."
• "These five products are cannibalizing each other."

That kind of semantic, product-aware reasoning is still uncommon in most PPC audit tools, which are largely rule-based today.

If you're considering building a SaaS, an AI-powered Shopping auditor that combines Google Ads + Merchant Center + product feed + search term analysis and automatically prioritizes the highest-impact fixes could be a compelling niche, especially for ecommerce brands spending more than about $10k/month on Shopping and Performance Max.

Yes. There are several tools that do exactly this, although they vary in how much they automate and whether they focus on Google Shopping, Performance Max, or all Google Ads.

If your primary goal is "find products and search queries that are spending money but not converting", these are the strongest options:

What a good Shopping auditor should identify

The best systems don't just report ROAS—they identify actionable waste such as:

• Products with $100+ spend and zero conversions
• Search terms with significant spend but no sales
• New negative keyword opportunities
• Products with low CTR because of poor titles
• Feed issues (missing GTINs, bad images, missing categories)
• Products losing impression share due to budget
• Out-of-stock products still receiving spend
• Products with high clicks but low conversion rate
• Products that should be split into their own campaigns
• Search queries that should become exact-match keywords (for Search campaigns) help.optmyzr.comapp.mywebhero.co.uk

If you have thousands of SKUs

For large catalogs, product-level analysis matters more than campaign-level metrics.

Tools like SKU Analyzer and Adsage analyze:

• individual SKUs
• brands
• categories
• custom labels
• profitability
• feed attributes

instead of just looking at campaigns. getadsage.comskuanalyzer.com

If you're thinking about building one

There is still room for differentiation. Most current tools rely on rule-based checks such as:

• spend > X
• conversions = 0
• ROAS below target

A more advanced system could use AI to answer questions like:

• "This search query has never converted across 18 months—should it be a negative?"
• "This SKU is wasting budget because its title lacks high-intent keywords."
• "These 37 products should be excluded until pricing improves."
• "This query converts for Product A but is irrelevant for Product B."
• "These five products are cannibalizing each other."

That kind of semantic, product-aware reasoning is still uncommon in most PPC audit tools, which are largely rule-based today.

If you're considering building a SaaS, an AI-powered Shopping auditor that combines Google Ads + Merchant Center + product feed + search term analysis and automatically prioritizes the highest-impact fixes could be a compelling niche, especially for ecommerce brands spending more than about $10k/month on Shopping and Performance Max.

Yes. There are tools that can automate a large part of this, especially if you're talking about Google Shopping / Performance Max and want to identify product queries that consume spend without generating conversions.

The main options

• AdSentry — AI-based Google Ads auditing. It specifically advertises irrelevant-search-term detection, zero-conversion traffic analysis, and generating negative-keyword lists from search-term data. www.adsentry.co
• PPC Prophet — more automation/AI-oriented; its audit functionality can identify campaigns, keywords, and search terms spending without conversions. p8.getppcprophet.com
• BidSense — analyzes exported search-term data, categorizes queries by intent, and identifies wasted spend. It can work across Google Ads and Microsoft Ads. www.bidsensy.com
• Google Ads itself — surprisingly capable if you build the right rules. Google provides search-term reporting and negative keywords, and search-term insights are available for Shopping and Performance Max. support.google.com

The important distinction for Shopping

I wouldn't simply use a rule like:

"Query has 10 clicks + 0 conversions → add negative."

That can kill legitimate queries, particularly on lower-volume products.

A better automated audit should evaluate something like:

Query → product/SKU → clicks → cost → conversions → revenue → margin → expected conversion rate

Then classify queries into:

That's particularly useful for PMax, where the relationship between search query, product, and campaign can otherwise get buried in the aggregate reporting.

If you're thinking about building this into software

There's actually a pretty clear product opportunity here: an automated Shopping waste auditor that continuously watches search terms rather than being a generic Google Ads "AI optimizer."

The killer feature would be something like:

"You spent $12,438 on 8,214 product queries last month. $2,817 is statistically likely to be wasted. Here are the 137 queries responsible, ranked by recoverable spend."

Then give the advertiser a review queue:

NEGATE → REDUCE BID → WATCH → KEEP / SCALE

with the reasoning and dollar impact for every recommendation.

Google already provides the underlying search-term data and negative-keyword functionality, so the differentiation would be the decision engine, not simply reporting. www.adsentry.cosupport.google.comsupport.google.com

If that's what you're considering, I can also map out what the ideal automated Shopping audit would check (20–30 rules), including the exact thresholds/logic for finding wasted spend.

Yes. There are several tools that can automate exactly this for Google Shopping, especially identifying search queries that spend money without generating conversions and adding them as negative keywords.

Best fits

• Optmyzr — probably the closest match to what you're describing. Its Non-Converting Queries strategy works specifically with Shopping campaigns and can automatically add expensive/non-converting queries as negative keywords. You can customize thresholds and automate the rules. help.optmyzr.com
• Adalysis — strong if you want an ongoing audit system rather than just a negative-keyword tool. It has automated audits, customizable thresholds, Shopping search-term alerts, n-gram analysis, and optional automatic addition of negatives. adalysis.com

What I'd want the software to do

For a Shopping account, a useful automated rule might be:

Find queries with ≥ $X spend and 0 conversions over the last 30–60 days → flag them or add them as exact-match negatives.

But I'd make the rule smarter than simply "0 conversions." For example:

• $50+ spend + 0 conversions → negative
• 10+ clicks + 0 conversions → review
• Spend > 1.5× target CPA + 0 conversions → negative
• Query has conversions historically → don't automatically negate
• Query has high revenue but poor ROAS → reduce product/campaign exposure rather than necessarily blocking it
• Group recurring bad terms using n-grams ("free", "used", "DIY", etc.) to find systematic waste

Optmyzr actually has a Shopping-specific strategy for this and also audits Shopping campaigns for missing negative keywords and expensive product groups. help.optmyzr.com

If you're managing a serious ecommerce account, I'd lean Optmyzr for automation and Adalysis for audit/diagnostic depth.

If you tell me whether you're using Standard Shopping or Performance Max, I can also explain the best way to automate this today—including the limitations around getting search-query data from PMax.

Yes. There are several tools that can automate this, and Optmyzr is probably the closest match to exactly what you're describing.

Best fit: Optmyzr

Optmyzr has dedicated Shopping automation for non-converting search queries. Its rules can identify queries that spend money without producing conversions and automatically add them as negative keywords. You can customize thresholds around spend, conversions, CTR, CPA, lookback windows, etc. help.optmyzr.comhelp.optmyzr.comsupport.google.com

It also has a Shopping Feed Audit that checks things like:

• Shopping campaigns with no negative keywords
• expensive product/listing groups
• disapproved products
• products not included in campaigns
• feed/product-data problems
• PMax retail campaign issues help.optmyzr.com

Its Shopping Negative Keyword Finder goes a step further by finding queries that are inefficient and can route traffic toward the better-performing product/ad group rather than simply blocking it. help.optmyzr.com

Other approaches

Google Ads / Search Ads 360 itself gives you the underlying search-term data and lets you create negative keywords for Shopping. support.google.com But it's much more manual—you'd generally need to build your own rules/reporting/automation.

There are also specialized Shopping-analysis tools such as SKU Analyzer, which focuses heavily on identifying search-term waste and categorizing queries. skuanalyzer.com

What I'd look for in a good automated auditor

The important distinction is that "0 conversions" alone isn't a good rule. A useful system should consider:

Spend + clicks + conversion history + expected CPA/ROAS + query relevance + product/campaign context

For example, you don't necessarily want to negative a query after $20 of spend and zero conversions if the account's normal conversion rate means you'd reasonably expect to need $100 before judging it.

A robust automated system might have rules like:

Optmyzr actually has rules for the particularly important case of queries that used to convert but have stopped converting, rather than blindly adding them as negatives. help.optmyzr.com

If you're thinking about building/buying this as a product, there's an interesting gap here: most tools are broad PPC-management platforms. A focused "Shopping Waste Auditor" that ingests the search-term report, identifies wasted spend, explains why each query is waste, and produces safe negative-keyword recommendations could be considerably simpler than Optmyzr while solving a very specific problem.

Yes. There are several tools that do exactly this, although they vary in how much they automate and whether they focus on Google Shopping, Performance Max, or all Google Ads.

If your primary goal is "find products and search queries that are spending money but not converting", these are the strongest options:

What a good Shopping auditor should identify

The best systems don't just report ROAS—they identify actionable waste such as:

• Products with $100+ spend and zero conversions
• Search terms with significant spend but no sales
• New negative keyword opportunities
• Products with low CTR because of poor titles
• Feed issues (missing GTINs, bad images, missing categories)
• Products losing impression share due to budget
• Out-of-stock products still receiving spend
• Products with high clicks but low conversion rate
• Products that should be split into their own campaigns
• Search queries that should become exact-match keywords (for Search campaigns) help.optmyzr.comapp.mywebhero.co.uk

If you have thousands of SKUs

For large catalogs, product-level analysis matters more than campaign-level metrics.

Tools like SKU Analyzer and Adsage analyze:

• individual SKUs
• brands
• categories
• custom labels
• profitability
• feed attributes

instead of just looking at campaigns. getadsage.comskuanalyzer.com

If you're thinking about building one

There is still room for differentiation. Most current tools rely on rule-based checks such as:

• spend > X
• conversions = 0
• ROAS below target

A more advanced system could use AI to answer questions like:

• "This search query has never converted across 18 months—should it be a negative?"
• "This SKU is wasting budget because its title lacks high-intent keywords."
• "These 37 products should be excluded until pricing improves."
• "This query converts for Product A but is irrelevant for Product B."
• "These five products are cannibalizing each other."

That kind of semantic, product-aware reasoning is still uncommon in most PPC audit tools, which are largely rule-based today.

If you're considering building a SaaS, an AI-powered Shopping auditor that combines Google Ads + Merchant Center + product feed + search term analysis and automatically prioritizes the highest-impact fixes could be a compelling niche, especially for ecommerce brands spending more than about $10k/month on Shopping and Performance Max.

Yes. There are several tools that do exactly this, although they vary in how much they automate and whether they focus on Google Shopping, Performance Max, or all Google Ads.

If your primary goal is "find products and search queries that are spending money but not converting", these are the strongest options:

What a good Shopping auditor should identify

The best systems don't just report ROAS—they identify actionable waste such as:

• Products with $100+ spend and zero conversions
• Search terms with significant spend but no sales
• New negative keyword opportunities
• Products with low CTR because of poor titles
• Feed issues (missing GTINs, bad images, missing categories)
• Products losing impression share due to budget
• Out-of-stock products still receiving spend
• Products with high clicks but low conversion rate
• Products that should be split into their own campaigns
• Search queries that should become exact-match keywords (for Search campaigns) help.optmyzr.comapp.mywebhero.co.uk

If you have thousands of SKUs

For large catalogs, product-level analysis matters more than campaign-level metrics.

Tools like SKU Analyzer and Adsage analyze:

• individual SKUs
• brands
• categories
• custom labels
• profitability
• feed attributes

instead of just looking at campaigns. getadsage.comskuanalyzer.com

If you're thinking about building one

There is still room for differentiation. Most current tools rely on rule-based checks such as:

• spend > X
• conversions = 0
• ROAS below target

A more advanced system could use AI to answer questions like:

• "This search query has never converted across 18 months—should it be a negative?"
• "This SKU is wasting budget because its title lacks high-intent keywords."
• "These 37 products should be excluded until pricing improves."
• "This query converts for Product A but is irrelevant for Product B."
• "These five products are cannibalizing each other."

That kind of semantic, product-aware reasoning is still uncommon in most PPC audit tools, which are largely rule-based today.

If you're considering building a SaaS, an AI-powered Shopping auditor that combines Google Ads + Merchant Center + product feed + search term analysis and automatically prioritizes the highest-impact fixes could be a compelling niche, especially for ecommerce brands spending more than about $10k/month on Shopping and Performance Max.

Yes. Optmyzr is probably the closest off-the-shelf tool to what you're describing.

It has a dedicated Non-Converting Queries workflow for Shopping that can identify queries spending money without producing conversions and add them as exact-match negatives. Its rules can be customized around things like spend, clicks, conversions, CPA/ROAS, and lookback periods. help.optmyzr.com

Optmyzr Shopping optimization

What it can automate

For example, you could establish rules such as:

If a Shopping query has spent $50+ with 0 conversions → flag/add as negative.

Or more intelligently:

If query spend exceeds the campaign's expected cost to acquire one conversion and it has 0 conversions → add as negative.

Optmyzr also has a Shopping Negative Keywords Finder that looks at query performance across ad groups and can identify queries that are underperforming relative to the campaign/ad-group baseline. help.optmyzr.com

One important caveat

If you're talking about Performance Max, it's more complicated. Google historically provides much less query-level control/data for PMax than standard Shopping. Optmyzr now has PMax search-term analysis and negative-keyword functionality, but its dedicated Shopping Negative Keywords Finder does not work directly on PMax because of Google's API limitations. help.optmyzr.com

If you're thinking about building something yourself

There's actually a potentially interesting product gap here. A good automated auditor could go beyond the simple:

"0 conversions + $X spend = negative."

It could calculate, for every product query:

• spend
• clicks
• conversions
• conversion value
• ROAS
• expected conversion probability
• expected CPA at that point in the funnel
• product margin
• query/product relevance
• statistical confidence that the query is actually wasteful
• recoverable spend if excluded

Then produce something like:

The interesting part is not finding zero-conversion queries—Optmyzr and scripts can already do that. The harder/valuable part is determining when zero conversions actually constitute statistically credible waste, while avoiding negatives that simply haven't had enough opportunity to convert.

If you're considering this as a software/product idea, I can also break down the existing competitors and what I'd build differently.