ChatGPT answers, unedited

Yes. There are several tools that can automate exactly this for Google Shopping/PMax: pull search-query data → identify spend with no/poor conversions → recommend or apply negative keywords → monitor continuously.

The main options

• optmyzr.com — probably the closest match to what you're describing. Its Non-Converting Queries tool specifically works with Shopping campaigns and can identify queries with spend but no conversions, then add them as exact-match negatives. It also has a Negative Keyword Finder that analyzes query-level performance and recommends negatives. Optmyzr Help Optmyzr Help
• Google Ads itself — you don't necessarily need third-party software. Google's Search Terms reporting lets you inspect queries and add negatives, and Shopping campaigns support negative keywords. Google Help Google Help
• Custom automation via Google Ads API — if you have engineering resources, you can build a system that applies your own rules, e.g. “flag any query with >$40 spend and 0 purchases, unless it has fewer than 20 clicks.” Google's search-term data is available programmatically, including for Shopping and PMax. Google Help

What I'd actually automate

Rather than simply blocking every non-converting query, I'd use rules something like:

That distinction matters because a query having zero conversions isn't necessarily evidence that it's bad—it might simply not have enough clicks/spend yet.

Optmyzr's current Shopping automation is interesting here because its documented rules include both no-conversion queries above a cost threshold and queries with unusually poor CTR, rather than blindly negative-matching everything that hasn't converted. Optmyzr Help Optmyzr Help

If you're asking because you're considering building one

There's definitely a product opportunity here. The basic Google Ads functionality already exists; the value-add is the audit/decision layer:

“Here are the 37 queries that wasted $2,814 in the last 30 days. Here is why each is being flagged, the recommended negative match type, and the estimated spend you're protecting.”

You could make it considerably smarter by clustering queries by intent, identifying recurring bad modifiers (“free”, “DIY”, “used”, “replacement”, etc.), distinguishing product mismatch vs. poor conversion performance, and requiring approval before pushing negatives.

If you tell me whether you're looking for software to use or an idea for building this as a SaaS, I can go one level deeper.

Yes. There are now several tools that can automate much of this, particularly for Google Shopping and Performance Max.

The basic workflow is: ingest search-term/query data → identify queries with spend but no conversions → account for statistical significance and conversion rate → classify irrelevant intent → estimate wasted spend → recommend negative keywords or exclusions.

Google itself provides the underlying data: its Search Terms Report shows queries that triggered Shopping ads, and Search Terms Insights can aggregate queries into intent-based categories for Shopping and PMax. Google Help Google Help

Tools worth looking at

• ppc.io — AI audit of a connected Google Ads account, including search-term analysis and wasted-spend recommendations. PPC.io
• ppctuner.ai — connects through the Google Ads API and audits search terms, including irrelevant queries and negative-keyword opportunities. PPC Tuner
• keywordninja.com — focuses heavily on wasted-spend scans, zero-conversion queries, n-gram analysis and automated negative themes. Keyword Ninja
• bidsensy.com — analyzes search-term exports, categorizes intent, and identifies irrelevant/competitor/brand queries. BidSense
• adswastescanner.com — simpler CSV-based option if you don't want to connect your Ads account; it identifies spending leaks and negative-keyword candidates. Ads Waste Scanner

The important distinction

I wouldn't simply define "wasted spend" as every query with zero conversions. That's too naive.

A better auditor should account for:

• spend relative to your normal CPA
• number of clicks without a conversion
• conversion rate of the campaign/product/category
• product margin or target ROAS
• branded vs. non-branded searches
• queries that are relevant but haven't converted yet
• statistical significance
• duplicate/near-duplicate query themes
• whether the query is actually appropriate for a different product in the catalog

For example, $30 spent / 2 clicks / 0 conversions isn't compelling evidence of waste. $300 spent / 40 clicks / 0 conversions may be a very different situation.

Google specifically recommends using search-term data to identify irrelevant searches and add them as negative keywords, while its Shopping search-term reporting also lets advertisers use query data to improve product-feed descriptions and targeting. Google Help Google Help

If you're thinking about building or buying something specifically for e-commerce Shopping campaigns, I can also break down what these tools actually automate, which ones connect directly to Google Ads, and what a good automated "wasted spend" algorithm should look like.

Yes. Optmyzr is probably the closest off-the-shelf tool to what you’re describing. It can automatically analyze Shopping search queries, identify queries that spend without converting, and add them as negative keywords based on rules you define. Optmyzr Help Center Optmyzr Help Center

What I’d look at

• optmyzr.com — strongest fit for automated Shopping auditing. Its Negative Keywords Finder – Shopping identifies low-performing queries and can add them as exact-match negatives. It also has rules for non-converting queries based on spend, CPA, CTR, ROAS, etc. Optmyzr Help Center Optmyzr Help Center
• Optmyzr PPC/Shopping Audits — beyond queries, it can audit feed issues, products not being advertised, missing negative keywords, disapproved products, overlapping products, and campaign structure. Optmyzr Google Ads Optimization Optmyzr Help Center
• Google Ads itself — you can do this manually with Search Terms reports and negative keywords, and Google supports negative keywords at campaign/ad-group level. Google Help Google for Developers

The important distinction

If your goal is specifically:

“Every week, find product queries that have spent $X without a conversion, determine whether they're genuinely wasteful, and automatically add appropriate negatives.”

Then Optmyzr is a very direct match. Its rules can be customized rather than simply using a blanket “0 conversions = negative” rule. Optmyzr Help Center Optmyzr Google Ads Optimization

That's important because blindly blocking every non-converting query can kill potentially valuable long-tail searches that simply haven't accumulated enough data yet.

One caveat: Performance Max is different. Google doesn't expose the same level of search-term data for PMax, and Optmyzr notes that its Shopping Negative Keywords Finder doesn't operate directly on PMax search terms. Optmyzr Help Center

If you tell me whether you're running Standard Shopping, PMax, or both, and roughly how much you spend per month, I can recommend the best software stack and the exact waste-detection rules I'd use.

Yes. If you mean Google Shopping / Performance Max, there are several tools that can automate exactly this kind of audit.

Best options

• Optmyzr — probably the closest match to what you're describing. Its Shopping tools identify non-converting queries, expensive queries, poor-performing product groups, and duplicate/competing queries, and can recommend or automatically add negative keywords. Optmyzr Help Center Optmyzr Help Center Optmyzr Help Center

optmyzr.com

• Adalysis — particularly good if you want an audit/alerting workflow. It analyzes Shopping search terms, identifies potential negatives, supports customizable thresholds, and has n-gram analysis to find recurring waste patterns such as expensive words appearing across many queries. Adalysis Docs

adalysis.com

• Google Ads / Search Ads 360 itself — you don't necessarily need third-party software. Google's search-term reporting exposes the queries matching Shopping product groups, and you can use those reports to create negative keywords. Google Help The downside is that the analysis and decision-making is much more manual.

What I'd want the software to flag

Rather than simply saying "0 conversions = bad," I'd build the audit around thresholds such as:

The important distinction is statistically meaningful waste, not just "hasn't converted yet." A query with one click and $3 spend shouldn't necessarily be negated, whereas a query with 35 clicks and $90 spend with zero conversions deserves attention.

Optmyzr, for example, has Shopping-specific rules that look at cost, conversions, CTR and campaign benchmarks, and can turn qualifying queries into exact-match negatives. Optmyzr Help Center Optmyzr Help Center

If you're thinking about building this into software

There is actually a pretty compelling product opportunity here: "Shopping Waste Auditor" rather than another generic PPC optimizer.

It could ingest Google Ads data and produce something like:

$12,840 potential wasted spend identified

427 queries exceeded your waste threshold
183 recommended negatives
64 queries need human review
91 high-performing queries that should be protected
27 product/query mismatches

Top 20 waste opportunities: $4,230

Then let the user approve negatives in bulk.

The interesting part would be making the audit profit-aware—using product margin, AOV, target ROAS, conversion lag, brand/non-brand status, and query intent rather than blindly applying a "no conversion after X clicks" rule.

If that's what you're considering, I can also map out what existing tools do vs. what they don't do, and where there may be a gap worth building a SaaS product around.

Yes. Optmyzr is probably the closest fit: its Shopping tools can automatically identify non-converting queries and add them as exact-match negative keywords, using thresholds such as spend/CPA and campaign performance. Optmyzr Help Center Optmyzr Help Center

Other options:

• Optmyzr — strongest for automated query audits + rules.
• Google Ads itself — Search Terms reports and negative keywords, but more manual. support.google.com support.google.com
• Optmyzr MCP — can analyze live Google Ads data conversationally and stage negative-keyword changes for approval. optmyzr.com

If you're looking for something that runs this audit automatically every week and flags “$X spent, 0 conversions” queries, Optmyzr is worth evaluating.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. There are now several tools specifically built to analyze Google Shopping and Performance Max accounts for exactly this use case: identifying search queries, products, and campaigns that are spending money without producing conversions.

Broadly, they fall into four categories:

The Shopping-focused platforms tend to go furthest. For example, Shopiator automatically highlights "money pit" products and non-converting search terms, while SKU Analyzer breaks down zero-conversion products, wasted search terms, and product-level profitability. Both are designed around Google Shopping rather than generic PPC audits. Shopiator SKU Analyzer

The dedicated search-term tools focus on one problem: identifying queries that should become negative keywords. NegKW, for example, analyzes Shopping search terms and suggests negative keywords automatically instead of requiring manual review. NegKW

What the better tools actually detect

The useful ones don't just report spend. They look for patterns like:

• Search terms with significant spend and zero conversions
• Products consuming budget without sales
• Search queries with informational rather than buying intent
• Negative keyword candidates
• Winning search terms that deserve their own campaigns
• Products with poor ROAS relative to the catalog
• Feed problems causing wasted impressions

What they cannot do

This is the important limitation.

No software knows whether a search query is actually irrelevant.

For example:

• "red running shoes" → maybe good
• "red running shoes review" → maybe bad
• "nike sizing" → depends
• "shoe repair" → definitely bad

The software can flag them, but someone (or AI with business context) still has to decide whether to add a negative keyword.

What agencies are increasingly doing

A lot of agencies have stopped paying for specialized software and instead use AI against exported Search Terms reports.

Typical workflow:

1. Export Search Terms from Google Ads.
2. Feed it into ChatGPT or Claude.
3. Tell the model: - what the business sells
4. acceptable CPA/ROAS
5. products offered
6. products not offered
7. Have it classify every query as: - Keep
8. Monitor
9. Negative
10. Add as exact match
11. Investigate

This often produces better recommendations because the AI understands business context instead of relying only on fixed rules. Community discussions among PPC practitioners increasingly describe this workflow as a major time saver for search term reviews. Reddit Reddit

If you're thinking about building a product in this space, there's still room for differentiation. Most existing tools identify what is wasting spend; few explain why in business terms or generate a confidence-ranked, review-ready list of negatives and optimization actions. Combining search-term analysis with product feed data, margins, inventory, and LLM reasoning would go beyond what many current tools offer.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. MyWebHero
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. Adtunez Softtrix
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. AdSentry

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. Campaign Owl

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense BidSense
• Cloudginny Cloudginny
• Dina Dina

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

Yes. This has become a fairly active category, especially for Google Shopping and Performance Max accounts. There are three levels of sophistication:

1. Purpose-built Shopping audit tools (best for finding wasted spend)

These connect to Google Ads and Merchant Center with read-only access and specifically look for:

• Search queries with spend but no conversions
• Products ("vampire SKUs") that consume budget without sales
• Missing negative keyword opportunities
• Feed issues that cause poor query matching
• Budget concentration on low-ROAS products

Examples include:

• AdTool (myWebHero) – focuses heavily on Shopping accounts and reports non-converting search terms, wasted spend by product, feed health, and Merchant Center issues. app.mywebhero.co.ukcloudginny.comgetdina.tech
• AdTunez – identifies zero-conversion keywords, product budget dominance, and high-converting search terms that should be promoted. www.adtunez.com
• AdSentry – AI-powered audits with estimated dollar value of wasted spend and negative keyword recommendations. www.adsentry.co

2. PPC optimization platforms

These continuously monitor accounts rather than performing one-off audits.

Examples:

• Optmyzr
• Karooya
• Opteo
• TrueClicks
• Campaign Owl

These generally provide:

• recurring search term reviews
• automated alerts
• negative keyword suggestions
• account health scoring
• optimization workflows

Campaign Owl, for example, includes AI search term classification and estimates the financial impact of issues. campaignowl.co.uk

3. AI-powered assistants

A newer category is AI agents that:

• classify every search term by intent
• estimate wasted spend
• suggest negatives
• sometimes even prepare changes for approval

Examples include:

• BidSense www.bidsensy.com
• Cloudginny cloudginny.com
• Dina getdina.tech

These are closer to "AI PPC analysts" than traditional dashboards.

What I'd actually want from a tool

If I were choosing one today, I'd expect it to answer questions like:

Simply flagging "low CTR" or "low ROAS" is much less actionable.

If you're thinking about building one

There's still room for a differentiated product because most current tools are rule-based. A stronger AI system could:

• understand semantic relevance instead of relying only on conversions
• identify patterns across thousands of search queries
• cluster irrelevant searches automatically
• estimate confidence before recommending negatives
• explain why a query is a poor fit
• generate Google Ads Editor bulk uploads
• prioritize fixes by expected ROI rather than by spend alone

That moves beyond an audit into a decision-support tool.

If you're considering this as a SaaS, I think there's demand—particularly among agencies and Shopify merchants spending $5k–$100k/month on Shopping campaigns—provided it saves significant manual review time and produces recommendations users trust.

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.