The Voice Commerce Revolution Is Here—And It's Burning PPC Budgets

Voice commerce is exploding. Consumers worldwide are projected to spend $81.8 billion through voice-enabled devices in 2025, representing a massive shift in how people shop online. Smart speakers powered by Alexa and Google Assistant have evolved from simple question-answering tools into sophisticated shopping platforms. For PPC managers, this creates an urgent challenge: traditional negative keyword strategies designed for typed searches fail catastrophically when applied to conversational voice queries.

The numbers tell a compelling story. According to recent industry research, 49% of U.S. consumers now use voice search for shopping—that's 128.4 million Americans speaking their purchase intent rather than typing it. Even more striking, 62% of smart speaker users plan to make a purchase using voice-enabled shopping in the next month. When 74% of consumers using voice-based AI have completed some part of the retail buying process through conversational assistants, ignoring voice commerce optimization isn't just shortsighted—it's financially reckless.

Here's the problem: voice searches are fundamentally different from typed queries. When someone types "buy running shoes," you know exactly what you're dealing with. When someone asks Alexa, "What are the best shoes for someone who runs in the morning and has bad knees but doesn't want to spend too much?" you're in entirely different territory. Your negative keyword lists built for text-based searches will hemorrhage budget faster than you can say "OK Google."

This guide reveals the specialized negative keyword strategies required to protect your PPC budget in the voice commerce era. You'll learn how to identify conversational query patterns that drain budgets, implement voice-specific exclusions across Alexa Shopping and Google Assistant platforms, and build negative keyword frameworks that adapt to the long-tail, question-based nature of voice search. By the end, you'll have actionable tactics to capture high-intent voice shoppers while blocking the budget-wasting queries that plague voice-enabled campaigns.

Why Voice Search Queries Demolish Traditional Negative Keyword Strategies

Voice searches don't just add a few extra words to your standard queries—they fundamentally restructure how people express purchase intent. Understanding these differences is critical before building your negative keyword strategy.

Conversational Length and Complexity

Voice queries average 6-10 words compared to 2-3 words for typed searches. More importantly, they include natural language patterns, filler words, and contextual phrases that traditional keyword matching struggles to handle. When someone types "laptop deals," your negative keyword list for "cheap," "free," and "discount" works perfectly. When someone asks, "Hey Google, what are some good laptops that aren't too expensive but also aren't cheap quality?" your entire negative keyword framework breaks down.

This complexity creates two problems. First, your existing negative keywords often won't match the natural language patterns in voice queries, allowing budget-draining searches to slip through. Second, adding too many long-tail negative keywords to catch these variations risks blocking legitimate high-intent queries that happen to include conversational phrasing.

Question-Based Intent Signals

According to voice search trend analysis, over 70% of voice queries are phrased as questions using "who," "what," "where," "when," "why," and "how." This question-based format introduces ambiguity that didn't exist in typed searches. A typed query "wireless headphones" clearly indicates shopping intent. A voice query "How do wireless headphones work?" might indicate research intent, purchase intent, or troubleshooting intent—and distinguishing between these requires entirely different negative keyword approaches.

The challenge intensifies when you consider that high-intent purchase questions often look identical to low-intent informational questions in their structure. "What are the best noise-canceling headphones?" could come from someone ready to buy immediately or someone casually browsing without purchase intent for months. Your negative keyword strategy must separate these intents without access to the contextual signals that differentiate them.

Local and Immediate Intent

Research shows that 58% of consumers have used voice search to find local business information. Voice queries disproportionately include location-specific language and immediate availability questions: "near me," "open now," "delivery today," "in stock nearby." If your campaigns target national or online-only inventory, these location-heavy queries represent pure budget waste. Yet they're phrased so naturally that standard negative keyword lists rarely catch them.

The voice commerce platforms themselves complicate this further. Alexa Shopping and Google Shopping Actions integrate with local inventory data, meaning voice searches automatically factor in geographic context that may not appear in the spoken query itself. You might think a query for "coffee maker" is location-neutral, but if the user's device has local shopping preferences enabled, your ad could serve to someone specifically looking for local pickup options when you only offer online shipping.

Platform-Specific Negative Keyword Challenges: Alexa vs. Google Assistant

Alexa Shopping and Google Assistant operate on fundamentally different architectures, requiring distinct negative keyword strategies. Understanding these platform differences prevents the costly mistake of applying a one-size-fits-all approach.

Alexa Shopping Ecosystem and Limitations

Amazon's Alexa dominates the smart speaker market with 68.2% of American smart speaker consumers using Echo devices. However, Alexa Shopping has significant limitations for PPC control. Unlike traditional Google Ads campaigns where you have granular negative keyword control, Alexa Shopping operates largely within Amazon's advertising ecosystem, where negative keyword implementation differs dramatically from standard PPC platforms.

Alexa Shopping uses Amazon's Sponsored Products and Sponsored Brands infrastructure, which means your negative keyword options are constrained by Amazon Advertising's rules. You can add negative keywords at the campaign and ad group levels, but the platform processes voice queries through Amazon's own interpretation layer before matching them to your keywords. This creates a black-box problem: you don't always see the actual voice query that triggered your ad, only Amazon's translation of that query into a text-based search term.

More problematically, Alexa's voice shopping experience prioritizes Amazon's Choice products and Prime eligibility, meaning your ads compete not just on keyword relevance but on Amazon's proprietary quality signals. Your negative keywords might successfully block low-intent queries, but if Alexa interprets a voice request as ambiguous, the assistant may present multiple options including competitors, reducing your ad's visibility regardless of keyword targeting precision.

Google Assistant Shopping Actions and Search Integration

Google Assistant is projected to reach 92 million users in the United States by 2025, with usage increasing 46% between 2020 and 2024—the fastest growth among major voice assistants. For PPC managers, this presents both opportunity and complexity because Google Assistant integrates directly with Google Shopping campaigns, meaning your existing negative keyword lists partially carry over, but with critical gaps.

Google Shopping Actions allow retailers to sell directly through Google Assistant, Google Search, and Google Images. When users make voice purchases through Google Assistant, the platform pulls from your Shopping campaigns, applying your negative keywords. However, Google processes voice queries through its natural language understanding system before matching them to your campaigns, introducing a translation layer that can bypass negative keywords phrased in traditional text-search formats.

Google Assistant's contextual awareness creates additional negative keyword challenges. The assistant remembers previous conversation context, meaning a follow-up voice query might reference an earlier question without repeating key details. For example, if someone asks, "What's a good blender?" followed by "Show me cheaper options," Google Assistant connects these queries contextually. Your negative keyword "cheap" won't necessarily block the second query because the actual voice input was "cheaper options," and Google's system interprets this within the conversation's context rather than as an isolated search term.

Cross-Platform Negative Keyword Strategy Requirements

Managing voice commerce across both platforms requires parallel but customized negative keyword lists. Your Alexa Shopping campaigns need negative keywords that account for Amazon-specific language patterns ("Prime," "free shipping," "returns," "reviews"), while your Google Assistant campaigns need exclusions that address broader shopping comparison queries ("versus," "compared to," "alternatives to," "better than").

The most effective approach implements a three-tier negative keyword structure: universal exclusions that apply across all platforms ("free," "DIY," "how to make," "tutorial"), platform-specific exclusions that address each ecosystem's unique patterns, and campaign-type-specific exclusions that account for whether you're running Shopping campaigns, Search campaigns, or Performance Max campaigns with voice search expansion enabled.

The Voice Commerce Negative Keyword Framework: Seven Essential Categories

Building effective negative keyword lists for voice commerce requires systematic categorization. These seven categories address the unique budget-draining queries that voice search introduces.

Category 1: Informational and Research Queries

Voice assistants excel at answering questions, which means a massive volume of voice queries seek information rather than purchases. These queries often include purchase-adjacent language that triggers shopping campaigns despite zero buying intent.

Essential negative keywords: "what is," "what are," "how do," "how does," "why do," "why does," "explain," "definition," "meaning," "difference between," "comparison," "pros and cons," "advantages," "disadvantages," "benefits," "history of," "invented," "works." For longer phrases, consider: "how to use," "how to set up," "how to install," "how to fix," "how to repair," "how to clean," "tutorial," "guide," "instructions."

The nuance here is critical: some "how" queries indicate high purchase intent ("how to buy," "how to order," "how to get"), while others indicate zero intent ("how to make," "how to build," "how to create"). Voice search's conversational nature means you'll encounter more nuanced variations. Testing and refinement based on search term reports remains essential, as does understanding when automation can help manage this complexity at scale.

Category 2: Price and Quality Signals That Indicate Wrong Fit

Voice queries about pricing create more complexity than typed searches because conversational language includes comparative and subjective price descriptors that traditional negative keyword lists miss.

Standard negative keywords: "cheap," "cheapest," "discount," "discounted," "sale," "clearance," "wholesale," "bulk," "free," "under," "less than," "budget," "affordable," "inexpensive." Voice-specific additions: "not too expensive," "won't break the bank," "reasonably priced," "good deal," "bargain," "steal," "value," "economical," "cost-effective," "worth it."

The challenge intensifies when users combine price and quality signals: "good but cheap," "quality but affordable," "not expensive but not cheap." These conversational qualifiers rarely appear in typed searches but proliferate in voice commerce. Your negative keyword strategy must decide whether to exclude all price-conscious queries or only those that clearly indicate bottom-barrel shopping. For premium brands, aggressive price-related exclusions protect margins. For value-positioned brands, more selective exclusions prevent blocking legitimate target customers.

Category 3: DIY, Alternatives, and Substitution Queries

Voice search users frequently explore alternatives to purchasing, including DIY solutions, substitutions, and workarounds. These queries drain budgets because they include product-related keywords despite representing zero purchase intent for your actual products.

Essential negative keywords: "DIY," "do it yourself," "homemade," "make your own," "make at home," "alternative to," "instead of," "replace," "replacement," "substitute," "substitution," "without buying," "without purchasing," "avoid buying," "skip," "hack," "life hack," "trick," "tip."

Voice queries phrase these searches conversationally: "Can I make my own [product]?" "What can I use instead of [product]?" "How to avoid buying [product]?" These question formats require negative keyword coverage beyond single words. Consider negative keyword phrases: "can I make," "can I use instead," "what to use instead," "how to avoid buying," "ways to avoid." This is particularly crucial for categories where DIY alternatives are common: beauty products, home improvement, cleaning supplies, and basic tools.

Category 4: Location and Immediate Availability Mismatches

If you don't offer local pickup, same-day delivery, or specific geographic service areas, location-heavy voice queries represent pure waste. Yet voice search users disproportionately include location and urgency signals because they're often asking while mobile or in immediate-need situations.

Critical negative keywords: "near me," "nearby," "close," "closest," "local," "in my area," "around here," "open now," "available today," "same day," "tonight," "right now," "immediately," "urgent," "emergency," "ASAP." Add location-specific terms if you don't serve certain areas: "in [city]," "in [state]," "[region] area."

Voice commerce platforms automatically infer location context even when users don't speak it explicitly, but your negative keywords should still block explicitly stated location requirements you can't fulfill. According to research on voice search negative keyword strategies, location-based exclusions are among the highest ROI negative keywords for national e-commerce brands because they prevent budget waste on inherently unfulfillable queries.

Category 5: Review, Rating, and Comparison Shopping

Voice searchers frequently ask assistants to read reviews, compare options, or provide ratings before purchasing. These queries indicate mid-funnel research rather than immediate purchase intent, yet they trigger shopping campaigns because they include product names and categories.

Essential negative keywords: "review," "reviews," "rating," "ratings," "rated," "testimonial," "feedback," "opinion," "thoughts," "versus," "vs," "compared to," "comparison," "compare," "better than," "worse than," "difference," "which is better," "best," "top," "top rated," "highest rated."

The strategy here requires nuance. Blocking "best" and "top" entirely might exclude high-intent queries like "buy the best noise canceling headphones." Consider match type strategy: use negative phrase match for "read reviews" and "show me reviews" to block review-seeking queries while allowing "best headphones to buy" to trigger your campaigns. Voice commerce queries phrase comparison shopping conversationally: "Which is better, [product A] or [product B]?" "Should I get [product] or something else?" These require longer negative keyword phrases to catch effectively.

Category 6: Jobs, Careers, and B2B Mismatches

If you sell to consumers, queries about employment at your company or B2B purchasing drain budgets without generating relevant traffic. Voice search exacerbates this because conversational queries about "working at [brand]" or "selling [product] wholesale" sound similar to purchase queries to keyword matching algorithms.

Critical negative keywords: "job," "jobs," "career," "careers," "hiring," "employment," "work at," "working at," "apply," "application," "resume," "wholesale," "bulk order," "distributor," "reseller," "become a dealer," "partnership," "B2B," "business account," "corporate," "enterprise."

Voice queries phrase these conversationally: "Is [brand] hiring?" "How do I get a job at [company]?" "Can I sell [product] at my store?" These questions include brand and product names that otherwise indicate high purchase intent, making them particularly insidious budget drains. For B2C campaigns, aggressive exclusion of employment and wholesale terms is essential.

Category 7: Troubleshooting, Support, and Post-Purchase Queries

Existing customers using voice search to troubleshoot problems or seek support represent negative ROI for acquisition campaigns. These queries include product-specific keywords but indicate post-purchase issues rather than new purchase intent.

Essential negative keywords: "broken," "not working," "stopped working," "fix," "repair," "warranty," "return," "refund," "complaint," "problem," "issue," "error," "troubleshoot," "support," "customer service," "help with," "contact," "phone number," "email." Voice-specific additions: "won't turn on," "won't connect," "not charging," "keeps freezing," "stopped responding."

Voice searchers naturally phrase troubleshooting as questions: "Why won't my [product] connect to WiFi?" "How do I return a [product]?" "What's the warranty on [product]?" These queries require longer negative phrases to block effectively: "why won't my," "how do I return," "what's the warranty," "where do I send," "how do I contact." For brands running both acquisition and retention campaigns, proper campaign segmentation ensures support queries route to appropriate post-purchase campaigns rather than bleeding budget from new customer acquisition efforts.

Implementation Tactics: Making Voice Commerce Negative Keywords Actually Work

Understanding what negative keywords to use matters little if you don't implement them correctly across voice commerce platforms. These tactical steps ensure your strategy translates into actual budget protection.

Match Type Strategy for Conversational Queries

Traditional negative keyword match type advice fails for voice commerce because conversational queries include so much natural language variation. The standard recommendation to use negative exact match for precision and negative broad match for coverage breaks down when queries average 6-10 words with unpredictable phrasing.

For voice commerce campaigns, prioritize negative phrase match as your primary match type. Negative phrase match blocks queries containing your negative keyword phrase in the specified order, while still allowing variations before and after. This strikes the right balance for conversational queries. For example, negative phrase match "-cheap quality" will block "are there cheap quality headphones," "show me cheap quality options," and "I want cheap quality products," while still allowing "cheap" and "quality" to appear separately in queries.

Start with negative phrase match for your core voice commerce exclusions, then analyze search term reports to identify whether you need tighter control (negative exact match) or broader blocking (negative broad match). According to testing across shopping campaign optimizations, negative phrase match typically provides the best balance for voice-heavy campaigns, blocking 60-75% of unwanted voice queries while maintaining 85-90% of valuable traffic.

Voice-Specific Search Term Mining

Your search term reports are the single most valuable data source for identifying voice commerce budget drains. However, you need to analyze them differently than text-based campaigns because voice queries appear as their text translations, making them harder to identify and categorize.

Look for these signals that indicate voice-originated queries: long query length (7+ words), question format (who/what/where/when/why/how), conversational phrasing ("I need," "I want," "I'm looking for," "can you show me"), natural language connectors ("but," "and," "or," "because"), filler words ("like," "maybe," "kind of," "sort of"), and location references ("near me," "around here," "in my area").

Conduct voice-specific search term reviews weekly during the first month of voice commerce campaign optimization, then bi-weekly once your negative keyword lists mature. Export search term reports filtered for queries with 6+ words—these disproportionately represent voice searches. Sort by cost to identify expensive voice queries first, ensuring you block the highest-impact budget drains before addressing high-volume, low-cost issues.

Campaign Structure and Voice Traffic Isolation

The most sophisticated negative keyword strategy in the world won't fully protect your budget if voice commerce traffic mixes indiscriminately with text-based search traffic. Proper campaign structure allows you to apply voice-specific negative keywords aggressively without risking blocked text-based conversions.

Consider creating separate campaigns or ad groups specifically for voice-heavy device targets. While Google Ads doesn't offer explicit "voice search only" targeting, you can use device targeting, location targeting, and daypart analysis to create campaigns that disproportionately serve voice searches. Smart speaker users tend to cluster in specific demographics and locations; targeting these specifically allows more aggressive negative keyword application without affecting your core text-search campaigns.

For advanced implementations, create a testing framework that compares voice-heavy campaigns (aggressive negative keywords, conversational ad copy, long-tail keyword targeting) against traditional campaigns. Measure performance differences in cost per acquisition, conversion rate, and average order value. This data informs whether voice commerce traffic warrants completely separate campaign structures or can coexist within your existing architecture with adjusted negative keyword lists.

Automation and AI Integration for Scale

Managing negative keywords for voice commerce manually doesn't scale. The volume of conversational query variations and the speed at which new patterns emerge require automation to maintain budget efficiency without full-time manual oversight.

Modern negative keyword automation tools analyze search term reports using natural language processing to identify voice query patterns and recommend exclusions. Platforms like Negator.io specifically address this challenge by continuously monitoring search terms, identifying budget-draining patterns, and automatically adding negative keywords based on customizable rules. This approach allows you to set thresholds (for example, "block any query containing 'DIY' or 'how to make' that costs more than $5 without converting") and let the system handle implementation.

Automation doesn't eliminate the need for strategic oversight—it amplifies your ability to execute at scale. Your role shifts from manually reviewing thousands of search terms to setting strategic parameters, reviewing high-level pattern reports, and refining automation rules based on performance data. For agencies managing voice commerce campaigns across dozens of clients, this transition from manual execution to strategic oversight is the only viable path to maintaining profitability as voice search adoption accelerates. Understanding how AI and automation continue evolving helps you stay ahead of emerging voice commerce challenges.

Measuring Voice Commerce Campaign Performance and Negative Keyword Impact

You can't optimize what you don't measure. Voice commerce requires specific metrics and measurement approaches that standard PPC reporting often overlooks.

Identifying Voice Traffic in Your Data

Google Ads and Amazon Advertising don't explicitly label which queries originated from voice search, creating an attribution challenge. However, you can infer voice traffic through query analysis and device signals.

Analyze query length distribution in your search term reports. Create custom segments for queries containing 7+ words—these disproportionately represent voice searches. Track device performance for mobile and smart speaker categories (when available), as voice queries heavily skew toward mobile and smart home devices. Monitor time-of-day patterns, as voice search usage peaks during morning routines (6-9 AM) and evening hours (6-10 PM) when users multitask.

Create custom labels or campaign naming conventions that identify voice-optimized campaigns, allowing you to track performance specifically for traffic influenced by voice-specific negative keywords. Compare conversion rates, average order values, and cost per acquisition between campaigns with aggressive voice-focused negative keywords versus standard campaigns to quantify the impact of your voice commerce optimization efforts.

Negative Keyword Impact Measurement

Most PPC managers track negative keyword counts but fail to measure actual impact. For voice commerce campaigns, focus on these specific metrics that reveal whether your negative keywords genuinely protect budget or unnecessarily restrict reach.

Track budget saved: calculate the total cost of blocked queries before they were added as negative keywords, then project savings over time. Monitor impression share: aggressive negative keywords can reduce impression share too much, indicating you're blocking valuable traffic along with waste. Measure conversion rate improvement: effective negative keyword additions should increase campaign conversion rates by removing non-converting traffic from the funnel.

For advanced measurement, track negative keyword efficiency ratios. Calculate impressions blocked divided by conversions lost (ideally zero) to identify whether specific negative keywords cause collateral damage. Use Search Query Performance reports to identify queries that stopped serving after negative keyword additions—review these quarterly to confirm you're still comfortable with those exclusions as your business and market evolve.

Voice Commerce ROI and Strategic Value

Measuring voice commerce ROI requires comparing performance against both text-based search campaigns and overall marketing channel performance. Don't evaluate voice commerce in isolation—context determines whether it deserves increased investment or represents an emerging channel not yet worth significant resources.

Calculate voice commerce customer lifetime value compared to customers acquired through text-based search. Research from smart speaker marketing analysis suggests voice commerce customers may exhibit different behavior patterns, including higher repeat purchase rates for routine consumables but lower average order values for discovery purchases. Understanding these patterns informs whether voice commerce optimization deserves proportional budget allocation or requires adjusted expectations.

Consider voice commerce's strategic positioning in your overall customer journey. Even if direct voice purchase conversions underperform, voice search queries may represent critical research touchpoints that influence purchases completed through other channels. Multi-touch attribution models can reveal whether voice commerce interactions assist conversions that ultimately complete via desktop or mobile web, indicating that voice-specific negative keywords protect budget while supporting broader funnel efficiency.

Future-Proofing Your Voice Commerce Strategy: 2025 and Beyond

Voice commerce is still early in its adoption curve. The strategies that work today will need continuous evolution as platforms mature and consumer behavior shifts.

Emerging Voice Commerce Technologies

According to voice search optimization research, visual search integration with voice assistants represents the next evolution. Users increasingly combine voice queries with visual inputs: "Show me shoes like this but in red" while pointing a phone camera at a product. These multimodal queries create new negative keyword challenges because the visual component introduces context that doesn't appear in the voice transcript.

Prepare for multimodal commerce by monitoring search term reports for queries that seem incomplete or context-dependent. Phrases like "show me this in," "that but," or "like this one" indicate visual+voice queries where negative keyword strategy must account for missing context. As these queries proliferate, consider whether visual search requires separate negative signal management beyond traditional keyword exclusions.

AI-Enhanced Voice Assistants and Purchase Prediction

Next-generation voice assistants incorporate predictive AI that anticipates purchase needs before users explicitly request products. Amazon's Alexa and Google Assistant increasingly proactively suggest products based on conversation context, purchase history, and inferred needs. This shift from reactive query response to proactive recommendation changes negative keyword strategy fundamentally.

When voice assistants proactively recommend products, your negative keywords may not prevent budget waste if the platform's AI determines your product matches user profile signals despite never matching an explicit query. This requires shifting focus from query-level negative keywords to audience exclusions, placement exclusions, and campaign-level controls that prevent serving to user segments unlikely to convert regardless of how the recommendation surfaces.

Voice Commerce Market Maturity and Competition

Voice commerce spending is projected to grow 321.7% over two years, representing a 105.4% compound annual growth rate. This explosive growth means competition for voice commerce queries will intensify dramatically, increasing costs per click and making budget efficiency even more critical.

As competition increases, the margin for error in negative keyword strategy shrinks. Budget waste that seems manageable at current CPCs becomes untenable when costs double or triple. Invest in robust negative keyword infrastructure now while competition remains relatively low. Build comprehensive exclusion lists, implement automation for continuous optimization, and develop expertise in voice-specific query analysis before market saturation makes these capabilities table stakes rather than competitive advantages.

Conclusion: Voice Commerce Negative Keywords as Competitive Advantage

Voice commerce represents both massive opportunity and significant risk for PPC campaigns. The same conversational query patterns that make voice search accessible to consumers create budget-draining complexity for advertisers. Traditional negative keyword strategies built for text-based searches fail catastrophically when applied to voice queries averaging 6-10 words with question-based, conversational phrasing.

The seven-category negative keyword framework outlined in this guide—informational queries, price signals, DIY alternatives, location mismatches, review shopping, B2B confusion, and support queries—provides systematic protection against the most common voice commerce budget drains. Implementing these exclusions across Alexa Shopping and Google Assistant campaigns using appropriate match types, supported by voice-specific search term mining and automation, transforms voice commerce from a budget liability into a controlled growth channel.

With 49% of U.S. consumers already using voice search for shopping and voice commerce spending projected to reach $81.8 billion in 2025, ignoring voice-specific optimization isn't sustainable. Your competitors are either already implementing voice commerce negative keyword strategies or hemorrhaging budget without realizing it. Either scenario creates opportunity: capitalize on efficient voice commerce acquisition while others waste budget, or capture market share from competitors who abandon voice channels after unsustainable losses.

Start by auditing your current search term reports for long-tail, question-based queries that indicate voice search origins. Calculate how much budget these queries consume versus their conversion contribution. Implement the informational query and DIY alternative negative keywords first—these categories typically deliver the fastest ROI by blocking obvious zero-intent traffic. Then systematically work through the remaining categories, measuring impact at each stage to build the business case for more sophisticated voice commerce optimization.

Voice commerce is no longer emerging—it's here, growing exponentially, and reshaping how consumers shop online. Your negative keyword strategy must evolve accordingly or watch budget efficiency deteriorate as voice queries consume increasing percentages of your campaign impressions. The choice isn't whether to optimize for voice commerce, but whether you do it proactively with strategic negative keyword frameworks or reactively after budget waste forces the issue. Choose proactive optimization. Your ROAS depends on it.