Why Most Advertisers Leave Money on the Table

Most businesses waste 20-30% of their advertising budget on irrelevant clicks. According to recent industry research, some advertisers report that up to 40% of their spend goes to irrelevant queries they couldn't block. This isn't just a minor efficiency problem - it's a systematic failure to leverage the free data sources already available in your advertising ecosystem.

While your competitors struggle with manual search term reviews and basic negative keyword lists, you can build a comprehensive discovery framework using seven completely free data sources. The difference between average advertisers and top performers isn't access to expensive tools - it's knowing where to look and how to systematically extract actionable insights from data you already have.

This framework will show you exactly how to mine these free sources, identify high-impact negative keywords your competitors are missing, and build a foundation that saves 10+ hours per week while improving ROAS by 20-35% within the first month.

Understanding the Negative Keyword Discovery Problem

The negative keyword discovery challenge has evolved dramatically in 2025. Google's expanded broad match capabilities mean your ads trigger on increasingly diverse queries, many completely irrelevant to your business. At the same time, manual search term reviews don't scale anymore, especially for agencies managing multiple client accounts or in-house teams running complex campaign structures.

According to industry analysis from Groas, 68% of advertisers didn't use a single negative keyword against Performance Max campaigns before 2025, and over 80% used 10 or fewer across account-level negatives and shared lists. This represents billions in wasted spend across the industry.

The good news: this widespread neglect creates your opportunity. When most advertisers ignore systematic negative keyword discovery, you can gain significant competitive advantage by implementing a structured framework. The difference isn't sophistication - it's consistency and knowing which data sources reveal the highest-value exclusions.

There's also a psychological component to why humans miss what automated systems catch. Pattern blindness, confirmation bias, and fatigue mean even experienced PPC managers overlook obvious waste when reviewing search term reports manually. Your framework needs to compensate for these human limitations.

Data Source #1: The Google Ads Search Term Report (Your Primary Intelligence Source)

The search term report remains your single most valuable free data source for negative keyword discovery. According to Google's official documentation, this report provides insight into the actual searches that triggered your ads and how those searches performed. The difference between your targeted keywords and actual search terms reveals exactly where your budget leaks.

Access the report by expanding the "Insights and Reports" menu in your Google Ads interface and clicking "Search terms." From there, you'll see performance for each search term, the keyword it matched to, and options to add terms as keywords or negative keywords. The key is not just reviewing this data, but systematically extracting patterns.

Systematic Search Term Analysis Methodology

Start with a 30-day lookback period for accounts with substantial traffic (1000+ clicks monthly). For smaller accounts, extend to 90 days to gather sufficient data for pattern recognition. Export the complete report to Excel or Google Sheets for advanced filtering and analysis.

Sort by cost descending, not clicks or impressions. Your goal is identifying expensive irrelevant traffic, not just high-volume waste. A single search term costing $200 with zero conversions deserves immediate attention, even if it only triggered three times.

Create these segmentation categories in your spreadsheet:

• Informational intent: searches including "how to," "what is," "guide," "tutorial," "tips" - users researching, not buying
• Job seekers: searches with "jobs," "careers," "hiring," "employment," "salary" - people looking for work, not your product
• Free seekers: terms with "free," "download," "crack," "torrent" - users who won't convert to paid customers
• Competitor names: direct competitor brand terms unless you're running a conquest strategy
• Geographic mismatches: locations you don't serve appearing in search queries
• Quality modifiers: "cheap," "discount," "wholesale" when selling premium products, or vice versa

Set a cost threshold based on your average CPA. Any search term that cost more than 50% of your target CPA with zero conversions becomes an immediate negative keyword candidate. Terms that cost 25-50% of CPA with poor conversion rates go on a watch list for the next review cycle.

Match Type Analysis: Where Waste Hides

The search term report shows both your keyword and how the actual query matched to it. This reveals which match types generate the most waste for your specific account. Broad match keywords might work beautifully for established brands but create massive waste for niche B2B services.

Filter your exported report by match type to identify patterns. If 80% of your wasted spend comes from broad match keywords triggering on tangentially related searches, you have a match type problem, not just a negative keyword problem. Document this insight for your broader account strategy.

Review search terms weekly for new campaigns or significant budget increases, bi-weekly for stable accounts, and monthly for mature campaigns with established negative keyword lists. Consistency matters more than frequency - sporadic deep dives miss emerging waste patterns.

Data Source #2: Google Search Console (The Organic Intelligence Mine)

Google Search Console provides completely free insight into how users find your website organically. This data reveals search intent patterns, query variations, and topic associations that inform your negative keyword strategy. Mining Search Console data costs nothing but delivers high-value insights most competitors completely ignore.

Access Search Console at search.google.com/search-console and navigate to Performance, then Search Results. You'll see every query that triggered your organic listings in the past 16 months, along with impressions, clicks, CTR, and average position.

Extracting Negative Keywords from Organic Data

Filter for queries with high impressions but zero clicks. These represent searches where users see your listing but don't engage - a strong signal of relevance mismatch. If your organic listing isn't compelling enough to generate clicks, paying for that traffic via ads makes even less sense.

Connect Search Console with Google Analytics to analyze bounce rate and time on site for organic search traffic by query. Queries with 80%+ bounce rates and under 10-second average sessions indicate poor intent alignment. Add these as negative keywords to prevent paying for similar traffic in paid campaigns.

Look for unexpected topic clusters in your Search Console data. If you sell marketing automation software but receive substantial organic traffic for "free email templates" or "marketing job descriptions," these topic areas should inform your negative keyword list. Users searching these topics aren't prospects for your paid campaigns.

Compare your top organic queries against your paid search term report. Queries performing well organically (high CTR, strong engagement metrics) but poorly in paid (high cost, low conversions) suggest intent differences between organic and paid contexts. Users clicking organic listings might be earlier in the buyer journey than those clicking ads.

Review Search Console data across different time periods to identify seasonal variations. Query patterns that work in Q4 might generate waste in Q1. Build seasonal negative keyword lists based on historical organic performance patterns.

Data Source #3: Internal Site Search Data (Your Customer's True Intent)

If your website includes search functionality, this data reveals what visitors actually want to find after clicking your ads. Site search data provides unfiltered insight into customer intent, questions, and product interests that should inform your negative keyword strategy.

Access site search data through Google Analytics 4 under Engagement, then Search. You'll see every query users entered in your site search box, along with engagement metrics. This data is pure gold for understanding the gap between what your ads promise and what visitors actually seek.

Analyzing Site Search for Negative Keyword Opportunities

Identify searches with zero results. If visitors click your ad, then search your site for products or features you don't offer, you're attracting the wrong traffic. A site search for "free trial" when you don't offer one, or "enterprise pricing" when you only serve small businesses, indicates ad copy or keyword targeting misalignment.

Review exit pages following site searches. Searches leading to immediate site exit represent failed visitor intent. If users search for "installation guide" then leave, they were looking for self-service resources, not your SaaS product. Add "installation guide" and similar terms as negatives.

Document product and service gaps revealed by site search. Repeated searches for offerings you don't provide should become negative keywords until you expand your product line. This prevents paying for traffic you cannot convert.

Notice search refinement patterns. When users search once, then modify their query, it reveals confusion about your offerings. If initial searches use industry jargon that your business doesn't align with, add that jargon as negative keywords.

Analyze the difference between product searches and support searches. High volumes of "customer service," "phone number," "contact," or "cancel subscription" searches from paid traffic indicate you're attracting existing customers or users with problems, not new prospects. Adjust your negative keywords to filter support-intent queries.

Data Source #4: YouTube Search Insights (Video Intent Signals)

If you run YouTube ads or campaigns across Google's network, YouTube's search data provides free insight into how users seek video content related to your topics. This reveals informational versus transactional intent differences that should inform your negative keyword strategy.

Access YouTube search insights through your YouTube Studio account under Analytics, then Audience. The "How viewers found your channel" section shows search terms viewers used to discover your content. Even without published videos, you can research competitor channels and industry topics.

Leveraging YouTube Data for Negative Keywords

YouTube searchers typically seek educational content, tutorials, reviews, or entertainment - not immediate purchases. Search terms performing well on YouTube often represent poor intent for conversion-focused paid search campaigns. Terms like "how to [your service]," "[product] review," or "[topic] explained" attract researchers, not buyers.

Research competitors' most popular videos and the search terms driving views. If competitor content about "free alternatives to [industry software]" generates substantial views, add "free alternatives" as a negative keyword in your paid search campaigns. Users seeking that content won't convert to paid plans.

Document question patterns from YouTube search data. "Why," "how," "what," and "when" questions indicate early-stage awareness, not purchase intent. While valuable for content marketing, these queries usually generate wasted spend in bottom-funnel paid search campaigns.

Monitor trending searches in your industry on YouTube to identify emerging topics that might trigger your paid ads. Early identification of trending but irrelevant topics lets you proactively add negative keywords before wasting budget.

Data Source #5: Answer the Public (Question-Based Intent Mapping)

Answer the Public is a free tool that visualizes search questions and autocomplete data from Google and Bing. It reveals the complete spectrum of questions users ask about topics, helping you distinguish between informational queries to exclude and transactional queries to target.

Visit answerthepublic.com and enter your core product or service keywords. The tool generates a comprehensive map of questions, prepositions, comparisons, and alphabetical search suggestions around your topic. You get two free searches per day without an account.

Extracting Negative Keywords from Question Data

The "Questions" section reveals informational intent to exclude from paid campaigns. Questions starting with "what is," "how does," "why is," and "when should" typically indicate research phase users who won't convert immediately. Build negative keyword lists around these question patterns.

Review the "Prepositions" section for context clues. Searches including "for free," "without," "versus," or "alternative to" usually represent users not ready to buy or actively seeking to avoid paid solutions. These become high-priority negative keywords.

The "Comparisons" section shows "versus" and "or" queries. While some comparison searches indicate purchase-ready users evaluating options, many reveal tire-kickers conducting preliminary research. Evaluate whether comparison traffic converts for your business before investing paid budget.

Don't ignore the alphabetical suggestions. These often reveal unexpected query variations and niche sub-topics that might trigger your ads. Scan for irrelevant associations - if you sell CRM software and the tool shows substantial search volume for "CRM jobs" or "CRM certification," add those variations as negatives.

Run new Answer the Public searches quarterly to identify emerging question patterns and seasonal variations. User intent evolves over time, and yesterday's research queries might become today's purchase queries (or vice versa). Maintain a living negative keyword list that adapts to changing search behavior.

Data Source #6: Google Autocomplete and Related Searches (Real-Time Intent Signals)

Google's autocomplete suggestions and related searches section provide real-time insight into popular query variations and associated topics. This free data source reveals what actual users search for right now, helping you identify irrelevant associations and intent mismatches.

Simply type your core keywords into Google's search box and observe the autocomplete suggestions. After performing a search, scroll to the "Related searches" section at the bottom of search results. Both features reveal popular query variations and unexpected topic associations.

Systematic Autocomplete Analysis

Start with your core product keywords and document every autocomplete suggestion. Add modifiers one by one: your keyword plus "free," plus "how to," plus "jobs," plus geographic terms, plus quality descriptors. Each combination reveals different search intent angles.

Look specifically for unexpected suggestions. If you sell premium consulting services and autocomplete suggests "[your keyword] DIY" or "[your keyword] templates," you're attracting do-it-yourself searchers who won't buy professional services. Add these intent mismatches as negatives.

Document competitor name associations. Autocomplete revealing "[competitor name] vs [your brand]" or "[your keyword] [competitor name]" shows users researching alternatives. Decide whether you want to pay for competitive traffic or exclude competitor-focused searches.

Notice geographic autocomplete patterns. If you serve the United States but autocomplete shows substantial search volume for "[your keyword] UK" or "[your keyword] Canada," add those geographic negatives unless you're expanding internationally.

Mine the "Related searches" section for topical drift. Related searches show what Google considers semantically similar to your keywords. Irrelevant related topics indicate where your ads might trigger on tangentially connected queries. If you sell email marketing software and related searches include "email etiquette" or "email format examples," add those negative keywords.

Perform autocomplete research in incognito mode to avoid personalized results. Your search history influences autocomplete suggestions, which can create a skewed view of what typical users search for. Incognito mode reveals unbiased popular searches.

Data Source #7: Competitor Ad Copy and Landing Page Analysis (Reverse-Engineering Their Strategy)

Analyzing competitor ads and landing pages reveals which keywords they target, which they probably exclude, and where opportunities exist to differentiate your strategy. Reverse-engineering competitor PPC gaps using publicly available data costs nothing but delivers strategic insights.

Use Google's Ad Preview and Diagnosis tool (in your Google Ads interface under Tools and Settings) to see competitor ads without influencing auction dynamics or inflating their costs. Search for your target keywords and document which competitors appear, their ad copy, and landing page focus.

Reverse-Engineering Negative Keyword Strategy

Notice where competitors don't advertise. If you search informational queries and no competitors bid, they've likely identified those terms as poor converters. While you shouldn't blindly copy competitor strategies, consistent advertiser absence on certain query types provides useful signals.

Analyze competitor ad copy for what they explicitly exclude. Copy stating "No contracts" reveals they're filtering "contract" searches. "Enterprise-only" messaging indicates they exclude small business intent. "US-based support" suggests they've added geographic negatives. Learn from their explicit positioning.

Review competitor landing pages for what they don't offer. Services, features, or customer segments absent from their positioning represent areas they've likely excluded via negative keywords. If enterprise software competitors don't mention pricing, they probably exclude "pricing" and "cost" related searches.

Identify search terms where no competitors bid consistently. These represent either overlooked opportunities or proven waste. Test small budgets on uncontested terms to determine which category they represent. If test campaigns generate waste, add similar terms as negatives across your account.

Set up a monthly competitor review cadence. Screenshot competitor ads, document messaging changes, and track landing page evolution. Shifts in competitor strategy often signal they've discovered new negative keywords or identified emerging waste patterns worth investigating.

Implementing Your Discovery Framework: From Data to Action

Having seven data sources means nothing without systematic implementation. The difference between successful advertisers and those still wasting budget is consistent execution of a repeatable framework. Here's how to transform these free data sources into waste reduction and ROAS improvement.

Creating Your Discovery Schedule

Schedule weekly reviews for your primary data source: the Google Ads search term report. Every Monday morning, export the previous seven days of search term data, sort by cost, and identify new negative keyword candidates. This weekly cadence catches emerging waste before it accumulates.

Conduct monthly deep dives into Search Console, site search data, and competitor analysis. These sources change more slowly than daily search terms, making monthly reviews sufficient for most accounts. Document patterns and update your negative keyword lists accordingly.

Perform quarterly research using Answer the Public, autocomplete analysis, and YouTube insights. These broader market research activities identify emerging trends and seasonal pattern shifts that inform strategic negative keyword decisions.

Block actual calendar time for these reviews. Without dedicated time, negative keyword discovery becomes perpetually deprioritized. Thirty minutes weekly, ninety minutes monthly, and three hours quarterly represents a minimal investment generating substantial returns.

Organizing Your Negative Keyword Lists

Build negative keyword list hierarchy based on theme and specificity. Create account-level lists for universal exclusions (jobs, free, careers, wholesale), campaign-level lists for product-specific exclusions, and ad group-level negatives for granular control.

Use shared negative keyword lists for themes that span multiple campaigns: competitor names, informational intent terms, geographic exclusions, and quality mismatches. Shared lists let you update once and apply everywhere, ensuring consistency and saving time.

Implement clear naming conventions: "NEG-Universal-Jobs," "NEG-Campaign-Informational," "NEG-Geographic-International." Descriptive names help agencies manage multiple clients and in-house teams maintain lists through staff changes.

Document why each negative keyword exists. In six months, you won't remember why "tutorial" seemed important to exclude. Brief notes like "Tutorial searchers = 0% conversion rate, $847 wasted Q1 2025" justify decisions and prevent removing negatives that still provide value.

If you're starting from scratch, build your first negative keyword library with a 500-term foundation covering universal exclusions before adding account-specific terms from your seven data sources.

Testing Before Excluding: The Safety Protocol

Never blindly add negative keywords without validating their impact. Even terms that seem obviously irrelevant might occasionally trigger valuable conversions in unexpected contexts. Implement a testing protocol before excluding at scale.

Create "watch lists" for questionable terms. Instead of immediately excluding searches, flag them for observation over 30-60 days. If cost exceeds 2x your target CPA with zero conversions, then add as negative. This prevents premature exclusion of seasonal or irregularly converting terms.

Start with phrase match negatives, not exact match. Phrase match provides broader protection while exact match only blocks that specific query variation. For example, adding [how to use] as phrase match blocks "how to use CRM software," "how to use marketing automation," and other variations in one addition.

Exercise extra caution with Performance Max negative keywords. According to industry analysis, Performance Max negatives only apply to Search and Shopping inventory, having zero impact on Display, YouTube, Gmail, and Discovery placements where 40-70% of spending typically occurs. Test Performance Max negatives conservatively to avoid inadvertently blocking valuable search traffic.

Implement protected keyword lists - terms you never want to exclude regardless of temporary performance fluctuations. Your brand terms, core product names, and strategic initiatives should be protected from accidental negative keyword overlap. Tools like Negator.io include protected keyword features specifically to prevent blocking valuable traffic during automated optimization.

Advanced Framework Optimization: Taking It Further

Once your basic framework runs consistently, these advanced optimizations compound your results and reveal waste invisible to competitors using standard approaches.

Cross-Channel Intent Comparison

Compare search term performance across different campaign types to identify channel-specific negative keywords. Terms performing well in branded campaigns might waste budget in non-branded. Queries converting in Shopping might generate waste in Search. Build channel-specific negative keyword lists instead of applying universal exclusions.

Segment search term analysis by device. Mobile searchers often exhibit different intent than desktop users for the same queries. Terms with strong desktop performance but poor mobile results might indicate user experience issues, not intent problems, requiring landing page optimization rather than negative keywords.

Analyze search term performance by time of day and day of week. B2B search terms triggering during evenings and weekends often represent personal research, not business purchases. Consider time-based bid adjustments as an alternative to blanket negative keywords for time-sensitive intent differences.

Automation and Scaling Your Framework

While manual discovery works for single accounts, agencies managing 20-50+ clients need automation to scale. The good news: automation doesn't require expensive enterprise software. Google Ads scripts can automate search term exports, Google Apps Script can process data in Google Sheets, and simple Python scripts can analyze patterns across all seven data sources.

Context-aware AI automation represents the next evolution beyond rule-based systems. Unlike simple scripts that flag terms containing "free" or "jobs," AI systems analyze business context to determine relevance. A "cheap" search might be irrelevant for luxury goods but valuable for budget products. Generic automation can't make these distinctions - contextual AI can.

Tools like Negator.io use AI-powered contextual analysis to automatically identify irrelevant search terms based on your business profile and active keywords. Instead of spending 10+ hours weekly reviewing search terms across multiple accounts, agencies can leverage automated suggestions with human oversight, maintaining control while scaling efficiency.

The key is balancing automation with human judgment. Fully automated negative keyword addition risks blocking valuable traffic. Fully manual review doesn't scale and suffers from human pattern blindness. The optimal approach combines automated discovery from your seven data sources with human validation before implementation.

Comprehensive Waste Audit Integration

Your negative keyword discovery framework should integrate with broader account auditing for comprehensive waste identification. Finding hidden waste that standard checklists miss requires examining negative keywords alongside match types, bid strategies, geographic targeting, and audience settings.

A search term generating waste might indicate poor negative keyword coverage, but it could also reveal overly broad match types, incorrect geographic settings, or audience targeting mismatches. Analyze negative keyword opportunities within broader account structure context for more effective optimization.

Conduct comprehensive waste audits quarterly, examining all seven data sources simultaneously rather than in isolation. Cross-reference patterns between sources - terms appearing across Search Console organic data, site search, and paid search reports represent especially strong negative keyword candidates.

Measuring Framework Success: Beyond Vanity Metrics

Track specific metrics to validate your negative keyword discovery framework effectiveness and demonstrate ROI to stakeholders or clients.

Key Performance Indicators

Calculate prevented wasted spend by tracking the cost of search terms you excluded before adding them as negatives. If a term cost $300 with zero conversions over 30 days, and you exclude it, that's $300 monthly in prevented waste. Multiply by 12 for annualized savings.

Monitor irrelevant click percentage: (clicks from irrelevant search terms / total clicks) × 100. Track this weekly as you implement your framework. Mature accounts with strong negative keyword coverage should see irrelevant click percentage below 5%. New accounts often start at 20-30% before systematic optimization.

Track ROAS improvement after implementing negative keywords. According to industry data, advertisers implementing comprehensive negative keyword strategies typically see 20-35% ROAS improvement within the first month. Document baseline ROAS before starting your framework, then measure monthly to demonstrate impact.

Quantify time savings from systematic framework implementation. If you previously spent 3 hours weekly manually reviewing search terms, and your framework reduces this to 30 minutes, that's 2.5 hours weekly or 130 hours annually. At a typical agency billing rate, that's substantial recovered capacity for strategic work.

Monitor CPA trends as negative keyword coverage improves. Removing wasted clicks naturally reduces cost per acquisition by focusing spend on higher-intent traffic. Track CPA weekly and correlate improvements with negative keyword additions to prove causation.

Reporting Framework Impact

Build a simple dashboard tracking: negative keywords added (by source), prevented wasted spend, irrelevant click percentage, ROAS trend, and CPA trend. Update monthly and share with stakeholders to maintain framework visibility and support.

Document specific examples of high-impact negative keywords discovered through each data source. "We identified $2,400 monthly waste on job-seeking searches through Search Console analysis" resonates more than abstract percentage improvements. Collect these stories throughout your framework implementation.

Compare your metrics against industry benchmarks. If your irrelevant click percentage drops from 25% to 8% while industry average remains 15-20%, you've achieved measurable competitive advantage. Context helps stakeholders appreciate your framework's value.

Common Framework Pitfalls and How to Avoid Them

Even well-designed frameworks fail through common implementation mistakes. Avoid these pitfalls to ensure your negative keyword discovery delivers consistent results.

Over-Exclusion: The False Efficiency Trap

The biggest mistake new negative keyword practitioners make is over-exclusion. In pursuit of perfect efficiency, they block so much traffic that campaign volume drops below statistical significance. You can't optimize campaigns that generate 10 clicks weekly because you've excluded everything remotely questionable.

Balance efficiency with volume. Some waste is acceptable if it maintains sufficient traffic for algorithmic learning and testing. Google's automated bidding strategies need minimum conversion volumes to optimize effectively. Over-aggressive negative keywords can starve campaigns of the data they need to perform.

Before adding broad negative keywords, test their volume impact. Use Google's Keyword Planner to estimate how many searches you'll exclude. If a negative keyword would remove 40% of your traffic, reconsider whether it's truly all irrelevant or if you're over-correcting.

Inconsistent Application Across Accounts

Agencies managing multiple clients often apply negative keywords inconsistently - thoroughly optimizing favorite accounts while neglecting others. This creates performance disparities and client satisfaction issues.

Implement the same framework schedule across all accounts. Every client gets weekly search term reviews, monthly deep dives, and quarterly research. Use shared templates and checklists to ensure consistency regardless of which team member performs the work.

Leverage tools that scale across multiple accounts. Negator.io's MCC integration lets agencies manage negative keywords across 20-50+ client accounts from a single interface, ensuring consistent optimization without multiplying workload linearly.

Ignoring Business Context

Generic negative keyword lists copied across accounts ignore crucial business context differences. "Cheap" might be irrelevant for a luxury brand but valuable for a discount retailer. "DIY" might be waste for a service business but gold for a product company.

Customize negative keywords based on business model, price positioning, customer segment, and competitive strategy. Start with universal exclusions (jobs, careers, free for all paid products), then build account-specific lists informed by your seven data sources and business understanding.

Before adding negative keywords, ask: "Could any reasonable buyer use this search term?" If yes, use watch lists and testing before excluding. If no, add confidently. Context determines the answer, not generic rules.

Turning Free Data Into Competitive Advantage

The seven free data sources in this framework - Google Ads search terms, Search Console, site search data, YouTube insights, Answer the Public, autocomplete analysis, and competitor research - provide everything you need to build comprehensive negative keyword coverage that rivals expensive enterprise tools.

The difference between advertisers who consistently reduce waste and those who struggle isn't access to data. It's systematic execution of a repeatable framework that transforms data into action. Your competitors have access to the same seven sources. Most won't use them consistently. That's your opportunity.

Implement this framework for 90 days with weekly search term reviews, monthly data source analysis, and quarterly research cycles. Track your metrics: prevented wasted spend, irrelevant click percentage, ROAS improvement, and time savings. The data will prove the framework's value.

For agencies and in-house teams managing multiple accounts or complex campaign structures, consider augmenting your framework with context-aware automation. Tools like Negator.io don't replace the framework - they scale it, applying the same systematic discovery across dozens of accounts while maintaining human oversight and business context.

Start today with your highest-spend campaigns. Export this week's search term report, sort by cost descending, and identify your top five wasted search terms. Add them as negatives. That simple action begins your framework implementation and starts saving budget immediately.

While your competitors manually review search terms sporadically and miss obvious waste, you'll systematically mine seven free data sources, build comprehensive negative keyword coverage, and gain measurable competitive advantage. The framework is free. The discipline to execute it consistently is what separates top performers from everyone else.