Why Demand Gen Campaigns Demand a New Approach to Negative Signals

Google's Demand Gen campaigns represent a fundamental shift in how advertisers reach audiences across YouTube, Discover, Gmail, and the Display Network. Unlike traditional search campaigns where keywords dictate traffic, Demand Gen campaigns rely on audience signals and automated optimization to capture engagement across Google's most visually immersive surfaces. This automation-first approach creates both unprecedented reach and new challenges for budget control.

For PPC professionals managing multiple accounts, the stakes are higher than ever. According to industry research, 75% of marketing teams cite improving campaign results as their top priority in 2025, yet many struggle with wasted spend in AI-driven campaign formats. Demand Gen campaigns eliminate traditional keyword targeting, replacing it with audience signals and automated placement decisions—which means your negative keyword strategy needs a complete overhaul.

This playbook provides the framework agencies and in-house teams need to protect budgets, maintain quality control, and scale Demand Gen campaigns without bleeding ad spend to irrelevant audiences. You'll learn how negative signals work differently in this format, what exclusion strategies actually move the needle, and how to implement proactive controls before waste happens.

Understanding the Demand Gen Campaign Format and Its Unique Challenges

Demand Gen campaigns launched as Google's evolution of Discovery campaigns, designed to capture attention and drive action across four primary placements: YouTube (including Shorts), Discover Feed, Gmail, and the Google Display Network. The format prioritizes visual storytelling through image carousels, video ads, and product feeds, automatically optimizing placement and audience targeting based on your conversion goals.

The critical difference from search campaigns is the absence of keyword targeting. Instead, you provide audience signals—demographics, interests, behaviors, and custom segments—that guide Google's machine learning toward your ideal customer profile. The system then expands beyond these signals using its own data to find additional converting users. This is where control becomes complex.

The Automation-Control Tradeoff

Traditional negative keywords don't apply to Demand Gen campaigns because users aren't searching with query terms—they're scrolling feeds and watching content. This eliminates your ability to block specific search terms but doesn't eliminate irrelevant traffic. Instead, you're dealing with irrelevant audiences, placements, and engagement that don't convert.

Google's automation still requires human context to perform effectively. The platform optimizes for the goal you set—conversions, clicks, or awareness—but it can't inherently understand your business nuances: which customer segments actually generate profit, which placements align with brand safety, or which audiences are already saturated.

This creates a paradox: Demand Gen campaigns promise sophisticated AI-driven targeting, yet without proper exclusion strategies, they often waste 15-30% of budget on low-quality traffic—the same waste rate that plagues poorly managed search campaigns.

Where Waste Happens in Demand Gen Campaigns

Existing customers and converted leads: Your remarketing lists may not exclude users who already purchased, signed up, or became clients. Demand Gen campaigns will happily show ads to people already in your CRM.

Demographics outside your target: Even with demographic signals set, optimized targeting can expand to age groups, income levels, or parental status segments that never convert for your business.

Irrelevant interest categories: Affinity audiences and in-market segments sound relevant until you realize "Business Services" includes everyone from enterprise software buyers to local handyman service seekers.

Low-performing placements: Not all YouTube channels, Gmail promotions tabs, or Discover feed positions drive equal results. Some placements generate clicks but zero downstream value.

Audience signal drift: As Google's algorithm explores beyond your initial signals, it can drift into tangentially related audiences that share surface-level characteristics but lack purchase intent.

The 2025 Negative Signal Framework for Demand Gen

Controlling waste in Demand Gen requires shifting from reactive negative keywords to proactive negative signals—exclusions implemented before bad traffic accumulates. This framework operates across four layers: audience exclusions, placement controls, signal refinement, and conversion quality filters.

Layer 1: Strategic Audience Exclusions

Audience exclusions are your primary defense against wasted impressions. Unlike search campaigns where you block keywords, here you block entire audience segments from seeing your ads. According to Google's official guidance, audience exclusions should be implemented after campaign creation and observed for at least two weeks before aggressive expansion.

Essential Customer Exclusions

Converted users: Create audience lists of users who completed your primary conversion action. For e-commerce, this means purchasers. For SaaS, this means active subscribers. For lead gen, this means qualified leads already in your pipeline.

App users (if applicable): If you run a mobile app, exclude users who already installed and actively use it. However, consider keeping users who installed but never completed onboarding or haven't used the app in 90+ days—they're reactivation opportunities, not wasted spend.

High-value customer segments: Exclude your top 20% customers by lifetime value unless you're running a specific retention or upsell campaign. These users don't need awareness ads; they need account management.

Demographic Precision Exclusions

Review your conversion data by age, gender, household income, and parental status. Any demographic segment with conversion rates below 50% of your account average should be excluded unless you're testing a new market expansion. This isn't about discrimination—it's about statistical performance.

For B2B campaigns, household income and parental status signals are generally irrelevant noise. Exclude these targeting dimensions entirely to prevent algorithm drift into consumer-focused audiences.

Affinity and In-Market Exclusions

Google's interest categories are broad by design. "Business Services" includes janitorial services and enterprise software. "Technology Enthusiasts" includes gaming PC builders and enterprise IT buyers. You need exclusions to carve out your specific niche.

Build exclusion lists by analyzing which in-market and affinity segments appear in your campaign reporting but generate low conversion rates or high cost-per-conversion. Common exclusions for B2B campaigns include:

• Consumer-focused segments ("Retail Shopping Enthusiasts", "Personal Finance Advice Seekers")
• Job seekers and career development audiences (often click ads but aren't buyers)
• Student and educational audiences (unless you sell to education)
• Competitor employee audiences (build custom segments of competitor domains and exclude)

Layer 2: Placement and Channel Controls

Demand Gen campaigns run across four primary surfaces, but not all surfaces perform equally for every business. Starting in March 2025, Google expanded channel controls globally, allowing advertisers to adjust budget allocation and exclusions by placement type.

Channel Performance Analysis

After 30 days of campaign runtime, segment your performance data by placement: YouTube (including Shorts), Discover, Gmail, and Display Network. Calculate cost-per-conversion and conversion rate for each. If any channel underperforms by 40% or more compared to your best channel, consider excluding it or reducing its budget allocation.

YouTube Shorts, for example, drives massive reach and low CPCs but often delivers bottom-funnel conversion rates 60-70% lower than standard YouTube In-Stream ads. For direct-response campaigns, Shorts may be better suited for awareness campaigns with micro-conversion goals (video views, channel subscriptions) rather than purchase conversions.

Specific Placement Exclusions

Within the Display Network component of Demand Gen, you can exclude specific apps, websites, and content categories. Implement these standard exclusions immediately:

• Parked domains and error pages
• User-generated content platforms (unless your brand safety review approves them)
• In-app gaming inventory (high accidental click rates, low conversion intent)
• Sensitive content categories (tragedy, crime, sexually suggestive content—protect brand safety)

For YouTube specifically, you cannot exclude individual channels or videos in Demand Gen format, but you can exclude content categories. Review Google's content suitability settings and tighten them if brand safety is a priority, understanding this will reduce reach.

Layer 3: Audience Signal Refinement and Optimized Targeting Controls

Audience signals guide Google's machine learning, but "Optimized Targeting"—a setting enabled by default—allows the system to ignore your signals entirely if it predicts better performance outside them. This is where building smarter campaign exclusions becomes critical.

The Optimized Targeting Decision

Optimized Targeting should be disabled if:

• Your account has limited conversion history (fewer than 50 conversions in the past 30 days)
• Your ideal customer profile is narrow and specific (niche B2B, luxury products, specialized services)
• You're running Performance Max campaigns in the same account (prevents audience overlap and budget cannibalization)
• You're testing specific audience hypotheses and need clean data

Optimized Targeting should remain enabled if:

• Your account has strong conversion history (200+ conversions per month with consistent cost-per-conversion)
• Your product has broad appeal and you're willing to let Google explore adjacent audiences
• You're in scaling mode and need to expand beyond your known audience segments

Audience Signal Quality Standards

The strength of your audience signals directly impacts how well Demand Gen performs during the learning phase and beyond. Google recommends providing signals that represent at least 10% of your target market size. Weak signals (overly broad categories like "All Website Visitors") give the algorithm nothing to learn from.

High-quality audience signals include:

• Customer Match lists (email addresses of converted customers—Google builds lookalikes)
• High-value website visitor segments (users who viewed pricing pages, started checkouts, or spent 5+ minutes on product pages)
• Custom segments built from relevant keywords, URLs, and apps (e.g., competitors' domains, industry publications, professional tools)
• Lifecycle-specific remarketing (cart abandoners, trial users, demo requesters)

Layer 4: Conversion Quality Filters and Value-Based Optimization

Not all conversions deliver equal value. A free trial signup from a student using a personal email differs vastly from a demo request from a director at a Fortune 500 company. Demand Gen campaigns optimizing for raw conversion volume will attract the former; campaigns optimizing for conversion value will attract the latter.

Implementing Value-Based Bidding

Switch from Target CPA to Target ROAS bidding once you have sufficient conversion value data (Google recommends at least 50 conversions with value in the past 30 days). This shift forces the algorithm to prioritize high-value conversions over high-volume conversions.

For lead generation campaigns where immediate transaction value isn't available, implement offline conversion imports. Track which leads close into revenue, then import those conversions back into Google Ads with actual deal values. This teaches the algorithm which audience segments generate real business outcomes, not just form fills.

Conversion Action Strategy for Better Signal Quality

Structure your conversion actions in a hierarchy that guides optimization toward quality:

• Primary conversions (set to "Primary" goal): High-value actions like purchases, qualified demo requests, contract signatures
• Secondary conversions (set to "Secondary" goal): Mid-funnel actions like resource downloads, webinar registrations, free trial starts
• Observational conversions (set to "Secondary" goal or excluded from bidding): Engagement metrics like email signups, video views, page visits

By default, Demand Gen campaigns optimize for all conversion actions marked as "Primary." If you're tracking 15 different conversion types and they're all marked Primary, you're teaching the algorithm that a newsletter signup equals a $50,000 contract—which is clearly false.

The 30-60-90 Day Demand Gen Negative Signal Implementation Workflow

Demand Gen campaigns require patience and systematic refinement. According to Search Engine Land's Demand Gen playbook, most advertisers don't fail at execution—they fail because they measure incorrectly and give up too early. This 90-day workflow ensures you implement negative signals strategically while giving the algorithm time to learn.

Days 0-30: Foundation and Initial Data Collection

Week 0 (Pre-Launch): Before launching your Demand Gen campaign, implement baseline exclusions:

• Exclude existing customers and active users (all-time customer lists)
• Exclude employee audiences (company domain-based segments)
• Implement standard placement exclusions (parked domains, sensitive content)
• Set demographic targeting parameters based on existing customer data

Weeks 1-2: Let the campaign run without major changes. Google's machine learning requires 10-14 days to exit the learning phase. During this period, monitor daily spend and ensure tracking is properly implemented, but resist the urge to optimize.

Weeks 3-4: Conduct your first performance review. Segment data by:

• Demographics (age, gender, household income, parental status)
• Audiences (which signals are driving conversions vs. impressions only)
• Placements (YouTube vs. Discover vs. Gmail vs. Display performance)
• Devices (mobile vs. desktop vs. tablet conversion rates)

Create your first round of performance-based exclusions: any demographic or audience segment with zero conversions and 1,000+ impressions gets excluded. Any placement with 500+ clicks and zero conversions gets excluded.

Days 31-60: Refinement and Expansion

Weeks 5-6: With 30+ days of data, you can make statistically relevant decisions. Calculate conversion rate and cost-per-conversion benchmarks for your account. Then identify underperformers:

• Any segment with conversion rate below 50% of account average
• Any segment with CPA above 150% of account average
• Any segment consuming 10%+ of impressions but driving less than 5% of conversions

Implement targeted exclusions for these underperformers. However, avoid excluding segments with fewer than 1,000 impressions—they lack statistical significance.

Weeks 7-8: Refine your audience signals based on what's working. Add new custom segments that mirror your best-performing audiences. If "Enterprise Software Buyers" converts well, add signals like competitor domains, industry publications (TechCrunch, VentureBeat), and business tools (Salesforce, HubSpot).

This is also when you should adjust channel-level budget allocation. If YouTube drives 60% of your conversions at half the CPA of Discover, shift more budget to YouTube while maintaining minimum spend on other placements for ongoing testing.

Days 61-90: Optimization and Scaling

Weeks 9-10: Your campaign has now matured. The algorithm understands your conversion patterns, and you have sufficient data for advanced optimization. This is when tailoring strategies by campaign type becomes essential—what works for Demand Gen differs from search and Performance Max approaches.

Implement value-based optimization if you haven't already. Switch to Target ROAS bidding and let the algorithm optimize for revenue, not just conversion volume. This single change often reduces wasted spend by 20-30% as the system deprioritizes low-value converters.

Weeks 11-12: Begin systematic testing of exclusion hypotheses. Create duplicate ad groups with different exclusion strategies and compare performance:

• Test A: Optimized Targeting ON with aggressive audience exclusions
• Test B: Optimized Targeting OFF with minimal exclusions (tight audience signals only)
• Test C: Single-channel focus (YouTube-only with all other placements excluded)

Once you identify your winning formula, scale budgets incrementally—10-20% increases every 7 days—while maintaining your exclusion framework. The same principles that prevent budget waste when scaling Performance Max apply here: systematic exclusions prevent efficiency loss during scale-up.

Advanced Negative Signal Strategies for 2025

Beyond the foundational framework, sophisticated advertisers implement advanced exclusion strategies that preempt waste before it accumulates. These tactics require more setup but deliver outsized returns in budget efficiency.

Predictive Exclusions Based on Search Campaign Data

Your search campaigns contain valuable negative signal intelligence that applies to Demand Gen. Analyze your search term reports to identify patterns in irrelevant traffic, then translate those patterns into audience exclusions.

For example, if your search campaigns consistently attract job seekers searching "[your company name] careers," "[industry] jobs," and "[position] salary," you know job seekers are a waste segment. Build a custom audience segment using career-related keywords (jobs, hiring, careers, salary, employment) and exclude it from Demand Gen campaigns. This proactive negative keyword strategy prevents waste before you spend a dollar testing the segment in Demand Gen.

Cross-Campaign Exclusion Coordination

If you're running both Performance Max and Demand Gen campaigns (common for comprehensive reach strategies), coordinate exclusions between them to prevent audience overlap and budget cannibalization. Both campaign types use AI-driven optimization that can bid against itself if you're not careful.

Create separate remarketing lists for each campaign type:

• Performance Max exclusions: Exclude users who clicked Demand Gen ads in the past 30 days
• Demand Gen exclusions: Exclude users who clicked Performance Max ads in the past 30 days

This forces each campaign type to find unique audiences rather than competing for the same users across different placements.

Lifecycle-Based Dynamic Exclusions

Build dynamic exclusion lists that automatically update based on user lifecycle stage. For SaaS businesses, this might include:

• Users in active trial (no need for acquisition ads—they need onboarding support)
• Recent subscribers (first 30 days—focus retention efforts elsewhere)
• Churned customers (cancelled in past 90 days—winback campaigns need different messaging)

These exclusion lists update automatically as users move through your funnel, ensuring Demand Gen campaigns always target net-new prospects rather than recycling existing customers through acquisition-focused creative.

Competitive Intelligence Exclusions

Build custom audience segments of competitor employees, then exclude them. Start with competitor domain-based audiences (users who visit competitor.com), then layer in LinkedIn job title targeting if you're using CRM-based Custom Match lists.

Competitor employees click your ads out of curiosity and competitive intelligence gathering—not purchase intent. They inflate your click-through rates while destroying conversion rates and wasting budget.

Measuring the Impact of Your Negative Signal Strategy

Effective negative signal strategies deliver measurable improvements across efficiency, reach, and conversion quality metrics. Track these KPIs to quantify your optimization impact.

Efficiency Metrics

Cost per conversion (CPA): Your primary efficiency metric. Effective exclusions should reduce CPA by 20-35% within 60 days as you eliminate low-conversion-rate segments.

Conversion rate: Should increase as you filter out non-converting audience segments. Mature Demand Gen campaigns with solid exclusion strategies typically achieve 3-8% conversion rates depending on industry.

Wasted spend percentage: Calculate the percentage of total spend that went to audience segments or placements with zero conversions. Target reduction from baseline 15-30% to below 10%.

Reach Quality Metrics

Impression share among target audiences: As you exclude irrelevant segments, your impression share among your defined target audiences should increase—you're focusing budget on the right people.

Audience overlap rate: Monitor how much overlap exists between your Demand Gen audiences and your converted customer base. High overlap (over 30%) suggests you're reaching people similar to existing customers—good signal quality.

Conversion Quality Metrics

Customer lifetime value (LTV) by acquisition source: Track whether Demand Gen converters deliver equal LTV compared to search or other channels. If Demand Gen LTV is significantly lower, your exclusions aren't filtering aggressively enough.

Lead quality scores: For lead generation campaigns, measure what percentage of Demand Gen leads qualify as sales-qualified leads (SQLs) versus marketing-qualified leads (MQLs). High MQL rates with low SQL rates indicate you need tighter demographic or job title exclusions.

Time to conversion: Measure how long users take to convert after first exposure. Demand Gen typically has longer conversion windows than search (14-30 days vs. 1-7 days). If your Demand Gen conversion lag exceeds 45 days, you may be targeting too early-stage or low-intent audiences.

Tools and Automation for Scaling Negative Signal Management

Managing negative signals across multiple Demand Gen campaigns, especially for agencies handling 20-50+ client accounts, requires systematic automation. Manual reviews can't scale beyond a handful of accounts.

Google Ads Scripts for Automated Exclusion Rules

Google Ads Scripts allow you to automate exclusion logic based on performance thresholds. Example script logic:

• Every 7 days, check all demographic segments for conversion rate and CPA performance
• Flag any segment with 1,000+ impressions, 0 conversions, and 100+ clicks
• Automatically add flagged segments to exclusion lists or send alert for manual review

This systematic approach ensures no account goes un-optimized for more than a week, even if you're managing dozens of clients.

Third-Party Optimization Platforms

Platforms like Optmyzr, Acquisio, and Adzooma offer automated rules and anomaly detection for Demand Gen campaigns. They can alert you when specific placements or audience segments suddenly spike in spend without corresponding conversion increases—early warning signals for waste.

However, these platforms typically lag 24-48 hours behind real-time data and require significant configuration to understand your specific business context. They're most valuable for large accounts with dedicated optimization teams.

Context-Aware Automation: The Negator Approach

While traditional exclusion automation relies on rigid rules ("exclude if conversion rate is below X%"), context-aware systems like Negator analyze business context to make intelligent recommendations. Although Negator focuses primarily on search term analysis for search campaigns, its core principle applies to Demand Gen: automation needs to understand your business, not just performance metrics.

For Demand Gen specifically, this means exclusion decisions should factor in:

• Your ideal customer profile and business vertical
• Seasonal performance patterns (some audience segments convert in Q4 but not Q2)
• Protected segments that shouldn't be excluded even during low-conversion periods
• Cross-channel behavior (users who don't convert on Demand Gen but convert after search remarketing)

This level of context prevents over-optimization—accidentally excluding valuable long-term segments because of short-term performance fluctuations.

Common Mistakes That Sabotage Demand Gen Negative Signal Strategies

Even sophisticated advertisers make predictable errors when implementing negative signals for Demand Gen campaigns. Avoid these pitfalls to protect your budget and performance.

Premature Exclusions During Learning Phase

The most common mistake is excluding audience segments or placements before they have statistical significance. Excluding a demographic segment that generated 300 impressions and zero conversions tells you nothing—it hasn't reached enough users to draw conclusions.

Minimum thresholds before exclusion decisions:

• Audience segments: 1,000+ impressions or 50+ clicks
• Placements: 500+ impressions or 25+ clicks
• Demographics: 2,000+ impressions (broader reach required)

Over-Exclusion That Limits Machine Learning

Implementing too many exclusions restricts the algorithm's ability to explore and find new converting audiences. If you exclude 80% of available audience segments, you're left with a tiny pool that may miss valuable niches.

Best practice: Start with broad reach and selective exclusions (remove obvious waste), then tighten gradually based on data. Don't start with narrow targeting and minimal exclusions—that's search campaign logic applied incorrectly to Demand Gen.

Ignoring View-Through Conversions in Performance Analysis

Demand Gen campaigns generate significant view-through conversions (VTCs)—users who saw your ad but didn't click, then converted later. If you only analyze click-through conversions, you'll exclude placements and audiences that are actually driving downstream value.

Review performance metrics with VTCs included, especially for upper-funnel campaigns. A YouTube Shorts placement with low click-through rate but high view-through conversion rate is valuable, not wasteful.

Set-and-Forget Exclusion Lists

Exclusions aren't permanent. Market conditions change, competitor activity shifts, and seasonal trends affect which audiences convert. Review and update your exclusion lists quarterly at minimum.

Implement exclusion list audits:

• Monthly: Review top 10 excluded segments to confirm they're still underperforming
• Quarterly: Test reintroducing 2-3 previously excluded segments to see if performance has improved
• Annually: Complete exclusion list reset—start fresh with only obvious waste exclusions, rebuild from data

The Future of Negative Signal Management in Demand Gen Campaigns

Google's roadmap for Demand Gen campaigns points toward increased automation, expanded inventory (Display Network integration is rolling out in 2025), and more sophisticated AI-driven audience discovery. This trajectory means negative signal strategies will become more important, not less, as control mechanisms shift further from manual targeting to exclusion-based guardrails.

The advertisers who thrive in this environment will be those who embrace what's becoming clear across all Google Ads formats: the future of AdOps is collaboration between AI optimization and human-defined boundaries. You provide the context—who your customers are, what value looks like, which audiences to avoid—and the algorithm provides the scale.

This partnership model requires different skills than traditional PPC management. Instead of keyword research and bid adjustments, you're designing exclusion architectures, defining value hierarchies, and teaching algorithms through strategic signal inputs. The technical execution may be automated, but the strategic thinking remains distinctly human.

Conclusion: Your 2025 Demand Gen Negative Signal Action Plan

Demand Gen campaigns represent Google's vision for the future of digital advertising: visually immersive, AI-optimized, and placement-agnostic. But without strategic negative signals, they also represent a fast track to budget waste and poor ROAS.

Your action plan starts with these immediate steps:

• Week 1: Implement baseline exclusions (existing customers, employees, obvious waste segments) before launching new Demand Gen campaigns
• Weeks 2-4: Monitor without optimization—let the algorithm learn while you collect performance data
• Week 5: Conduct your first optimization pass, excluding zero-conversion segments with 1,000+ impressions
• Weeks 6-12: Implement systematic bi-weekly reviews, progressively refining exclusions based on statistical significance
• Ongoing: Establish quarterly exclusion list audits and continuous testing protocols

The difference between Demand Gen campaigns that waste 25% of budget and those that deliver profitable scale comes down to systematic negative signal management. You can't control where Google shows your ads or which specific users see them—but you can definitively control who doesn't see them, which placements are off-limits, and what "valuable conversion" actually means for your business.

That control is your competitive advantage in an increasingly automated advertising landscape. Use it strategically, refine it continuously, and watch your Demand Gen campaigns deliver the results Google promises—without the budget waste most advertisers accept as inevitable.