Category: PPC

Uncover the Top Blocker to PPC Growth and Fix It
I’ve been there myself. A client approaches me, eager to upscale their Google Ads spend from €10,000 to €100,000 monthly. Like any dedicated PPC manager, I dive into the usual strategies:
- Refine bidding strategies.
- Test new ad copy.
- Expand keyword lists.
- Optimize landing pages.
- Boost Quality Scores.
- Launch Performance Max campaigns.
Several months in, the ad spend only grows by 15%. The client is content, but I know we can do better.

Here’s a harsh truth I’ve learned: much of what we consider PPC optimization is really just sophisticated procrastination.

The theory of constraints, introduced by Eliyahu Goldratt, offers insights for PPC much like it does for manufacturing. It shows that every system has a single constraint that limits its potential.

It doesn’t matter if the marketing team is super-efficient if the production capacity is what’s limited. Likewise, a 20% improvement in ad copy CTR isn’t useful if the real constraint lies in budget or conversion tactics.

This theory calls for radical focus: pinpoint the weakest link, make it your priority, and tune out the rest.

Applying this to PPC means stopping the widespread optimization efforts. Detect the primary barrier, resolve it, and press on.

Over time, managing PPC accounts has shown me that scaling challenges usually fit within one of seven categories:

Budget: Profitability could be higher, but client approval caps spending.

For instance, a campaign might run successfully at €10,000 monthly, with scope to go to €50,000, yet the client hesitates due to risk aversion or cash flow concerns.

Developing a compelling business case that showcases past ROI and projected returns is vital here.

I ignore ad copy tests or keyword expansions because, if I can’t increase budget, they won’t help.

Impression Share: Already capturing over 90% share, limiting traffic growth.

Entering new markets or ad platforms can often be the solution for these scenarios.

The Creative aspect needs tightening when high impressions yield low CTRs, and so on for conversion rate, fulfillment, profitability, and tracking or attribution challenges.

With my diagnostic steps, I start by running an audit to benchmark the key metrics—impression share, CTRs, CPCs, and conversion rates— to pinpoint what’s genuinely holding the account back.

The moment I finish an audit and single out the top challenge, the focus becomes precise. For instance, if it turns out conversion rate optimization can unlock growth, that’s where all my efforts channel into until I see a breakthrough.

Every time the constraint is overcome, a new bottleneck emerges, signifying growth and the movement to new phases. It is both a marker of success and a roadmap to what needs attention next.

Inspired by this post on Search Engine Land.
February 9, 2026
Embracing Challenges: Leadership and Creativity in Marketing

I recently had the pleasure of speaking with Amanda Farley, the brilliant CMO of Aimclear, on episode 340 of PPC Live The Podcast. Amanda’s journey from owning a gallery and tattoo studio to leading award-winning global campaigns is nothing short of inspiring. Her unique T-shaped marketing expertise, combining in-depth PPC knowledge with a broad skill set across social, programmatic, PR, and integrated strategies, offers valuable insights into modern marketing.

Through our engaging conversation, Amanda shared her lessons on overcoming setbacks and balancing AI with human insight. Her experience underscores the importance of mixing calm leadership with a relentless curiosity and drive for continuous learning.

Overcoming Limiting Beliefs and Embracing Creativity

Amanda once ran an gallery and tattoo parlor while believing she wasn’t an artist herself. Surrounded by creatives, she eventually realized her only barrier was a limiting belief. After embracing painting, she created hundreds of artworks and discovered a powerful outlet for expression.

This mindset shift mirrors marketing growth. Success isn’t just technical — it’s mental. By challenging internal doubts, marketers can unlock new skills and opportunities.

When Campaign Infrastructure Breaks: A High-Stakes Lesson

Amanda recalls a global campaign where tracking infrastructure failed across every channel mid-flight. Pixels broke, data vanished, and campaigns were running blind. Multiple siloed teams and a third-party vendor slowed resolution while budgets continued to spend.

Instead of assigning blame, Amanda focused on collaboration. Her team helped rebuild tracking and uncovered deeper data architecture issues. The crisis led to stronger onboarding processes, earlier validation checks, and clearer expectations around data hygiene. In modern PPC, clean infrastructure is essential for machine learning success.

The Hidden Importance of PPC Hygiene

Many account audits reveal the same problem: neglected fundamentals. Basic settings errors and poorly maintained audience data often hurt performance before strategy even begins.

Outdated lists and disconnected data systems weaken automation. In an machine-learning environment, strong data hygiene ensures campaigns have the quality signals they need to perform.

Why Integrated Marketing Is No Longer Optional

Amanda’s background in psychology and SEO shaped her integrated approach. PPC touches landing pages, user experience, and sales processes. When conversions drop, the issue may lie outside the ad account.

Understanding the full customer journey allows marketers to diagnose problems holistically. For Amanda, integration is a practical necessity, not a buzzword.

AI, Automation, and the Human Factor

While AI dominates industry conversations, Amanda stresses balance. Some tools are promising, but not all are ready for full deployment. Testing is essential, but human oversight remains critical.

Machines optimize patterns, but humans judge emotion, messaging, and brand fit. Marketers who study changing customer journeys can also find new opportunities to intercept audiences across channels.

Building a Culture That Welcomes Mistakes

Amanda believes leaders act as emotional barometers. Calm investigation beats reactive blame when issues arise. Many PPC problems stem from external changes, not individual failure.

By acknowledging stress and focusing on solutions, leaders create psychological safety. This environment encourages experimentation and turns mistakes into learning opportunities.

Testing Without Fear in a Changing Landscape

Marketing is entering another experimental era with no clear rulebook. Amanda encourages teams to dedicate budget to testing and lean on professional communities for insight.

Not every experiment will succeed, but each provides data that informs smarter future decisions.

The Tasmanian Devil Who Practices Yoga

Amanda describes her career as If the Tasmanian Devil Could Do Yoga — a blend of fast-paced chaos and intentional calm. It reflects modern marketing: demanding, unpredictable, and balanced by thoughtful leadership.

Inspired by this post on Search Engine Land.

February 6, 2026
Harness Google Ads’ New Diagnostics Tool for Seamless Campaigns

I’ve always found it challenging to keep my Google Ads campaigns running smoothly without a hitch. When I heard about Google Ads’ new diagnostics hub for data connections, I knew I had to explore it. This tool promises to catch issues early, which could significantly enhance my conversion tracking and overall campaign performance.

Recently, Google Ads introduced a data source diagnostics feature within their Data Manager. It’s designed specifically to help people like me monitor the health of my data connections. The tool is a lifesaver, flagging issues linked to offline conversions, CRM imports, and tagging mismatches.

How it works. The dashboard is centralized, and it assigns clear connection status labels like Excellent, Good, Needs Attention, or Urgent. It also provides actionable alerts, which is a huge plus for me. I can easily identify problems such as refused credentials, formatting errors, or failed imports. Additionally, there’s a run history that displays recent sync attempts and error counts.

Why we care. I’ve noticed that when conversion data breaks, campaign optimization collapses too. It’s the minor data connection failures that can distort conversion tracking and weaken automated bidding. This diagnostics tool is crucial as it helps my team and me spot and fix issues early, safeguarding our campaign performance and reporting accuracy. If you’re relying on CRM imports or offline conversions like I am, it’s truly a needed safety net.

Who benefits most. If you’re running complex conversion pipelines like I do, including Salesforce integrations and offline attribution setups, this feature is a game-changer. It addresses disruptions that could otherwise ripple through our bidding and reporting process.

The bigger picture. As we increasingly depend on accurate first-party data for automated bidding, having visibility into data pipelines has become as crucial as the campaign settings themselves.

Bottom line. Google Ads has effectively given us an early warning system for data failures, helping us fix broken connections before they affect performance.

First seen. I learned about this update when Digital Marketer Georgi Zayakov shared it on LinkedIn. I’m grateful to Georgi for sharing this valuable insight.

Inspired by this post on Search Engine Land.

February 6, 2026
Google Ads: From Keywords to Intent-Driven Success
I’ve noticed a significant shift in how Google Ads operates. No longer is it about simply targeting keywords. Now, it’s all about understanding and leveraging user intent. Here’s what this evolution means for eligibility, structure, and PPC strategy.

Most PPC teams, myself included, have operated on autopilot: compiling keyword lists, assigning match types, and structuring ad groups around search terms. This was the norm.

However, Google’s auction process has transformed. Search interactions are evolving into more conversational experiences. People engage with AI as if they’re having a dialogue, asking follow-up questions and refining their inquiries. AI now reasons through a question before linking it to suitable ads.

Today, the auction isn’t kicked off by a keyword but by the user’s implied intent. If I’m still relying on exact and phrase match structures, I’m planning for a system that’s no longer there. It’s time to embrace intent as the foundation—not the specific words typed, but the underlying goals they signify.

With this intent-first approach, I find a more resilient strategy. It allows me to effectively design campaigns, creativity, and metrics, especially as Google rolls out new AI-focused formats.

While keywords still play a role, they no longer serve as the framework.

Recently, I’ve learned about changes happening under the hood during a search.

Google’s AI now utilizes a method called “query fan out,” which breaks down complex queries into subtopics and conducts simultaneous searches to provide a comprehensive response.

The auction begins even before users finish typing. Importantly, AI can deduce commercial intent from purely informational searches.

For example, if someone asks, “Why is my pool green?” Google understands they’re troubleshooting, not shopping, but identifies potential product needs and displays ads for pool-cleaning supplies. The AI’s reasoning layer recognizes the solution products offer.

This change in auction logic focuses on matching offerings to the user’s inferred intent, rather than merely matching keywords to queries. Recognizing this shift is crucial, or I risk misinterpreting the user journey.

I’ve come to appreciate the intricacies of an intent-first approach. It doesn’t eliminate the need for keyword research but changes how I prioritize keywords. Now, I align campaigns to the user’s intent.

This strategy encourages me to consider:
- What problem is the user addressing?
- What stage of decision-making are they in?
- What role does the product play in solving their issue?
Realizing that the same intent can emerge from various queries and that identical queries can express different intents based on context has been illuminating. Phrases like “Best CRM” might indicate a need for feature comparison or a readiness to purchase; Google’s AI can now make those distinctions, and so should my campaigns.

This shift is more mental than tactical. While I still build keyword lists, they’re now organized by intent rather than match type. My ad copy speaks directly to user goals instead of echoing search terms.

Moving from keywords to intent isn’t merely a tactical alteration—it’s a strategic lens through which I plan for future campaigns, especially as Google enhances its AI-driven ad formats.

Reorganizing campaigns around intent rather than keywords has its immediate effects, impacting eligibility and landing page efficacy while fundamentally influencing system learning.

Inspired by this post on Search Engine Land.
February 5, 2026
Harnessing First-Party Data for AI-Enhanced Ad Success

I recently discovered how crucial first-party data has become in the evolving landscape of AI-powered advertising. It’s fascinating to see how it shapes the optimization and measurement of automated ad campaigns.

During a chat with Search Engine Land, I learned from Julie Warneke, CEO of Found Search Marketing, about the profound impact first-party data has on profitable advertising, regardless of potential changes to Google’s third-party cookie policies.

Embracing first-party data means tapping into customer information that I own, typically stored in a CRM, like lead details, purchase history, revenue, and customer value collected from various touchpoints.

This type of data is distinct from platform-owned or browser-based data, over which I have limited control.

Digital advertising has evolved over the years. The shift from focusing on impressions and clicks to outcomes emphasizes profitable conversions, according to Warneke. Advertisers who provide AI systems with quality customer data gain a significant edge.

Although rising cost-per-clicks (CPCs) are inevitable in paid media, first-party data enhances conversion quality, revenue, and return on ad spend, making higher costs justifiable with better results.

By leveraging first-party data tied to revenue and customer value, AI bidding systems can target users resembling high-value customers, even beyond usual demographic or geographic signals, leading to better conversions.

Among campaign types, Performance Max (PMax) thrives with first-party data activation. It performs best when I shift from manual optimizations to feeding it accurate data, allowing the system to learn, as Warneke highlighted.

Even small and mid-sized businesses can leverage first-party data, as seen in Warneke’s examples of success with small customer lists. The challenge lies in setting up proper infrastructure for tracking, consent management, and data flow.

Common mistakes include weak data capture, where brands rely on browser-side tracking that falters on platforms like iOS, and broken feedback loops from sporadic CRM data uploads. Continuous data streams are crucial.

Warneke advises taking a step back to audit how data is captured, stored, and relayed to platforms. Incremental improvements can pave the way for significant long-term gains, even starting with a small portion of a budget as a test.

Ultimately, AI optimization reflects the quality of signals received. By refining first-party data, I can influence outcomes favorably, avoiding inefficiency risks.

Inspired by this post on Search Engine Land.

February 5, 2026

Mastering Google Ads: Harnessing Signals for Success in 2026

By 2026, Google Ads automation has transformed drastically, with signal quality becoming paramount for exceptional performance. In this post, I’ll guide you on how signals drive these changes and how you can align them for optimal outcomes.

Back in 2015, I had tight control over my PPC campaigns. I directed Google on which keywords to pursue, set manual bids, and handled budgets with precision. Skillful use of spreadsheets allowed me to efficiently manage vast keyword inventories.

Those meticulously controlled days have faded. Now, in 2026, automation steers the wheel, moving beyond being a mere helper to a key driver of our advertising success. Fighting it is futile; embracing it is wise.

Automation has evened the playing field, liberating time for PPC marketers like me. But effectiveness now hinges on understanding how automation gleans insights from our data.

This piece delves into the intricacies of Google Ads signals, illustrating how to preserve their quality and prevent automation from veering off course.

The Mechanics of Signals in Automation

Contrary to seeing Google’s system as a mystery, it requires input of robust signals to perform optimally. Accurate signals lead to triumph; flawed data gears us for failure.

Automation runs on the signals I provide. AI interprets these signals, adjusting bids and targeting with unparalleled precision and efficiency.

While traditional documentation might suggest a primary focus on audience segments, the reality is that automation learns from a broader spectrum of signals.

Decoding What Qualifies as a Signal

In my experience, every component in a Google Ads account serves as a signal—shaping Google’s algorithm to determine successful advertising strategies.

Structural elements, budgets, conversion quality, and more provide insights into user intent, modeling a detailed blueprint for targeting.

The entire ecosystem, from landing pages to real-time data, contributes—guiding the AI in its decision-making process.

Here’s what stands out:

Conversion Actions: These signal what success looks like for my business.
Keyword Signals: Essential for decoding user search intent.
Creative Signals: Influences user attraction via visual cues.
Landing Page Signals: Ensures alignment with user expectations.
Bid Strategies: Communicates my advertising priorities to Google.

Innovation in signal interpretation has shifted, with the introduction of campaign total budgets, indicating a comprehensive financial commitment to Google.

Retailers, like Escentual.com, witnessed increased traffic through this approach, showcasing how signal precision offers tangible results.

Understanding Auction-Time Realities

Every user search triggers a unique bid calculation based on myriad signals, moving beyond generalized assumptions to precise decision-making.

This tailored approach ensures identification of “pockets of performance,” optimizing for predicted user outcomes aligned with our objectives.

Without quality signals, however, the system is left with assumptions, demonstrating the critical nature of providing accurate inputs.

Identifying and Prioritizing Signals

Not all signals wield equal influence. I’ve recognized that conversion signals bear the most weight, providing essential guidance for AI performance.

Conversion Dominance

Accurate conversion tracking underpins robust algorithmic learning, crucial for successful B2B and eCommerce advertising.

Enhanced Conversions and First-Party Data

In an era where third-party cookies disintegrate, relying on enriched data tracking is invaluable for understanding user interactions.

Quality audience signals and custom segments are imperative, enabling nuanced targeting, especially in niche markets.

Signal Category	Specific Input	Weight	Importance
Primary	Offline Conversion	Critical	Speaks to profit, not mere leads.
Primary	Value-based Bidding	Critical	Prioritizes profitable products.
Secondary	Customer Match Lists	High	Offers AI a model audience.
Tertiary	Keywords	Medium	Identifies search semantics.
Pollutant	Soft Conversions	Negative	Skews intent towards lower value.

Proper signals form the foundation for successful automation, requiring constant vigilance and correction of detrimental factors like signal pollution.

Combating and Correcting Signal Drift

Signal drift occurs when automation diverges from desired outcomes. Identifying subtle shifts in user targeting and making strategic corrections is key.

By tightening conversion signals, reinforcing audience data, and refining campaign structures, I can steer systems back to intended paths.

Tighten Conversion Signals: Eliminate non-revenue conversions.
Reinforce Audience Patterns: Update lists and segments.
Adjust Campaign Structure: Separate high and low intent traffic.

Remaining proactive is about guiding automation, ensuring the system aligns with my business goals while leveraging Google’s robust AI insights.

Building a Winning Signal Strategy

Creating a coherent signal strategy in 2026 requires segmenting data wisely, isolating brand traffic, and differentiating products by ROAS for clarity in campaign objectives.

Achieving Competitive Edge

In a landscape where automation is universally accessible, the true advantage lies in the quality of signals I feed to Google.

By protecting these signals and timely correcting any drift, I ensure Google’s automation works for me, transforming it into a powerful asset in my advertising arsenal.

Inspired by this post on Search Engine Land.

February 4, 2026

Google Ads Boosts Security with Multi-Party Approval Feature

I recently discovered an exciting update from Google Ads that promises to enhance the security of high-risk account changes. They have silently introduced a multi-party approval feature that ensures a second administrator must approve specific actions before they are finalized. This step adds a critical layer of protection against unauthorized or malicious changes, enhancing the overall safety of our accounts.

This new feature is particularly important as our ad accounts grow larger and carry more value. A single unauthorized change can quickly disrupt campaigns and even affect our billing. By requiring approval from another administrator, this feature effectively reduces such risks without hindering our regular campaign management processes.

For agencies and large teams like mine, this tool becomes invaluable. It helps us avoid costly mistakes and significantly bolsters our account security. I appreciate how Google is responding to the increasing necessity for robust access control.

Here’s how it works: when I, as an admin, initiate a sensitive change, Google Ads automatically sends an approval request to other eligible admins. This request is delivered as an in-product notification, requiring an action within 20 days—either approval or denial—otherwise, it simply expires, and the change will not be implemented.

Moreover, tracking the status of these requests is hassle-free. Each change request is tagged as Complete, Denied, or Expired, allowing my team to easily monitor and review our account changes.

To manage these approval requests, we can head over to the Access and security section within the Admin menu. It’s quite straightforward and keeps us in the loop with all ongoing requests.

This update points to a growing concern about account security, especially for advertisers managing large teams with multiple user permissions. With reports of expensive hacks escalating, this added security is a much-welcomed relief for us.

In the end, although multi-party approval may add a bit of friction to the process, it’s definitely a good kind. It grants us more control over who can make vital changes to our accounts, thus protecting them from unauthorized access. In my opinion, it’s a prudent step towards safer, more secure ad management.

Inspired by this post on Search Engine Land.

February 4, 2026
Boost Your Google Ads ROI by Mastering Quality Score

Have you been noticing those high CPCs? It might not be due to aggressive competition or your bidding strategy. What if the real issue lies in your ad quality? By improving your Quality Score, you can achieve better results without overpaying.

If you’re finding that CPCs are on the rise, it might not be about your budget or competitive bids. The hidden issue could be low ad quality, something I’ve come to recognize over time.

Allow me to guide you through understanding the most foundational metric in your Google Ads account— the Quality Score. If you want to stop overpaying and start winning on merit, you need to grasp how the Quality Score truly works.

Before we continue, let’s clear up any confusion. Google presents numerous “scores” and diagnostics. However, Quality Score is the one that genuinely matters and can’t be ignored.

Ad strength focuses on your ad-level diagnostics, ensuring your responsive ad adheres to best practices. Although important, it doesn’t affect auction performance directly.

Optimization score is more of a guiding tool for using Google’s recommendations, not a reflection of true campaign success.

However, Quality Score goes deeper. It plays a vital role, as it summarizes the quality of your ads at the keyword level. Its interaction with your bid decides your Ad Rank, influencing your ad’s position on the SERP and the cost per click.

Here’s the basic formula: Ad Rank = price × quality. The 1–10 score you see reflects the real-time quality evaluation Google conducts for every search. Simple, yet crucial.

Let’s set up your Google Ads dashboard to locate your Quality Score. Navigate to your Keywords report and add these columns: Quality Score, Expected CTR, Ad Relevance, and Landing Page Experience.

I recommend analyzing Quality Scores at the ad group level instead of focusing on individual keywords. If most of your keywords score a 7 or higher, you’re on the right path. Should they average a 5 or below, start improving ad quality swiftly.

Let’s address the three components you can improve:

1. Ad Relevance: The ‘message match’ involves ensuring that your keywords match both the ad and its landing page. Use Dynamic Keyword Insertion to automate this, or manually check that keywords feature in your ad copy and landing pages.

2. Landing Page Experience: The “Delivery” can be evaluated using PageSpeed Insights. If your landing page receives a “Below average” rating, the reasons often involve slow load times, inadequate mobile experiences, or poor navigation.

3. Expected CTR: The “Popularity Contest” shows that Google favors ads that get clicks. You can use Auction Insights for competitive analysis or check the Google Ads Transparency Center to see and learn from competitors’ successful ads.

While aiming for a 10/10 Quality Score everywhere may be overambitious, a regular quality review can pinpoint underperforming ad groups. Tackle the most lagging components to gradually lift your results.

Improving ad quality involves more work than just raising budgets, but the rewards of increased clicks at lower costs are undeniable.

This piece is part of our ongoing Search Engine Land series, presenting concise insights into Google Ads. In quick reads, Jyll covers diverse features to optimize your Google Ads results.

Inspired by this post on Search Engine Land.

February 4, 2026
Navigating Google Ads: Why Performance Max May Fail You

As a new advertiser, I’ve often found myself overwhelmed by Google’s Performance Max recommendations.
While well-intentioned, following them blindly can reduce my control and insight, leaving me to wonder if I’m truly making the best strategic decisions.
Initially, my journey with Performance Max felt promising. Google Ads reps offered support, but I soon realized their alignment was more with Google’s interests than my own business objectives.
It’s important to remember that they don’t have insight into my specific needs or business goals. They encourage the adoption of new features that might not align with my early-stage needs.
Understanding Google Reps’ Role
Google Ads reps are not strategic consultants for my business. Their main role is to promote Google’s products and services.
Your margins or cash flow are not their concerns. Their focus isn’t on whether my ads are profitable, but on pushing newer ad types and increasing my ad spend.
Therefore, understanding their incentives helps in taking their advice with the right perspective.
Performance Max provides efficiency and scale for Google. However, for a new advertiser, this can lead to unclear insights and misaligned strategies.
Performance Max: Who Does it Really Benefit?
Performance Max often benefits Google more than it benefits me as the advertiser.
Google controls how my budget is allocated across various channels, offering limited visibility into how these funds drive results. For me, this can be challenging, especially when new and needing clear insights.
This model monetizes Google’s ecosystem efficiently, but leaves me with diluted budgets and unpredictable costs.
Understanding these dynamics helps ensure my campaign choices are aligned with my actual business needs.
Rethinking Google’s ‘Best Practices’
What Google labels as ‘best practices’ might not fit my specific business strategy.
Recommendations often stem from aggregated data rather than being tailored for my unique circumstance, creating a gap between my needs and their blanket solutions.
For budding advertisers like myself, what’s globally optimal might not serve my business nuances and constraints.
The Value of Earning Automation
I’ve learned that automation success is something to be earned with data, not started with blindly.
Shopping Ads have provided me with high-intent, controllable data—essential for testing and learning.
This approach allows a clearer understanding of what truly works, paving the way for informed decisions.
When done right, these strategies lay a solid foundation for future automation without risking budget waste.
A Lesson in Practicality: Reviewing a Case Study
Consider a chocolatier’s experience—a new Google Ads account, $3,000 spent, but only one purchase. Incorrect conversion tracking led to misleading data.
After reworking the setup to a Shopping campaign, results began improving quickly, informing future campaigns with real performance data.
Why Shopping Ads Offer Insight
Focused on real behaviors and intent, Shopping Ads give granular control and transparency, which is crucial when each marketing dollar counts.
This control allows me to experiment deliberately, understanding and scaling the strategies that work.
Adopting a Hybrid Approach
A mix of Standard Shopping and selective Performance Max can be powerful once a data foundation is set.
This balance ensures sustainable growth by protecting proven strategies while allowing room for innovation driven by Performance Max.
Strategizing for Long-term Success
Starting small with clear data-driven campaigns creates a launchpad for successful automation.
By validating products and refining acquisition costs through Shopping Ads, I set the stage for Performance Max to elevate proven strategies.
It’s all about disciplined, strategic advertising that safeguards my investment and fuels long-term growth.

Inspired by this post on Search Engine Land.

February 4, 2026
Master Pro-Level Google Ads Targeting Strategies Today
I’ve discovered a game-changing PPC framework that not only predicts user intent but also extends beyond traditional search methods to connect your content with the right audience.

Search marketing continues to thrive, with Google reaching over $100 billion in ad revenue in just one quarter, primarily driven by search ads. However, relying solely on search won’t yield the results many businesses anticipate anymore.

During the SMX Next event, I learned from Google Ads Coach Jyll Saskin Gales that genuine performance now hinges on integrating traditional search with an expansive PPC strategy.

The challenge with traditional Search Marketing

In my experience as a search marketer, I excel at reaching individuals actively searching for what I offer. Yet, there’s an entire audience segment that aligns with my target market but hasn’t started their search journey.

The actual opportunity lies at the crossroads of user intent and audience fit.

Consider the term [vacation packages]. This could be queried by different groups like a family with kids, honeymooners, or retirees. While the keyword remains the same, each group requires unique messaging and offers.

Understanding targeting capabilities in Google Ads

There are two primary targeting types I focus on:
- Content targeting places ads in specific locations.
- Audience targeting displays ads to particular user types.
For instance, targeting [flights to Paris] is content targeting, while targeting users “in-market for trips to Paris” uses audience targeting. Google’s in-market audiences are crafted by analyzing various signals like user searches, browsing behavior, and location data.

The three types of content targeting
- Keyword targeting: Engage users when they search on Google, extending to dynamic ad groups and Performance Max.
- Topic targeting: Present ads next to content about specific subjects in display and video campaigns.
- Placement targeting: Present ads on particular websites, apps, YouTube channels, or videos where my ideal customers already engage.
The four types of audience targeting
- Google’s data: Prebuilt segments include detailed demographics, affinity segments, in-market segments, and life events, usable by any advertiser across most campaigns.
- Your data: Target website visitors, app users, and those engaging with my Google content using Customer Match, though remarketing is restricted for sensitive topics.
- Custom segments: Convert content targeting into audience targeting by crafting segments based on search behavior, interests, and user site or app preferences. Names vary across campaigns, such as “custom segments” and “custom search terms” in video.
- Automated targeting: This entails optimized targeting, audience expansion, and lookalike segments deriving new users from existing data.
Building a targeting strategy

To construct a cutting-edge targeting strategy, I need to address these two essential questions:
- How can I leverage Google Ads to promote my offer?
- How can I connect with a specific audience using Google Ads?
For instance, targeting Google Ads professionals for lead generation software could involve building tailored segments targeting users of the Google Ads app, visitors of industry-relevant sites like searchengineland.com, or searchers utilizing specific Google Ads terms like “Performance Max.”

Layering in content targeting, such as YouTube placements on industry educational channels and topic targeting around search marketing, enhances my outreach.

Strategies for sensitive interest categories

In cases where I operate within restricted categories like legal or healthcare, and cannot employ custom segments or remarketing, non-linear targeting becomes crucial. I focus entirely on the audience and ignore direct offers. Selecting any Google data audience with an overlapping potential and letting creative content filter it out helps tremendously.

Employ industry-specific terminology, acronyms, and visuals that resonate with and are recognizable to my target audience. Others will likely disregard it.

Remember: High CPCs aren’t the enemy

From my perspective, low-quality traffic poses the real challenge. It’s more beneficial to incur a $10 click with a 10% conversion rate than a $1 click with an infinitesimal 0.02% conversion rate.

When analyzing targeting strategies, I focus on conversion rates and cost per acquisition instead of merely cost per click.

Search alone can’t deliver the results you’re used to

By expanding beyond traditional search keywords and incorporating content and audience targeting, I can ensure the right people see my ads and achieve robust results.

Watch: Building a Modern Targeting Strategy Like a Pro + Live Q&A

Inspired by this post on Search Engine Land.
February 2, 2026