How display ads can boost organic reach and ROI: What SEOs need to know

Display ads are a form of pay-per-click (PPC) advertising, where marketers pay each time someone clicks their visual ad rather than a text ad. 

While traditional PPC campaigns—like Google Search Ads—target people actively searching for something, display ads appear across websites, YouTube, Gmail, and apps within Google’s Display Network, reaching users based on interests, demographics, or browsing behavior. 

In other words, display ads focus more on awareness and retargeting than on direct intent.

For SEOs, display ads matter because they influence brand signals, search behavior, and click-through rates. A strong display campaign can make users more familiar with a brand before they ever see it in search results—raising branded search volume and engagement. This “halo effect” improves the likelihood that organic listings perform better, particularly for competitive keywords.

Additionally, display and SEO data can work together to reveal cross-channel insights: which creative or audience segments drive more organic traffic, which landing pages retain users from both paid and organic sources, and how remarketing impacts conversion from organic sessions. 

SEOs who understand display ad strategy can better align their content, messaging, and measurement with broader visibility goals across the full marketing funnel.

What is display advertising?

Display advertising refers to visual promotional content that appears across websites, apps, and digital platforms. They’re not just old-school banner ads you’re thinking of from 2005—the format has evolved into something far more sophisticated. 

Modern display advertising includes:

• Static images and responsive units that adapt to different screen sizes
• Rich media with interactive elements
• Video ads that play in-stream or out-stream
• Programmatic formats that use AI to optimize creative combinations in real time

Display ads are practically everywhere online, such as:

• Google Display Network (GDN), a collection of millions of websites, apps, and videos
• Direct publisher placements on premium sites like The New York Times or Forbes
• Social media platforms like Facebook, Instagram, and LinkedIn, where ads appear in users’ feeds and sidebars

The ecosystem is massive, with global display ad spending hitting $207.4 billion in 2023, and it’s projected to reach $266.6 billion by 2026.

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Types of display ads and their strategic uses

Display ads encompass five main formats, each designed to achieve different marketing objectives while supporting your broader SEO and brand visibility goals.

Understand when and how to deploy each type to enhance your display campaigns to drive strategic growth.

Static banners

The workhorses of display advertising, these fixed-image ads might seem basic compared to flashier formats, but they’re incredibly cost-efficient for building broad brand awareness. 

Think of them as digital billboards that appear across millions of websites. 

Static banners typically cost less than rich media formats and can still deliver consistent impressions. They’re perfect for when you need maximum reach on a limited budget or when testing new audience segments before investing in more complex creative assets.

Responsive display ads

Responsive display ads dynamically adjust their size, appearance, and format to match the content and layout of websites where they appear. So whether your ad shows up on a mobile app, desktop website, or tablet interface, it’ll look native and properly formatted. 

Rich media ads

These ads elevate engagement through interactivity and movement. They might include expandable galleries, mini-games, or interactive product configurators that invite users to engage rather than just view. 

These work exceptionally well for complex products that benefit from demonstration or when targeting audiences who’ve already shown purchase intent.

Example: A car manufacturer could create an ad where users can customize vehicle colors and features right within the banner, generating qualified interest before anyone clicks through. 

Video display ads

These ads appear as in-stream (playing before YouTube videos) or outstream (embedded within article content), capturing attention through sight, sound, and motion. 

Example: A B2B software company runs a 15-second explainer video to highlight their core benefits, knowing that even viewers who don’t click will remember the brand when they’re ready to research solutions. 

Dynamic retargeting ads

The pinnacle of personalization at scale, especially for ecommerce operations, these ads automatically pull product images, prices, and details from your website’s structured data to show users exactly what they viewed but didn’t purchase. 

Example: Someone who browsed three specific running shoes on your site might see those exact shoes with current pricing and a “10% off if you buy today” message across multiple websites they visit afterward. 

The display advertising paradox facing SEOs today

Traditional SEO is largely measured in organic traffic and rankings. But display advertising operates in a murky world of brand awareness and future intent creation while also living outside the organic reporting dashboard, which may be challenging for SEO professionals with limited paid advertising experience.

But since display ads indirectly strengthen organic performance by building brand familiarity, increasing branded searches, and reinforcing topical authority, they cannot be ignored.

While search campaigns respond to what users explicitly want, display ads pop up uninvited, hoping to capture attention before someone scrolls past.

Display advertising works by:

• Creating demand by interrupting users during their regular browsing, unlike search ads, which respond to existing demand through keyword targeting and search intent. 
• Creating a feedback loop that amplifies your SEO content marketing efforts—the more touchpoints users have with your brand across display and organic channels, the stronger your expertise in specific topics becomes.
• Supporting remarketing campaigns that keep your content top-of-mind for users who’ve already visited your site, increasing the likelihood they’ll return through organic search rather than bouncing to competitors. 

Display advertising doesn’t compete with search, it feeds it. Every impression plants a seed that might bloom into a branded search weeks later. 

But if you’re measuring success with last-click attribution (like most SEO teams do), it’s hard to see this connection.

Display ads are essentially priming the pump for your organic search performance—they generate brand awareness that translates into more branded queries, which in turn sends positive signals to Google about your site’s authority and relevance.

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Read more: Organic search vs. paid search

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Display advertising fundamentals for SEO

Display advertising operates on fundamentally different principles than organic search optimization. It requires SEO professionals to shift their thinking from responding to user intent to creating demand before intent even exists.

Push vs. pull marketing models

Traditional SEO strategies pull users in through search queries. Display advertising flips that marketing approach by pushing out messages to audiences, rather than waiting for them to search.

Think about it this way: SEO is like setting up a shop on a busy street and waiting for people who need what you’re selling to walk in. Display advertising is more like sending out a sales rep to knock on doors in neighborhoods where your ideal customers live.

Display ads appear while users browse other content, essentially interrupting current activity rather than responding to an expressed need. This interruption model means you’re catching people during their daily content consumption—reading news, watching videos, checking social media—rather than during active problem-solving moments.

Targeting beyond keywords and search intent

Display advertising opens up sophisticated targeting mechanisms that go way beyond the keyword-centric approach SEOs are used to. It lets you reach audiences based on who they are rather than what they’re searching for, such as:

• Demographics
• Browsing behavior
• Interests
• Past interactions with your brand

The audience insights you gather from display campaigns provide invaluable intelligence for developing SEO personas and understanding user behavior beyond search queries, including:

• Which demographics engage most
• What creative messaging resonates
• Which placements drive quality traffic

Behavioral targeting takes this even further. You can reach users based on their purchase history, content consumption patterns, or even life events. Someone just started researching business loans? Perfect time to introduce your accounting software. Someone’s been reading multiple articles about remote work tools? They might be ready for your productivity platform.

How display ads and organic search performance can work together

Display advertising generates demand rather than just capturing it. While SEO waits for intent to develop, display advertising actively creates intent by making audiences aware of solutions they didn’t know existed. 

Those newly aware users then turn to search, where your optimized content is perfectly positioned to capture them.

Here’s how this works: 

1. Someone sees your display ad while reading their favorite blog. 
2. They don’t click right away (honestly, most people don’t). 
3. But two days later, when they face the problem your product solves, guess whose brand name pops into their head? 
4. Then they will do a branded search for your product, giving you a higher conversion rate than a generic keyword.

Display advertising doesn’t just drive direct conversions—it creates a compounding effect that significantly boosts your organic search performance through increased brand awareness and search demand.

This creates what B2B marketers increasingly recognize as the awareness-to-conversion pipeline. Display advertising fills the top of your funnel with brand-aware prospects who later convert through organic search. 

The impact on click-through rates alone makes this worthwhile. When your brand appears in organic results after users have seen your display ads, they’re significantly more likely to click on your listing over competitors. 

Google’s algorithm will pick up on these improved engagement signals—higher CTR, longer dwell time, lower bounce rates—and reward you with better rankings.

And the relationship works both ways: A strong organic presence makes your display advertising more effective because users recognize and trust brands they’ve seen in search results. 

Each channel reinforces the other, compounding returns that neither could achieve alone.

Attribution and privacy challenges in display advertising

Measuring success can be challenging in display advertising, making it difficult for marketers to understand which elements of a campaign actually drive results. 

Measuring search vs. display advertising

The push methodology completely changes how to think about targeting and measurement. The real measure of display ad success isn’t immediate conversions—it’s influence on future behavior. 

In SEO, you can directly correlate keyword intent with conversions because users tell you what they want. 

Display ads, on the other hand, excel at planting seeds. If someone sees your ad for accounting software while reading business news, they may not be ready to buy today, but when tax season rolls around, your brand may likely pop into their head.

Metrics look completely different in display advertising. Instead of measuring immediate conversions, you often track metrics that happen days or weeks after exposure to an ad, including:

• View-through conversions
• Brand lift
• Assisted conversions 

While a great click-through-rate (CTR) for SEO might be anything above 3%, display advertising averages below 1%, because you’re reaching people who weren’t actively looking for you. This allows you to develop entirely new audience segments that never would have found you through search alone.

iOS privacy changes and cookie deprecation impacts

Privacy changes have fundamentally reshaped how display advertising operates. Apple’s App Tracking Transparency framework and Safari’s Intelligent Tracking Prevention, combined with Google’s planned allowing users to make informed choices about privacy, have forced advertisers to rethink their entire attribution and targeting strategies.

These privacy shifts have hit display advertising particularly hard because it relies heavily on cross-site tracking and device identifiers. Advertisers can no longer easily follow users across websites and apps to build comprehensive behavioral profiles. 

This means:

• Less precise audience targeting
• Reduced campaign personalization
• Significantly more challenging attribution measurement

Many brands are seeing their display campaign performance metrics become murkier, making it harder to prove ROI and optimize spending.

And the ripple effects keep expanding. Display advertising networks have scrambled to develop privacy-compliant alternatives like contextual targeting, first-party data solutions, and privacy sandboxes. But these replacements often deliver less granular insights than the tracking methods they’re replacing. 

So while user privacy has improved, advertisers are grappling with higher costs per acquisition, broader audience targeting, and the need to invest heavily in first-party data collection strategies to maintain display advertising effectiveness. 

Cross-device tracking limitations

Display ads rarely generate immediate clicks—they create awareness, build consideration, and influence future search behavior, impacts that last-click models ignore entirely.

Last-click attribution, which gives 100% of the conversion credit to the final touchpoint before a purchase, completely overlooks display ads that may have introduced customers to your brand weeks earlier.

Example: A marketing director sees your display ad on their phone during their commute. Two weeks later, they search for your brand on their work laptop. A month after that, they fill out a demo request form after clicking a LinkedIn ad. 

This journey involved three different devices, three different channels, and 45 days between first touch and conversion. How do you attribute that sale?

Cross-device tracking limitations make this puzzle hard to solve with current technology. Display platforms can’t connect mobile ad views to desktop conversions unless users are logged into the same account across devices. Also, business and personal device usage creates additional blind spots, and VPNs and privacy tools fragment the picture further.

Different touchpoints serve different purposes in the customer journey. The initial display impression might seem worthless in conversion reports because it doesn’t directly drive the final click or purchase—making it appear like wasted ad spending if you’re only looking at last-click attribution.

But without it, the subsequent search might not have happened. Display advertising often plays catalyst rather than closer, a role that traditional attribution models can’t properly value or track.

Platform-specific measurement conflicts and data siloing

Every advertising platform uses its own model to measure attribution, creating a confusing landscape. For example: 

• Google Ads gives display campaigns credit for conversions within a 30-day window using data-driven attribution.
• Meta attributes conversions within 1 day of view or 7 days of click.
• Amazon DSP uses a 14-day attribution window.
• Google’s Smart Bidding optimizes for modeled conversions that include statistical estimates.
• LinkedIn counts video views differently than YouTube.

These measurement conflicts force you to build a custom model to track metrics for each platform, forcing you to combine information from multiple sources, use separate resolution tools to match users across platforms, and normalize conflicting data into actionable insights.

Data siloing can happen when information gets trapped in separate systems, departments, or tools that don’t communicate with each other. 

This fragmentation can create a frustrating reality where your marketing team can’t see the full customer journey, your sales team lacks context about behavior, and your content team misses crucial insights about what actually drives conversions. 

So instead of having one unified view of your audience, you end up with scattered puzzle pieces that never quite form a complete picture.

And the impact goes beyond just inconvenience: Data silos can lead to duplicated efforts, inconsistent messaging, missed opportunities, and decisions based on incomplete information. 

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Read more: Marketing attribution guide

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5 advanced display ad targeting strategies

Basic targeting won’t cut it anymore when you’re trying to compete for attention in today’s crowded display ad ecosystem. 

Advanced targeting strategies will help you move beyond basic demographic filters to reach highly specific audience segments based on behavior, intent, and context, ultimately improving ad relevance and campaign efficiency.

Each of these strategies works best when combined with others. Think of them as layers in your targeting strategy rather than standalone solutions. The real power comes from understanding which combinations make sense for your specific audience and campaign goals.

Contextual targeting aligned with SEO content categories

Contextual targeting places your ads alongside content that matches specific topics, keywords, or categories. Basically, you’re showing ads based on what someone’s reading right now, not their past browsing history.

This works brilliantly when you’ve already done your SEO research and persona development to understand exactly what content your audience consumes. 

Say you’re selling project management software and SEO research shows your audience reads productivity blogs and remote work guides. You can target those exact content categories, catching readers when they’re thinking about workflow optimization.

However, context doesn’t always equal intent. Someone reading about productivity hacks might just be procrastinating (we’ve all been there). 

That’s why you’ll want to layer this strategy with other signals like time of day or device type—mobile users reading during work hours often have different intent than desktop users browsing at 10 PM.

Custom intent audiences based on competitor keyword searches

Google’s Custom Audiences feature lets you target people based on their recent search behavior by entering specific keywords and phrases into the platform. 

You can build these intent-driven audiences using search terms people actually type into Google, including your competitors’ brand names and product keywords. This means you’re reaching users who’ve already shown interest in what you’re selling, right when they’re actively researching solutions.

Think of this as intercepting users who’ve already shown purchase intent through their search behavior. This strategy shines when you’re a challenger brand trying to take some market share. 

If someone searches for “Salesforce alternatives” or “HubSpot pricing,” that’s your moment to appear with a compelling offer. 

Mix branded competitor terms with problem-aware keywords for better quality scores. For example, instead of just targeting “Mailchimp,” also include “email automation for ecommerce”—you’ll catch people at different awareness stages while keeping costs reasonable.

Customer matching plus first-party data layering

Customer matching is essentially your secret weapon for precision targeting in display advertising. It works by taking your existing customer data—email addresses, phone numbers, or other identifiers—and matching it against user profiles on advertising platforms like Google, Facebook, or programmatic networks. 

Instead of casting a wide net and hoping for the best, you’re targeting people you already know have a relationship with your brand.

Customer matching lets you create highly specific audience segments based on actual customer behavior and value. You can target high-spending customers with premium product ads or reach recent purchasers with complementary offerings. 

But the real magic happens when you layer in additional first-party data—information collected directly from a user—like purchase history, browsing behavior, or engagement patterns.

This approach dramatically improves your display ad performance metrics. You’re not just reducing wasted impressions on irrelevant audiences—you’re increasing click-through rates, conversion rates, and overall ROI because you’re reaching people who already have a proven interest in what you’re selling. 

Once you’ve established matched audiences, you can layer on additional first-party data to create hyper-targeted segments. Maybe you want to show different creative assets to customers who purchased in the last 30 days versus those who haven’t bought in six months. Or perhaps you want to exclude recent purchasers from acquisition campaigns entirely. 

Customer matching gives you granular control, turning generic display ads into personalized experiences that actually drive results.

Geographic and language segmentation for international SEO support

Geographic targeting becomes essential when you’re running international SEO campaigns and need display ads to support local market penetration. 

For example: A company expanding into Germany might target Berlin’s tech district with English ads (for international workers), while running German campaigns for the broader metro area.

However, IP-based location targeting isn’t perfect, as VPNs and mobile networks can throw off accuracy. This can be compounded by combining location signals with language preferences and time zone data. 

Also, remember that Google’s location targeting defaults to “people in, regularly in, or interested in” your location, so always switch to “presence” for true local targeting.

Negative placement lists to avoid brand safety issues

Block specific websites, apps, or content categories where you don’t want your ads appearing, a tactic called negative placement. This isn’t just about avoiding controversial content—it’s about protecting your brand’s positioning and ensuring contextual relevance.

Smart advertisers maintain dynamic exclusion lists based on performance data and brand guidelines. For example, you might exclude gaming sites if you’re selling B2B software, or block news sites during volatile news cycles that could overshadow your message. 

However, be wary of over-blocking, which can severely limit your reach—you’re essentially bidding on a smaller inventory pool. 

The sweet spot is excluding the bottom bit of placements by performance and to use category exclusions sparingly. Also, remember that new sites and apps launch constantly, so update your exclusion list quarterly to stay effective.

AI and display advertising

AI has transformed how search professionals connect paid and organic channels, moving beyond surface-level automation into strategic intelligence that drives measurable outcomes. It has shifted from a nice-to-have feature to the backbone of efficient display ad campaigns. 

Instead of manually A/B testing a handful of ad variants, machine learning algorithms can now simultaneously test hundreds of creative combinations across networks, adjusting headlines, images, colors, and CTAs in real-time based on engagement patterns. 

These systems can learn which creative elements resonate with specific audience segments, effectively creating personalized ad experiences at scale without the traditional overhead of building dozens of individual campaigns.

Creative production

AI can automatically generate, test, and optimize thousands of creative element variations for ads, while simultaneously measuring their impact on organic search behavior.

Tools like MidJourney, DALL-E, and Adobe Firefly can now generate thousands of unique visuals tailored to specific SEO personas in minutes. 

These aren’t generic stock photos with different filters—these AI systems can create hyper-personalized imagery that aligns with audience segments. Imagine generating distinct visual styles for each stage of your buyer’s journey, matched to content themes that already perform well for you in organic search. 

The strategic advantage extends beyond just faster production. AIs can test multiple visual concepts that would be cost-prohibitive with traditional design. 

For example, running 100 variations to find the exact color psychology that resonates with your ICP, automatically adjusting imagery based on geographic and cultural preferences for international campaigns, or testing which visual metaphors drive engagement for specific keyword themes.

Predictive bidding

Predictive bidding represents the biggest leap forward in display advertising efficiency since automated ad buying. This shift has fundamentally changed how advertisers reach audiences at scale.

For context, automated ad buying uses algorithms and real-time data to purchase digital advertising space in real-time. Predictive bidding replaces the traditional manual process of negotiating and buying ads directly from publishers. 

Machine learning models can now analyze millions of intent signals, such as browsing patterns and time-of-day behaviors, to dynamically adjust cost-per-milles (CPMs) and cost-per-clicks (CPCs) millisecond by millisecond. 

Modern AI bidding engines factor in cross-device journeys, seasonal trends, competitive auction dynamics, and even weather patterns to predict conversion probability before placing each bid. 

LLM-driven campaign insights

Instead of wrestling with complex reporting interfaces or waiting for analysts to pull custom reports, marketers can now query campaign performance using natural language. 

For example, typing “Show me which display placements drove the most branded search lift last quarter” becomes an answerable question in seconds, not hours, when working with AI. 

AI assistants don’t just retrieve data, they identify patterns, suggest optimizations, and even flag anomalies that human reviewers might miss. 

For SEO professionals, this might feel more like having a conversation with your campaign instead of interrogating it through rigid report templates.

Expanded conversion tracking

Traditional last-click models completely miss display ads’ impact on SEO. But machine learning attribution can track how display impressions correlate to increases in branded searches, direct traffic, and even organic conversion rates weeks after initial exposure. 

By combining display impression data with SEO conversion tracking, AI models can forecast blended ROI across channels. 

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For example, a display campaign driving a 0.05% CTR might actually be generating a 25% lift in organic branded searches two weeks later. 

This unified view can transform how teams allocate budget between paid display and content creation, moving from siloed channel optimization to a true cross-channel strategy.

Build display advertising competency as an SEO professional

Display advertising might seem challenging at first, but it’s a natural extension of the audience intelligence, content strategy, and data analysis skills you’ve already mastered through SEO work. 

Where SEO responds to existing demand through search queries, display ad marketing creates that demand by reaching users before they even know what to search for.

For SEO professionals ready to experiment with display campaigns, start small with remarketing to your existing organic traffic. This lets you leverage an audience you already understand—people who’ve engaged with your content—while learning the mechanics of campaign setup, creative testing, and performance optimization. 

Approach display advertising with the same test-and-learn mindset that makes great SEOs successful. Experiment, measure, adjust, and gradually build expertise. Display advertising rewards that same systematic approach to improvement.

Learn more on how display ads fit into the SEO big picture with our guide on content marketing strategy.