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Personalization

Dynamic Creative Ad Optimization in 2026: Definition, Benefits, and Best Practices

Aug 8, 2024

Learn how Dynamic Creative Optimization boosts ad performance in 2026. Personalize, test, and optimize campaigns for higher engagement.

Ankur Goyal

/home

Blog

Personalization

Dynamic Creative Ad Optimization in 2026: Definition, Benefits, and Best Practices

Aug 8, 2024

Learn how Dynamic Creative Optimization boosts ad performance in 2026. Personalize, test, and optimize campaigns for higher engagement.

Ankur Goyal

/home

Blog

Personalization

Dynamic Creative Ad Optimization in 2026: Definition, Benefits, and Best Practices

Aug 8, 2024

Ankur Goyal

Give your website a mind of its own.

The future of websites is here!

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Give your website a mind of its own.

The future of websites is here!

Book a demo

Free CRO Audit

Introduction

You spend hours tweaking ad visuals and copy, only to see flat engagement and wasted spend. It’s frustrating, especially when your audience scrolls past your best ideas. But what if your ads could automatically adjust based on what works?

Dynamic Creative Optimization uses AI to test, learn, and serve the most effective ad combinations in real-time. No more manual A/B testing or creative fatigue. Your campaigns will always run personalized ads that evolve with your audience.

If you’re wondering whether DCO works, the Dynamic Creative Optimization (DCO) market is expected to reach $1.9 billion by 2032, from $871 million in 2024. Now, these numbers paint a pretty positive picture.

But how do you get started?

In this guide, we’ll help you understand DCO: what it is, how it works, how AI helps, and the tools you need for the process.

But how do you get started?

In this guide, we’ll help you understand DCO: what it is, how it works, how AI helps, and the tools you need for the process.

But how do you get started?

In this guide, we’ll help you understand DCO: what it is, how it works, how AI helps, and the tools you need for the process.

What is dynamic creative optimization (DCO)?

Dynamic Creative Optimization is an advertising technology that uses AI to generate multiple, real-time ad variations.

It analyzes audience data, contextual signals, and past performance to optimize ad elements such as headlines, images, and CTAs to deliver more relevant and personalized ads that drive better conversions.

Here are the key highlights of DCO:

Personalizes ads in real time using data on user behavior and context.
The machine learning (ML) system learns what performs best and adjusts automatically.
You save time that would otherwise go into manual testing and redesign.
Maintains steady ad performance by preventing creative fatigue.
Works across different platforms and maintains consistent messaging.

Let’s break down how DCO really works in practice:

When you set up a DCO campaign, you feed the platform creative assets like headlines, visuals, product descriptions, CTAs, and brand messages.

The platform’s AI then mixes these pieces in different ways to create multiple ad combinations. It monitors how each version performs across different audiences and automatically adjusts which ads are shown based on what’s working best.

Example

Imagine you’re promoting a new electric car. Instead of creating one ad about “clean driving,” DCO lets you create hundreds of versions.

Someone browsing on a mobile device in a metro area might see an ad about “saving on fuel in city traffic.” A family researching cars on a weekend might see a version highlighting “spacious design and safety.” A tech enthusiast could get one that emphasizes “smart dashboard and connectivity.” All of this happens automatically, powered by audience data and live performance feedback.

Here’s what happens behind the scenes:

The DCO system gathers user data from sources like cookies, CRM records, or ad networks.
It segments users into groups based on behavior, interests, or intent.
It dynamically selects ad elements that best match each user segment.
The system runs continuous performance tests and replaces low-performing creatives with better ones.
Over time, it learns which messages drive the highest engagement and conversions.

DCO can also work hand in hand with marketing automation and CRM tools.

For example, if someone visits your site, adds a product to their cart, but doesn’t check out, DCO can trigger a retargeting ad for that same product with a personalized discount.

If a visitor browses your blog about home loans, they might later see an ad highlighting flexible mortgage options. In simple terms, DCO connects audience intent with creative delivery in real-time.

Dynamic Creative Optimization is an advertising technology that uses AI to generate multiple, real-time ad variations.

Here are the key highlights of DCO:

Personalizes ads in real time using data on user behavior and context.
The machine learning (ML) system learns what performs best and adjusts automatically.
You save time that would otherwise go into manual testing and redesign.
Maintains steady ad performance by preventing creative fatigue.
Works across different platforms and maintains consistent messaging.

Let’s break down how DCO really works in practice:

When you set up a DCO campaign, you feed the platform creative assets like headlines, visuals, product descriptions, CTAs, and brand messages.

Example

Imagine you’re promoting a new electric car. Instead of creating one ad about “clean driving,” DCO lets you create hundreds of versions.

Here’s what happens behind the scenes:

The DCO system gathers user data from sources like cookies, CRM records, or ad networks.
It segments users into groups based on behavior, interests, or intent.
It dynamically selects ad elements that best match each user segment.
The system runs continuous performance tests and replaces low-performing creatives with better ones.
Over time, it learns which messages drive the highest engagement and conversions.

DCO can also work hand in hand with marketing automation and CRM tools.

For example, if someone visits your site, adds a product to their cart, but doesn’t check out, DCO can trigger a retargeting ad for that same product with a personalized discount.

If a visitor browses your blog about home loans, they might later see an ad highlighting flexible mortgage options. In simple terms, DCO connects audience intent with creative delivery in real-time.

How does dynamic creative optimization work (in detail)?

Dynamic Creative Optimization follows a clear process that blends creative testing with real-time learning. Each step helps you move from manual ad setup to data-led, adaptive advertising.

Creative asset management

First, you add all your ad elements, such as headlines, taglines, product photos, offers, and calls to action, to the AI system. Basically, you feed AI the building blocks for your ads.

AI reviews these assets and groups them based on type and theme
Spots missing details like a weak call to action or repetitive visuals, before you launch
Creates a structure that allows endless combinations without breaking brand consistency.

Audience data collection

Next, the platform gathers information from various sources, including CRM systems, analytics tools, ad platforms, and user interactions. This data tells you who your audience is and how they behave.

AI reads this data to find behavioral patterns like buying habits, browsing time, and preferred devices
Builds smaller and more focused audience segments
Over time, it refreshes these segments according to new user actions and campaign feedback

Creative assembly and variation building

Now the platform starts creating ad variations by mixing the assets you uploaded. It can build dozens or even hundreds of versions in minutes.

AI tests which image fits best with a headline or which color drives more clicks.
Removes weak combinations before they go live, saving time and budget.
Ensures every version adheres to your layout and brand tone

Real-time ad delivery

Once the ad variations are ready, the system delivers them automatically to users across all your channels.

AI decides which version to display to each person based on demographic data such as age, location, and interests.
Reacts to small signals such as time of day and the user’s past clicks to pick the most relevant ad.
This keeps your campaigns personal and responsive without constant manual input.

Continuous performance tracking

Every time the system runs an ad, it also records the subsequent actions, including clicks, conversions, and engagement.

AI reviews this data constantly to see which creatives get the best response
Identifies patterns you might overlook, such as how tone and image style affect performance
Predicts when engagement might drop and starts testing new variations early

Automated scaling and optimization

As the campaign progresses, the system identifies the most effective combinations and expands their reach.

AI shifts more budget toward high-performing creatives automatically
Pauses or replaces weak ads while keeping tests running in the background
You keep improving results daily without needing to rebuild campaigns from scratch.

This process helps you transition from static ads to dynamic, constantly learning campaigns that adjust automatically to your audience and performance data.

Dynamic Creative Optimization follows a clear process that blends creative testing with real-time learning. Each step helps you move from manual ad setup to data-led, adaptive advertising.

Creative asset management

First, you add all your ad elements, such as headlines, taglines, product photos, offers, and calls to action, to the AI system. Basically, you feed AI the building blocks for your ads.

AI reviews these assets and groups them based on type and theme
Spots missing details like a weak call to action or repetitive visuals, before you launch
Creates a structure that allows endless combinations without breaking brand consistency.

Audience data collection

Next, the platform gathers information from various sources, including CRM systems, analytics tools, ad platforms, and user interactions. This data tells you who your audience is and how they behave.

AI reads this data to find behavioral patterns like buying habits, browsing time, and preferred devices
Builds smaller and more focused audience segments
Over time, it refreshes these segments according to new user actions and campaign feedback

Creative assembly and variation building

Now the platform starts creating ad variations by mixing the assets you uploaded. It can build dozens or even hundreds of versions in minutes.

AI tests which image fits best with a headline or which color drives more clicks.
Removes weak combinations before they go live, saving time and budget.
Ensures every version adheres to your layout and brand tone

Real-time ad delivery

Once the ad variations are ready, the system delivers them automatically to users across all your channels.

AI decides which version to display to each person based on demographic data such as age, location, and interests.
Reacts to small signals such as time of day and the user’s past clicks to pick the most relevant ad.
This keeps your campaigns personal and responsive without constant manual input.

Continuous performance tracking

Every time the system runs an ad, it also records the subsequent actions, including clicks, conversions, and engagement.

AI reviews this data constantly to see which creatives get the best response
Identifies patterns you might overlook, such as how tone and image style affect performance
Predicts when engagement might drop and starts testing new variations early

Automated scaling and optimization

As the campaign progresses, the system identifies the most effective combinations and expands their reach.

AI shifts more budget toward high-performing creatives automatically
Pauses or replaces weak ads while keeping tests running in the background
You keep improving results daily without needing to rebuild campaigns from scratch.

This process helps you transition from static ads to dynamic, constantly learning campaigns that adjust automatically to your audience and performance data.

Dynamic Creative Optimization follows a clear process that blends creative testing with real-time learning. Each step helps you move from manual ad setup to data-led, adaptive advertising.

Creative asset management

First, you add all your ad elements, such as headlines, taglines, product photos, offers, and calls to action, to the AI system. Basically, you feed AI the building blocks for your ads.

AI reviews these assets and groups them based on type and theme
Spots missing details like a weak call to action or repetitive visuals, before you launch
Creates a structure that allows endless combinations without breaking brand consistency.

Audience data collection

Next, the platform gathers information from various sources, including CRM systems, analytics tools, ad platforms, and user interactions. This data tells you who your audience is and how they behave.

AI reads this data to find behavioral patterns like buying habits, browsing time, and preferred devices
Builds smaller and more focused audience segments
Over time, it refreshes these segments according to new user actions and campaign feedback

Creative assembly and variation building

Now the platform starts creating ad variations by mixing the assets you uploaded. It can build dozens or even hundreds of versions in minutes.

AI tests which image fits best with a headline or which color drives more clicks.
Removes weak combinations before they go live, saving time and budget.
Ensures every version adheres to your layout and brand tone

Real-time ad delivery

Once the ad variations are ready, the system delivers them automatically to users across all your channels.

AI decides which version to display to each person based on demographic data such as age, location, and interests.
Reacts to small signals such as time of day and the user’s past clicks to pick the most relevant ad.
This keeps your campaigns personal and responsive without constant manual input.

Continuous performance tracking

Every time the system runs an ad, it also records the subsequent actions, including clicks, conversions, and engagement.

AI reviews this data constantly to see which creatives get the best response
Identifies patterns you might overlook, such as how tone and image style affect performance
Predicts when engagement might drop and starts testing new variations early

Automated scaling and optimization

As the campaign progresses, the system identifies the most effective combinations and expands their reach.

AI shifts more budget toward high-performing creatives automatically
Pauses or replaces weak ads while keeping tests running in the background
You keep improving results daily without needing to rebuild campaigns from scratch.

This process helps you transition from static ads to dynamic, constantly learning campaigns that adjust automatically to your audience and performance data.

What are the benefits of dynamic creative optimization?

Dynamic Creative Optimization helps you get more value out of your ad spend by using data and automation to refine what your audience sees. But if you are still doubtful about it, here are five clear benefits that make DCO worth using.

Better ad relevance

75% of marketers believe personalized experiences drive sales and repeat business. People respond better to content that resonates with their unique experiences and needs. But creating that level of personalization manually is almost impossible, especially for ads.

DCO helps you show the right message to the right person at the right time. Instead of running one generic ad, it tailors content based on audience data like age, location, and browsing behavior.

When your ads speak directly to people’s interests, they feel more personal and relatable. This often leads to higher engagement and stronger click-through rates without extra manual effort.

Faster creative testing

With DCO, you don’t have to spend days running manual A/B tests. The system automatically tests headlines, visuals, and calls to action to see what works best.

You can launch campaigns faster because testing happens in real time. As soon as one variation performs better, it gets more visibility while weaker versions are adjusted or removed.

This saves you a lot of time that you can invest in more strategic tasks. In fact, reports note that AI can save marketers up to 5 hours a week.

Continuous optimization

Unlike static ads that lose performance over time, DCO campaigns continue to improve. The system learns from every impression, click, and conversion. This means your ad creative stays fresh and relevant without constant redesigns. You can focus on strategy and storytelling while the platform handles daily fine-tuning.

Stronger ROI

Because DCO reduces wasted impressions and improves targeting, you get more results from the same budget. It helps you spend money on ads that actually convert instead of guessing what might work. Over time, this leads to higher returns on investment and a better understanding of which messages drive sales, sign-ups, and other key actions.

Easier scaling across channels

DCO works across platforms like social media, display, and video, so your message stays consistent everywhere. You can use one set of creative assets and let the system adapt them to different formats and audiences.

This saves you time and effort when running large campaigns. You can focus on the big picture while your ads adjust automatically to each channel’s audience and context.

Better ad relevance

DCO helps you show the right message to the right person at the right time. Instead of running one generic ad, it tailors content based on audience data like age, location, and browsing behavior.

When your ads speak directly to people’s interests, they feel more personal and relatable. This often leads to higher engagement and stronger click-through rates without extra manual effort.

Faster creative testing

With DCO, you don’t have to spend days running manual A/B tests. The system automatically tests headlines, visuals, and calls to action to see what works best.

You can launch campaigns faster because testing happens in real time. As soon as one variation performs better, it gets more visibility while weaker versions are adjusted or removed.

This saves you a lot of time that you can invest in more strategic tasks. In fact, reports note that AI can save marketers up to 5 hours a week.

Continuous optimization

Stronger ROI

Easier scaling across channels

This saves you time and effort when running large campaigns. You can focus on the big picture while your ads adjust automatically to each channel’s audience and context.

Better ad relevance

DCO helps you show the right message to the right person at the right time. Instead of running one generic ad, it tailors content based on audience data like age, location, and browsing behavior.

When your ads speak directly to people’s interests, they feel more personal and relatable. This often leads to higher engagement and stronger click-through rates without extra manual effort.

Faster creative testing

With DCO, you don’t have to spend days running manual A/B tests. The system automatically tests headlines, visuals, and calls to action to see what works best.

You can launch campaigns faster because testing happens in real time. As soon as one variation performs better, it gets more visibility while weaker versions are adjusted or removed.

This saves you a lot of time that you can invest in more strategic tasks. In fact, reports note that AI can save marketers up to 5 hours a week.

Continuous optimization

Stronger ROI

Easier scaling across channels

This saves you time and effort when running large campaigns. You can focus on the big picture while your ads adjust automatically to each channel’s audience and context.

What are the best practices for dynamic creative optimization?

Setting up a DCO campaign can feel overwhelming, but a structured approach helps you get clear insights, higher engagement, and better results. Here is how you make sure your DCO works properly:

Choose the right creative

Start with images, videos, headlines, product descriptions, and calls to action. Think about your audience’s needs, emotions, and motivations.

Include multiple variations for each asset type. For example, test short and long headlines, bright and subtle images, or different product angles. This gives the AI more options to find high-performing combinations.

Pro tip: Label your assets clearly. Organize them by theme, offer, or audience type. Clear labeling saves time when tracking which elements work best.

Segment your audience clearly

Divide your audience into groups based on demographics, behavior, past purchases, and engagement history. More precise segments let your ads speak directly to each group.

Use micro-segmentation. For example, separate frequent buyers from one-time visitors. AI can target each segment with highly relevant creative variations.

Pro tip: Keep your segments updated. Refresh them weekly with new user data to maintain relevance and prevent audience overlap.

Define campaign goals upfront

Decide whether your campaign focuses on clicks, conversions, sign-ups, or revenue. Clear goals guide which metrics you track and which creatives perform best. Break goals into smaller, measurable milestones. Track daily engagement, click-through rate, and conversion rate to see early trends.

Pro tip: Align creative elements with goals. For example, if you want conversions, highlight product benefits and limited-time offers prominently.

Set up proper tracking

Connect your DCO system to analytics, CRM, and ad platforms. Accurate tracking lets you see which creative combinations and audience segments perform best.

Test tracking before launch. Check every link, pixel, and tag to avoid gaps in data collection.

Pro tip: Monitor multiple metrics, not just clicks. Look at conversions, time on page, and bounce rates to get a full picture of performance.

Test and refine continuously

Run multiple ad variations and monitor real-time performance. Pause low-performing combinations and scale high-performing ones. Test one variable at a time when possible, such as the headline and image. This makes it easier to identify what drives results.

Keep a performance log and document which variations worked for which segments and during what time periods. This helps with planning future campaigns. However, the right AI tool will do it automatically.

Pro tip: Experiment with timing and placement. Test ads on different days, times, and channels to find peak engagement periods.

Keep creative fresh

Even top-performing ads lose impact over time. Rotate images, headlines, and offers regularly to maintain engagement. Use seasonal trends, current events, or user behavior insights to refresh content. Ads tied to relevant moments perform better.

Drop assets that consistently underperform. Replace them with new variations and track whether they improve overall results. While AI will keep the ad campaigns fresh, it doesn’t hurt to be proactive on your end as well. If anything, it would help you improve your marketing performance further.

Pro tip: Combine high-performing elements from different campaigns to create new variations. This can boost performance without needing a completely new creative.

Setting up a DCO campaign can feel overwhelming, but a structured approach helps you get clear insights, higher engagement, and better results. Here is how you make sure your DCO works properly:

Choose the right creative

Start with images, videos, headlines, product descriptions, and calls to action. Think about your audience’s needs, emotions, and motivations.

Pro tip: Label your assets clearly. Organize them by theme, offer, or audience type. Clear labeling saves time when tracking which elements work best.

Segment your audience clearly

Divide your audience into groups based on demographics, behavior, past purchases, and engagement history. More precise segments let your ads speak directly to each group.

Use micro-segmentation. For example, separate frequent buyers from one-time visitors. AI can target each segment with highly relevant creative variations.

Pro tip: Keep your segments updated. Refresh them weekly with new user data to maintain relevance and prevent audience overlap.

Define campaign goals upfront

Pro tip: Align creative elements with goals. For example, if you want conversions, highlight product benefits and limited-time offers prominently.

Set up proper tracking

Connect your DCO system to analytics, CRM, and ad platforms. Accurate tracking lets you see which creative combinations and audience segments perform best.

Test tracking before launch. Check every link, pixel, and tag to avoid gaps in data collection.

Pro tip: Monitor multiple metrics, not just clicks. Look at conversions, time on page, and bounce rates to get a full picture of performance.

Test and refine continuously

Pro tip: Experiment with timing and placement. Test ads on different days, times, and channels to find peak engagement periods.

Keep creative fresh

Pro tip: Combine high-performing elements from different campaigns to create new variations. This can boost performance without needing a completely new creative.

Setting up a DCO campaign can feel overwhelming, but a structured approach helps you get clear insights, higher engagement, and better results. Here is how you make sure your DCO works properly:

Choose the right creative

Start with images, videos, headlines, product descriptions, and calls to action. Think about your audience’s needs, emotions, and motivations.

Pro tip: Label your assets clearly. Organize them by theme, offer, or audience type. Clear labeling saves time when tracking which elements work best.

Segment your audience clearly

Divide your audience into groups based on demographics, behavior, past purchases, and engagement history. More precise segments let your ads speak directly to each group.

Use micro-segmentation. For example, separate frequent buyers from one-time visitors. AI can target each segment with highly relevant creative variations.

Pro tip: Keep your segments updated. Refresh them weekly with new user data to maintain relevance and prevent audience overlap.

Define campaign goals upfront

Pro tip: Align creative elements with goals. For example, if you want conversions, highlight product benefits and limited-time offers prominently.

Set up proper tracking

Connect your DCO system to analytics, CRM, and ad platforms. Accurate tracking lets you see which creative combinations and audience segments perform best.

Test tracking before launch. Check every link, pixel, and tag to avoid gaps in data collection.

Pro tip: Monitor multiple metrics, not just clicks. Look at conversions, time on page, and bounce rates to get a full picture of performance.

Test and refine continuously

Pro tip: Experiment with timing and placement. Test ads on different days, times, and channels to find peak engagement periods.

Keep creative fresh

Pro tip: Combine high-performing elements from different campaigns to create new variations. This can boost performance without needing a completely new creative.

Dynamic Creative Optimization case studies

Now, let's see how DCO efforts bring real results through these two case studies:

Flipkart case study

The Flipkart team analyzed historical data for the mobile category and observed that, while users frequently viewed multiple products, they rarely converted. Many added items to their carts and then abandoned them. To re-engage these users, Flipkart used Dynamic Creative Optimization to deliver a series of personalized ad creatives for the Samsung Galaxy J7 Pro.

Each ad focused on a different feature or motivator:

The first ad showcased the camera quality
The second highlighted its social-camera appeal
The third focused on display and memory performance
The fourth featured quick delivery
The fifth promoted affordability, positioning it as “under ₹10,000”
The sixth mentioned its bestseller status with a 4.4 rating
The seventh emphasized positive user reviews
The eighth displayed limited-time offers, exchange deals, and discounts
The final ad reminded users that the offer was about to end

Results

Flipkart later scaled the campaign across the entire mobile category, using automation to generate real-time creative variations for different SKUs. This approach helped them deliver more relevant ads, segment audiences better, and boost conversions through smarter, data-driven personalization.

FEEDB<CK case study

FEEDB<CK, a Spanish creative-production agency, collaborated with premium food retailer Ametller and used automation to create dynamic video ads for social channels. They generated over 2,000 ad variations using real-time product and campaign data. The team automated creative production and campaign management, ensuring each ad stayed fresh and relevant to daily product and promotion updates.

Results

Thanks to their DCO efforts, the brand:

Achieved a 58% increase in ROAS through dynamic video personalization
Recorded a 30% reduction in CPA, improving campaign efficiency
Produced 2,000+ ad variations with real-time updates
Delivered high-quality creatives at scale without manual edits

Ruokabokshi case study

Genero, a growth marketing agency, noticed that Ruokaboksi’s generic ads weren’t cutting through in local markets. They automated and personalized ad creatives across 110+ locations. The workflow involved:

Connecting a dynamic feed listing cities, demographics, and promotions.
Building template creatives that pulled in city names, local slang, and demographic-specific imagery.
Launching a master ad set that generated 1,200+ ad variants automatically from the feed. Each variant targeted neighborhoods, family types, singles, and couples with tailored visuals and CTAs.

Results

Lowered cost-per-acquisition by 47%.
Reduced cost-per-lead by 82.4%.
Launched 230 ad sets and over 1,200 localized ads across Finnish markets.
Produced highly relevant creative at scale without overwhelming design resources.

This case shows how localized dynamic creatives can significantly boost efficiency and performance when automated correctly.

The future of Dynamic Creative Optimization looks promising as brands move toward more personalized and data-driven advertising. It’s becoming smarter, faster, and more automated, making it easier to create thousands of ad variations that resonate with your audience in real time.

Here’s what’s shaping the future of DCO:

AI-driven personalization: Ads will automatically adapt visuals, copy, and offers to match user behavior and context.
Real-time decision-making: Campaigns will learn and optimize on the go instead of waiting for manual updates.
Deeper integrations: DCO will connect directly with CRM, analytics, and eCommerce tools for sharper audience targeting.
Creative automation at scale: Marketers will be able to test hundreds of ad combinations in minutes instead of days.
Improved measurement: DCO platforms will offer better visibility into nuanced KPIs like engagement quality, creative fatigue, conversion lift, and audience segment performance

How can Fibr AI help with your DCO strategy?

With Fib AI, you can automate your entire DCO strategy and ensure your audience sees the most personalized version of your ads, landing pages, and other campaigns.

Fibr AI’s personalization agent, Liv, makes every user interaction feel personal. You just have to sign up with Google, Meta, TikTok, or LinkedIn, and Liv automatically imports your ad campaigns and audience segments. You can also link the landing page you want personalized for your ads.

Once the assets are imported, Liv:

Scans key elements, such as headlines, images, and CTAs.
Analyzes which parts to personalize for maximum impact.
Lets you see all ads tied to your URL across platforms in one dashboard
Prioritizes high-impact ads to maximize growth potential.
Generates clear impact scores for each to help you identify the best campaigns.

You also get MAX, the AI-powered experimentation partner. It:

Crawls the page on both desktop and mobile viewports to extract headlines, CTAs, images, and layout blocks
Pulls real-time GA4 data, including bounce rates, scroll depth, and exit percentages, to reveal user behavior insights
Analyzes ad structure to pinpoint key areas with high optimization potential.
Generates variants according to the hypotheses, incorporating changes to copy, images, and layout.
Lets you personalize variants through an intuitive no-code visual editor.
Offers one-click approval for quick experiment setup, with options for more detailed customization

The multivariate tests run continuously, and your audience always sees the most personalized variant.

Privacy-first optimization: With new data laws, tools will rely more on contextual and first-party data for personalization.

Give your website a mind of its own.

The future of websites is here!

Book a demo

Free CRO Audit

Give your website a mind of its own.

The future of websites is here!

Book a demo

Free CRO Audit

Make your ads smarter with DCO

Dynamic Creative Optimization turns your static ads into campaigns that learn and adapt.

Instead of guessing what works, AI-powered DCO runs multiple variations, tracks performance in real time, and reaches the right audience with the right message. You save time, reduce spends, and improve engagement across every channel.

By using DCO, you get continuous insights into which creative combinations perform best. You can test headlines, images, and offers instantly, and the system adjusts campaigns based on actual audience behavior. This keeps your ads relevant and engaging without constant manual effort.

Fibr AI takes DCO further and helps you get more from your campaigns. With Fibr AI, you can:

Test hundreds of ad variations at once and see what resonates with each audience.
Segment audiences precisely using behavior, interests, and past engagement.
Track performance across all channels in real time.
Adjust campaigns automatically to maintain strong results and reduce wasted spend.

Sign up for a 30-day free trial with Fibr AI and watch your ads adapt, improve, and deliver better results for every campaign.

FAQs

What is DCO used for?

DCO is used for creating personalized, dynamic ads that adapt in real time to audience behavior, preferences, and context. It helps increase engagement, improve conversions, and reduce wasted ad spend.

What is the future of DCO?

The future of DCO is more automated and AI-driven, with deeper personalization, cross-platform integration, and predictive optimization that allows campaigns to adapt instantly to changing audience behavior and trends.

How does DCO work?

DCO works by combining creative assets like headlines, images, and calls to action with audience data. AI tests multiple combinations, delivers the best-performing versions to each segment, tracks results, and continuously optimizes campaigns in real time.

Is $10 a day enough for Google ads?

$10 a day can be enough for Google Ads if you target a very specific, low-competition audience or run campaigns with limited reach. However, in competitive markets or for broader goals, higher daily budgets are usually required for meaningful results.

What is the difference between DCO and programmatic?

The difference between DCO and programmatic is that programmatic automates the buying and placement of ads across channels based on audience targeting, bidding, and inventory availability.

DCO, on the other hand, focuses on creating multiple ad variations and dynamically optimizing them for each viewer.

While programmatic decides where and to whom an ad is shown, DCO determines which creative that specific viewer needs to see to maximize engagement and conversions.

About the author

Ankur Goyal

Ankur Goyal, a visionary entrepreneur, is the driving force behind Fibr, a groundbreaking AI co-pilot for websites. With a dual degree from Stanford University and IIT Delhi, Ankur brings a unique blend of technical prowess and business acumen to the table. This isn't his first rodeo; Ankur is a seasoned entrepreneur with a keen understanding of consumer behavior, web dynamics, and AI. Through Fibr, he aims to revolutionize the way websites engage with users, making digital interactions smarter and more intuitive.