What is Dynamic Creative Optimization (DCO)? Benefits & Examples
By IBM Watson Advertising | 15 August 2022
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Advertising technology is rapidly advancing, opening up opportunities for advertisers to target their audience with highly personalized, relevant material that is more likely to convert. Dynamic creative optimization (DCO) is a key example, helping to uncover meaningful insights and achieve campaign success.

In this article, we’ll define dynamic creative optimization and explain how it works. Then, we’ll dive into the benefits of dynamic advertising and explore some case studies showing how dynamic creative can be used to increase conversions.

What is dynamic creative optimization?

Dynamic creative optimization personalizes advertisements toward specific viewers based on information about that viewer. For example, the ad may show different users different creative items based on their previous browsing habits or products added to their shopping cart.

Dynamic ads, because they are relevant and targeted, often outperform traditional static ads which appear the same no matter who is viewing them.

Why is dynamic creative optimization (DCO) important?

Consumers see thousands of ads each and every day. For this reason, it is very important for brands to actively engage customers through messaging and creative. DCO, or dynamic creative optimization, helps these same advertisers deliver more relevant and impactful ad experiences to these users.

In addition, DCO can also help improve the scale and efficiency of advertising. Instead of creating multiple versions of an ad to be placed on different locales, DCO does this automatically for them.

How does dynamic creative optimization work?

Dynamic creative optimization uses real-time analytics and testing to create hyper-personalized display ads. It begins by analyzing several data inputs (for example, the viewer’s geolocation, weather, device, shopping habits, browsing history, and more).

This data is fed to the DCO which automatically chooses key creative elements that are relevant to the viewer. With the elements in hand, the DCO algorithm then chooses how to display the ads in a way that has the right feel for the viewer. Powerful DCO solutions are able to then analyze how viewers respond to the ad, optimizing it further in real-time. 

The benefits of dynamic creative optimization

DCO brings several benefits to the table, including the ability to:

Produce scalable, targeted campaigns

In an age of near-universal advertising and ad-blockers, creating ads that speak to your audience is necessary to cut through the noise. DCO makes it possible to produce personalized, relevant ads at any scale.

Optimize campaigns easily

Powerful DCO solutions are able to analyze consumer engagements in real-time and optimize campaign performance on the fly. 

Automate processes

AI-driven creative optimization means you can reduce the time necessary to get started and allocate resources more efficiently.

Develop more effective campaigns

DCO helps you to deliver the perfect combination of elements that drive engagement and conversions. For example, IBM Watson Advertising Accelerator drives on average a 127% lift in campaign performance.

Reduce bias

DCO makes it easier for marketers to test their assumptions, instead of relying on biases to create campaigns. However, bias can become embedded into the tools we use. Companies, like IBM Watson Advertising, are committed to mitigating advertising biases through the advancement of AI tools that can segment groups in a more equitable manner. As these machine learning tools become more sophisticated, teams can further reduce bias in their advertising efforts.

How to use dynamic creative in a campaign

There needs to be a foundation of high-quality data to enable you to understand your customers, where they are, and so you can use data science to target them. To use dynamic creative efficiently, you need to consider the following three steps:

1. Create buyer personas with high-quality data

The first step is to build buyer personas for each segment that you are going to target. To do this, you need to analyze your data and learn the key characteristics of each group. For example:

  • Demographic data - Age, gender, ethnicity, income, and so on.
  • Geographic data - Country, region, and timezone.
  • Behavioral data - Spending, browsing, and purchasing habits, as well as how the customer interacts with your brand.
  • Psychographic data - Personality traits, hobbies, goals, values, and lifestyle. 

This is just the beginning - there are many characteristics that might be important depending on your industry, product or service, and target segments.

The important thing is to build a picture of who your customers are, what their problems and priorities are, how you can target them, and how you can convince them to make a purchase.

2. Create multiple messages and ad elements

The next step is to feed the AI a set of assets. These assets could include product photography or videography, background elements, headline variations, and different voiceovers and calls-to-action (CTAs).

The more assets, the more variations are possible. The AI will then make use of advanced targeting data and predictive modeling to create unique experiences for each user.

The trick is to create compelling copy and CTAs based on the buyer personas you created in step one. Further, it’s crucial to stay on brand and align your messaging with your brand voice and audience needs.

3. Monitor performance and optimize campaigns

As the campaign continues, monitoring success is vital. Prior to launching your campaign, you should decide on the KPIs that will best describe whether your campaign is having success or needs to be optimized. 

Using a powerful DCO solution like IBM Watson Advertising Accelerator means that the AI is able to self-train based on the highest-performing ad variations and improve performance across the board. You can track performance in the dashboard, introducing and removing ad elements as required based on how well they are being received.

Industries that Can Benefit from DCO

DCO can benefit a large range of companies and organizations. The following industries can benefit from taking a dynamic approach to their advertising campaigns.


With issues caused by supply chain disruptions, advertising executives are under increased pressure to make sure each dollar counts. Through DCO, automotive advertising campaigns can be personalized, while targeting users more likely to make a conversion.


Contextual signals matter in retail. Weather data can dictate the kinds of purchases someone makes, whether that be for ice cream, winter boots, or an umbrella. By leveraging location insights with weather information and AI advertising, retailers can deliver cognitive ads that will convert their audiences.


For healthcare advertisers, it’s important that ads don’t feel invasive, since patient data is highly personal. DCO can deliver personalized campaigns without relying on cookies or sensitive information.

Case studies and examples of dynamic creative optimization

There are several industries now utilizing dynamic creative optimization to increase their campaign performance, including automotive, pharmaceutical, and retail.

Here are a few case studies that illustrate how dynamic creative optimization can boost your engagement and conversions:

Mastercard: Spreading awareness through dynamic ads

Mastercard reached out to IBM Watson Advertising to let their customers know about their partnership with ‘Stand Up to Cancer’. Accelerator utilized AI to continuously determine which creative ads would resonate with each audience. This was based on how consumers reacted, but also on a multitude of other key signals such as DMA, device type, and time of day.

Mastercard leveraged IBM Watson Advertising Accelerator in order to predict and serve ads that were most likely to be relevant - increasing engagement and action, as well as ultimately educating consumers, uncovering new creative insights, and highlighting the power of AI.

Using Accelerator, Mastercard was able to discover key insights about their audience, and with 81 creative variations had a 54% increase in click-through rate (CTR) above their benchmark.

National Beverage Brand: Delivering effective digital creative

The National Beverage Brand wanted to increase engagement over the holiday season and connected with IBM Watson to achieve this goal. The brand utilized Accelerator with Click2Cart technology in order to deliver effective digital creative to each and every user while driving their primary conversion metric, which was consumer clicks to the cart at five key retailers.

Accelerator was able to increase the conversion rate from the start to the end of the campaign by 143% and delivered valuable creative insights such as which elements resonated with audiences.

The Ad Council: Creating personalized creative at scale

In an effort to raise awareness about their “Love has no Labels” campaign, the Ad Council utilized IBM Watson Advertising. IBM Watson Advertising Accelerator helped deliver personalized, high-performing creative at scale for The Ad Council by harnessing the power of AI to predict optimal combinations of creative elements. These are all based on key signals such as consumer reaction, weather, and time of day.

Accelerator enabled the Ad Council to develop a deeper understanding of their audiences. With 81 variations (an average of 93% beating brand CTR benchmarks), using Accelerator resulted in a 113% lift in CTR and a 69% increase in conversions.

Chevrolet: Increasing engagement and overall action

Chevrolet’s goal was to drive consideration for their 2021 Trailblazer model in the crowded SUV marketplace. With Accelerator, they were able to predict and serve ad units meant to increase engagement and action, which would ultimately educate consumers about their SUV. This also uncovered insights about which creative helps to drive the highest engagement.

Powered by Accelerator’s AI, Chevrolet was able to increase CTR by 100% over the course of the campaign.

The future of dynamic creative

Personalization matters in advertising. More than half of consumers (opens outside of ibm.com) noted that they are more likely to make a purchase from a company that provides personalized ads. Even with privacy regulations, brands need to deliver ads that are relevant to users.

By employing dynamic creative, brands can leverage contextual signals and weather-based targeting to deliver better ads without feeling invasive to consumers. In a world where advertising is becoming cookieless, dynamic creative optimization will become more important for brands who want to remain competitive.

Dynamic creative is also no longer just limited to display advertising. With IBM’s Advertising Accelerator, you can take advantage of these contextual targeting across video and OTT as well, for a more comprehensive approach.

Drive better creative with IBM Watson Advertising Accelerator

IBM Watson Advertising Accelerator enables marketers to deliver dynamic creative optimization for display, video, and OTT without extensive manual groundwork. Using powerful artificial intelligence, Accelerator is able to do the decision-making for you, producing high-performing, personalized ad creative at scale. To learn more, contact our team today.

Frequently asked questions about dynamic creative optimization

DCO marketing is a form of programmatic advertising that leverages dynamic creative to showcase the right messaging to the right person at the right time. It employs predictive analytics with AI and contextual targeting to deliver the right creative.

Does dynamic creative optimization use cookies?

Traditionally, DCO utilizes cookies to collect data on each user. However, in a post-cookie world, some DCO solutions now use powerful AI-generated contextual targeting to make advanced predictions without cookies.

So, what is the difference between DCO and a CMP?

A CMP is a production design engine which works to mass-produce and control the different design versions that are required for a DCO campaign. Being a part of that, DCO is the actual real-time technological process which serves the hyper-relevant ads.

What’s the difference between dynamic and static creative?

Static creative cannot be changed based on targeting signals such as weather information, location, context, or likelihood of conversion. Static ads may use A/B testing to determine effectiveness, but DCO has more flexibility leading to better results. DCO uses AI to gather information and deliver the best ad for the target audience.

Why is dynamic creative optimization needed?

DCO has been used across different industries and sectors for years, but its application in marketing, as well as its development within display advertising is newer and more innovative. This is because it taps into growing trends of data-driven advertising as well as in-house marketing. Since many brands are beginning to harness the power of commercially available artificial intelligence (AI), they are also starting to understand data better and more effectively engage their consumers through DCO.