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In an e-commerce world that continually evolves, brands are learning to leverage technologies to engage new markets and speak to new consumers. To stay competitive, marketers need to tell stories and deliver experiences that reflect the changing desires of consumers. That means personalization — creating content and creative tailored to each potential customer. Without customization, even brands with excellent reach across digital marketing channels will struggle to connect with consumers and remain relevant.
Dynamic creative optimization offers a powerful tool for constructing a more comprehensive and immersive digital environment for audiences. Powered by machine learning technology, dynamic creative optimization serves personalized ad content that's selected according to an individual's shopping history and online behavior. Here's how it works.
Dynamic creative optimization, or DCO, is a type of ad-serving system that chooses personalized ad content and creative elements based on each shopper's data. Powered by machine learning technology, DCO incorporates consumer data such as online shopping history, product views, geolocation, age, and gender. Through enhanced personalization and customized ad environments, DCO can improve consumer engagement and boost high-value metrics like click-through and conversion rates. DCO-generated ads tend to be more effective than traditional static ads. The result is a double benefit: better sales performance and increased consumer trust and recall of your brand.
Customer data fuels the machine learning technology that performs DCO to offer ads that reflect the values and interests of your audience. 52% of consumers say that they'd switch brands if they were served with ads that didn't cater to their needs. That's why DCO is so valuable. It decides in real-time which content and creative assets will most effectively speak to the user and spur buying interest. If you've worked hard to build your target audience and understand what drives their decisions, you'll be ready to take advantage of DCO.
Typically, DCO pulls user data from a data management platform (DMP) that's integrated with an ad server. Geographic and IP data can also help shape ad-serving decisions. Over time, machine learning technology adapts its ad generation to user behavior and helps brands isolate valuable audience segments and evaluate ad performance.
For additional reading around data-driven marketing:
The ability to customize content according to specific user data makes dynamic creative optimization highly adaptable across various marketing campaigns.
Build your customer journey map:
Here are the basics of how to use DCO to improve engagement and drive sales:
Learn how to write stand-out CTAs:
DCO proves useful across a range of industries and brand types. Let's look at an automotive dealership example. The following items demonstrate how to approach consumers with personalized, dynamic ad experiences that transform leads into sales:
Though dynamic creative optimization may seem complicated, it's an intuitive tool for marketers that want to automate campaigns and improve ROAS. DCO does most of the personalization work for you. It can strengthen consumer perceptions of your brand, attract shoppers who are most likely to be interested in your products, and usher viewers toward a purchasing decision. Its ability to refine and strengthen your marketing strategy in the short- and long-term, makes DCO an essential tool for brands to remain relevant and fresh in the eyes of consumers.
Last updated on December 6th, 2022.