What are dynamic ads?
Dynamic ads are automated digital ads that adapt their message and content to each individual user. Platforms such as Google and Meta combine product and user data, so an ad always shows the content that best fits the person's current needs. That could be anything from a specific product the user has viewed before to a new recommendation based on search behaviour or areas of interest. In other words, the system draws dynamically on your company's product feed, combined with signals from the user's behaviour, and puts together a relevant ad in real time.
Dynamic ads are powered by both machine learning and extensive datasets. The machine learning analyses users' interactions across channels, optimises image choices, headlines and prices, and adjusts automatically based on performance. That flexibility makes the format well suited to a digital marketing strategy where you work with Google Ads, social media ads and remarketing. In an SEO context, they can also complement your organic efforts, because they fill keyword gaps and reach users you might not capture with standard search ads.
How do you use dynamic ads?
You use dynamic ads as a tool to personalise ads at scale. It works by connecting your product catalogue or feed to an advertising platform, where you define the overall framework, such as target audience, budget and campaign goals. The algorithm then handles the rest: it chooses the products and creative elements that best match the user's profile and intent. For e-commerce, this means users see exactly the products they've previously looked at, while a travel provider can show specific destinations based on recent searches or geographic location.
You can use the format both for new customers (prospecting) and to re-engage people who have already been in contact with your brand. On social media such as Facebook and Instagram, prospecting typically happens through broad audience set-ups, while remarketing is driven by pixels and user data. In practice, this approach ties in closely with the rest of your SEM strategy, because you can use keywords and ad type to control how the dynamic ads complement your static campaigns.
Why you should use dynamic ads
Dynamic ads increase relevance across your advertising ecosystem, because they automatically match the ad content to each user's intent. That reduces waste in your campaigns and improves the conversion rate, without you having to create hundreds of variants manually. With automated optimisation, you save both time and resources while giving users an experience that feels personal. This is especially valuable in campaigns with lots of products or services, where it's impossible to manage everything manually.
Another advantage is scalability. Dynamic ads can run across countries, languages and product categories from a single feed, and the system handles the adaptation itself. That makes the solution relevant for businesses that combine branding with performance marketing, because you can test messages and creative elements in real time without running manual A/B tests.
What types and variants are there?
Dynamic ads cover several formats, each serving a specific purpose in the customer journey. The most widely used types cover the whole spectrum, from search ads to display and social remarketing.
- Dynamic Search Ads (DSA): Generates ads based on your website's content, without you having to specify keywords manually. Google matches the user's search query with relevant pages on your domain and automatically creates an ad with a dynamic headline and landing page.
- Dynamic Product Ads (DPA) / Catalog Ads: Pulls product data from a feed and shows it as specific product ads, e.g. in Meta Ads. They're typically used by webshops to show products the user has already visited.
- Dynamic Remarketing: Combines pixel data and the product feed to show users exactly the products they've previously viewed. It's one of the most effective ways to close the sale after a user has left your webshop.
- Dynamic Creative Optimization (DCO): Adjusts visual and text elements such as price, offers and CTAs in real time, based on what performs best with specific segments.
- Dynamic Ads for Broad Audiences (DABA): Uses machine learning to find new potential customers through broad audiences, based on likelihood of interest rather than specific behaviour.
How do you use dynamic ads in practice?
You set up dynamic ads directly in platforms such as Google Ads Manager or Meta Ads Manager. First, you connect your product feed so the platform can pull data such as title, image, price and URL. Then you define which action should trigger the ad – e.g. a previous visit to a product page – and choose a campaign goal such as traffic or conversions. Once the system has these inputs, it generates dynamic content and continuously adjusts the bidding strategy, e.g. via CPM or CPC.
Example:
On social media it works in a similar way, but with more visual freedom. Here you can, for example, vary the image, CTA and message dynamically depending on where the user is in the customer journey. To get the full benefit, you should link the set-up closely to the rest of your data and tracking structure, so the pixel and feed are always in sync. The combination of precise advertising and ongoing optimisation makes the format effective in both performance-driven and brand-led campaigns.
What should you watch out for?
Even though dynamic ads automate most of the work, they need a solid data foundation to deliver good results. Your product feed must be up to date with correct prices, descriptions and images, otherwise you risk showing users incorrect information. Tracking also needs to work, so data on behaviour and conversions flows smoothly between your website, pixel and ad platform. It's worth building this into your overall digital strategy, where data integration, web tracking and creative content work together.
You should also monitor how the algorithm prioritises your products. The system learns continuously, but if, for example, you have low-volume campaigns, it can take time for the machine learning to find the best pattern. That's why it's important to combine automation with ongoing evaluation of performance and design — just as when you work with your other SEM and social media campaigns. This ensures the technology doesn't just run on autopilot but actually strengthens your overall marketing effort.
