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Prospecting with Dynamic Ads

Dynamic Product Ads (DPA) for Retargeting has for a long time been an appreciated feature in Facebook Ads, since it’s automating Ad creation through product feeds – along with securing a high relevance for the users exposed for the Ad. Dynamic Prospecting is a (groundbreaking) new feature, giving you the opportunity to utilize your Product Feeds for prospecting…

Dynamic Product Ads (DPA) for Retargeting has for a long time been an appreciated feature in Facebook Ads, since it’s automating Ad creation through product feeds – along with securing a high relevance for the users exposed for the Ad.

Dynamic Prospecting is a (groundbreaking) new feature, giving you the opportunity to utilize your Product Feeds for prospecting towards relatively broad audiences. Machine learning algorithms will utilize the tremendous amount of user data (absorbed by the Facebook Pixel related to your Product Catalogue) in order to show relevant products towards the most relevant users. In other words; When a Facebook user is about to see your ad, Facebook will analyze similar users to see what kind of products they’ve been interested in (in terms of browsing and buying) – which will result in showing a specific set of relevant products from your Product Set.

How to set up Dynamic Prospecting

In the Zalster platform, you simply specify your relevant markets and their corresponding Product Sets, along with relevant age ranges and genders.

Example

  • Gender: Females
  • Ages: Between 20 and 45
  • Markets: Germany & United Kingdom.
  • Product Set: “All Product In Stock & Priced Over $10”

What we will do in this example is create 2 Campaigns, consisting of 1 Ad Set in each Campaign. One of them will be towards females (20-45 of age) in Germany – and the other one towards females (20-45 of age) in United Kingdom.

In each Ad Set, there will be a Dynamic Carousel Ads based on your selected Product Set.

We’ve seen great initial results, especially for E-commerce advertisers with more than 1000 products in their Product Set. Our recommendation is to have a daily budget for each market corresponding to the estimated cost per purchase (CPA) times 20. This is to secure a statistical significance for the algorithms to optimize upon.


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