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Preference Data for Better Ads Better Traffic

Shopper Preference data is the key to putting your ads on target and getting the right people shopping on your ecommerce site
Photo of our Content Strategist, Ian McKinnon
Ian McKinnonApril 26th 20234 min read
Some poker chips and two aces

If you’re with a brand selling lifestyle products like apparel, cosmetics and accessories, your shoppers’ preference data is a valuable source of content for creating better retargeting ads. But what is it? And how is it different from the other types of data you need for running great ads?

Preference data vs table stakes data for ads

You probably know all about the table stakes data. It includes demographic, psychographic, geographic, etc., as outlined below.

Nowadays, those basic data points are the minimum requirement for running ads. To make ads great you need to get your hands on the much more valuable stuff: the preference data.


Demographic information, such as age, gender, income, education, and occupation, can help target your audience effectively.


Interests, hobbies, values, and personality traits inform your audience's mindset and help create resonant ads.


Use location data to target customers in particular regions/cities and adjust ad messaging accordingly.


Use purchase history, browsing, and search to create ads that appeal to customers interested in similar products/brands.


The website or app where your ad appears can affect its effectiveness. For instance, an ad for cosmetics on a beauty blog can be more effective than on a general news site.

Brands can create targeted ads that appeal to their ideal customers on the GDN by leveraging these standard types of customer data but the results aren’t as personalized as they can be if you have good preference data.

What is preference data?

Imagine this: what if your brand had a website plugin that could analyze the product attribute preferences of each individual shopper? And what if that analysis could be compiled into preference profiles? Surely, this kind of first party data would be great for running retargeting ads!

That’s Preference data! It’s super valuable for running retargeting ads on the Google Display Network because as shoppers move from the ad to your website, the likelihood of them finding what they're looking for is much higher.

Preference data and retargeting ads

Retargeting ads are designed to target customers who have shown interest in a product but have not yet made a purchase. By using the preference profiles compiled by the website plugin, you can create highly targeted and personalized ads that speak directly to the individual preferences of each of your customers.

For instance, if your Preference Analytics report indicates that a specific customer favors organic and natural ingredients in their cosmetics, the brand could create a retargeting ad that emphasizes the natural ingredients in their products. Likewise, if a customer prefers bright and bold colors in their apparel, the brand could create a retargeting ad that showcases their most colorful pieces.

Brands can create highly relevant and personalized retargeting ads that are more likely to convert customers who have previously shown an interest in their products by leveraging this kind of customer data.

Visual AI Preference Analytics

The heart and soul of a powerful recommendation system

What else does it take to convert on ad-generated traffic?

Retargeting ads are often more effective than other forms of advertising as they target customers who have already shown interest in the brand or product. By reminding these customers about the brand or product they had previously engaged with, retargeting ads can drive conversions.

In general, the likelihood of converting traffic generated from retargeting ads depends on:

  • The quality and relevance of the ad to the customer's interests.
  • The ease of use of the brand's website.
  • The price and perceived value of the product.

However, it is important to note that not all retargeting ads are equally effective, and not all customers are equally likely to convert. To increase the likelihood of conversion, you must create compelling and relevant ads that:

  • Appeal to the customer's interests.
  • Provide clear value propositions.
  • Make it easy for the customer to take action.

In addition, your website should be optimized for conversion. This means including clear calls-to-action and an easy checkout process.

Lastly, high prices or a perception that the value of the product does not match the price may lower the conversion rate.

Preference data and product recommenders

Imagine this scenario: what if your website had personalized product recommenders and exit-intent promotions that show shoppers the same products they saw in the ads that drove them to the website?

Personalized product recommenders use data analysis and machine learning algorithms to recommend products that are most likely to appeal to a particular customer based on their browsing and purchase history, as well as their preferences and behavior on the website.

However, good preference data is the hardest to get. The ecommerce giants with the resources to obtain it use it mercilessly to not only get shoppers to convert but also add to cart (think about the amazing accuracy of product recommendations during an Amazon shopping experience).

By using good preference data on your website's personalized product recommenders, you can create a more engaging and tailored shopping experience that increases the likelihood of a conversion.

Exit-intent promotions, meanwhile, are designed to capture the attention of customers who are about to leave the website without making a purchase. By showing these customers the same products they saw in the retargeting ads, you can remind shoppers of their initial interest in the product and provide additional incentives or discounts to encourage them to complete the purchase.

Final thoughts

With good preference data in hand, and personalized product recommenders and exit-intent promotions on your website, your retargeting ads will perform better and your sales cycle will be more complete. This approach not only makes the customer feel more valued and understood, but it also provides additional opportunities to close the sale and convert the customer into a loyal fan of your brand.

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