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
Demographic information, such as age, gender, income, education, and occupation, can help target your audience effectively.
Psychographic
Interests, hobbies, values, and personality traits inform your audience's mindset and help create resonant ads.
Geographic
Use location data to target customers in particular regions/cities and adjust ad messaging accordingly.
Behavioral
Use purchase history, browsing, and search to create ads that appeal to customers interested in similar products/brands.
Contextual
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.