Everything you need to know about…

Everything you need to know about data and audiences – Part 1

Marketers have never had more data at their disposal than they do today.

But as the technology used to achieve marketing goals gets more sophisticated, the terms and definitions associated with data-driven marketing can become increasingly confusing.

So, to make this simple we’ve put together a two-part glossary for you. You will find the most common industry terms, as well as explanations on how brands and marketers can use these different data and audience types.


Declared Data

Definition: Personal or specific information that an individual willingly shares by filling out a form, completing an online sale or taking another purposeful action.
How marketers can use it: “Declared” data is often considered high-quality data because it is directly reported from the consumer. It also implies permission for future use of their information, such as for an email campaign. Generally, this data contains details about demographics, interests and purchase behaviour. Declared data forms the foundation of content personalisation and product recommendations popularised by Amazon and now used by most e-commerce sites.

Inferred Data

Definition: Data and characteristics assigned to a person based on their activities and behaviours online, often based around content consumption.
How marketers can use it: Marketers can assign a classification, lifestyle or data to an individual depending on what they searched, read, watched or bought. This can be paired with declared data to build a richer customer profile. A brand could learn that a particular customer prefers to consume video content instead of text, or is interested in reading about particular topics, like fashion; this can help them tailor their messaging, advertisements or experience to fit the preferences of the individual.

Observed Data

Definition: Data based on a person’s engagement with a very specific category of content or product.
How marketers can use it: With observed data, marketers receive information about a customer that is more specific—and often lower in the purchase funnel—than inferred data. Although the individual did not purchase or fill out a form, as with declared data, the person did spend time visiting pages about a specific product category or product(s). Observed data can serve as the basis for a retargeting ad campaign or email program that persuades a potential customer to return to the site with the promise of a desired product, content or deal.

Interest Data

Definition: Data about a consumer’s interests based on the subject matter consumed via content websites.
How marketers can use it: This data enables a marketer to target someone based on interest, with the presumption he or she would be a likely customer for products related to that interest. Interest data can be useful for targeted display advertising campaigns, aimed at building awareness of a brand, a product or both. For example, a retailer could target their latest apparel line to young women who read fashion blogs.

Intention Data

Definition: il s’agit des données relatives à une personne dont les actions en ligne expriment une intention d’acheter un produit ou un service spécifique.
How marketers can use it: Ads and other marketing techniques can target customers who have identified themselves as interested in buying a product. This self-identification can take many forms, such as searching for certain terms, comparing pricing options or adding a specific product to their shopping cart. Intent data provides the basis for search engine marketing by identifying keywords and terms that will target high-intent buyers. It also can be used as the basis of a retargeting campaign for prospects who may have abandoned a shopping cart, compared products or received a price quote on another site.

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