Demographic Data

Demographic data is used in web analysis and online marketing to provide deeper insights into a website’s target audience or in order to create personas. Demographic data is used above all to strategically adapt offers to certain target groups, and can be used as a basis for business analyses and performance reports.

What is demographic data?

Demographic data is information about groups of people according to certain attributes such as age, gender, place of residence, and can include socio-economic factors such as occupation, family status, or income. Demographic data and interests belong to some of the most important statistics in web analysis, consumer analysis and targeting. In contrast to data collection in the academic field of demographics, the focus of demographic data in marketing is less about data regarding fertility and mortality, but rather about age, gender and interests.

Significance of demographic data in online marketing

In web analysis and online marketing, demographic data is collected to gain a deeper insight into the target group of a website or to create personas on the basis of this information. Demographic data is mainly used for strategic targeting of the offering and can also be used for business analysis and performance reporting.

Demographic data and interests are key metrics in web analytics, consumer analytics, advertising planning and targeting. In contrast to data collection in population science and statistics, marketing usually focuses less on data on fertility or mortality, but on age, gender and interests.

Examples of demographic data

• Age: Age is one of the most important demographic factors. It is a good indicator of the user groups that visit a website, as well as the age groups that purchase the most. It provides information about what content on the website is interesting for a particular age group, and where potential can be identified.
• Gender: Information about the gender shows which parts of a websites or which products are more suitable for men or women. Sorting hits based on gender can be used as a basis to plan campaigns that are targeted to men or women.
• Education: Data regarding education indicates for example whether users attended university.
• Income: Information about income makes it easier to target high earners for example to buy a high end product.
• Interest: Data about users' interests show what visitors to a website are interested in, and they make it possible to draw conclusions on consumer behavior. For instance, if there is affinity to specific product categories from the side of the users, sellers can come up with advertisements that focus on these interests.

Furthermore, using demographic data makes it possible to segment user groups, for example to establish a connection between persons aged from 18 to 24 years with certain keywords and interests. This type of segmentation is particularly useful for remarketing campaigns.

Collection of demographic data

Demographic data is collected by software solutions such as Google Analytics. Here, a subset of the total number of users is used to extrapolate data for the total number of users. The software collects this data using different protocols that ensure tracking. For instance, geographical and language information is collected in the communication between the server and client. Through the use of cookies or event tracking, more information about the gender and interests is recorded and saved.

The information is acquired from the Google Display Network and participating partners. It therefore makes sense to use this data for advertisements. To be able to collect demographic data, a corresponding tracking code must be integrated or altered accordingly.

In addition, activation in the account is necessary for one to be able to use the functions as reports. Here, it is important to also take notice of eventual changes in the Google Analytics Privacy Policy on the website before activating the new functions.

Apart from the use of data via google products, website operators can also use their own data to collect and segment demographic data. This way, online shops can analyze and evaluate their own customer data to optimize advertising campaigns.Here, too, it is important to comply with current data protection regulations and GDPR.

Examples of demographic data

• Age: Age is one of the most important demographic factors. It is a good indicator of the user groups that visit a website, as well as the age groups that purchase the most. It provides information about what content on the website is interesting for a particular age group, and where potential can be identified.
• Gender: Information about the gender shows which parts of a websites or which products are more suitable for men or women. Sorting hits based on gender can be used as a basis to plan campaigns that are targeted to men or women.
• Interest: Data about users’ interests show what visitors to a website are interested in, and they make it possible to draw conclusions on consumer behavior. For instance, if there is affinity to specific product categories from the side of the users, sellers can come up with advertisements that focus on these interests.
• Language: for online marketing and website design, the language of the target group is important. This is especially true for internationally oriented online shops. For example, advertising measures and content must be geared to the language spoken by the target group.
• Countries: From which region, city or country do my users come? This question is important in order to target advertising measures specifically to these geographical reference points.

Furthermore, using demographic data makes it possible to segment user groups, for example to establish a connection between persons aged from 18 to 24 years with certain keywords and interests. This type of segmentation is particularly useful for remarketing campaigns.

What does demographic data tell us?

There are many different scenarios where demographic data is useful for website analysis. Reports related to demographic data could provide answers to the following questions:

• What groups of users visit the website? Young users have interests that differ from those of older users.
• Which of these groups provide the most revenue? The most profitable clientele is usually from a certain age group.
• Where should content be placed in order to increase sales? Relevant content can be tailored to age, gender, and interests.
• How can advertisements be targeted in a better way? Young female users want to see different types of advertisements compared to older male users.
• Which factors improve remarketing? Through the segmentation, downstream measures can be tailored to the target group and the corresponding interests.
• How can e-mail campaigns be more efficient and targeted more directly to certain groups? In this case, newsletters or emails can be sent to particular groups.

Conclusion

Compared to conventional tracking, demographic data in web analysis provides a much deeper insight into the user behavior. Information about user groups can be used to improve the effectiveness of advertisement campaigns, optimize the website’s offer, and last but not least, boost sales. Although a detailed understanding of the software used is required, this effort pays off in the long term, particularly when demographic data is used for the strategic alignment of the product range, advertisement measures, and remarketing. At the same time, the lawful use of this data should not be disregarded – the data should be anonymous, and the user must be informed about the collection of data as well as the use of cookies. At the same time, users must have the opportunity to conflict data collection.

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• Demographics and Interests