What are sociodemographic factors

Demographic data

What is demographic data? [Edit]

Demographic data is specific information about groups of people. These include characteristics such as age, gender, languages ​​used, place of residence and social characteristics such as occupation, marital status or income. Demographic data are usually collected through direct surveys of the target group.

Importance of demographic data in online marketing

In web analysis and online marketing, demographic data is collected in order to gain deeper insights into the target group of a website or to create so-called personas on their basis. Demographic data mainly serves to strategically align the offer to the respective target group and can also be used for business analysis and performance reports.

Features [edit]

Demographic data and interests are among the most important key figures in web analysis, consumer analysis and advertising planning as well as targeting. In contrast to data collection in population science and statistics, the focus in marketing is usually less on data on fertility or mortality, but on age, gender and interests.

Collection of demographic data [edit]

Software solutions such as Google Analytics collect demographic data by extrapolating a subset of the total number of users. The software collects this data via various protocols that ensure tracking. For example, geographic and language data are collected during communication between server and client. Further information on gender and interests is registered and stored via cookies and event tracking.

The data comes from the Google network and from participating advertising partners. It therefore makes perfect sense to also use this data in the area of ​​advertisements. Before demographic data can be collected, a corresponding tracking code must be integrated or changed.[1]

A release in the account is also necessary in order to be able to use the functions as reports. It is essential to note any changes in the data protection provisions on the website before the new functions are activated. The tracking must, among other things, comply with the GDPR.

In addition to using data via Google products or other advertising marketers, website operators also have the option of using their own data sets to collect and segment demographic data. In this way, online shops can analyze and evaluate their own customer data in order to optimize advertising measures. Here, too, it is important to comply with the current data protection regulations and the EU GDPR.

Examples of demographic data [edit]

  • Age: Age is one of the most important demographic factors. It shows which user groups visit a website and which age groups have the highest turnover. It provides information on whether the content of the website is interesting for an age group and where potential can still be identified.
  • gender: The gender makes it clear which parts of the website and which products are more suitable for men or women. If hits are sorted by gender, campaigns can be planned specifically for women or men on this basis.
  • Interests: The data on user interests show what the website visitors are interested in and allow conclusions to be drawn about consumer behavior. If there is an affinity on the part of the user to special product categories, advertisements with these interests can be placed, for example.
  • languages: For online marketing and the design of your own website, it is important which language the target group speaks. This is especially true for internationally oriented online shops. Advertising measures and content must be geared towards the language that the target group speaks.
  • countries: Which region, which city or which country do my users come from? This question is important in order to target advertising measures even more precisely to these geographical reference points.

This also makes it possible to segment user groups, for example to bring male people between 18 and 24 into connection with certain keywords and interests. The segmentation is extremely useful for any remarketing campaign.[2]

Application examples [edit]

The possible scenarios for the application of demographic data are complex. The demographic-related reports can provide answers to the following questions:[3]

  • Which groups of users visit the website? Young users are naturally interested in other things than older users.
  • Which of these groups generate the most revenue? The clientele with the highest turnover usually has a certain age range.
  • Where does content have to be placed in order to increase sales? Relevant content can be tailored to age, gender and interests.
  • How can ads be more targeted? Young female users want to see different ads than young or older male users.
  • Which factors improve remarketing? The segmentation enables downstream measures to be tailored precisely to the target group and their interests.
  • How can e-mail campaigns be made even more efficient and target-group-oriented? In this case, newsletters or emails can be sent to specific groups.

Conclusion [edit]

Demographic data in web analysis allow far deeper insights into user behavior than is the case with conventional tracking. Information on user groups can increase the effectiveness of campaigns, optimize your own website and, last but not least, increase sales. A detailed study of the software used is necessary, but this effort is worthwhile in the long term. Especially when demographic data can be used for the strategic orientation of the offer, advertising measures and remarketing. The use of this data in accordance with the law should not be neglected - it must not be personal and users must be informed about the collection of the data and the use of cookies. At the same time, users must be able to object to the data collection.

References Edit]

  1. ↑ Enable remarketing and advertising reporting features in Analytics support.google.com. Retrieved on March 27, 2019
  2. ↑ Google Analytics: Rollout of Demographic Characteristics and Interests Reports thomashutter.com. Retrieved on August 9, 2014
  3. ↑ Analyze data on demographics and interests support.google.com. Retrieved on March 27, 2019

Web links [edit]