Implications of age group analysis
In the social sciences, the term “age group” refers to a group of individuals who have experienced a significant event in a similar way. Age group standards can be classified in different ways, depending on the type of data to be analyzed, such as country of residence, city, age, and income level. The process of calculating specific outcomes or indicators from a group of individuals grouped according to similar standards is called age group analysis.
The reason why age group analysis is important is because it helps you escape the trap of averages. Vietnam’s overall average income may be increasing, but if age group analysis shows significant differences by region of residence or even a decrease in some regions, we can avoid misunderstanding that average income in Vietnam is increasing. Age group analysis can also be used as a powerful tool to reasonably predict the future behavior of users who have not yet reached a particular behavioral cycle.
Start Age Group Analysis at DataS
Adbrix provides age group analysis by dividing into ‘attribute-based analysis’ and ‘behaviour-based analysis’.
Attribute-based analysis: Group by
‘Attribute-based analytics’ relies on user attribute values defined through DataS. The most basic age group analysis is to identify users’ repeated behavior through DataS’s recognition settings and analyze the results. This includes the distinction between organic user data flow and flow through advertising media, campaign flow, keywords and creative. Age group analysis based on attributes is also analysis based on different attributes such as time (by time zone, day, month…), platform (Android, iOS), country information, city information. city, device model and telecommunications company.
DataS provides metric analysis based on attribute values through the ‘Group by’ selection in each report type. For example, if you want to analyze ad media inflow results by Android/iOS platform based on date, you can set it up as follows in Report Builder.
Group by= Daily > Platform > Country (IP) > Ad Partner
If you want to track advertising media performance reporting separately based on country of origin, you can set it up as follows.
Group by = Daily > Platform > Country (IP) > Ad Partner
Adbrix provides a total of 40 basic group conditions. Additionally, it offers custom conditions (like product categories, payment methods, levels, etc.) that can be added depending on the level of integration, allowing marketing professionals to increase Freelance data analysis leader.
Behavioral age group analysis: Audience Studio
Behavior-based age group analysis at DataS based on application usage behavior. To do this, you need to create a segment of users based on their behavior, then combine multiple segments to create the final group. DataS’s Audience Studio provides an easy-to-use “Drag and Drop Venn Diagram” interface so any marketer can easily create the desired group.
Because behavioral age group analysis relies on the results of user behavior, it represents user characteristics more strongly than attribute-based analysis. By comparing analytics by age group, you can examine results that you don’t see in analytics across all users. This is also a reasonable way to predict the next behavior of an age group that has not yet reached a particular behavior.
Audience Studio by DataS – Create behavior-based groups using combined segments and conditions
- By becoming familiar with DataS’s Audience Studio, growth marketers can create user groups with the following conditions within 3 minutes.
- The user has been running the app for the past 3 months but has not completed membership registration
- Of the new users introduced through advertising in the past month, those who have not completed membership registration
- Among users who arrived via search ads in the past month, those who did not purchase products from a particular keyword
- The user has run the app in the past 3 months but has not purchased a product
- Users have a history of purchasing products in the child care category worth more than 1 million VND in the past 6 months
- User came to the app under a jewelry promotion, but purchased products other than the jewelry promotion’
User groups thus created can be analyzed immediately by adding them to ‘Audience Conditions’ in the Report Builder. You can improve in-app user experience and optimize ad performance by analyzing retention and progression based on membership subscriptions, or by analyzing specific products and users. responded to the jewelry promotion ad, what product did you buy and how much.
DataS Audience Condition – Analyze results created in Audience Studio by adding them to analysis conditions
Age group analysis is a tool to clarify the nature of the data
Through age group analysis, growth marketing experts can meticulously analyze “Why? What results are displayed? and use the results of this analysis to find and verify growth decision points for app improvements and ad optimization. If we assume that ‘membership registration’ is the growth deciding point that drives retention and increases sales of our app, we can only evaluate effectiveness by how we now analyzes age groups based on membership registration. If validity is verified (i.e. if usage of the app by ‘subscribed’ users is quite good), the user experience needs to be improved so that newly referred users can convert to ‘members’. sign up as a member’ as quickly as possible, and ads will be created with the objective ‘sign up for members’.
Age group analysis is a powerful way to break out of the trap of averages and capture the core meaning of data. Analyzing age groups based on behavior also makes great sense as a way to predict users’ next actions. We hope that through this article, growth marketing professionals will rethink the usefulness of age group analysis and be able to immediately implement the most optimal age group analysis for their application. me using the CDP DataS product.