How to promote information flow advertising?

Information flow advertisements can be placed through super apps such as Bi Li, Netease Cloud Music, homework help, Aauto Quicker and Tik Tok, and there are more and more information flow channels to choose from in the market.

Only by understanding the characteristics of major information flow channels and screening out the channels suitable for our products can we formulate different advertising modes according to the characteristics of different information flow channels.

Before launching, we need to know what characteristics your users have and how to make a preliminary positioning for the user audience. We need to do user research with product thinking, write targeted advertising copy for the audience, and also rely on user research data as the basis. Next, I will share with you how to conduct user research for different types of users to ensure the accuracy of the audience.

1. Existing user type: this type of user is the user precipitated from the old product, and the user characteristic information is summarized by counting the converted user data; Or user characteristics obtained through direct questionnaire survey of product groups or industry groups, or user characteristics obtained through on-the-spot inquiry and consultation. Organize and form a kind of user audience information.

2. User behavior performance: If your product is a Sass product, you can clearly monitor and analyze it by analyzing the flow chart and heat map after users arrive at the website, the market where users stay, the web pages they browse, the areas where users are located, the terminals they use and the channels through which they come to the product. Google Analyze is recommended here, which can help you monitor user behavior very well.

If it is an App application product, user behavior data can be obtained in the application, and user behavior can also be monitored by a third party to verify user behavior characteristics.

3. User's interest characteristics: Based on the cross analysis of the first two types of data, the user's portrait is summarized and assumptions are put forward.