WeChat explosion of this topic, we must be very concerned about, but really want to create their own explosive text this is not an easy thing. In general, we all need to be able to build a long-term accumulation of their own detonation. So to create a burst of text, we need to do what we need to do the following two points
first: for user analysis
analysis of the user this is mainly to see what our fans are of type. More fans of men or women more fans. This is what we can directly from the background of our fans to see the property. In general, our male fans are like beauty, a little bit of lust. So what we need to do with these fans is to satisfy their wishes. Lust is the innate nature of every normal man. If it is not a male, then say it is also a ghost, who believe ah.
, for example, I was shocked, so for me, the content of our material is more wonderful, funny anecdotes, etc., these materials are suitable for my fans to read. However, it is not to say that all these elements are suitable for my fans, which may have video, text or text. These are not the same for each public number. Some may be suitable for graphics, and some are suitable for video content. Take me for example, my fans like some of the video content, after a long period of data analysis, I send text content is far below the amount of reading video. So my position is to put all the content into video content, we usually see a good title, there may be and I don’t want just video, graphic content, video content so I can want me through WeChat or other search, from which pushed to my fans.
second: background data analysis
is very important for the analysis of the background data, only through the analysis of the data to be able to know our fans love is what type of content, and those of us who copy is fit in headlines, who is fit in the middle of the. We are in accordance with the contents of typesetting reading our typesetting, we are after long-term analysis, we first need to determine is our fans love what type, how much amount of reading and analysis of each content.
headline reading volume (18%-20%)
second readings (18%)
third readings (15%)
fourth readings (12%)
fifth readings (10%)
sixth readings (10%)
seventh readings (5%)
eighth readings (5%)
generally we read each content according to this