Users' following, comments, unfollowing, etc. can directly reflect the status of the expert's fans. The expert's fan life cycle is derived based on the user life cycle in marketing. Gaining fans, retaining fans, increasing user stickiness... How do influencers determine the stage of the fan life cycle and use this as a guide for adjusting operational strategies? Generally speaking, the life cycle of influencer fans is divided into five stages: new attention period, stickiness period, user loyalty period, user fatigue period, and possible loss period. The problem that experts face when their fan base increases from 0 to 1 is how to quickly increase the number of fans. For experts who increase their fan base from 1 to 100 (more than 5,000 fans), more attention should be paid to the stage of the life cycle of the experts' fans. Use the real feedback from user comments to judge the current problems and focus on operational strategies accordingly. Figure: Qiangua Data 01 How to discover the attractive points of content and the efficient fan acquisition strategy of influencers[New attention period]: In the comments of experts' notes, words such as "good-looking", "young lady", and "temperament" are mainly used to evaluate the experts themselves. Users with these keyword comments are basically in the new attention stage. When an account reaches more than 5,000 followers, it has basically entered the stage of determining the account positioning. At this stage, it is necessary to gain more fans to break through the expert level. The comments on the notes can intuitively reflect the user's recognition of the note content, thereby obtaining the user's preferences, and based on this, make corresponding adjustments to the content and direction of the account. Export the comment content from the note details, filter the user comments, and obtain the proportion of each part of the expert's fan life cycle. Qiangua data shows that the article "My Travel Without Makeup/Must-Haves" by junior expert Mr. Jia received more than 2k interactions, exceeding the normal level of interaction data for experts in the past 30 days. The content of the notes mainly shares the versatile earrings, must-have sunglasses, lipsticks and other goodies that experts carry with them when traveling without makeup. Figure丨Qiangua Data-Note Analysis Qiangua data shows that as of February 21, 2022, the expert fan life cycle percentage chart of this note shows that most users are in the new attention period, accounting for as high as 43% (40 related comments). There are many comments about the expert herself, such as "Sister is so elegant", "This skin is so good", "You are so beautiful", etc. The user is likely to follow the expert from this note or recent notes. Figure: Qiangua Data By obtaining users' intuitive feedback on their notes, we can understand their focus and provide a more accurate direction for the development of expert accounts. Among the account types of junior expert Mr. Jia, beauty and fashion account for a large proportion, but judging from the unstable amount of interaction (sometimes dozens, sometimes thousands), the account content has not yet determined an accurate style and has failed to attract more user attention. Figure丨Qiangua Data-Expert Analysis With the interactive effects and user comments of the note "My bare-faced travel/essential magic weapon" as a reference, we can develop in the direction of the content of this note and continue to output similar notes to attract more user attention. 02 During the critical period of user retention, create accounts with strong stickiness and high loyalty[Stickiness Period]: In the comments on the expert's notes, the key words are mostly "what brand" and details related to the question notes, indicating that there is an intention to be interested in the expert's content. Users with this kind of attribute are basically in the stickiness period for the expert. [User loyalty period]: In the comments of expert notes, the content of the comments tends to urge for updates and is full of expectations for the expert's subsequent content, or contains words such as "already ordered", "please provide a link", "I like this advertisement" and so on, which highly recognize the expert's content. This part of users has transitioned from the stickiness period to the loyalty period and has a high degree of loyalty to the expert. According to Qiangua data, this food tutorial by waist expert Kang Kang Xiaotian, "My boyfriend asked me to open a barbecue restaurant❗️Barbecue㊙️Recipe is here❗️" has received more than 130,000 interactions. The main content is to introduce a variety of marinated meat recipes and universal dipping sauces that are comparable to barbecue restaurants. The whole process is full of practical information and easy to use. The angles of food photography are attractive, which can attract the attention of users. Figure丨Qiangua Data-Note Analysis Qiangua data shows that as of February 21, 2022, users in the stickiness and user loyalty period accounted for a relatively high proportion of the user comments on this note, reaching 76% (75 relevant comments). Users in these two stages are more concerned about the products and content used by the experts. For example, the comment with the highest number of likes is "Can you come up with a timer for the oven version?" Users ask questions about the tutorial notes and seek accurate operating procedures, hoping to replicate the same barbecue made by the expert. This is exactly what users in the stickiness period show, with a high degree of recognition of the expert's content and a strong sense of dependence. Another highly-rated comment reads "What is that iron plate? Please ask~", which shows the advantages of the barbecue iron plate through the usage scenario of the food tutorial. The expert's unintentional sharing behavior makes users curious about the kitchen utensils used by the expert, and they actively express the demand for recommendation. It can be seen that users have developed a strong sense of trust in experts. Figure: Qiangua Data Qiangua data shows that the notes of waist expert Kang Kang Xiaotian in the past 30 days are basically video notes. Although the update frequency is not high, the interaction volume of each note content is maintained in the range of 2k~4k, and the explosive rate is as high as 29%. Most of the note topics revolve around simple and easy-to-use food tutorials, and the rich food information brings enough sense of value to users. Figure丨Qiangua Data-Expert Analysis User retention is closely related to the quality of the account. To increase strong stickiness and high loyalty of fans, it is necessary to create richer note content, enhance its social attributes, and bring more valuable content to users. 03 Enable user churn warning, a mirror reflecting account status[User Weakness Period]: A small number of users follow an influencer for a long time and tend to lack interest and attention in the same type of content posted by the influencer. Comments containing keywords such as "this ad is too hard" and "not interesting" reflect that the influencer's content cannot reach users, indicating that this part of users has begun to enter a weak stage. [Potential churn period]: Note comments contain some negative comments such as "so boring", "too ugly", "doesn't look delicious", etc. Users show no interest in the expert's content and may enter the churn period. A note about the daily life of babies by a waist expert received more than 7k interactions. The content was a funny conversation between a cute baby and his father. According to the TOP10 hot words in Qiangua Data comments, the hot word "cute" appears most frequently, which shows that some users are in the stickiness period and express their love and recognition for the content presented by the experts. Figure丨Qiangua Data-Note Analysis Qiangua data shows that as of February 21, 2022, user comments on this note reflect that users in the stickiness and loyalty period account for the highest proportion, reaching 55% (35 related comments), followed by users in the user weakness period and possible churn period, accounting for as high as 30% (19 related comments). The high proportion of users in the weak and churn periods requires immediate vigilance, and corresponding content adjustments should be made to users' negative comments to avoid losing more users. Figure: Qiangua Data A highly praised comment during the user weakness period reads "Following the script completely, getting further and further away from the innocence of children..." Users have made negative comments on the expert's recent content, and their attention and popularity have declined. Users at this stage can easily transition to a period of possible churn. The user comments such as “I liked it very much, but now it’s boring with ads” show that users are disgusted with influencers’ “advertising”, which marks the transition from user loyalty period to user weakness period. It can be seen that if the influencers’ recommendation notes do not pay attention to the form and are not shared with users in a more sincere way, hard-embedded advertisements will only increase users’ disgust. The comment "Always full of ads, I don't like your website anymore" proves that some of the content in the expert's notes is stiff and fails to reach users, causing possible user loss. 04 ConclusionThrough user comments, we can reflect the different stages of the life cycle of influencers’ fans, and use the data percentage to present targeted strategies to help influencers better grow their accounts from 1 to 100.
Author: Qiangua Data Source: Qiangua Data |
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