Is the Data Analysis Absent in Your Content Operation Strategy?
What is content operation?
Content operation refers to a series of marketing activities related to content based on product content planning, content creation and editing, content optimization and publishing. For different channels, content operation has new media content operation (such as WeChat’s content operation), content platform operation (for example, the content operation of Jane’s book), etc. According to different business, content operation can be divided into promotion content operation, product content operation, user content operation, etc.
The importance of content operations.
Content operation occupies a very important position in the whole operation activity. First of all, the content can establish the connection between users and products. The content can convey the brand value while also cultivating the user’s cognition of the product. Secondly, content operation is also a part of product service. Users can not only consume content directly, but also help users to consume products. In a word, good content operation is very helpful for users to pull new, retain and transform users.
The steps of content operation.
Using data-driven content to run content is an essential skill for marketers. Before creating content, we can use data analysis to identify the target users and set the right goals (for example, how many new users will we bring after our content is released?). And to a certain extent the impact that the content is about to have. To use data-driven content, we must master these three steps:
Data collection, data analysis, data feedback.
1. Data acquisition: understand target users and competitors.
The difficulty with data-driven content operations is that we must understand our target users accurately. Only by accurately understanding the target users can we output the content that is close to the user’s needs and arouse the resonance of users.
In order to understand users, we need to collect as much user information as possible, including users’ online and offline behaviors. For example, a user in the online search what questions, which topic is active in social media, like click what content and so on these online behavior are we to understand the need to collect information. User behavior data acquisition is to let us understand the user’s interest and interests, and the common behavioral characteristics of users. After that, we can group users according to their common interests and behaviors, and produce targeted content for different user groups.
In addition to collecting user behavior data, we also collect behavioral data from competitors, for example, what they developed. In what channel to promote; How many new users, how many transformations, and so on. Through understanding the performance of competitors, we can speculate about what keywords or subject to users more attention, the user has no interest in what content and to attempt to innovation, find the breakthrough point, to create some fresh content to win the user’s heart.
The purpose of data collection is to better understand target users and competitors. We can use these data to think about how to add value to our brand, how to produce differentiated content to attract users.
2. Data analysis: identify the most effective content promotion channels.
By collecting user behavior data and competitor’s behavioral data, we have a very deep understanding of when and where the target users are and what they want.
After we have produced targeted content, then it is how to promote it through the most effective and influential channels. In a blog to share is far from enough, no matter how much we output the contents of the user requirements, if the user had never seen these content, then we are purely a waste of time and energy.
There are many channels for promotion, such as email push, paid-for display advertising, big V cooperation with large impact on target users, or simple repeat marketing. Regardless of the promotion channel, we need to analyze target user behavior data and competitor behavior data to determine.
Data analysis can prevent us from promoting blindly. We can find out the best distribution channels for user feedback by analyzing the different performance of different content distribution channels.
3. Data feedback: prove the value of content.
After content output and promotion, we evaluate the content of our output and prove the value of our efforts.
How does the user interact with our content? Does our content cause a lot of discussion? What actions do users have after they have access to our content? · such analysis can give us a clear understanding of the value of content.
It is difficult for some brands to set the return on content investment, but we can describe the impact of content through proxy indicators. We can use different scoring systems to evaluate the participation of different stages and compare the effects of different content modules. For example, click browse content 1, and further participate in thumb up 2, collect content 3, share content 4, and then evaluate the purchasing habits of different scoring levels. Ultimately, we can figure out the relationship between these scoring data and sales data. The higher the sales, the greater the value of the content we produce.
The success of content marketing is no accident. The key to the success of content operations is the ability of operators to properly manage and use data output to be beautiful and to guide participation and transformation.