Scene setting: create a local life information station
Assuming that we plan to create an information website focused on “living chengdu”, the goal is to attract local users and search flows by distributing a large amount of content on chengdu foods, tourism, local news, etc., and thus to generate profits through advertising or collaboration. We need to produce a large number of original articles every day, but with limited manpower. And that's when our automation tools came in handy。
Step 1: site initialization and task targeting
Add our website site to the back of the tool and name it "the life of the world." this step is the basis for telling the tool where we're going to send our content。
We're going to tell the tools what kind of articles they need. In the context of “adding mission objectives”, we have set up a series of key words relevant to all aspects of the mission, such as “recommendment of the chengdu hotpot”, “one day tour around chengdu”, “new mall at 2026” and “chun heelu's food strategy”. Based on these keywords, the tool will look for material on the internet. This is the starting point for the entire process, and the quality of keywords directly determines the thematic relevance of subsequent content。
Step two: core functionality configuration — the creation of an exclusive artificial stream of water
This is the most critical step, determining the final quality and originality of the articles. We use the task of "recommendation of the chandu hotpot" as an example of a fine-tuned configuration。
In the functional details of the mission, we set the "original mission state" to "open" and set the "number of original articles per hour" to five. At the same time, the “collect mission status” was maintained as a start-up to obtain raw material. In this way, the tool will generate five articles per hour based on deep source algorithms and will also generate a backup for related articles. If you only want to use the original depth, you can set the number of collections to zero。
Select a high-quality original algorithm: in the “calculator version”, select a “100% machine original and readable” version and set an “expected length” according to the type of article, such as 1,200 words, to ensure that the article is sufficiently informative。
3. Finely rewrited articles (false originals): we cannot use them directly and must rewrite them. In the "article rewrite" option, we choose "deep rewrite". This model has greatly enhanced the uniqueness of the articles by recasting the original text from the chapter level to reduce the similarity of the original text to about 25 per cent. At the same time, the "auto-generating subheading" function is selected to make the article more structured and to enhance readers' reading experience. In order to further increase the timeliness and heat of the articles, we can turn on the "hotspot implant" feature to allow ai to automatically refer to the hotspot information on the network when creating or rewriting the articles and to make the content more popular。
4. Seo optimization of titles: titles are key to attracting hits. In the title format, we select " ai original title " and set the style to " seo style " . Based on the content of the article, ai automatically produces titles that contain both core keywords (e. G., “change pan”) and search engine-friendly. At the same time, we can filter out some unwelcome words in the title general settings。
5. Content enhancement and seo interlinking:
Keyword insertion: in the keyword insertion function, we can preset a long list of keywords, such as the “sundu old-name hotpot” and “sundu red hotpot”. Sets the number of two to three and selects the text " randomly inserts " , which will effectively increase the key word density and relevance of the article。
Content replacement: using the "content replacement" function, we can replace the generic terms that appear in the text with our particular term. For example, to replace “many” with “too many”, to replace “good” with “bacca”, to make the articles more in line with the local language style。
Automatic inner chain: enables the " automation inner chain " function and ensures that the " tags label " is set to " smart extract label " . In this way, when the words associated with labels (e. G., "wide alleys" and "spicy beef") appear in the body text, the system automatically adds links to relevant articles in the station, greatly optimizing the inner chain structure of the site and facilitating the capture and weighting of search engines。
6. Photo processing and optimization: pictures can greatly improve the readability of articles。
