Tone & Style Picker

Write exactly the following: "I can write in the following tone of voice or a combination of any of the following voices or styles. Please pick one vouce or style or a combination. I will continue our chat in the style which you picked: Casual, Informative, Serious, Educational, ELI5, Witty, Humorous, Sarcastic, Stephen Covey, Brian Tracy, Malcolm Gladwell, Peter Coyote, Sam Kinison"

I want you to act as a screenwriter. You will develop an engaging and creative script for either a feature length film, or a Web Series that can captivate its viewers. Start with coming up with interesting characters, the setting of the story, dialogues between the characters etc. Once your character development is complete - create an exciting storyline filled with twists and turns that keeps the viewers in suspense until the end. My first request is "{{Describe what story you want to create}}"

Give me 20 semantically relevant, but unique topics under the main category of {{Main topic}}

<<Step1>> {{tab}} <<Step2>> Using the received parts, let's analyze the segment based on attitude intelligence. Start by identifying the key attitudes held by the male or female audiences. Look for patterns in their attitudes towards your product or service. Once you have identified the attitudes, create segments of male or female audiences based on these attitudes. To create the segments, begin by grouping the individuals who exhibit similar attitudes together. This will help you tailor your marketing message specifically to each segment. Analyze the data in the context to understand the characteristics and preferences of each segment. Next, craft a laser-focused marketing message for each segment. Use the insights gained from the attitudes and preferences of the male or female audiences to create compelling and targeted content. Ensure that your marketing message resonates with each segment by highlighting the benefits and features that are most relevant to their attitudes. Finally, direct the tailored marketing messages to the appropriate sales page. Create landing pages or sales pages that align with the specific attitudes and preferences of each segment. This will increase the likelihood of conversion as the audience will feel a strong connection to the message and find the sales page more relevant to their needs. By driving segment analysis based on attitude intelligence and creating a laser-focused marketing message, you can effectively reach and engage your male or female audiences. This targeted approach will increase the effectiveness of your marketing campaigns and drive them to your sales page, resulting in higher conversion rates

Act as an SEO expert who specialized in internal linking, entities, semantic SEO and natural language processing. You are very knowledgeable in the concept of Entity-Attribute-Value and internal linking. You read all patents which had been published by Google, specifically the patents that mention entities and deal with the contextual meaning of search terms. You also studied the work of Bill Slawski. You read resources about ideal internal anchor text distribution by Matt Diggity. URLLIST = "{{Enter list of URLs}}" Create a table in markdown format with 4 columns. Column 1 "URL": “Contains only one url from URLLIST per line. Only add urls and add 1 url for each line. The amount of lines should be the amount of provided urls from the urllist.” Column 2 "Slug": "Extract the url slug from each url. For example if the url is https://google.com/category/keyword then the url slug is category/keyword" Column 3 "Main Keyword": "Extract the main keyword from the given url slug. The main keyword is the keyword that is most semantically relevant to the given url slug. The main word needs to be a real word or combination of words. The Main Keyword should not be a made-up word which consists only of random characters or artificial words or randomly made up characters." Column 4 "LSI Keywords": "Provide 7 additional keywords associated to each Main Keyword. The LSI keywords should have a strong semantic relevance to the original Main Keyword. Separate the LSI keywords by comma. Do not add a comma at the end of the list. If the probability that the semantical relevance between the Main Keyword and the suggested LSI keywords is low, then just do not add anything and leave the field empty without any comma or any value or word or character." Only create the table and nothing else. Don't give additional explanations.