Efficient Content Automation with Make.com

Hey everyone, welcome to this video where I'll be walking you through an amazing automation built with Make.com. This automation simplifies the process of generating articles, images, and social media posts automatically. Let's dive right into the details and go step by step. The automation starts with our database hosted on Airtable. Here, we are pulling in search results or data from an Airtable base. Airtable serves as our source of information to kickstart the process. Once the data is retrieved, we move on to the next step where it gets routed to different paths. The next component is a router. This acts as a decision point that directs the data into various branches, allowing multiple parallel workflows to occur simultaneously. From here, our automation splits into six different branches. In the first branch, we aim to generate the article's structure. Let's break it down. The first step here is to generate the top 10 keywords based on the input data. Then, we summarize key facts and figures related to the article topic. In this step, we create long-tail keywords to optimize the article for SEO. Finally, a concise summary and the list of all keywords are created and sent back to Airtable. In the second branch, we focus on writing the blog post itself. The blog content is generated automatically based on the data input. The raw text is parsed and formatted for clarity. The final version of the article is saved in Airtable for further use. Next, we move to the third branch, which handles image generation. Here, we generate an image prompt based on the article topic. To remove modules follow to clean up any irrelevant data from the prompt. We pause the automation to give some time for the image to be generated by an external service. Once the image is ready, it's retrieved from the service. The final image is downloaded and saved locally. Finally, the image is saved back into Airtable for later use. In the fourth branch, the blog post gets published on Shopify. The image generated earlier is downloaded for Shopify use. All necessary tags for the blog post are fixed and optimized. In this case, I wrote the keywords separated by comma. The article is automatically published to Shopify, including the image and the optimized tags. This module confirms that the blog post is successfully published on Shopify. The fifth branch automates the generation of social media posts. The blog post is converted into plain text, suitable for social media captions. An Instagram post is created based on the blog content. A Twitter or X post is generated. The content is formatted for a Facebook post. A post is prepared for LinkedIn. The post is adapted for Pinterest. Finally, all social posts are confirmed to be generated and are stored back in Airtable. In the final branch, the social posts are automatically published across various platforms. The image needed for the social posts is downloaded again for this workflow. Another router splits the workflow into multiple social media platforms. In my case, I used Instagram, Pinterest, and Facebook. You can add alone any other social platform you use. This entire automation, built with Make.com, streamlines the process of creating content from scratch, optimizing it for SEO, generating images, and posting the final product on various social media platforms. It's an excellent example of how you can save time and automate your content production. Log into your Airtable account and click on Add a base. Now that we have our table ready, it's time to create all the necessary fields. Let's start with the most important one, the article name. Next up, let's create a status field that tracks where each blog post is in the content creation process. The status field will have multiple stages. and each will represent a different part of the workflow. Choose single select as the field type. Now, here are the options you'll want to add. Start generating. When I will choose this option, we will start generating keywords and a summary for the article. Next option is keyword generated. The automation has successfully generated a list of relevant keywords for your article. This includes both primary and long tail keywords that are essential for improving search engine rankings. In prepare sections, we begin structuring the article. This is where the system organizes the content into logical sections. The sections generated step confirms that the structure of the blog post is in place. At this point, all the article sections have been created. whether it's the introduction, body paragraphs, or conclusion. This step signals that the article is ready for more detailed content generation. Once the article's structure is set, the next task is to generate image. Well-designed visuals are key to grabbing attention. In image-generated, the automation confirms that the visual content has been successfully created. At this point, the custom images or graphics are available and can be used within the blog post or on external platforms. Once the content and visuals are ready, the next step is post to Shopify. Article posted is the confirmation stage where the system verifies that your blog post has been successfully published on Shopify. The next phase is generate social posts. Here, the system automatically creates tailored social media posts for platforms like Instagram, Twitter, OREX, Facebook, LinkedIn, and Pinterest. The content generated for each platform is designed to drive traffic back to your newly published blog post, ensuring consistency in your messaging while optimizing for each platform's unique style. and audience preferences. After you create the option, social posts generated, please create also published to social. The automation takes things a step further by actually posting the social media content on your various platforms. This includes pushing posts to Instagram, Twitter or X, Facebook, LinkedIn, and Pinterest, driving traffic to your blog post automatically. Finally, the last step is done, posts published. This step confirms that all tasks in the content creation and publication workflow have been completed. For each option in the status field, you have the flexibility to customize the colors to visually represent the progress of your blog post. As demonstrated in my recording, I've chosen to use green for steps that are complete, signaling that they're ready to move forward. Toward the final stages, I opted for a red color, which marks the process as fully finished and published. Now that we have the status tracker, let's move on to the additional fields. Add a new field called Keywords and set it to Long Text. This will store the keywords used for SEO purposes. I will delete this column because I do not need it, and then create a field called Summary, also using long text, to store a brief description of the article. If you want, you can duplicate the previous column, if this is easier for you. For long-tail keywords, create another long-text field, where you can store your long-tail SEO terms. Let's now add fields to store your blog posts, HTML, links to images, and thumbnails. Add a field named Blog Post HTML and set it to Long Text. This will store the HTML code of your blog post. Create URL 1 and Image 1 fields to store the first image URL and the corresponding image. I'll show you later in this tutorial how to obtain these links. They are crucial because we'll be incorporating them into the final article. By adding them, we'll enhance the article's readability, making it more appealing to both readers and search engines. If you want to include more images in the final article, feel free to add as many as you'd like. In my case, I believe two images are enough. Repeat the same steps for URL 2 and Image 2. Later in this tutorial, this will be handled as a manual step. While it's possible to automate this process, we will intentionally select these links and images manually to ensure they align perfectly with the content of our article. Now let's add the main blog post thumbnail. Create a field named Main Thumbnail and set it to Attachment to store the image file. If you set it as an attachment, later in the table you can see it. If you do not like the main thumbnail, you can recreate it. Finally, let's add fields for your social media posts, so you can manage everything in one place. Add a field for Instagram posts and set it to Long Text to store the caption and hashtags for Instagram. Repeat this for Twitter, X post, Facebook post, LinkedIn post, and Pinterest post, all using the long text field type. You've now created a fully functional Airtable table that can help you manage the entire content creation process. Later, we will move to Make.com to create the automation for our content creation. At this point, your table should have the following fields, article name, status, keywords, summary, long tail keywords, blog post, HTML. two URLs and two images, main thumbnail and the social media fields. Let's move to the automation. Today, we're doing things a bit differently. Instead of building from scratch, I'll be walking you through an existing automation. This way, we can focus on understanding each part of the workflow. I'm assuming you already know the basics, like how to add a module to the canvas or create a connection. We'll be examining each module, explaining its purpose, and showing how it fits into the bigger picture of our automation. Let's start with the very first module of our automation, Airtable. We're using the search records action here, which is crucial for pulling in the data that'll drive our entire workflow. The first step is connecting to Airtable. Click the Add button to set up your Airtable connection. Choose the Token or Key connection type. Now, enter your Airtable credentials. Once connected, select your base from the drop-down menu. Then, Choose the specific table you want to work with. For the output fields, we want to grab all the data, so select All here. After you've done that, just click OK to save your settings. Great job! You've set up the first module. Now let's move on to the next step in our automation. Add a new router module and ensure it's connected to the Airtable module. Create six routes. On the first route, add a perplexity.ai module. I'm using Perplexity because it's excellent for generating up-to-date keywords and factual information when connected to the internet. Note that you'll need to fund your Perplexity account. For reference, I added $3, and this large automation has only cost me a few cents so far. You can generate your API key for Perplexity only after you add some credits. In the Perplexity module, use the Create a Chat Completion action and select the model of your choice. I've used Llama 3 Sonar Online for this setup. In the content area, input the prompt to generate 10 keywords for the article name. Make sure the role is set to user. Click OK to save and proceed to the next step. Add another perplexity module and enter the prompt you want Perplexity AI to process in the content section. Adjust the message to fit your needs. Set the role to user and leave the rest blank. Click OK. Now, create a module to extract long tail keywords. Use the same settings, but change the prompt. You can either pause the video to copy the prompt or create your own. The next module is an Airtable module. Update a record. In this step, we will update the Airtable database with the corresponding fields. Be sure to select the correct base, table, and record ID. At the bottom, input the values from the previous perplexity modules. Keywords Summary and long tail keywords. We have to create a filter in make.com by clicking on the line connecting two modules. In my case, the router and the first perplexity module. Right click on the line and choose Set up a filter. Add a condition by selecting a data variable. In this case, status. Choose an operator. In the screenshot, it's equal to. Enter the value for comparison. In this case, it's one start generating. Once the filter conditions are set, click OK to apply the filter. This will ensure that only data meeting the specified conditions, status equals 1-start-generating, will pass through to the next module in your scenario. When I update the status in my Airtable base to 1-start-generating and run the automation, the workflow will follow this specific route. Let's test the first route by using the following article title. the benefits of using high-quality stock images in your graphic design projects. I'll then run the automation to see it in action. Once I click Run Once, the automation will begin executing. It should take just a few seconds to complete the process. The keywords have already been generated, and from here, the automation will move step-by-step through the workflow until it reaches the final stage, where it will update the Airtable database. As you can see, the results are truly impressive. showcasing the effectiveness of this automation process. This sets a solid foundation for the upcoming stages, ensuring a smooth and efficient workflow. Now that we've set the foundation for our scenario, let's move forward with creating the second route and ensure all the components work together smoothly. Before diving into the details of each module, please take a moment to update your Airtable by adding the two URLs and corresponding images. as these will be automatically inserted into the blog post. For this example, I'll visit my website, sumobundle.com, and copy the link for a bundle featuring 2,700 dog images. I'll paste this link into the URL 1 column in Airtable. Next, I'll right-click on the image, select Copy Image Address, and paste that URL into the Image 1 field. This will ensure the correct images and links are seamlessly integrated into the final blog post. I'll repeat the same process for another bundle. this time for the one featuring 3,300 bird images. I'll copy the link and paste it into the URL-2 column in Airtable. Then, I'll right-click on the image, select Copy Image Address, and paste the URL into the Image 2 field in Airtable. Now, let's return to the automations, and I'll walk you through each step in detail. Our first module is where the magic happens, writing the blog post. We'll use the OpenAI connection to generate the blog post content. As you can see in the video, I've selected the OpenAIG PT4 model and configured two message prompts. In the first prompt, I tell the system to behave like an experienced writer using a personal tone, speaking from the first-person perspective to engage the readers. For the second prompt, I specify the blog post content. I input the article title, summary, and keywords that we previously generated. and instruct it to write the blog post in HTML format. Additionally, I've included instructions for SEO best practices and ensured the images and URLs will be included correctly. The next module is a text parser. In my experience, the ChatGPT module sometimes adds strange characters at the beginning of the text. By using this parser, I can remove those unwanted characters and clean up the content. The final module in our route is the Airtable Update a Record module. Here's how we set it up. Make sure you've connected your Airtable account using the API key or token. Select the correct Airtable base. In this case, we are using createArticlesForMake.com. Choose the correct table within your base. For this example, it's Table 1. Map the Record ID field to ensure the correct record in Airtable is updated. In this example, it's set to 1 ID from the previous step. We'll set the status to 2 Sections Generated to reflect the progress. Insert the blog post HTML content here. You can map it from the previous text parser module or similar. Once all the fields are mapped correctly, click OK to finalize the module setup. The next step is setting up the 2 Prepare Sections filter. Here's how we do it. Right-click on the root and select. Set up a filter. Name the filter to prepare sections. We'll configure this filter to check the status field in Airtable. The condition will be set to trigger when the status equals to-prepare-sections. Once the condition is set, this filter will make sure the automation follows the correct path and only moves forward when the blog post sections are ready to be finalized. To test this, I will first update the status in Airtable to 2 Prepare Sections. This should signal the automation to continue down the correct route, moving forward with preparing the sections of the blog post. I'll then run the automation and carefully monitor to see if it flows through the 2 Prepare Sections filter as expected. If the filter is working correctly, the scenario will proceed to the next module, which focuses on preparing and organizing the blog post sections for publication. This is a critical step, so it's important to ensure the automation runs smoothly through this part of the workflow. Let's run the test and see how it performs. It will take just a few moments for the full blog post to be generated and subsequently update the Airtable base. The process is efficient and ensures that all relevant data is seamlessly transferred and organized in Airtable. Take a look at the result. I'll copy the entire HTML code and then search for an HTML viewer using Google to display the final outcome. This way, you can see exactly how the content looks when rendered. As you can see, the blog post is fully formatted and ready for publication. One key feature is that images are seamlessly integrated within the body of the article, enhancing the visual appeal. Additionally, there's a well-structured FAQ section at the end, providing valuable information and improving the overall user experience. Once the post is created, you'll notice that the status in Airtable has automatically updated to green, labeled... two sections generated. Now, let's move on to the third route in our automation, image generation. In this section, we will generate images based on prompts, retrieve them, and update the Airtable database accordingly. Let's walk through each module step by step. Our first module is create image prompt. In this step, we use the OpenAI connection to generate an image prompt. based on the content we've already created. The GPT model will take the information and create a prompt that will guide the image generation process. This prompt will provide detailed instructions on what type of image to generate, ensuring it aligns with the blog post content. Next, we have two replace modules. The first module is used to remove single quotation marks, there, and the second one is to remove double quotation marks from the generated prompt. From my experience, ChatGPT sometimes adds these characters. which can interfere with the API requests for image generation in the next module. So, these modules clean up the text and ensure the prompt is well-structured for the image generation process. Following this, there's a Wait 3 Seconds module, which ensures a slight pause before proceeding. Now I'll be using an HTTP module and selecting the Make a Request option. To generate images, we'll need an API, and there are several options available. For this tutorial, I'll be using Replicate.com. On Replicate.com, I'll search for either FluxSchnel or FluxPro to handle the image generation. You'll need to create an account on Replicate.com if you don't already have one. Note that you'll need to add your credit card information to obtain your API key. To get your API key, Simply search for the model you want to use. In this case, I'll search for Schnell. Once I find the model, I'll click on it. As you can see, the cost to generate an image is $0.003 per image. On the Models page, click on the API tab, followed by the HTTP option. This will display the URL needed for your API request. In the URL field, Input the API endpoint for the Flux Image Generation model. Select POST as the method. This will send data to the API endpoint for creating the image. Add an authorization header to authenticate the request. Name. Authorization value. This field contains your API key, which is required to access the API. It should be formatted as follows. Bearer set body type to raw. since we'll be sending raw JSON data to the API. Set content type to JSON, application JSON. This ensures that the request body is sent in the correct format that the API expects. In the request content field, input the JSON object that will be sent to the API. Here it is mine with some parameters. Once everything is set up, click OK to save the module. Next, we'll add a module that pauses the automation for 30 seconds. This pause gives the system enough time to generate the image. If you're using FluxPro, I recommend increasing the pause to 60 seconds to ensure the image has time to process. Additionally, don't forget to update the URL with the FluxPro API endpoint accordingly. After the waiting period, the Get Flux Image module retrieves the generated image from the Flux API. This step is critical as it... brings the newly generated image into our workflow, making it ready for further use. For this module, please ensure that you configure the URL exactly as shown in my setup, and don't forget to change the method to GET to retrieve the necessary data. Once the image is retrieved, we use the Download Image module to save the file locally, or in a cloud-based system. This ensures we have a downloadable copy of the image. that can be used within our blog post or stored for future purposes. The final module in this route is image generated. In this step, we update our Airtable database with the image we just generated and also the status. We map the image file to the appropriate field in Airtable, ensuring that the blog post is fully populated with the necessary visual content. Once completed, the image is now ready to be used in the blog post. And that's the complete process For the image generation route, we've successfully generated images based on a custom prompt, cleaned up the text, retrieved the image, and updated our Airtable database with it. Don't forget to set up your filter. I won't be walking you through this step to keep things moving and avoid unnecessary details. Now, let's test this step to ensure everything is working properly. I'll run the automation and check that the image is generated successfully after the pause. This will confirm that the API request is functioning correctly and that the workflow is moving smoothly through each module. Let's see how it performs. The entire process will take around 30 to 40 seconds. Since I'm using the Flux Schnell model, the image quality can be a hit or miss. If you're looking for higher quality images, I recommend switching to Flux Pro. Alternatively, you can regenerate the images by repeating the process. My image has been generated, but there's a small issue with the text. This is an easy fix in Photoshop. The first module in this section is Download the Image. This module retrieves the generated image from the Airtable base, allowing us to download it and use it in the blog post. Make sure the image URL is correctly mapped from the previous steps. This will ensure the image is properly downloaded and ready to be embedded in the Shopify blog post. Next, we use the ChatGPT module to generate the keywords separated by commas. This step ensures that the keywords are properly formatted before publishing. The OpenAI connection reviews the previously generated keywords, identifying and correcting any issues to ensure the final content is optimized and won't interfere with the blog post's appearance or SEO performance. Now we move to the Write the blog post on Shopify module. This step publishes the blog post to your Shopify store, complete with the formatted content and images. Before using this module, ensure that you have a proper connection set up with Shopify. To connect Shopify to Make.com, visit the following link and follow the steps outlined. This guide will help you generate your API key and complete the connection, allowing you to automate blog post publishing seamlessly. Once connected, the module will automatically create an article on Shopify with the content and images generated in the previous steps. Be sure to map the title, content, and image fields properly so the post is published correctly. Finally, the article posted to Shopify module updates your Airtable base or record to reflect that the blog post has been successfully published. The status will be updated to indicate that the task is complete and the post is live on your Shopify store. This module ensures your Airtable record stays in sync with the actions completed in Shopify, providing a clear status update on the post publishing process. Now let's test the automation. I'll update the status in Airtable to 4 post to Shopify, and then trigger the automation. In just a few seconds, I'll head over to my blog and refresh the page a couple of times until the new blog post appears. By automating the blog posting process with properly formatted content and optimized keywords, you'll experience several key benefits. The automation ensures that your posts are SEO-friendly, helping your blog rank higher on search engines like Google. Consistently publishing well-optimized content can improve your site's visibility, making it easier for potential customers to find you. As your site climbs the search engine rankings, it will attract more traffic, ultimately leading to higher conversion rates and increased sales. Now let's move on to the next step, generating posts for social media. Now that we've completed the blog posting automation, it's time to move on to the fifth route, five generate social posts. In this step, we will create social media posts, tailored for various platforms, ensuring a consistent presence across all key networks. Let's walk through the process using the workflow image provided. The first module is convert to plain text. Since the content generated for the blog may contain HTML, we need to convert it to plain text for use in social media posts. This module strips out any HTML formatting, providing us with clean, ready-to-use text that's suitable for all platforms. Next, we use the Instagram post module. In this step, the OpenAI GPT model generates a social media post specifically tailored for Instagram. The prompt includes the plain text from the previous step, and instructs the AI to create an engaging post with relevant hashtags, mentions, and a call to action. After Instagram, we move on to the Twitter X post module. Here, the GPT model generates a post optimized for Twitter, now known as X. This post will be shorter, adhering to Twitter's character limits, and focus on concise messaging, relevant hashtags, and a call to action. The Facebook post module comes next. Using the same plain text, the GPT model generates a post designed for Facebook's platform. This post will likely be a bit longer than the one for Twitter, allowing for more detail while still keeping the message clear and engaging. Next, we have the LinkedIn Post module. This GPT-powered module generates a post that's suitable for LinkedIn's professional audience. It's likely to have a more formal tone, focusing on the business or industry-specific aspects of the content, while also encouraging engagement through content. comments or shares. The last platform-specific module is Pinterest Post. In this step, the GPT model creates a Pinterest-friendly post that aligns with the visual nature of the platform, typically highlighting the most visual or shareable aspects of the content. The final module is Social Posts Generated, where the automation updates the Airtable record to indicate that the social media posts have been successfully generated. This ensures everything is logged and the workflow stays organized. Before testing the fifth route, make sure to set up a filter for this step. The filter should check that the status in Airtable is set to 5 generate social posts. This ensures the workflow only proceeds when the correct trigger is in place. Once the filter is configured, go to your Airtable and update the status to 5 generate social posts. This will activate the automation and begin generating the social media posts for Instagram, TwitterX, Facebook, LinkedIn, and Pinterest. As the posts are generated, the automation will also update Airtable to confirm that the social posts have been successfully created. You can now run the automation and verify that everything is working as expected. In this final route, we will be posting the content directly to various social media platforms such as Pinterest, Facebook pages, and Instagram for business. Let's go step-by-step through the process while ensuring a filter is set up to trigger the automation at the correct time. The first module in this route is Download the Image. This module retrieves the image generated in the previous steps and downloads it for use in the social media posts. The router module is next and is used to to direct the workflow to the appropriate social media platforms. This helps to manage multiple routes simultaneously, posting content on each platform separately, and ensuring that everything is executed properly. In the Pinterest post module, we create a pin using the content and image generated from previous steps. The module automatically publishes the content on your Pinterest account, creating an eye-catching pin for your followers. Make sure to map the post content and image to the relevant fields. This will allow the pin to be published with the right text and image for your campaign. Next, the Facebook Pages module is used to post the content directly to your Facebook business page. This ensures your blog post reaches your Facebook audience, keeping them engaged with fresh and relevant content. Again, map the content fields and images correctly to ensure that the post is published with the necessary information. For Instagram, we use the Instagram for... Business module. This module creates a photo post on your Instagram business account, complete with the image and captions generated in the earlier steps. As Instagram is a visual platform, it's essential to ensure the image and captions are correctly formatted for optimal engagement. Map the image URL and caption fields to ensure everything is properly posted to Instagram. Once all social media posts are published, the final module in this route is Post Published on social. This module updates your Airtable record to indicate that the posts have been successfully published across Pinterest, Facebook pages, and Instagram for business. Before running this automation, don't forget to set up a filter to control when this route is triggered. You should configure the filter to check that the status field in Airtable is set to 6 posts to social. This ensures that the workflow only runs when you intend to publish the social media posts. With this final route, you've automated the entire content creation process, from generating blog posts to publishing social media content across major platforms like Pinterest, Facebook, and Instagram. This streamlined workflow saves you time and effort, ensuring consistent and effective communication with your audience. To wrap things up, I'm excited to let you know that the JSON automation and the Airtable base used in this tutorial will be available soon on our website, sumobundle.com. You'll be able to find the download link in the description below once it's published. Thank you for following along with this tutorial. In future videos, I'll be sharing even more unique and powerful automations to help you streamline your workflows and improve your productivity. Be sure to subscribe and hit the notification bell so you don't miss out on any of the upcoming content. If you found this video helpful, Give it a like and feel free to drop any questions or suggestions in the comments below. Thanks again for watching and I'll see you in the next tutorial.

Here, we are pulling in search results or data from an Airtable base. Airtable serves as our source of information to kickstart the process. Once the data is retrieved, we move on to the next step where it gets routed to different paths.

The next component is a router. This acts as a decision point that directs the data into various branches, allowing multiple parallel workflows to occur simultaneously. From here, our automation splits into six different branches.

In the first branch, we aim to generate the article's structure. Let's break it down. The first step here is to generate the top 10 keywords based on the input data. Then, we summarize key facts and figures related to the article topic.

In this step, we create long-tail keywords to optimize the article for SEO. Finally, a concise summary and the list of all keywords are created and sent back to Airtable. In the second branch, we focus on writing the blog post itself. The blog content is generated automatically based on the data input.

The raw text is parsed and formatted for clarity. The final version of the article is saved in Airtable for further use. Next, we move to the third branch, which handles image generation. Here, we generate an image prompt based on the article topic.

To remove modules follow to clean up any irrelevant data from the prompt. We pause the automation to give some time for the image to be generated by an external service. Once the image is ready, it's retrieved from the service. The final image is downloaded and saved locally. Finally, the image is saved back into Airtable for later use.

In the fourth branch, the blog post gets published on Shopify. The image generated earlier is downloaded for Shopify use. All necessary tags for the blog post are fixed and optimized. In this case, I wrote the keywords separated by comma.

The article is automatically published to Shopify, including the image and the optimized tags. This module confirms that the blog post is successfully published on Shopify. The fifth branch automates the generation of social media posts.

The blog post is converted into plain text, suitable for social media captions. An Instagram post is created based on the blog content. A Twitter or X post is generated.

The content is formatted for a Facebook post. A post is prepared for LinkedIn. The post is adapted for Pinterest. Finally, all social posts are confirmed to be generated and are stored back in Airtable.

In the final branch, the social posts are automatically published across various platforms. The image needed for the social posts is downloaded again for this workflow. Another router splits the workflow into multiple social media platforms.

In my case, I used Instagram, Pinterest, and Facebook. You can add alone any other social platform you use. This entire automation, built with Make.com, streamlines the process of creating content from scratch, optimizing it for SEO, generating images, and posting the final product on various social media platforms. It's an excellent example of how you can save time and automate your content production.

Log into your Airtable account and click on Add a base. Now that we have our table ready, it's time to create all the necessary fields. Let's start with the most important one, the article name. Next up, let's create a status field that tracks where each blog post is in the content creation process. The status field will have multiple stages.

and each will represent a different part of the workflow. Choose single select as the field type. Now, here are the options you'll want to add. Start generating. When I will choose this option, we will start generating keywords and a summary for the article.

Next option is keyword generated. The automation has successfully generated a list of relevant keywords for your article. This includes both primary and long tail keywords that are essential for improving search engine rankings.

In prepare sections, we begin structuring the article. This is where the system organizes the content into logical sections. The sections generated step confirms that the structure of the blog post is in place.

At this point, all the article sections have been created. whether it's the introduction, body paragraphs, or conclusion. This step signals that the article is ready for more detailed content generation. Once the article's structure is set, the next task is to generate image. Well-designed visuals are key to grabbing attention.

In image-generated, the automation confirms that the visual content has been successfully created. At this point, the custom images or graphics are available and can be used within the blog post or on external platforms. Once the content and visuals are ready, the next step is post to Shopify.

Article posted is the confirmation stage where the system verifies that your blog post has been successfully published on Shopify. The next phase is generate social posts. Here, the system automatically creates tailored social media posts for platforms like Instagram, Twitter, OREX, Facebook, LinkedIn, and Pinterest.

The content generated for each platform is designed to drive traffic back to your newly published blog post, ensuring consistency in your messaging while optimizing for each platform's unique style. and audience preferences. After you create the option, social posts generated, please create also published to social. The automation takes things a step further by actually posting the social media content on your various platforms.

This includes pushing posts to Instagram, Twitter or X, Facebook, LinkedIn, and Pinterest, driving traffic to your blog post automatically. Finally, the last step is done, posts published. This step confirms that all tasks in the content creation and publication workflow have been completed.

For each option in the status field, you have the flexibility to customize the colors to visually represent the progress of your blog post. As demonstrated in my recording, I've chosen to use green for steps that are complete, signaling that they're ready to move forward. Toward the final stages, I opted for a red color, which marks the process as fully finished and published.

Now that we have the status tracker, let's move on to the additional fields. Add a new field called Keywords and set it to Long Text. This will store the keywords used for SEO purposes.

I will delete this column because I do not need it, and then create a field called Summary, also using long text, to store a brief description of the article. If you want, you can duplicate the previous column, if this is easier for you. For long-tail keywords, create another long-text field, where you can store your long-tail SEO terms.

Let's now add fields to store your blog posts, HTML, links to images, and thumbnails. Add a field named Blog Post HTML and set it to Long Text. This will store the HTML code of your blog post.

Create URL 1 and Image 1 fields to store the first image URL and the corresponding image. I'll show you later in this tutorial how to obtain these links. They are crucial because we'll be incorporating them into the final article.

By adding them, we'll enhance the article's readability, making it more appealing to both readers and search engines. If you want to include more images in the final article, feel free to add as many as you'd like. In my case, I believe two images are enough.

Repeat the same steps for URL 2 and Image 2. Later in this tutorial, this will be handled as a manual step. While it's possible to automate this process, we will intentionally select these links and images manually to ensure they align perfectly with the content of our article. Now let's add the main blog post thumbnail.

Create a field named Main Thumbnail and set it to Attachment to store the image file. If you set it as an attachment, later in the table you can see it. If you do not like the main thumbnail, you can recreate it. Finally, let's add fields for your social media posts, so you can manage everything in one place. Add a field for Instagram posts and set it to Long Text to store the caption and hashtags for Instagram.

Repeat this for Twitter, X post, Facebook post, LinkedIn post, and Pinterest post, all using the long text field type. You've now created a fully functional Airtable table that can help you manage the entire content creation process. Later, we will move to Make.com to create the automation for our content creation. At this point, your table should have the following fields, article name, status, keywords, summary, long tail keywords, blog post, HTML. two URLs and two images, main thumbnail and the social media fields.

Let's move to the automation. Today, we're doing things a bit differently. Instead of building from scratch, I'll be walking you through an existing automation. This way, we can focus on understanding each part of the workflow. I'm assuming you already know the basics, like how to add a module to the canvas or create a connection.

We'll be examining each module, explaining its purpose, and showing how it fits into the bigger picture of our automation. Let's start with the very first module of our automation, Airtable. We're using the search records action here, which is crucial for pulling in the data that'll drive our entire workflow. The first step is connecting to Airtable. Click the Add button to set up your Airtable connection.

Choose the Token or Key connection type. Now, enter your Airtable credentials. Once connected, select your base from the drop-down menu.

Then, Choose the specific table you want to work with. For the output fields, we want to grab all the data, so select All here. After you've done that, just click OK to save your settings. Great job! You've set up the first module.

Now let's move on to the next step in our automation. Add a new router module and ensure it's connected to the Airtable module. Create six routes. On the first route, add a perplexity.ai module.

I'm using Perplexity because it's excellent for generating up-to-date keywords and factual information when connected to the internet. Note that you'll need to fund your Perplexity account. For reference, I added $3, and this large automation has only cost me a few cents so far.

You can generate your API key for Perplexity only after you add some credits. In the Perplexity module, use the Create a Chat Completion action and select the model of your choice. I've used Llama 3 Sonar Online for this setup. In the content area, input the prompt to generate 10 keywords for the article name. Make sure the role is set to user.

Click OK to save and proceed to the next step. Add another perplexity module and enter the prompt you want Perplexity AI to process in the content section. Adjust the message to fit your needs.

Set the role to user and leave the rest blank. Click OK. Now, create a module to extract long tail keywords.

Use the same settings, but change the prompt. You can either pause the video to copy the prompt or create your own. The next module is an Airtable module.

Update a record. In this step, we will update the Airtable database with the corresponding fields. Be sure to select the correct base, table, and record ID. At the bottom, input the values from the previous perplexity modules. Keywords Summary and long tail keywords.

We have to create a filter in make.com by clicking on the line connecting two modules. In my case, the router and the first perplexity module. Right click on the line and choose Set up a filter. Add a condition by selecting a data variable. In this case, status.

Choose an operator. In the screenshot, it's equal to. Enter the value for comparison. In this case, it's one start generating. Once the filter conditions are set, click OK to apply the filter.

This will ensure that only data meeting the specified conditions, status equals 1-start-generating, will pass through to the next module in your scenario. When I update the status in my Airtable base to 1-start-generating and run the automation, the workflow will follow this specific route. Let's test the first route by using the following article title. the benefits of using high-quality stock images in your graphic design projects.

I'll then run the automation to see it in action. Once I click Run Once, the automation will begin executing. It should take just a few seconds to complete the process. The keywords have already been generated, and from here, the automation will move step-by-step through the workflow until it reaches the final stage, where it will update the Airtable database.

As you can see, the results are truly impressive. showcasing the effectiveness of this automation process. This sets a solid foundation for the upcoming stages, ensuring a smooth and efficient workflow. Now that we've set the foundation for our scenario, let's move forward with creating the second route and ensure all the components work together smoothly. Before diving into the details of each module, please take a moment to update your Airtable by adding the two URLs and corresponding images.

as these will be automatically inserted into the blog post. For this example, I'll visit my website, sumobundle.com, and copy the link for a bundle featuring 2,700 dog images. I'll paste this link into the URL 1 column in Airtable. Next, I'll right-click on the image, select Copy Image Address, and paste that URL into the Image 1 field. This will ensure the correct images and links are seamlessly integrated into the final blog post.

I'll repeat the same process for another bundle. this time for the one featuring 3,300 bird images. I'll copy the link and paste it into the URL-2 column in Airtable. Then, I'll right-click on the image, select Copy Image Address, and paste the URL into the Image 2 field in Airtable. Now, let's return to the automations, and I'll walk you through each step in detail.

Our first module is where the magic happens, writing the blog post. We'll use the OpenAI connection to generate the blog post content. As you can see in the video, I've selected the OpenAIG PT4 model and configured two message prompts. In the first prompt, I tell the system to behave like an experienced writer using a personal tone, speaking from the first-person perspective to engage the readers. For the second prompt, I specify the blog post content.

I input the article title, summary, and keywords that we previously generated. and instruct it to write the blog post in HTML format. Additionally, I've included instructions for SEO best practices and ensured the images and URLs will be included correctly.

The next module is a text parser. In my experience, the ChatGPT module sometimes adds strange characters at the beginning of the text. By using this parser, I can remove those unwanted characters and clean up the content.

The final module in our route is the Airtable Update a Record module. Here's how we set it up. Make sure you've connected your Airtable account using the API key or token.

Select the correct Airtable base. In this case, we are using createArticlesForMake.com. Choose the correct table within your base.

For this example, it's Table 1. Map the Record ID field to ensure the correct record in Airtable is updated. In this example, it's set to 1 ID from the previous step. We'll set the status to 2 Sections Generated to reflect the progress. Insert the blog post HTML content here. You can map it from the previous text parser module or similar.

Once all the fields are mapped correctly, click OK to finalize the module setup. The next step is setting up the 2 Prepare Sections filter. Here's how we do it.

Right-click on the root and select. Set up a filter. Name the filter to prepare sections.

We'll configure this filter to check the status field in Airtable. The condition will be set to trigger when the status equals to-prepare-sections. Once the condition is set, this filter will make sure the automation follows the correct path and only moves forward when the blog post sections are ready to be finalized.

To test this, I will first update the status in Airtable to 2 Prepare Sections. This should signal the automation to continue down the correct route, moving forward with preparing the sections of the blog post. I'll then run the automation and carefully monitor to see if it flows through the 2 Prepare Sections filter as expected.

If the filter is working correctly, the scenario will proceed to the next module, which focuses on preparing and organizing the blog post sections for publication. This is a critical step, so it's important to ensure the automation runs smoothly through this part of the workflow. Let's run the test and see how it performs.

It will take just a few moments for the full blog post to be generated and subsequently update the Airtable base. The process is efficient and ensures that all relevant data is seamlessly transferred and organized in Airtable. Take a look at the result. I'll copy the entire HTML code and then search for an HTML viewer using Google to display the final outcome.

This way, you can see exactly how the content looks when rendered. As you can see, the blog post is fully formatted and ready for publication. One key feature is that images are seamlessly integrated within the body of the article, enhancing the visual appeal. Additionally, there's a well-structured FAQ section at the end, providing valuable information and improving the overall user experience. Once the post is created, you'll notice that the status in Airtable has automatically updated to green, labeled...

two sections generated. Now, let's move on to the third route in our automation, image generation. In this section, we will generate images based on prompts, retrieve them, and update the Airtable database accordingly.

Let's walk through each module step by step. Our first module is create image prompt. In this step, we use the OpenAI connection to generate an image prompt.

based on the content we've already created. The GPT model will take the information and create a prompt that will guide the image generation process. This prompt will provide detailed instructions on what type of image to generate, ensuring it aligns with the blog post content. Next, we have two replace modules. The first module is used to remove single quotation marks, there, and the second one is to remove double quotation marks from the generated prompt.

From my experience, ChatGPT sometimes adds these characters. which can interfere with the API requests for image generation in the next module. So, these modules clean up the text and ensure the prompt is well-structured for the image generation process. Following this, there's a Wait 3 Seconds module, which ensures a slight pause before proceeding.

Now I'll be using an HTTP module and selecting the Make a Request option. To generate images, we'll need an API, and there are several options available. For this tutorial, I'll be using Replicate.com.

On Replicate.com, I'll search for either FluxSchnel or FluxPro to handle the image generation. You'll need to create an account on Replicate.com if you don't already have one. Note that you'll need to add your credit card information to obtain your API key.

To get your API key, Simply search for the model you want to use. In this case, I'll search for Schnell. Once I find the model, I'll click on it. As you can see, the cost to generate an image is $0.003 per image. On the Models page, click on the API tab, followed by the HTTP option.

This will display the URL needed for your API request. In the URL field, Input the API endpoint for the Flux Image Generation model. Select POST as the method.

This will send data to the API endpoint for creating the image. Add an authorization header to authenticate the request. Name. Authorization value. This field contains your API key, which is required to access the API.

It should be formatted as follows. Bearer set body type to raw. since we'll be sending raw JSON data to the API. Set content type to JSON, application JSON.

This ensures that the request body is sent in the correct format that the API expects. In the request content field, input the JSON object that will be sent to the API. Here it is mine with some parameters.

Once everything is set up, click OK to save the module. Next, we'll add a module that pauses the automation for 30 seconds. This pause gives the system enough time to generate the image.

If you're using FluxPro, I recommend increasing the pause to 60 seconds to ensure the image has time to process. Additionally, don't forget to update the URL with the FluxPro API endpoint accordingly. After the waiting period, the Get Flux Image module retrieves the generated image from the Flux API. This step is critical as it...

brings the newly generated image into our workflow, making it ready for further use. For this module, please ensure that you configure the URL exactly as shown in my setup, and don't forget to change the method to GET to retrieve the necessary data. Once the image is retrieved, we use the Download Image module to save the file locally, or in a cloud-based system.

This ensures we have a downloadable copy of the image. that can be used within our blog post or stored for future purposes. The final module in this route is image generated. In this step, we update our Airtable database with the image we just generated and also the status.

We map the image file to the appropriate field in Airtable, ensuring that the blog post is fully populated with the necessary visual content. Once completed, the image is now ready to be used in the blog post. And that's the complete process For the image generation route, we've successfully generated images based on a custom prompt, cleaned up the text, retrieved the image, and updated our Airtable database with it.

Don't forget to set up your filter. I won't be walking you through this step to keep things moving and avoid unnecessary details. Now, let's test this step to ensure everything is working properly.

I'll run the automation and check that the image is generated successfully after the pause. This will confirm that the API request is functioning correctly and that the workflow is moving smoothly through each module. Let's see how it performs.

The entire process will take around 30 to 40 seconds. Since I'm using the Flux Schnell model, the image quality can be a hit or miss. If you're looking for higher quality images, I recommend switching to Flux Pro.

Alternatively, you can regenerate the images by repeating the process. My image has been generated, but there's a small issue with the text. This is an easy fix in Photoshop.

The first module in this section is Download the Image. This module retrieves the generated image from the Airtable base, allowing us to download it and use it in the blog post. Make sure the image URL is correctly mapped from the previous steps. This will ensure the image is properly downloaded and ready to be embedded in the Shopify blog post.

Next, we use the ChatGPT module to generate the keywords separated by commas. This step ensures that the keywords are properly formatted before publishing. The OpenAI connection reviews the previously generated keywords, identifying and correcting any issues to ensure the final content is optimized and won't interfere with the blog post's appearance or SEO performance. Now we move to the Write the blog post on Shopify module.

This step publishes the blog post to your Shopify store, complete with the formatted content and images. Before using this module, ensure that you have a proper connection set up with Shopify. To connect Shopify to Make.com, visit the following link and follow the steps outlined. This guide will help you generate your API key and complete the connection, allowing you to automate blog post publishing seamlessly. Once connected, the module will automatically create an article on Shopify with the content and images generated in the previous steps.

Be sure to map the title, content, and image fields properly so the post is published correctly. Finally, the article posted to Shopify module updates your Airtable base or record to reflect that the blog post has been successfully published. The status will be updated to indicate that the task is complete and the post is live on your Shopify store. This module ensures your Airtable record stays in sync with the actions completed in Shopify, providing a clear status update on the post publishing process. Now let's test the automation.

I'll update the status in Airtable to 4 post to Shopify, and then trigger the automation. In just a few seconds, I'll head over to my blog and refresh the page a couple of times until the new blog post appears. By automating the blog posting process with properly formatted content and optimized keywords, you'll experience several key benefits.

The automation ensures that your posts are SEO-friendly, helping your blog rank higher on search engines like Google. Consistently publishing well-optimized content can improve your site's visibility, making it easier for potential customers to find you. As your site climbs the search engine rankings, it will attract more traffic, ultimately leading to higher conversion rates and increased sales.

Now let's move on to the next step, generating posts for social media. Now that we've completed the blog posting automation, it's time to move on to the fifth route, five generate social posts. In this step, we will create social media posts, tailored for various platforms, ensuring a consistent presence across all key networks. Let's walk through the process using the workflow image provided.

The first module is convert to plain text. Since the content generated for the blog may contain HTML, we need to convert it to plain text for use in social media posts. This module strips out any HTML formatting, providing us with clean, ready-to-use text that's suitable for all platforms.

Next, we use the Instagram post module. In this step, the OpenAI GPT model generates a social media post specifically tailored for Instagram. The prompt includes the plain text from the previous step, and instructs the AI to create an engaging post with relevant hashtags, mentions, and a call to action. After Instagram, we move on to the Twitter X post module. Here, the GPT model generates a post optimized for Twitter, now known as X.

This post will be shorter, adhering to Twitter's character limits, and focus on concise messaging, relevant hashtags, and a call to action. The Facebook post module comes next. Using the same plain text, the GPT model generates a post designed for Facebook's platform. This post will likely be a bit longer than the one for Twitter, allowing for more detail while still keeping the message clear and engaging. Next, we have the LinkedIn Post module.

This GPT-powered module generates a post that's suitable for LinkedIn's professional audience. It's likely to have a more formal tone, focusing on the business or industry-specific aspects of the content, while also encouraging engagement through content. comments or shares.

The last platform-specific module is Pinterest Post. In this step, the GPT model creates a Pinterest-friendly post that aligns with the visual nature of the platform, typically highlighting the most visual or shareable aspects of the content. The final module is Social Posts Generated, where the automation updates the Airtable record to indicate that the social media posts have been successfully generated. This ensures everything is logged and the workflow stays organized. Before testing the fifth route, make sure to set up a filter for this step.

The filter should check that the status in Airtable is set to 5 generate social posts. This ensures the workflow only proceeds when the correct trigger is in place. Once the filter is configured, go to your Airtable and update the status to 5 generate social posts.

This will activate the automation and begin generating the social media posts for Instagram, TwitterX, Facebook, LinkedIn, and Pinterest. As the posts are generated, the automation will also update Airtable to confirm that the social posts have been successfully created. You can now run the automation and verify that everything is working as expected. In this final route, we will be posting the content directly to various social media platforms such as Pinterest, Facebook pages, and Instagram for business. Let's go step-by-step through the process while ensuring a filter is set up to trigger the automation at the correct time.

The first module in this route is Download the Image. This module retrieves the image generated in the previous steps and downloads it for use in the social media posts. The router module is next and is used to to direct the workflow to the appropriate social media platforms.

This helps to manage multiple routes simultaneously, posting content on each platform separately, and ensuring that everything is executed properly. In the Pinterest post module, we create a pin using the content and image generated from previous steps. The module automatically publishes the content on your Pinterest account, creating an eye-catching pin for your followers. Make sure to map the post content and image to the relevant fields. This will allow the pin to be published with the right text and image for your campaign.

Next, the Facebook Pages module is used to post the content directly to your Facebook business page. This ensures your blog post reaches your Facebook audience, keeping them engaged with fresh and relevant content. Again, map the content fields and images correctly to ensure that the post is published with the necessary information. For Instagram, we use the Instagram for...

Business module. This module creates a photo post on your Instagram business account, complete with the image and captions generated in the earlier steps. As Instagram is a visual platform, it's essential to ensure the image and captions are correctly formatted for optimal engagement. Map the image URL and caption fields to ensure everything is properly posted to Instagram.

Once all social media posts are published, the final module in this route is Post Published on social. This module updates your Airtable record to indicate that the posts have been successfully published across Pinterest, Facebook pages, and Instagram for business. Before running this automation, don't forget to set up a filter to control when this route is triggered. You should configure the filter to check that the status field in Airtable is set to 6 posts to social. This ensures that the workflow only runs when you intend to publish the social media posts.

With this final route, you've automated the entire content creation process, from generating blog posts to publishing social media content across major platforms like Pinterest, Facebook, and Instagram. This streamlined workflow saves you time and effort, ensuring consistent and effective communication with your audience. To wrap things up, I'm excited to let you know that the JSON automation and the Airtable base used in this tutorial will be available soon on our website, sumobundle.com. You'll be able to find the download link in the description below once it's published.

Thank you for following along with this tutorial. In future videos, I'll be sharing even more unique and powerful automations to help you streamline your workflows and improve your productivity. Be sure to subscribe and hit the notification bell so you don't miss out on any of the upcoming content. If you found this video helpful, Give it a like and feel free to drop any questions or suggestions in the comments below. Thanks again for watching and I'll see you in the next tutorial.

Transcript for:Efficient Content Automation with Make.com

Transcript for:
Efficient Content Automation with Make.com