Creating engaging Instagram Reels can be a daunting task, especially when trying to stand out in a crowded space.
In this post, I’ll guide you through an automation process that leverages competitor analysis and data scraping to generate compelling scripts and visuals for your own Instagram posts, all managed through Google Sheets.
I’ve put together a full walk-through below, but if you want to see if all in action from start to finish then check out my video:
To start off with an example, I focused on a few competitors in the cleaning niche. First, I looked at their follower count, engagement rates, and the types of content they shared. This gave me a clear idea of their strengths and weaknesses. For instance, Go Clean Go boasts a following of over 2.4 million, while The Organized MOM has almost 300,000 followers. Both have unique styles that attract their audiences.
Identifying the most engaging posts is crucial. I gathered data on their recent posts to see which ones garnered the most likes, comments, and views. This information helps in understanding the content that captures attention and drives engagement. By analyzing these metrics, I could determine patterns and themes that work well within this niche.
Not every post will perform equally, and that’s normal. Some themes may resonate more with the audience than others. By tracking these variations, I can refine my content strategy to align with what viewers find appealing. The goal is to leverage successful elements from competitors’ content while adding a unique twist to my own posts.
Setting Up the Automation System
I created an automation system that streamlines the data collection process for competitor analysis. This system uses a no-code platform called Make, which allows for seamless integration with various tools. One of the key components is Apify, a web scraping tool that pulls the latest posts from selected Instagram profiles.
To set this up, I first logged into Apify and searched for the Instagram profile scraper. This tool extracts relevant data, such as the latest posts and engagement metrics, from competitor accounts. After entering the usernames of my competitors, I initiated the scraping process. This step is crucial as it gathers all the necessary data for further analysis.
Once the data was scraped, it was time to integrate it into my automation workflow. I connected Apify to Make, allowing me to run the Instagram profile scraper and fetch the data in real time. This integration ensures that I always have the latest information on my competitors, making my analysis timely and relevant.
After setting up the integration, I created a Google Sheet to store the scraped data. This sheet serves as a central hub for all the information collected from competitors. The structure of the sheet includes columns for usernames, follower counts, and engagement metrics, which makes it easy to analyze the data later.
Storing Data in Google Sheets
Storing data in Google Sheets provides a convenient way to manage and analyze the information collected from competitors. Once the data is scraped from Apify, it automatically populates into the designated Google Sheet. This eliminates the need for manual data entry, saving time and reducing errors.
Each competitor’s data is organized into specific tabs within the sheet. I created a tab for competitors, which includes their usernames, follower counts, and engagement metrics. Another tab is dedicated to individual posts, where I track details such as post ID, content type, likes, comments, and views. This structured approach allows for easy access and analysis of the data.
As I analyze the posts, I look for trends in engagement. For example, I categorize posts based on their content type—whether they are videos, images, or carousels. By doing this, I can identify which formats generate the most interaction. This insight is invaluable for shaping future content strategies.
In addition to tracking engagement, I also developed a unique metric called the “content impact score.” This score considers various factors, including follower count and engagement rates, to assess the effectiveness of each post. By weighing these elements, I can pinpoint which posts truly resonate with the audience.
Overall, the combination of Apify, Make, and Google Sheets creates a powerful system for competitor analysis. By automating data collection and organization, I can focus more on creating engaging content rather than getting bogged down in data entry. This efficiency is key to staying ahead in the competitive landscape of Instagram.
Calculating Engagement Metrics
Engagement metrics are essential for understanding how well your posts resonate with your audience. I’ve integrated several key performance indicators (KPIs) into my automation system to measure this effectively. These metrics help determine whether a post is successful and how it compares to others.
First, I created a new tab in my Google Sheet specifically for KPIs. This tab pulls in essential information from the posts tab, such as likes, comments, and views. To analyze how old a post is, I added a formula that calculates the number of days since the post was published. This gives insight into the freshness of the content and allows for comparisons across different timelines.
Next, I included engagement rates, calculated as the sum of likes and comments divided by the number of views. This metric is particularly useful for video posts, as it provides a clear picture of how engaging the content is. For posts that aren’t videos, I also created an engagement rate based on the number of followers, which offers a broader view of engagement across all types of content.
To further enhance my analysis, I added additional metrics such as likes to views ratio and comments to likes ratio. These ratios help me understand not just how many people liked a post, but how engaged they were relative to the views it received. Lastly, I implemented a recency KPI that weighs newer posts more heavily than older ones, ensuring that my analysis reflects current trends.
Generating Content Sheets
Generating content sheets is a crucial step in my automation process. These sheets allow me to organize and prepare the content I want to create based on the insights gathered from competitor analysis. I’ve set up a dedicated tab called “Prompts” where I can continually update the prompts I use for generating new content.
Each prompt sheet includes a brief description of my Instagram page, which helps orient the content generation process. I also include a source ID for tracking purposes. This ID is essential for linking back to the original post that inspired the new content, providing a clear reference point.
When I want to generate new content, I input the source ID into the content sheet and trigger the automation. This process pulls in relevant information from the posts tab using a VLOOKUP function. It fetches details like the post content, image, and video URL, which are essential for crafting the new post.
Once the source information is gathered, I can trigger the automation to generate the content. The system processes the information and creates a new draft that aligns with my brand while taking inspiration from successful competitor posts. This ensures that the content is fresh and relevant, increasing the chances of engagement.
Creating Generation Scenarios
Creating generation scenarios is another vital component of my automation workflow. After setting up my content sheets, I established a new automation specifically for generating content based on the prompts I created. This involves using a Google Sheets add-on to create a webhook that watches for changes in specific columns.
By monitoring the “Ready” column, I can trigger content generation whenever I type “Go” into the sheet. This seamless integration allows me to initiate the automation quickly without needing to manually run scripts or processes.
Once the trigger is activated, the automation fetches the prompt details and begins processing the input. It distinguishes between video and image posts, directing the workflow accordingly. For video posts, it transcribes the audio to generate a script, while for images, it analyzes the visual content to create descriptive text.
This structured approach ensures that each piece of content is not only inspired by high-performing posts but also tailored to fit my brand’s voice and objectives. The automation efficiently generates new scripts, hashtags, and image prompts for each new post, saving significant time and effort in content creation.
Generating Images for Posts
Generating images for posts is the final step in my automation process. After creating the text content, I utilize an image generation tool to produce visuals that complement the new posts. I’ve integrated a powerful image generator that uses advanced algorithms to create high-quality images based on prompts.
When it comes to generating images, I input descriptive prompts that reflect the content of the post. For example, if the post is about organizing a cluttered space, I might prompt the generator with a description of a transformed area. This ensures that the images align perfectly with the narrative of the post.
The image generator processes the prompt and produces a visual that captures the essence of the content. This allows me to maintain a cohesive aesthetic across my Instagram feed, which is crucial for brand identity. Once the images are generated, they are automatically saved to the content sheet, ready for use in upcoming posts.
By automating the image generation process, I can create visually appealing content quickly and efficiently, ensuring that my posts stand out in the crowded Instagram landscape. This comprehensive automation system not only saves time but also enhances the quality and engagement potential of my social media presence.
Demo of the Automation in Action
To illustrate the effectiveness of my automation, I ran a demo that showcased how the system generates content based on competitor analysis. The output was impressive. For instance, it created a script focused on transforming a kitchen space into a cozy breakfast nook. While the original inspiration was a birthday breakfast post, the automation adapted creatively to present a more engaging theme.
The generated content included not just text for the post but also hashtags and a detailed video script. It outlined various scenes where the character, Emily, declutters countertops and sets up a coffee station. This level of detail helps in visualizing the reel’s flow and structure, making it easier to shoot.
I decided to run the automation again to see what it would produce. This time, it shifted focus to a family movie night concept, providing steps to set up a home theater in the living room. The generated content was engaging and visually appealing, showcasing the flexibility of the automation in generating diverse themes.
The system works seamlessly across various content formats, including Instagram galleries, images, and reels. It takes inspiration from high-performing posts, ensuring that the generated content resonates with the target audience. This analytical approach significantly increases the chances of engagement since it leverages data from successful competitors.
To ensure the automation accommodates both video and image posts, I made some adjustments. For instance, I duplicated certain modules to create a fallback route when a video isn’t available. This flexibility allows for generating content that suits various formats without compromising quality.
After finalizing the setup, I renamed the automation to “Instagram Generate Content.” This name reflects its purpose: generating viral posts, scripts for reels, stories, images, and galleries. The automation is designed to run weekly, adapting to the frequency of new posts from competitors.
Final Steps in the Automation Process
Completing the automation involved adding several new features to enhance usability. One such feature is a cover page that allows users to trigger a full data import easily. This button utilizes a Google Apps script, making it convenient to initiate the analysis without needing to log into external platforms.
With this setup, there’s no need to access Make.com regularly. Instead, users can simply press the import data button to trigger the analysis, streamlining the entire process. This feature is especially useful for those who prefer a straightforward approach to managing their automation.
The only requirement for this feature to work effectively is that the script must trigger a webhook on Make.com. This integration allows the automation to function seamlessly, ensuring that users can manage their content generation without hassle.
Additionally, I’ve created a dashboard that showcases a viral report. This report highlights the top five posts based on their content impact score, likes, views, and comments. It’s an excellent tool for quickly assessing which posts are performing well, even if they are relatively new.
These enhancements make the automation not just effective but also user-friendly. The system is designed to adapt to individual needs, providing valuable insights into content performance while simplifying the process of generating new posts.
