How to Use Make.com AI Content Extractor

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How to Use Make.com AI Content Extractor

The latest AI Content Extractor and Shopify app updates in make.com let you reliably extract, structure, and reuse website and Shopify data inside your scenarios with far less manual work. This guide walks you through how to use these changes step by step.

What Changed in Make.com AI Content Extractor

The AI Content Extractor in make.com has been redesigned to generate more consistent, structured outputs and to give you better control over which content is captured.

  • Improved consistency of extracted fields.
  • Clearer distinction between static and dynamic data.
  • Better handling of lists, sections, and blocks of content.
  • More predictable mapping options for downstream modules.

These improvements directly reduce the amount of manual cleaning or additional tools you previously needed between the extractor and your next modules.

Before You Start in Make.com

To follow this how-to, you need:

  • An active make.com account.
  • Access to the AI Content Extractor feature.
  • A URL, webpage, or source you want to analyze (for example, a blog page or product description).
  • Optional: Shopify store access if you want to use the new Shopify-related updates.

You should also be familiar with creating a basic scenario, adding modules, and mapping output fields, as those are core skills for working efficiently in make.com.

How to Configure the Make.com AI Content Extractor

Use the steps below to add and configure the improved AI Content Extractor in a scenario.

Step 1: Create or Open a Scenario in Make.com

  1. Log into your make.com dashboard.
  2. Click Create a new scenario or open an existing one where you want to use extracted content.
  3. Identify where in the data flow content extraction should happen (usually after a trigger that provides a URL or text).

Step 2: Add the AI Content Extractor Module

  1. Click the + icon to add a new module.
  2. Search for AI Content Extractor.
  3. Select the module and connect it at the correct point in your scenario.

This module is where the updated extraction logic from make.com will process your source content.

Step 3: Define the Source Content

You can feed the extractor from different sources, depending on your use case:

  • URL – Extract content from a live webpage.
  • Raw HTML – Use HTML pulled from another module.
  • Plain text – Analyze blog articles, support tickets, or product descriptions.
  1. Choose the appropriate input type in the module.
  2. Map the relevant field from the previous module (for example, a URL from a webhook or Shopify product).

Step 4: Configure Extraction Targets

The updated extractor in make.com focuses on clearer, more predictable structures. Typical configurations include:

  • Titles and headings (H1, H2, etc.).
  • Body content as long-form text.
  • Lists and bullet points converted into arrays.
  • Metadata such as author, date, or tags, when available.
  1. In the module settings, choose which elements you want to capture.
  2. Enable or disable optional sections you do not need to simplify downstream mapping.
  3. Optionally provide instructions or guidelines to fine-tune what the extractor should prioritize.

Step 5: Test the Extraction

  1. Click Run once in your scenario.
  2. Trigger the scenario so the AI Content Extractor receives data.
  3. Open the execution detail and inspect the module output.

Confirm that:

  • The main content you need is present.
  • Lists, sections, and fields are structured in a way that fits the rest of your flow.
  • There are no missing or unexpected fields.

If needed, adjust the extractor settings and re-run until the output from make.com matches your requirements.

Using Make.com AI Content Extractor Output

Once extraction is configured, use the structured data in other modules to automate and enrich your workflows.

Common Ways to Use Extracted Content

  • Summarization: Send extracted text to an AI or text-processing module for shorter summaries.
  • Tagging and categorization: Analyze text for keywords or categories and write them to a database.
  • Translation: Route content into translation modules and publish localized versions.
  • Reporting: Combine extracted fields into dashboards or scheduled reports.

Mapping Extracted Fields in Make.com

  1. Add a downstream module such as Google Sheets, Airtable, email, or another app.
  2. In the mapping panel, open the output from the AI Content Extractor module.
  3. Drag and drop extracted fields (for example, title, main_text, bullets[]) into the destination fields.

The structured output ensures you spend less time cleaning data and more time automating valuable tasks in make.com.

New Shopify Version Updates in Make.com

Alongside the AI Content Extractor, a newer Shopify app version in make.com improves how product and store data is handled.

What the New Shopify Version Improves

  • More up-to-date coverage of Shopify APIs.
  • Better support for current product, order, and customer fields.
  • More reliable connections and mapping options.

These updates help ensure your Shopify workflows stay aligned with platform changes and integrate smoothly with extracted content.

How to Use Shopify with AI Content Extractor

  1. Add a Shopify module as a trigger or data source (for example, Watch Products or Get a Product).
  2. Map fields such as product descriptions or pages into the AI Content Extractor module.
  3. Configure the extractor to pull key details (highlights, benefit bullets, SEO text, etc.).
  4. Send the enriched data to your CMS, emails, ads, or analytics tools through other make.com modules.

This combination creates powerful content pipelines that start directly from new or updated Shopify items.

Best Practices for Make.com AI Content Extractor

To get stable results over time, follow these practices when using the updated extractor in make.com.

  • Keep inputs consistent: Use similar page templates and structures whenever possible.
  • Limit noise: Avoid feeding navigation, footers, and unrelated sections when you only need main content.
  • Validate outputs: Add filters or conditions to handle missing or malformed content.
  • Log examples: Store a sample of extracted outputs in a sheet or database to track quality over time.

Troubleshooting Make.com Content Extraction

If the extractor output is not what you expect, you can systematically fix it.

Common Issues and Fixes

  • Important fields are missing
    Refine extraction settings or adjust the source content so headings and sections are more explicit.
  • Too much irrelevant text
    Limit extraction to specific areas or use filters after extraction to remove unwanted sections.
  • Structure changes between pages
    Group similar templates into separate scenarios or use conditional logic to handle variations.

If issues persist, compare a working and non-working example side by side and adjust page structure or extractor configuration accordingly within make.com.

Additional Resources for Make.com Users

For full technical details and the latest release information, review the official update article at the make.com AI Content Extractor and Shopify updates page.

If you need strategic help designing complex automations, you can also consult experienced implementation partners such as Consultevo, who specialize in automation platforms.

By combining the improved AI Content Extractor with the updated Shopify app version in make.com, you can turn unstructured content into consistent, reusable data that powers advanced, scalable workflows.

Need Help With Make.com?

If you want expert help building, automating, or scaling your Make scenarios, work with ConsultEvo — certified workflow and automation specialists.

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