How to scrape alternative data from SE Ranking using the Minexa.ai extension

Website traffic data is one of the most useful signals for competitive research, SEO benchmarking, and market sizing. SE Ranking publishes traffic estimates for domains directly on its website traffic checker page, and with the Minexa.ai Chrome extension, you can pull that data into a structured spreadsheet without writing a single line of code.

This walkthrough shows you exactly how to do it, step by step, with screenshots at each stage so you know what to expect.

Watch the full tutorial first

Before going through the screenshots, watch the video below. It covers the entire extraction from start to finish and gives you a clear sense of how the process flows before you try it yourself.

Step-by-step extraction walkthrough

Step 1: Open Minexa.ai

Start by opening the Minexa.ai extension from your Chrome browser. You will land on the Minexa.ai home screen, where you can begin a new scraping job. If you have not installed it yet, you can get it from the Chrome Web Store.

Once the extension is open, navigate to the SE Ranking website traffic checker page at seranking.com/nl/website-traffic-checker.html. This is the page containing the traffic data you want to extract.

Step 2: Confirm you are on the right page

After the SE Ranking page loads, Minexa.ai detects the page structure automatically. A popup appears in the extension asking you to confirm that you are on the correct page. Click the "I'm on the right page" button to proceed.

This confirmation step is quick. Minexa.ai has already identified the repeating data patterns on the page at this point, so you are not pointing out fields manually. You are simply confirming the right starting point.

Step 3: Review pagination detection

Minexa.ai then shows you which pagination method it detected on the SE Ranking page, along with a Continue button. Review the detected pagination option and click Continue to move forward.

Minexa.ai handles pagination automatically across all common types including next page buttons, infinite scroll, and load more buttons. You do not need to configure anything here.

Step 4: Choose your scraping scope

Next, you choose whether to scrape just the list visible on the SE Ranking page, or to follow each result link and also extract data from the individual detail pages. For most traffic data use cases, scraping the single list is sufficient.

Step 5: Select your scraping mode

After choosing your scope, you select between simple scraping mode and advanced mode. Simple mode works well for most pages. Advanced mode is available if you need custom interactions or a more specific workflow before extraction begins.

Step 6: Highlight the data container

Minexa.ai now highlights the full data container on the SE Ranking page automatically. This is the section of the page holding all the traffic records. You are selecting the wrapper element, not individual fields. Minexa.ai discovers all the data points inside it on its own.

Once you confirm the container, click "Create Scraper" and wait a short moment while Minexa.ai builds the scraper for this page structure.

Step 7: Review extracted data points

After the scraper is created, all extracted data points appear as columns. You can navigate through them using the next and previous arrows to review what was captured from the SE Ranking traffic checker page.

What the extracted data looks like

Here is an example of what Minexa.ai returns from the SE Ranking traffic checker page. Each row corresponds to one domain entry, with fields covering the domain name, traffic volume, change indicator, and position data.

[
  {
    "domain": "example.com",
    "traffic_volume": "142,300",
    "traffic_change": "+8.4%",
    "ranking_position": "12",
    "source_label": "Organic"
  },
  {
    "domain": "samplesite.org",
    "traffic_volume": "87,500",
    "traffic_change": "-2.1%",
    "ranking_position": "34",
    "source_label": "Organic"
  }
]

The traffic_change field captures directional movement as a signed percentage, making it straightforward to filter domains gaining or losing traffic over a given period. The source_label field identifies the channel attribution per record as SE Ranking classifies it.

Install the Minexa.ai extension to start extracting SE Ranking data into a structured format today.

Step 8: Complete the configuration and export

Once you have reviewed the data points, complete the scraper configuration. You will see a summary screen with options to connect Google Sheets or set up a recurring schedule so the job runs automatically at whatever interval suits your workflow.

After the job runs, the scraped data appears in a table. You can export it to Excel, JSON, or push it directly to Google Sheets depending on where you need the data to go.

Why this matters for alternative data workflows

Traffic data from SE Ranking is a practical alternative data source for competitive intelligence, market sizing, and SEO gap analysis. Collecting it manually domain by domain is slow and does not scale. With Minexa.ai, you train the scraper once and can re-run the same job on demand or on a schedule, building a historical dataset over time without any additional setup.

The extraction is tied directly to the page structure, so each field maps to the correct element every time. If a value is not present on the page, the output returns empty for that field rather than filling in an incorrect value.

For a related tutorial using the Minexa.ai extension on a different data type, see: How to scrape finance market data from FRED using the Minexa.ai extension.