Whether you're a recruiter identifying hiring companies, a job seeker tracking new openings, or a researcher analyzing employment trends, manually opening job listings and copying information into a spreadsheet takes time.
Each listing may contain useful details such as the job title, company name, location, salary, employment type, and required skills. But collecting this information across multiple searches can quickly become repetitive.
Spidra's Indeed Job Search template simplifies this process by converting publicly available job listings into structured data without requiring you to build a scraper.
Instead of manually collecting listings, you can specify a job title and one or more locations, run the template, and review the extracted results in a table.
In this guide, you'll learn how to:
- Extract Indeed job listings using Spidra's no-code template.
- Collect job titles, companies, locations, salaries, and other available details.
- Review and export results as CSV or JSON.
- Access Indeed job data programmatically using the Spidra API.
- Monitor searches for newly available listings.
- Understand the limitations of Indeed data extraction.
What is Indeed job scraping?
Indeed job scraping is the process of automatically collecting information from job listings published on Indeed and converting it into structured data.
For example, suppose you're researching Data Analyst opportunities across different cities.
You might want to answer questions such as:
- Which companies are currently advertising Data Analyst positions?
- What salary ranges are being advertised?
- Which locations have relevant job openings?
- What skills and qualifications appear in job descriptions?
- Which new listings have appeared since your previous search?
You could manually search Indeed and record the results in a spreadsheet. However, repeating the same process for different locations or job titles becomes time-consuming.
A job scraper automates the collection stage, allowing you to focus on reviewing and analyzing the information.
What is Spidra's Indeed Job Search template?
The Indeed Job Search template is a ready-made workflow within Spidra that extracts publicly available job information from Indeed.
Unlike traditional web scraping methods that may require Python scripts, HTML selectors, or browser automation, the template provides a form-based interface.
You enter your search criteria, run the workflow, and receive structured results.
Depending on the available information, these results can include job titles, hiring companies, locations, salary information, posting dates, requirements, and links to the original listings.
The template is particularly useful for people who need job market data without developing or maintaining custom scraping infrastructure.
What data can you extract from Indeed?
Spidra can return several useful fields from publicly available Indeed job search pages.
| Data field | What it tells you |
|---|---|
| Job title | The position advertised by the employer |
| Company | The organization advertising the role |
| Location | The city, region, or other location information |
| Salary | Available salary range, amount, currency, or pay period |
| Posting date | When the listing was posted, where available |
| Employment type | Full-time, part-time, contract, or other listed arrangements |
| Requirements | Skills or certifications included in the listing |
| Remote status | Whether the role is marked as remote |
| Job URL | A link to the original Indeed posting |
| Sponsored status | Whether the listing is marked as sponsored |
Not every listing contains all these details. For instance, some employers do not disclose salaries, while others provide only limited information about job requirements. These fields should remain empty when the source does not provide them rather than being populated with guesses.
Search result pages may also contain only a description snippet. To retrieve the full description of a particular role, you can process its individual job page using Spidra's Indeed scraper.
How to scrape Indeed job listings with Spidra
Let's walk through a practical example. Suppose we want to research Data Analyst openings in Austin, Texas, and Dallas, Texas.
Our objective is to collect relevant job listings and organize them into a dataset that we can review or export.
This is an illustrative search configuration. Your own results will depend on the jobs available when you run the template.
Step 1: Open the Indeed Job Search template
Start by visiting the Spidra dashboard and signing in to your account.
From the dashboard navigation:
- Select Templates.
- Locate the Indeed Job Search template under Popular templates, or use the search function.
- Click Indeed Job Search to open its configuration page.
The template page provides information about the workflow, available inputs, and expected output.
You don't need to write code or configure your own web scraper.
Step 2: Configure your job search
Next, enter the job title and location information for your search. lets you collect results from multiple geographic searches inFor our example, the search criteria are:
| Input | Example |
|---|---|
| Job title | Data Analyst |
| Location 1 | Austin, TX |
| Location 2 | Dallas, TX |
Using more than one location allows you to collect results from multiple geographic searches within the workflow.
Choose specific job titles rather than overly broad terms whenever possible.
For example, searching for "Data Analyst" is likely to produce a more focused dataset than searching for "Jobs."
Review any additional search options available on the template before proceeding.
Step 3: Check the estimated cost and run the search
Before you run it, check the credit estimate shown above the Run button. It’s based on the searches you’ve set up, so more searches cost more.
Select Run. Spidra collects the job listings from the Indeed pages you requested and organizes them into rows.
Step 4: Review the extracted job listings
When the run finishes, the results appear in two views. The table view shows each listing as a row, so you can compare titles, companies, locations and salaries at a glance. The JSON view shows the same data as structured fields, ready to use in code.
Keep in mind that the results cover the searches you ran, not every Data Analyst role in those cities.
Step 5: Export the results as CSV or JSON
Once you've reviewed the results, you can export the dataset for further analysis.
Spidra supports both CSV and JSON downloads.
CSV export is useful for spreadsheet-based analysis in tools such as Microsoft Excel or Google Sheets. You can sort listings by company, filter by location, review salary information, and maintain a record of jobs collected during different searches.
JSON export is better suited for developers integrating job data into applications, databases, internal dashboards, or automated processing pipelines.
Before exporting, verify the selected columns and check whether important fields are missing.
It's also useful to record the date of extraction, particularly when working with job market information that changes frequently.
Step 6: Save your search or monitor new job listings
Job listings change as employers publish new vacancies and remove positions that are no longer available.
If you regularly research the same job titles or locations, manually entering the same configuration every day becomes inefficient.
Spidra provides two useful features for repeatable workflows.
Save as Preset
A preset saves your template inputs and selected columns, making it easier to repeat the search later.
For example, you could save a search for Data Analyst positions across Austin and Dallas and rerun it when needed.
Watch for Changes
Spidra's monitoring feature can run a template on a schedule and notify you when new rows appear.
Depending on the configured delivery method, notifications can be sent through channels such as email, Slack, Discord, or a webhook.
This is particularly useful for recruiters monitoring active hiring, analysts studying job market changes, or job seekers following specific opportunities.
How to scrape Indeed jobs with the Spidra API
The dashboard is the easiest starting point for users who prefer a no-code workflow.
Developers can also use Spidra programmatically. There are two relevant approaches.
Option 1: Run the Indeed Job Search template through the API
Spidra provides a template execution endpoint:
POST https://api.spidra.io/api/templates/indeed-job-search/runsEach template accepts a defined set of input keys.
To obtain the exact request format for the current Indeed Job Search template, open the template in the dashboard, configure the desired search, and select its API tab.
Alternatively, retrieve its definition from:
GET https://api.spidra.io/api/templates/indeed-job-searchUse the documented input keys when sending your request. This avoids relying on assumed field names.
The template execution API returns a run record. Depending on how long processing takes, it may include the completed results or a run identifier that can be used to retrieve them once processing finishes.
See the Spidra Templates API documentation for the complete request and response structure.
Option 2: Scrape an Indeed search URL directly
If you want to work with a specific Indeed search URL, Spidra also supports extracting its structured data through the Scrape API.
For example, this request targets a search for Data Analyst roles in Austin:
curl --request POST \
--url "https://api.spidra.io/api/scrape" \
--header "Authorization: Bearer $SPIDRA_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"urls": [
"https://www.indeed.com/jobs?q=data+analyst&l=Austin%2C+TX"
],
"output": "json",
"wait": true
}'Replace SPIDRA_API_KEY with your own API key stored in your environment.
For supported Indeed search pages, Spidra can return a structured collection of jobs with fields such as IDs, titles, company names, locations, posting dates, salary details, and source links.
The direct Scrape API is not the same operation as running the Indeed Job Search template. It is a useful alternative when you already have an Indeed URL or want more control over your extraction workflow.
For additional examples, see the Spidra Indeed documentation.
What can you build with Indeed job data?
1. Job opportunity trackers
Job seekers can collect listings matching their preferred roles and locations.
After exporting the results, they can create a structured tracker containing job titles, employers, application links, application status, and follow-up dates.
This helps separate discovering opportunities from managing applications.
2. Recruitment research dashboards
Recruitment teams can monitor which companies are advertising roles in specific locations or industries.
The data can help identify hiring activity and support sourcing research.
However, a job advertisement should not automatically be interpreted as proof that a company is expanding its workforce.
3. Salary and skills research
Researchers can compare advertised compensation and identify recurring skills or certifications across job listings.
For example, analyzing Data Analyst vacancies may reveal recurring references to SQL, Python, Excel, or visualization tools.
Actual findings should come from the collected data, rather than assuming these skills appear in every listing.
4. Hiring-signal monitoring
Sales and business development teams may use hiring activity as one possible signal of demand for services.
For instance, a company advertising several data engineering positions could be worth researching if your business provides relevant infrastructure or analytics services.
Hiring signals provide research leads, not definitive evidence of purchasing intent.
What are the limitations of scraping Indeed?
Before building a workflow around Indeed data, it's important to understand a few constraints.
- Search-page access is limited. Spidra's public-page workflow can read the first Indeed search-results page. Later pages may require an Indeed login and are not available through the ordinary public-page approach.
- To cover more relevant listings, Spidra recommends running narrower searches using different locations, more specific job titles, or date-related search criteria.
- Not every field is available. Employers may omit salaries, benefits, experience requirements, or other details. Missing values should not be interpreted as negative responses.
- Some results are sponsored. Sponsored listings may make up a substantial portion of a search page, so decide how to handle them before drawing conclusions.
- Job information changes. Employers can update or remove listings. An exported dataset is a snapshot of the available information at the time of collection.
- Public access does not automatically mean unrestricted reuse. Indeed's terms restrict certain automated activities, and applicable privacy, copyright, and data-protection requirements may vary. Review the relevant terms and obtain appropriate guidance before collecting or redistributing information at scale.
Spidra is not affiliated with Indeed.
How much does Indeed job scraping cost with Spidra?
Spidra uses a credit-based pricing model. Our Indeed scraping documentation describes a base cost of 1 credit per successfully retrieved page for ordinary structured extraction, without an AI prompt.
However, a template run may involve multiple pages or additional operations, so the total depends on its configuration.
The safest approach is to check the estimated credit cost displayed by the template before selecting Run.
New Spidra accounts currently include 300 free credits, allowing users to experiment with supported workflows before selecting a paid plan.
For current details, see Spidra's pricing and credit documentation.