Web Scraping for Data-Driven Recruitment: Benefits and Best Practices

Data-driven recruitment using web scraping

A vast amount of information is being created and collected daily, and most industries have realized the value they can draw from it.

Sectors like marketing are already using data to support or test their hypothesis, allowing them to make better decisions. HR has followed suit by incorporating a data-driven approach to recruitment, utilizing data collected during and after recruitment to improve their efforts, resulting in better hires and increased talent retention.

In this article, we’ll discuss why you should invest in data-driven recruitment to ensure your talent acquisition (TA) success and how web scraping can give you an advantage over your competitors.

What is Data-Driven Recruitment?

Data-driven recruiting uses analytical data to improve all aspects of the hiring process and guarantee timely talent acquisition to support business goals. By tracking and analyzing a wide range of metrics, modern talent acquisition teams can make decisions based on objective insights instead of intuition and guesswork.

Here are five common data points recruiters can and should consider:

  • Time to fill – the number of calendar days that it takes for the position to be filled after the talent acquisition request is approved.
  • Time to hire – the number of days it takes a potential candidate to accept an offer after he/she was approached or applied for the job.
  • New hire turnover – the turnover of a new hire in their first year of employment. It can either be managed (the employer ends the contract) or unmanaged (the employee ends the contract).
  • Quality of hire – the new hire’s performance during their first year of employment.
  • Cost per hire – the total financial cost of hiring a new employee, including the cost of advertising, HR hours, and tools, to name a few.

Each metric brings a new piece to the puzzle. By managing this information, recruiters can fine-tune their process for future talent acquisition and refine the quality of the talent they’re hiring. However, for this approach to work, you must adopt an analytical mindset.

For example, by going deeper into “quality of hire” to spot trends on personality traits, background, etc., your high performers share, you can create better filters to spot them within your pool of candidates.

Benefits of Data-Driven Recruitment

As you can imagine, there are many benefits to adopting a data-driven approach. However, here are some of the most relevant ones:

1. Improve Overall Hire Quality

Improving the quality of the talent you bring to the company is one of the most important goals of data-driven recruiting. Understanding what traits, background, skills, work experience, etc., the highest-performing new hires share will help you set effective hiring criteria based on the results you’ve gotten instead of a gut feeling.

2. Speed the Hiring Process

By collecting and analyzing data from your hiring process, you can identify bottlenecks slowing your team down, like application drop-off points or time-consuming processes. Data can also strengthen your filtering, allowing you to focus your time and energy on effective candidates, making the list of prospects smaller but better qualified.

3. Decrease Hiring Costs

Faster and better talent acquisitions translate into fewer HR hours invested per hire and a lower turnover rate. Both improvements contribute to making hiring expenditure more efficient.

However, there are many other ways data can help decrease costs:

  • Identifying platforms bringing the most and best candidates allows your team to double down on the strategies working the best.
  • At the same time, you can cut down platforms and channels burning the most cash for the least return.
  • Picking the right candidate that’ll perform best and stay in the company the longest will also reduce wasted onboarding hours on low-quality hires.

4. Run More Accurate Forecasting

With all the data at your disposal, it’s easier to understand how talent moves within the company. Considering metrics like turnover, promotions, and lateral movements, the TA team can predict which positions need to be filled at what frequency.

Accurate forecasting lets your team prepare for the hiring process before the positions are requested and procure the necessary funding to complete the task faster. This allows the company to prevent setbacks due to a lack of talent.

Beyond Internal Data: Using Alternative Data to Make Better Recruitment Decisions

When talking about adopting a data-driven approach to recruiting, it is common for leaders and teams to think about internal analytics.

In fact, if you run a Google search, most publications mention using HR analytics and other internal sources, like surveys, as the primary source of recruiting data. Yet, there’s a whole world of data out there that can help you improve your talent acquisition strategy. This type of untraditional data source is what we call alternative data, and it’s already being used in other industries like finance and marketing.

The idea behind alternative data is to collect information from non-traditional sources to gather unique insights and get an edge over the competition or just improve your operations with data you wouldn’t have access to otherwise. But where do you get this data? Simple; the web! There are thousands of websites, like job boards and social media, that provide an immense amount of quality data to leverage.

Of course, doing it manually is not only a waste of time and money but an impossible task. Instead, you can use web scrapers to automate data collection from alternative sources and build your own datasets.

How Web Scraping Supports Data-Driven Recruiting

In simple terms, web scraping is “the process of extracting publicly available web data using automated tools (…) in – usually – a structured format for repurposing or analysis.” Using web scraping, you can collect data at scale from millions of URLs and build datasets that allow you to inform your decisions, improve processes and strategies.

Let’s explore a few examples to better understand the role of web scraping in your data-driven recruitment process:

1. Improve Job Descriptions

Job descriptions are crucial to effectively communicate your job’s requirements, the profile you’re looking for, and the benefits you’re offering. A strong job description can make a difference in attracting the right candidates.

By collecting job posts targeting the position you want to fill, you can find patterns in the language used in the space, the structure of the job post, main locations looking for the role, responsibilities, and skill listings, etc., you can then repurpose to improve yours.

Scraping job listings can also give you an idea of how fast jobs are getting filled, as you can monitor changes on the job boards – if a job listing is closed or no longer exists, you can measure the time it took from the first time scraped to the moment it was closed.

Resource: How to Scrape 15k LinkedIn Job Posts in Seconds

2. Proactive Candidate Sourcing

Forecasting your company’s demand is meaningless if you can’t respond. Instead of reacting to talent acquisition requests, you can build and maintain a pool of qualified candidates using programmatic web scraping. For example, you can scrape social media and professional profiles and store their contact information in a database you can then use to start building relationships with candidates.

You can also monitor certain hashtags and categories within social platforms and forums to find interesting candidates looking for new opportunities.

3. Create a More Competitive Compensation Package

Your compensation package needs to be competitive enough for candidates to choose your company over your competitors (other recruiters and companies hiring).

Hiring teams can scrape job boards like Glassdoor to collect salary ranges for positions of interest and set different criteria to determine how salary changes based on years of experience, geographic location, level of education, etc.

With this data, HR departments can build strong cases for upper management and the salary range they should offer to attract the best candidates.

According to sources like WorkforceHub, there are at least 25,000 job board websites in the US alone. Collecting compensation data from that many sources can allow your team to have a clear and accurate idea of salary expectations for specific positions and their growth trajectory.

Besides money, you can also scrape similar job posts directly from companies’ career pages to find what other benefits they are offering with the role.

If you can find that 9/10 companies don’t offer PTO, for example, this can be an excellent incentive to add to your offer to make you stand out from the rest.

4. Improve Job Ads

Another great thing web scrapers can do for your team is collect advertising data from search engines and social platforms.

By collecting ad data from, for example, keywords related to specific roles, you can understand how other companies are positioning themselves and the job opening, what aspects of the role they’re focusing on in their copy, and what keywords they are targeting the most.

You can also collect geo-specific ad data to find differences in the language other companies are using to target local talent.

All this information can help you craft a more engaging and related job ad to increase its effectiveness, whether by providing new ideas or by discovering job ads with weak copy you can outperform.

5. Build Data-Rich Dashboards

One of the key components of a data-driven HR strategy is creating a central hub for your data, so your team can have access to find the information they need in a timely manner.

When you build your own data collectors using web scraping, you can connect your scripts and workflows to your dashboards, integrating internal data with the alternative scraped data you’ve found; and because your scrapers will continuously monitor your sources, these datasets will keep expanding.

When you can see in real-time shifts in salary ranges, benefits, role/job demand, etc. It’s easier for your team to act on the data and make the best decision possible.

5 Best Practices to Keep in Mind When Using Public Data for Recruitment

Creating a data-driven recruiting strategy takes time and planning, and it needs to be a continuous exercise for you to get the most out of it. After all, as time passes, you’ll be able to gather more internal data and compare it with previous stages, creating more value for your team.

The same happens with alternative data. As things progress and change, you’ll be able to make better predictions and improve your processes based on the data you’ve collected.

That said, there are a few principles to keep in mind to invest in efforts that’ll bring the highest return:

1. Set clear goals

Collecting data just for the sake of collecting data isn’t a smart investment. Web scraping should be a tool to collect the necessary information to understand a situation better, inform a decision or test a hypothesis.

For example, if your job listings are not bringing any candidates or are attracting the wrong applicants, scraping job posts is a smart way to collect hundreds of samples quickly to understand where you can improve your own. Maybe you’re using the wrong terms, or you’re not showing a critical piece of information.

If most offers are declined after salary negotiations or upper management isn’t sure how much they should offer, scraping salary data can help inform this decision.

Having a clear goal in mind and choosing the right sources to achieve it is crucial to avoid wasting resources on unproductive initiatives.

2. Formulate a plan to analyze the data

The web is messy and full of noise (faulty or incomplete data), so you’ll need to have a plan on how you’ll process the data before your scrapers bring you millions of data points per month.

When you understand what data and in what format you need your data, it’s going to be 100x easier to build your data collectors and integrates them into your workflow.

Your scripts can clean and format the scraped data as you want, but you must define it first.

3. Stay away from private data

For your operation to stay 100% legal and out of trouble, you have to ensure that the data you’re collecting is public, so anyone can access it without having to, e.g., log into a system. Any information behind any type of wall (paid, login, etc.) should not be scraped!

4. Don’t forget about niche and small sources

When thinking about salary and job data, you probably think about LinkedIn, Glassdoor, and Indeed. However, there are thousands of other sources you can collect relevant information from.

A lot of sites create unique communities around specific interests, and so do specialized job boards and networking platforms.

If you need to collect role-specific information, finding websites specialized in the role or industry can give you even more and better insights than the big platforms.

5. Keep your mind open to the possibilities

Although we’ve been talking mostly about job boards, social media, and networking platforms, there are many other data sources you can use to find great candidates.

For example, scraping sites like www.smashingmagazine.com is a great way to find professional developers and designers specialized in specific technologies and industries.

If you’re looking to fill engineering roles, collecting author data from https://www.indiehackers.com/ can help you find active and passionate professionals you can add to your candidate pool.

The power of web scraping is its flexibility. If you keep your mind open and think creatively, you’ll be able to find more ways you can use web scraping to improve your recruitment process.

Want to learn more about web scraping?

Here are a few guides to help you get started:

About the author

Zoltan Bettenbuk

Zoltan Bettenbuk

Zoltan Bettenbuk is the CTO of ScraperAPI - helping thousands of companies get access to the data they need. He’s a well-known expert in data processing and web scraping. With more than 15 years of experience in software development, product management, and leadership, Zoltan frequently publishes his insights on our blog as well as on Twitter and LinkedIn.

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