In my years of experience, I’ve seen firsthand how the rise of has transformed the way the recruitment industry operates. It has now become possible to collect public web data from online sources (thanks, Internet) and these sources provide invaluable information about candidates. big data However, that’s not all. You can also get incredible amounts of data and ingest it into your platform, creating data-driven products with huge potential, only limited by your creativity. In this article, I will deep-dive into the benefits and importance of using public web data for recruitment platforms. After reading this article, you will know the main steps involved in building or substantially improving a recruitment platform. Navigating your data needs First things first, let’s talk about identifying your data needs. Public web data is great, but it branches out to so many different options that it’s easy to get lost. For recruitment platforms specifically, I’d recommend looking into the following. Firmographic data Firmographics will provide you with the main characteristics of companies, such as industry, size, location, revenue, and more. This type of data is beneficial if you want to tailor your recruitment platform to specific industries or company types. Example A recruitment platform that specializes in the technology industry can use firmographics to create tailored company profiles and job recommendations for software developers. For instance, it can filter out job postings from established tech companies like , Amazon, and and present these jobs to job seekers with relevant skills and experience. Google Microsoft Employee data Employee data will provide you with information about professionals, such as experience, skills, location, education, job title, and more. This data will help you create and fine-tune your pool of candidates. It will ensure that the candidates you provide are truly the best-fit talent for the employers. Let’s say your client has an employee that is so extraordinary that the management can’t wait to find another one just like them. You can build a unique candidate model that consists of the skills, experience, education, and other qualities that the employee has. Then, using employee data, you can compare that model to the millions of profiles to see what pops out. And if you manage to provide your client with extraordinary talent, what better way is there to retain clients? Example A recruitment platform can analyze thousands of resumes of marketing professionals and gather insights into the most common skills, experiences, and tenure of these employees. This data, in turn, helps the platform tailor the candidate profiles that would be the best match for your client. It can anticipate future hiring needs and help you propose a long-term hiring strategy. Also, a platform fueled with millions of employee records can help you enable the automation of candidate screening. Job posting data Job posting data will provide you with information about job openings, job descriptions, requirements, technological capacities, and overall job market trends. This data will help you improve job matching and provide insights into market dynamics. Example A recruitment platform can analyze job postings to identify the most popular job titles, skills, and requirements in the data science field. This data can help provide personalized job recommendations to data scientists at companies that require expertise in machine learning, data visualization, big data processing, or more. Combining several data categories You don’t have to use the data categories individually. You absolutely can combine them and make your recruitment platform even better and more sophisticated. By doing so, you can benefit from all the features of these separate datasets and build a product that’s hard to beat. For example, there are recruitment platforms that can help customers source talent, evaluate it, automate some processes, and even help with onboarding. That’s a relatively long journey and if your product can help with a big part of it, you’re on the right track. All in all, there are more types of data that would further benefit your recruitment platforms, such as user behavior data, feedback data, and more. However, I recommend these 3 as the cornerstones of your data-driven product. How to get the data? Now you know the data that you need for your recruitment platform. But where do you get it? Well, there are 2 main ways you can go about it: scrape it yourself or buy from a data provider. You might be wondering which one is better, and that’s a fair question. It all depends on your goals. If you need a small amount of data that you won’t need to refresh, then it may be cheaper for you to scrape it. However, if you need data that is always fresh and ready to use, then it’s a lot more cost-effective to get the data from a data provider. No matter the scale. “It's safe to say that most companies that work with web data create the most value in the data analysis stage. Therefore, you may be better off concentrating on working with the data, rather than working on getting it.” - Laurynas Gruzinskas, Coresignal’s Head of Product Data from providers is relatively expensive, yes, but once you find a trustworthy provider, you can always know that the data you use is fresh, accurate, and useful. And it will allow your business to generate more value than it costs. Now that all the formalities are out of the way and you know the data that you need and where to get it, let’s see how you can put it to use. What should you keep in mind when developing your recruitment platform? In this section, I will provide you with several advices while building (or improving) a recruitment platform. However, I haven’t built any recruitment platforms myself, so this is only a rudimentary logic around building the platform. It’s more about the things you need to keep in mind and tips that would help make your recruitment platform better. H ere are 10 things you should focus on: Identify the industries, job titles, and company types that your recruitment platform will deliver talent to. It will help you focus on the right data and tailor talent solutions to your target audience. Define your target audience. Use scrapers or data providers to get the data that you need. Collect the data. If you scraped it yourself, you will definitely need to spend some time on this step. If you relied on a data provider, you might be able to skip it, depending on the data you got. However, you still need to dig deeper into the underlying logic of data cleaning procedures, check what portion of the data has been cleaned and how much cleaning you still have to do yourself. Also, in terms of data structure, you need to figure out how it connects with your existing data, how it can be mapped, and other aspects that are relevant to you. Clean and structure the data (if needed). Identify trends, patterns, and insights that can help you improve the platform. You can analyze job postings, for example, to determine the most popular skills in your target industry or the most in-demand job roles. Analyze the data. Next, you need to develop matching algorithms that connect jobs with candidates. Consider data points like skills, experience, location, education, and other relevant factors. Develop matching algorithms. Your product is only as good as it is easy to use. Work on simplifying complex interfaces so users find it intuitive and easy to understand. Design a user-friendly interface. Feedback allows you to improve your platform based on direct comments from your users. You can also implement feedback mechanisms on companies as well so you can later filter out the best companies based on people’s choices. Integrate feedback mechanisms. If you’re getting the data from a provider, it’s highly likely that they will take care of legal matters. If not, then you must adhere to GDPR and CCPA regulations to avoid trouble. Ensure data privacy compliance. Launch a beta version first for the early users. Test, test, and test to improve your platform and rid it of any annoying bugs. Test and iterate. Track KPIs such as time-to-fill, quality of hire, cost-per-hire, and more to assess the success of your recruitment platform. These indicators will also serve as good marketing material. Measure success and adapt. I hope you can put all this advice to good use and get your recruitment platform to a whole other level. To sum up Public web data is a powerful tool that can transform your recruitment platform and bring it to new heights. High-quality matching will bring better talent to the employers while saving expenses at the same time. Especially when nowadays the . cost of a bad hire can go up to $240,000 By leveraging public web data, you can help employers cut these costs and minimize the chances of bad hires in general. And that’s one of the ways to build long-lasting relationships with your clients. Also published here.

Processes and New Technologies in Data Transformation

How Public Web Data Can Improve Your Sales Intelligence

How to Build or Transform Recruitment Platforms Using Web Data?

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

Data Quality: Its Definitions And How to Improve It

How to Achieve Optimal Business Results with Public Web Data

Go Clean to Be Lean: Data Optimization for Improved Business Efficiency

Public Web Data for Business: Common Challenges And How to Solve Them

The Noonification: Feature Optimization for Price Prediction (11/26/2023)

10 Ways to Optimize Your Database

Data Quality: Its Definitions And How to Improve It

How to Achieve Optimal Business Results with Public Web Data

Go Clean to Be Lean: Data Optimization for Improved Business Efficiency

Public Web Data for Business: Common Challenges And How to Solve Them

The Noonification: Feature Optimization for Price Prediction (11/26/2023)

10 Ways to Optimize Your Database

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps