Beyond the Obvious

Continued pressure on Talent Acquisition to increase velocity in identifying skilled professionals while being provided with fewer resources has driven recruitment teams to adopt tools that provide “instant results” by searching large datasets of already indexed, categorized and aggregated profiles.  

However, there's a growing realization that relying solely on these established platforms leaves a significant talent pool untapped. This blog post delves into why "Deep Search" is the essential element currently missing in modern talent sourcing and how it can revolutionize the way we identify and engage top talent.

The Limitations of Existing Platforms

Dominance and Drawbacks of Traditional Sources 

The current dominant trends in professional networking are undeniable. Extensive databases, professional insights, and networking features make those a primary destination for recruiters. However, ubiquity also leads to certain drawbacks:

Oversaturation

Recruiters rely heavily and sometimes even depend on LinkedIn exclusively, leading to candidate oversaturation. Top talent receives a flood of outreach messages, diluting the effectiveness of any single message.

Visibility Bias

LinkedIn primarily showcases individuals who actively maintain their profiles. Many highly skilled professionals, especially those in specialized or niche fields, may not actively participate or optimize their profiles, making them invisible to standard LinkedIn searches.

Algorithm Limitations

LinkedIn's search algorithms, while powerful, are optimized for the platform's specific structure and data. They do not identify candidates who exist outside this structure, on personal websites, industry forums, and other less mainstream online spaces.

The Illusion of Exhaustive Search

Relying solely on established platforms creates an illusion of exhaustive search. Recruiters may believe they have covered all potential candidates, whereas they have only accessed a fraction of the available talent pool.

Defining Deep Search in Talent Sourcing

Deep Search goes beyond simple keyword searches on known platforms. It involves a live, AI-driven comprehensive and investigative approach to identifying potential candidates, mirroring how a skilled Talent Sourcer conducts manual research to identify not only candidates but also sources of talent, new search techniques and destinations. It is these novel discovery methods that identify people hidden in plain sight. 

Deep Search begins by scanning thousands of websites and identifying vectors that will produce profiles. It is not instant because it crawls the content to compile profiles from multiple fragments, confirms and verifies findings, then presents them in a recruiter-friendly way.

Mimicking the Human Sourcer

At its core, Deep Search aims to replicate the intuitive, investigative and iterative methods of an experienced Talent Sourcer. This includes:

Identifying Relevant Websites

Instead of drowning in the noise of mainstream platforms, Deep Search involves pinpointing websites, communities, blogs, and other online spaces where professionals in a target field might gather or be mentioned.

Extracting Data Points

Once relevant web pages are identified, data points such as names, affiliations, and contact information are extracted. This data may be scattered across different parts of a website and not neatly compiled into a single database. Names, for example, may appear separate from skills, job titles, and current employers.

Building Detailed Profiles

The collected data points are then synthesized to build comprehensive candidate profiles, often including information not available on standard platforms.

Exhaustive Sources 

Deep Search draws from a multitude of sources:

Industry Forums

Many professionals participate in online forums specific to their industry. These forums can be rich sources of candidate information, particularly for niche roles.

Personal Websites and Blogs

Professionals often maintain personal websites or blogs showcasing their work. These sites can provide detailed insights into their skills and expertise.

Academic Publications and Conference Proceedings

For academic or research-oriented roles, publications and conference proceedings can be invaluable resources.

Open Web Data

Any information publicly available on the web can be a potential source for Deep Search.

The Advantages of Deep Search

Accessing Hidden Talent Pools

The primary advantage of Deep Search is its ability to uncover candidates not easily found on standard platforms. This "hidden talent pool" can offer unique skills, experiences, and perspectives that traditional searches may miss.

Gaining a Competitive Edge

In a highly competitive talent market, accessing this hidden talent pool provides a significant advantage. Organizations that excel at Deep Search can identify and engage top talent before their competitors do.

Building More Comprehensive Profiles

By discovering relevant content in its natural context, Deep Search often yields far more detailed and nuanced candidate profiles than standard platform searches. Not limited to what a professional chooses to share on their public profile, this additional information can be invaluable.

Enhancing Candidate Quality

By accessing a wider range of potential candidates, Deep Search can improve the overall quality of hires. Organizations can find individuals with specialized skills and experience, leading to better matches, improved job performance and increased retention. These “less visible” candidates are less likely to have competing offers or continue receiving new offers from recruiters active in the mainstream sources. 

Reducing Sourcing Time

While Deep Search may initially seem time-consuming, tools and techniques can automate many aspects, significantly reducing overall sourcing time. By focusing efforts on truly relevant sources, recruiters can avoid sifting through irrelevant profiles on standard platforms.

Implementing Deep Search in Talent Sourcing

Identifying Target Websites

The first step in Deep Search is to identify relevant websites. This requires understanding the target role, its required skills, and where professionals with those skills might congregate online.

AI-Driven Identification of Target Websites

The initial phase of Deep Search involves a specifically designed, trained and continuously updated AI system autonomously identifying pertinent websites. This necessitates a sophisticated understanding of the target role, its requisite skills, and the digital spaces where professionals possessing these attributes are likely to be present.

Automated Keyword Identification and Search

The AI leverages advanced natural language processing to identify and refine relevant keywords associated with the target role and industry. Subsequently, it conducts intelligent searches across various search engines to pinpoint potentially valuable websites.

Analysis of Industry Publications

The AI can be trained to analyze and extract information from industry-specific publications, automatically identifying lists of relevant websites, forums, and other online resources mentioned within these documents.

Intelligent Network Analysis

By processing information from professional networks and online communities, the AI can identify key influencers and their associated platforms, uncovering niche websites and forums frequented by professionals in the target field.

Extracting and Organizing Data

Once relevant websites are identified, data must be extracted and organized. This can be a manual process or aided by automation tools.

Manual Data Extraction

Manually extracting data involves reviewing web pages and copying relevant information, such as names and affiliations, into a spreadsheet or database.

Automated Data Extraction

Automated data extraction tools can scrape web pages and automatically collect specific data points. These tools can significantly speed up the data collection process.

The Future of Talent Sourcing

Deep Search is not merely an additional tool but a paradigm shift in talent sourcing. As the talent market becomes increasingly competitive and dynamic, organizations must adopt more sophisticated sourcing strategies.

Integration with AI and Automation

Integrating AI and automation technologies can enhance Deep Search capabilities, allowing for more efficient data collection, analysis, and profile building.

Continuous Learning and Adaptation

The landscape of online resources is constantly evolving. Talent sourcers must continuously learn and adapt their strategies to stay ahead of the curve.

Investing in Training

Organizations must invest in training their sourcing teams on Deep Search techniques and tools to fully realize its potential.

Conclusion: The Imperative of Deep Search

In conclusion, Deep Search is the missing piece in modern talent sourcing. By going beyond standard platforms and accessing the hidden talent pool on the open web, organizations can gain a significant competitive advantage. Deep Search allows for the identification of unique skills and experiences, leading to higher-quality hires and improved talent acquisition strategies. As the talent market continues to evolve, Deep Search will become increasingly crucial for organizations seeking to attract and retain top talent. Embracing Deep Search is not just a strategic advantage but a necessity for thriving in today's competitive landscape.

Written by Shally Steckerl