Hiring is arguably the most important job at any workplace, yet the process hasn’t undergone much innovation over the last twenty years. At least, that was the case before the AI-powered talent graph.
This article explains Celential.ai’s proprietary talent graph in detail and how it can supercharge your recruitment efforts.
What is a talent graph?
Traditionally, a talent graph refers to the network of professionals you’re (maybe unknowingly) tapped into. It’s a constellation of connections between you, your colleagues, and talented professionals outside your organization to whom you have direct or indirect access.
Leveraging a traditional talent graph can give you a competitive edge in the talent market by generating fresh leads, warm introductions, and personal and professional information about a candidate not available on a resume.
Celential.ai has taken the concept to the next level and developed the AI-powered proprietary talent graph — a digital map of exclusive talent networks created by technologies and various data inputs. Read on for an in-depth look at how it works.
Proprietary talent graph: the ins and outs
What goes into a proprietary talent graph?
Data are essential for a high-value talent graph. The more relevant datasets you draw from in the proprietary talent graph, the more powerful it is likely to be for your recruiting process.
Celential.ai takes a vertical approach that starts by solving the specialized needs in technical recruiting rather than horizontally across all fields of talent recruiting. As a result, we can collect from far more data sources than generalized professional network sites, including many long-tail or specialized niche ones. We are also able to build ML models specifically with software engineers in mind, allowing us to understand the backgrounds of professionals in our talent graph more deeply.
The talent graph for engineers is created with billions of signals and data points from sources where software engineers have a presence, including technical communities (e.g., GitHub, Stack Overflow), professional and social networks, company websites, personal websites, and data provided by partners.
Celential.ai’s platform leverages AI algorithms to process, enrich, and aggregate vast datasets into a dynamic talent graph. It grows efficiently over time and becomes an increasingly powerful resource every day.
What comes out of a talent graph?
By connecting the dots across a variety of data sources, Celential.ai’s intelligent system can uncover many hidden insights about individuals, organizations, and the connections between them, and even make meaningful inferences that are not readily available anywhere across the web.
- Talent profile covers the precise data you need while recruiting talent: work experience, primary role, specializations, skill proficiency, likely compensation level, and career trajectory.
For example, Claire has been a backend engineer in her last two roles; she specializes in machine learning and is strong in Python and many other skills. With her 5+ years of solid startup experience, she is a mutual fit for a particular role as a Senior Machine Learning Engineer at a new AI/Business Analytics startup.
- Company profile includes information about the product, domain, investors, customers, growth trajectory, selectivity, employees, technology stacks, job openings, etc. Information on companies where a candidate has worked can help you determine if they are compatible with your business’s goals, structure, and needs.
Frequently, an engineer may have a bare public profile without meaningful details on their technical background. However, our talent graph can infer that John, a software engineer, has had significant experience in Node.js — since John has worked as a full-stack engineer for five years at two small startups, which use Node.js as the primary programming language.
See a talent example below for the depth of insights Celential.ai ‘s talent graph can provide compared to information from public networks.
Our talent graph can also effectively expand to cover additional vertical markets with the methodology, data, and machine learning infrastructure we’ve built. With the new Virtual Recruiter for Sales solution announced in July 2021, Celential.ai’s proprietary talent graph now provides a massive coverage of 20M+ engineering and sales talent in the United States and Canada, Latin America, and India.
How can an AI-powered proprietary talent graph empower your recruitment process?
1. Access complete networks of candidates, including untapped, diverse talent pools
Recruiters often compete for the same slice of talent with detailed profiles on professional networks. Yet, this approach misses many strong candidates who don’t need or wish to market themselves online. Our AI platform helps you easily access passive candidates that constitute 75%+ of the entire talent pool at any given time.
Traditional recruitment strategies also risk excluding diverse candidates, who may struggle to be included in professional networks or may not put themselves forward for advertised opportunities. Celential’s AI-powered talent graph provides extensive talent coverage for diverse candidates throughout the United States and Canada, enabling proactive targeting of female and minority candidates.
2. Deepen understanding of individual candidates to match them with opportunities accurately and efficiently — at scale
It’s no secret that public talent profiles and resumes aren’t the best representation of candidates’ actual qualifications. Some may inflate claims and exaggerate their fit. Others may be ‘diamonds in the rough.’
Our AI-powered talent graph provides instant access to a deep understanding of talent’s background and career potential. Each candidate is scored using precise contextual parameters, making finding those best suited to a role and hiring team easy and efficient.
As a recruiter, it can be difficult to compare even 100 similar candidates for the same position. On the other hand, our AI algorithms can analyze thousands of potential candidates and assess their mutual fit to a job in moments, exponentially slashing time and cost.
3. Enable personalized and highly effective engagement — at scale
Leveraging in-depth insights about candidates and the hiring team, Celential.ai directly engages passive talent with hyper-personalized messages at scale. It results in a response rate of up to 30% — more than twice the rate of traditional recruiting outreach.
A recruiter with extensive technical knowledge might be able to generate an artificially high response rate by selecting and researching a small number of potential candidates in-depth and composing a personalized email for each. However, this strategy is impossible to scale.
Celential.ai’s Virtual Recruiter solution delivers warm candidates to clients in a fast and frictionless process, resulting in a 70%+ present-to-acceptance ratio.
4. Provide exclusive insights to inform recruiting planning
A proprietary talent graph can also glean valuable market insights for your targeted sectors and regions. The AI engine makes sense of what it sees in the talent graph — generating workforce statistics, identifying trends, and uncovering other evidence to inform recruitment planning.
Celential.ai has made significant efforts to build up timelines of individuals and organizations, allowing us to continue to innovate with AI/ML to extract valuable insights from current and historical data.
Celential.ai has already published the 2021 Silicon Valley Software Engineering Talent Report. It provides exclusive insights into the supply of the workforce, covering population, experience, tenure, education, and salary across a variety of roles (frontend, backend, full-stack, QA, DevOps, data science, security, etc.) as well as tips for hiring a software developer at a startup.
Want to learn more about Celential.ai’s proprietary talent graph and how it can help your team find the best hires cost-effectively, reach out to our team today!
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