What Is Candidate Engagement?
Candidate engagement is a lot like customer engagement — it centers on an organization developing an ongoing relationship with an individual.
But instead of encouraging people to buy, the goal of candidate engagement is more relational than transactional. Recruitment isn’t just about getting qualified candidates through the door; it’s about keeping them interested throughout the application process and helping them land a job they’ll love.
That means offering a better candidate experience from awareness to the final decision.
“A good recruiting process focuses and aligns recruiters to deliver the best to the organization. Ultimately, recruiting really should be viewed as a business partner, someone who is critical to the success of the business.”
Head of Talent, Instacart
Given the importance of candidate engagement, the natural question most recruiters ask is where to begin. Engaging candidates involves three functional areas of business: people, processes, and technology.
- People: The most obvious of the three, it relates to someone inside the organization who is familiar with the candidate journey. This person owns the engagement and understands the target audience’s motivations, aspirations, and behaviors.
- Processes: These are the strategic methods of engaging candidates before they become applicants. These processes entail direct communication methods like text, email, or face-to-face interactions as well as indirect approaches like an appealing website, video, or case study.
- Technology: These are the tools used to implement and facilitate engagement methods in addition to measuring their efficacy. If you have no means of measuring your methodology, you’ll never know when or why a tactic isn’t resonating.
Technology also opens your organization to more data-driven decisions. You can pull together analytics and identify areas in the recruiting process where people lose interest. Obviously, an adjustment is necessary.
Consistency in the Candidate Journey
Of course, engagement has been around in one form or another for years now. Although the methods continue to evolve, one constant remains: Consistency is the key to a great candidate experience.
If you’re continuously engaging candidates on a personal basis, you hold their attention and stay top of mind. That’s a benefit in and of itself. But with hiring timelines up 15% since 2009, regular communication lowers the chances of your ideal candidate losing interest — as 40% of them do if they don’t hear back within a week of an interview.
Focusing on the candidate experience also has a way of attracting higher-quality recruits. The hiring process is often the first time a candidate interacts with your organization, which means top talent will likely drop off your company’s radar if that first experience is negative.
Besides, a better candidate experience attracts more applicants and naturally improves the diversity of talent. This doesn’t take away from the fact that unconscious biases can still affect the hiring process. Nevertheless, AI has been beneficial in removing the favor of one type of applicant over another.
What Is Traditional Recruitment?
How to be an effective recruiter doesn’t mean abandoning tried-and-true candidate engagement tactics. There are some definite advantages of traditional recruitment methods. Email, for one, offers a convenient way to keep candidates in the loop on their application status or to relay next steps — evidenced by the fact that 85% of recruiters use email as their primary relationship-building tool.
If you’re only using email to communicate with talent, then you’re probably not recruiting as effectively as you could. Even when personalizing your message, it may not have the impact that you think. A Temple University study found that 95% of customers respond negatively when email ads greet them by name.
As informal as it may sound, a quick text message can be a convenient and efficient way to send updates. According to a Forbes study, both Gen Y and Millennials prefer social media and instant messaging to talking on the phone. With these age groups set to account for more than 50% of the workforce by 2020, technology will become an increasingly important part of candidate engagement.
Whether the disadvantages of traditional recruitment outweigh the advantages will likely remain up for debate. There will come a time when all recruitment professionals leverage AI, machine learning, and other technology platforms, so an old-fashioned mailer may help you stand out in the crowd.
But one thing is for sure: The traditional techniques of recruitment were often akin to a hunt. They lacked the right strategy, time efficiency, and data to make the best decisions for companies and candidates alike. It involved wide-ranging search strings, scouring multiple channels for potential hires, trying to locate contact information, and cobbling together a contact list — all culminating in a generic message blasted out to a pool of faceless inboxes.
In other words, conventional recruitment methods alone won’t likely drive engagement. It takes a multi-channel approach that often includes machine learning and AI — that is, of course, if you want to take engagement to another level.
Using AI in Recruitment
Because AI has become an overused buzzword, it’s an easy term to latch onto should you use any technology. Automation is a perfect example, and many companies do employ some form of automation for experiential purposes like customer or candidate engagement.
But that’s not true AI.
When using AI in recruitment, it generally entails collecting data points from myriad sources to create a profile of your ideal candidate. You are no longer left guessing what motivates the individual or whether this person is suited to your company culture. AI provides you with all the necessary data and analytics to thin the talent pool, going so far as to analyze word choice and the tone of social media posts to draw your conclusions.
Let’s say, for example, that AI finds a few candidates favor words like “please” and “thank you” on social media. These patterns can be a sign of empathy and a possible disposition for working with customers. You can move these people, with greater certainty, to the interview phase for a client service role.
“AI is not a Pandora’s box, it’s a sound business decision.”
Senior Director, Staffing Industry Analysts
AI for hiring also allows you to leverage complex algorithms to determine the messaging and content that will resonate with a target audience. This provides valuable talking points to better engage with people before initial contact even occurs. It helps employers and recruiters begin meaningful conversations with potential hires, improving the overall candidate experience from the outset.
AI vs. Automation
With that said, a question remains: Do I really need AI if we’re already using automation?
Automation helps improve both candidate engagement and experience, but AI can learn. AI tracks what resonates with candidates, and it can remember the length of the recruiting lifecycle while identifying specific data points like background, experience, and career trajectory.
All of these points are key to what attracted a candidate to a job posting for a specific role. This sort of information can then be used to improve the targeting and results with the next group of candidates for the next time a position opens within your organization.
AI and automation differences don’t stop there, however. Automation isn’t personal — it’s there to perform repetitive tasks, freeing up your team to focus on more important responsibilities.
AI, on the other hand, can be trained to bridge the gap between data and people. Depending on the functionality, it can even be used to carry on basic conversations with potential hires.
These are automated responses, triggered by certain words and phrases from whoever is conversing with the tool. But it’s still AI, learning from and acting on all the necessary data points gathered from previous interactions.
How to Use Big Data in Recruiting
Big data and AI often go hand in hand, and some would argue they’re actually two of the top characteristics of effective recruitment. Big data provides deeper insight into people, and AI helps facilitate engagement between company and candidate.
Logic would tell you that data-driven talent acquisition efforts can bolster recruitment strategies and expedite the hiring process, improving the overall quality of hires.
“Understand your candidates and why they’re making job changes. People leave people, not companies. Make sure you’re giving them something they’re excited to come to.”
Founder and President, MeeDerby
The reasons to use big data in recruiting are too numerous to name. But as far as impacting engagement, they often revolve around three strategies: relevancy, personalization, and branding.
- Relevancy: Gathering and analyzing data points within the profiles of candidates who’ve accepted a particular role can provide insights into active and passive job seekers. These insights can help better tailor your messaging and target talent best suited for a role. You’re putting relevant job postings in front of the right people at the right time.
- Personalization: Painting a better portrait of your ideal candidate allows you to get to know job seekers better. You’re then able to determine your next move — and the move after that — to personalize the candidate experience, which can engage and/or reengage talent with potential job opportunities. Each touchpoint resonates deeper than before.
- Branding: Did you know 75% of job seekers consider the company brand before deciding to apply for a job? Data-driven market research allows you to create more targeted content while telling more compelling stories about your brand, improving the credibility of your organization, and improving customer (as well as candidate) engagement.
Quality of hire measures to keep top of mind: current role, industry experience, personality traits, work ethic, leadership abilities, biggest wins, and reviews and recommendations from peers.
AI in the Recruitment Process
AI can be a tremendous benefit to talent acquisition teams, improving candidate quality and engagement. But integration and implementation are critical processes — get either wrong, and no amount of technology can maintain the interest of applicants.
That’s why you must still follow the best practices for recruiting employees by using AI in talent acquisition strategically and prudently:
- Never make candidates wait. Our on-demand economy has made people impatient, setting new standards for almost all customer interactions. This includes any interactions during the hiring process. Candidates now expect near-instantaneous responses from potential employers.
Enter the chatbot. This piece of AI can initiate conversations with applicants upon résumé submission and improve the candidate experience by answering pre-indexed questions about the role, next steps, and other basic information that candidates want immediately.
- Personalize interactions. Applicants don’t want to feel like they’re just a number. Unfortunately, that’s what happens when you rely on generic email blasts to dispense job information, status updates, and other application materials.
Customize your outreach with a recruitment platform. AI recruiting technology gathers candidate data and then provides insights into each individual’s career trajectory, which can later help you personalize engagement efforts.
- Consider the career path. Conducting research doesn’t just help determine whether an applicant is a good fit for the company, culture, and role. It can also better ensure that the company and role align with a candidate’s career aspirations.
AI tools can fill in information gaps and assist in identifying valid reasons why a job may be a good career move for an applicant. Done right, it’ll take little convincing to bring top talent on board — and limit the chances of new hire turnover.
Not so fast.
No new initiative would be complete without measuring its ROI, and AI recruiting technology is no different. To get a clearer picture of how AI tools bolster your recruitment strategies, follow these four metrics:
- Time to Source: This refers to the time it takes to source and move talent through each step of the recruitment funnel (e.g., submittal, screen, selection, interview, etc.), allowing you to establish a yield ratio per step.
- Time to Hire: Time to hire measures the length of time between candidate identification and offer acceptance. It shouldn’t be confused with time to fill, which tracks the time from job posting to offer acceptance.
- Quality of Hire: Though somewhat subjective, quality of hire can be measured based on a tool’s ability to meet your talent acquisition needs. Tracking performance evaluations, promotion rates, and productivity can give you some idea.
- Retention Rate: What you’re looking for here is the percentage of hires who complete their first year of employment. Below average retention is a good indication of an ineffectual recruitment program.
Frequently, speed (time to source/time to hire) and quality (quality of hire/retention rate) are of utmost concern to hiring teams. Asking third-party providers for metrics and case studies around these qualifiers can help you make more informed decisions around which direction to take.
Final Checklist for AI Selection
Speaking of decisions, you’ve got a few more boxes to check before settling on one AI tool over another.
- Review business needs. AI is rarely a one-size-fits-all endeavor. Take a step back and evaluate your HR departmental goals — and whether any pain points need fixing. Are your job postings attracting the right candidates? Are you able to capture the correct data to determine the cost to fill? What about the quality of communication between candidates and recruiters?
- Shop around. No one needs to tell you the importance of shopping around. You want to make sure your choice of vendors supports your recruitment strategies while scaling with your business as your talent requirements evolve. Look under the hood, so to speak, to ensure you’re not investing in a dated product.
- Get buy-in. Employees can often get uncomfortable when broaching the topic of AI integration. The first thing that comes to mind is job security — or insecurity. Explain exactly how the AI solution will make everyone’s job more comfortable and more effective. Make it clear that you’ll still rely on the existing team to add that human touch.