Is It a Waste of Time to Send Personalized Messages to Candidates?

The answer to the title of this article is dependent on our definition of "personalized." So, to begin, let us note that approximately 50% of sourcing time is spent attempting to engage with candidates. Candidate engagement is difficult, time-consuming, and frequently frustrating. Passive candidates are especially difficult to entice.

As a result, recruiters devote an inordinate amount of time to writing messages to candidates via LinkedIn, email, and, yes, even phone calls. They believe that the more personal a message is, the more likely it will elicit a response. Furthermore, there is no shortage of advice on crafting messages; LinkedIn offers several suggestions, including a compelling subject line and a message that focuses on the candidate rather than the company, a call for action, and more.

This is all good advice, but it isn't scalable. When drafting a message, it may take 10 to 20 minutes to research each candidate's background. If you want to reach out to 50 candidates, this can add up to up to eight hours of engagement per job. Meanwhile, the average response rate for InMail is 10% to 25%. This means that 75% to 90% of your candidates will be unresponsive.

If you send messages to 50 candidates for each job and only five respond, you may have two or three qualified candidates for interviews. In a market where candidates have multiple options, that may not be enough to make a hire.

And only through LinkedIn messages. You can also make cold calls and send emails. However, this adds to the time already spent on engagement and contributes to its inefficiency. On the other hand, everyone in marketing understands that getting a response requires multiple touchpoints. Recruitment marketing is no different.

AI technology is the most effective and efficient way to create more touchpoints. However, when leveraging technology, it is critical to consider a variety of factors to ensure that you are not creating touchpoints for the sake of creating touchpoints. That is, the quantity as well as the quality of touchpoints, as well as how they are managed, are equally important. Here are some things to keep in mind when using AI technology to engage candidates.

Enhanced reach - AI can choose and contact a large number of candidates on your behalf. It can generate a list of hundreds of potential candidates based on a job description and some feedback from you (thumbs-up and -down on profiles). It can then reach out to these candidates on a larger scale. Although the response rate will be lower than with a manual approach, with 200 candidates contacted, even a 5% response rate will result in 10 additional interviews.

Drip marketing - AI can run a drip campaign with a series of messages delivered at the optimal time. If the candidate does not respond to the first message, a second message is sent to him or her. Sending up to three email messages and giving the candidate the option to click "Interested" or "Not Interested" is a good practice. If "Not Interested" or "Unsubscribe" is clicked, the campaign is halted. Frequently, the second and third emails generate more than half of all positive responses.

Message delivery time- When sending individual messages, you may be unsure of the best time to send them. The best day of the week and time of day may differ depending on the candidate's seniority, job, and location.

Personalization is important - True, a human-generated email can be more personalized than one generated by AI technology. But it's worth considering what kind of personalization is truly important.

AI can still send personalized messages based on the candidate's skills, prior experience, and relevance to the job. AI-created messages can also reveal a lot about the role, the company, and their relevance to the candidate. Furthermore, such communication can display profiles of people who are currently working in a similar role at the company or who used to work in that role before being promoted to more senior positions. So the future seems to be moving towards AI technology, but for now with a human presence. A good example of this is IceHrm , an automated reference checking platform that simplifies a traditionally tedious part of the hiring process.