It’s no secret that marketing is one of the fields that has been amongst the best and most adept at incorporating data and technology. And as that advancement is applied to recruitment marketing, we can expect to see faster progress through the recruitment marketing funnel.
Currently, HR professionals are not doing a good job of progressing through that funnel. Only 32% of organizations really understand recruitment marketing and of that 32%, only 20% do a really good job.
But in order to understand recruitment marketing, we first have to dissect every stage of the funnel. The recruitment marketing funnel has beeen around long before the advancement of technology and big data; it’s a series of marketing steps that become increasingly specific toward a set goal: an action or decision.
And now that we have artificial intelligence (AI) to enhance every step of that process, it means funneling down faster and with more insight.
Step 1: Awareness
Employers spend 30% of their recruiting budget on advertising to build awareness of the company and job openings. But (and there’s always a but!) is that cash investment being used as effectively as it could be? When recruitment dollars are spent on advertising without efficient targeting and transparency, up to $10 billion is wasted every year. Carpeting many job sites with paid ads, releasing hit-or-miss campaigns without visibility into ROI, and using manual processes all contribute to that time and resource suck. If a particular site isn’t delivering high-quality traffic or applicants, what are you getting for your ad investment?
Here’s where the AI comes in. Job advertising, the way it’s currently structured, often lacks cohesion and data standards. AI-enabled programs can automate posting (reducing the number of manual touchpoints), analyze large volumes of data from the sites, and optimize campaigns by learning over time and making adjustments programmatically.
Step 2: Attraction
By using dynamic algorithms that analyze historical data, you can predict performance and allocate budget accordingly, while AI-enabled targeting algorithms take your ads and puts them where they’re most likely to be seen by the candidates you want. For example, a $10,000 investment on LinkedIn may yield a certain percentage of hires per year, but if it turns out that Indeed or another site is actually yielding more (or higher quality) hires, an AI-enabled program can reallocate the spending and maximizes visibility on the sites that are likely to produce the best results and attract the right people.
Step 3: Interest
AI-enabled algorithms are also able to gauge traffic and user engagement with posts and ads, developing a base of metrics to show how people are finding and interacting with the content. Predictive algorithms measure the ROI of various campaigns, giving you clear transparency into how the ads are being received and acted upon out in the wild. The data can also be used to refine job ad details and redesign them to make sure they’re aligning with the most qualified applicants-all automatically, without you having to pour in time and manual labor.
Step 4: Application
Down at the bottom of the funnel, Big Data and AI software still play a significant part. The applicant data becomes part of the AI-enabled machine, delivering data transparency at your fingertips, allowing you to measure ROI across all your spend; helping you develop insights and refine the process for future campaigns. At this point in the process, the AI-enabled algorithms have helped target your recruitment marketing dollars and efforts to the places that are likely to yield the best results. Real-time information on applicants, their skill levels, and other essential metrics can help you determine where to spend your ad money. It can also help you come up with any necessary interventions, like switching to alternative sourcing strategies.
At every step of the way, the answer involves AI-it helps you find a clearer path down through every level of recruitment marketing and not only create better campaigns right now, but also build a more efficient, cost-effective, and real-time-responsive plan for tomorrow.