Artificial intelligence and machine learning are so integrated into everyday life that most people overlook the technologies.
Consider recommendation engines, which describe the system of collecting, storing, analyzing, and filtering large amounts of data for the purpose of suggesting products, services, or information to users.
These predictive models are utilized in all walks of life from online dating to travel and entertainment. According to McKinsey, 35% of what people buy on Amazon and 75% of what people watch on Netflix derive from product recommendations based on algorithms.
Put simply, these algorithms are the online equivalent of a sales rep at a retail store asking if they can help you find something. The main difference is you don’t have to ask when you’re online because everything is automated. The objective is to drive better outcomes.
Advantages of Recommendation Engines
Companies use this technology to facilitate product discovery, optimize conversion rates, customize the user experience, and improve customer satisfaction.
The two most common types of recommendation engines are peer-to-peer and content-based.
The former matches users with similar characteristics, behaviors, and preferences, and then makes recommendations based on the buying history of similar audiences. The latter uses metadata and other criteria to identify what a user likes, and then uses that information to find similar content or products.
For companies with millions of users, small percentage increases in product usage or purchase rates can make a huge difference. As such, there’s been a surge in hiring for data science, statistics, machine learning, and computer engineering roles. It’s truly a talent war when you think of the heated competition between apps like Spotify and Pandora, or TikTok and Instagram. And these are just a few of the examples.
The most coveted candidates are PhDs with expertise in programming languages like C++, Python, or R. If you’ve published peer-reviewed papers and have management experience, that’s a bonus. The demand for these candidates outpaces the supply by a large margin, and it will take years to close the talent gap.
recruitAbility.ai has experience in identifying talent with these credentials and placing them into full-time roles and contract positions. If your company is in need of help in this area – or you’re just curious on how to leverage artificial intelligence – please contact us for a free consultation at email@example.com.