- December 1, 2008
- 0 Comments
5 Things You Don’t Know About Recommendation Engines
Sometimes I just don’t get Pandora. My latest infatuation, the music recommendation engine keeps trying to slip John Mayer into the same category as my beloved Ben Folds. No offense to Mayer fans, but “Wonderland” is no “Brick,” and my efforts to skip over him, sadly, are in vain.
Thus is the frustration of recommendation technology. And it’s not limited to Pandora, either. (Just because a person makes the mistake of renting one Dane Cook movie once, it doesn’t mean she wants to see every straight-to-DVD comedy that’s just been released.) Designed with good intentions, it’s these little hiccups – inaccurate results, duplicate suggestions, spam – that give recommendations a bad rap…and why hiring managers often shy away from using such technology for their hiring efforts.
Not all recommendation technology, however, is created equal, and it’s especially important that hiring managers and recruiters understand this, because they should know that not only is this technology available, but that it’s sophisticated, easy to use and results-oriented. Let me clear some things up about recommendation engines:
Misconception #1: They’re designed to sell (especially stuff you don’t need) – While retail stores might recommend products simply to get consumers to purchase more, it would be unfair to think this is the sole purpose of such a tool. CareerBuilder.com’s Recommendation Engine, for instance, is a service that matches customers with relevant candidates. It doesn’t charge for access to individual resumes.
Misconception #2: They generate random results – Many recommendation databases have access to buying history and select – often what seem like arbitrary – recommendations from there. But again, this doesn’t apply across the board. CareerBuilder.com’s Recommendation Engine puts more emphasis on customer preference. Customers choose key words and concepts from which the database draws its matches, and the engine even provides ratings to illustrate how closely candidates match to a customer’s stated preferences.
Misconception #3: They’re an invasion of privacy – Thankfully, many recommendation engines have started moving away from the pesky reminders that you never asked for but nonetheless automatically appear every time you visit. The Recommendation Engine is an opt-in feature offered to those who already use Resume Database. Customers request this feature and specify the results that they want to see, so there are no unsolicited resumes showing up in their inboxes.
Misconception #4: They produce the same results over and over again – The context-sensitive technology of our Recommendation Engine is streamlined to give the customer more control over the results they receive. It identifies applicants and sorts them based on the desired requirements specified by the customer.
By uploading a resume they like into the engine, customers can then search for similar resumes or upload a job description of the position they are trying to fill. New technology even enables them to click on a resume they like in the Resume Database and instantly link to up to 100 of the closest-matching resumes, or even link from a job posting to the resumes that best match the job.
Misconception #5: Technology has yet to catch up – While the concept of recommendations is good in theory, for all of the reasons mentioned above, users are often disappointed when the technology doesn’t meet their expectations. Using customer input, CareerBuilder.com is constantly upgrading its existing technology to create a better user experience, with a soon-to-debut faster and easier interface, quicker search results and even more user-friendly design.
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- Categories: Employee Attraction
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