{"id":24972,"date":"2014-01-22T13:23:01","date_gmt":"2014-01-22T20:23:01","guid":{"rendered":"https:\/\/www.smartrecruiters.com\/blog\/?p=24972"},"modified":"2017-10-17T10:07:36","modified_gmt":"2017-10-17T17:07:36","slug":"big-data-is-critical-for-paid-job-ad-optimization","status":"publish","type":"post","link":"https:\/\/www.smartrecruiters.com\/blog\/big-data-is-critical-for-paid-job-ad-optimization\/","title":{"rendered":"Big Data is Critical for Paid Job Ad Optimization"},"content":{"rendered":"

OpenMethodology<\/strong> defines big data as \u201ca collection of data sets so large and complex\u00a0that it becomes difficult to process using on-hand database management tools or traditional data processing applications.\u201d With literally millions of ads spread across hundreds\u00a0of thousands of websites, employers need help in determining both where and when to\u00a0place their paid job ads<\/a>. The best way to do so is through application of big data techniques. Big data is at the core of creating a <\/span>scientific approach to job advertising<\/a>. Let\u2019s\u00a0see how it works.<\/span><\/p>\n


\n\"Big<\/a><\/p>\n

There are thousands of places an employer can advertise\u00a0its jobs \u2013 but through real-time data analysis of how other job ads<\/a> have performed\u00a0(i.e., Big Data), the employer can determine\u00a0which sites are most likely to produce good\u00a0results for a particular ad given the position and location. Predicting which sites to\u00a0use can dramatically lower job ad costs\u00a0and improve both the quantity and quality\u00a0of applications. \u00a0<\/em>SmartRecruiters customers<\/a> have posted 300,000+ jobs\u00a0to a myriad of job sites<\/a>, and based on the\u00a0quantity and quality of candidates received,\u00a0SmartRecruiters recommends where to post\u00a0your next job.<\/p>\n

Such an approach will yield both a mix of large, general sites, and smaller, more\u00a0focused niche sites<\/a>. By tuning the job ad distribution based on actual response data\u00a0from similar ads, the employer can generate a specific number of relevant responses during a set\u00a0time period \u2013 thus avoiding the \u2018I\u2019m overwhelmed with applications\u2019 problem that is endemic with large, high traffic sites. Big data can also unearth useful sources of candidates that the employer might otherwise miss. This data-based method provides an \u2018apples to apples\u2019 comparison of a site\u2019s productivity in terms of qualified applicants, instead\u00a0of a simple tally of traffic or \u2018clicks\u2019.\u00a0For more ofn how big\u00a0data can work for you, read “Where to Post Jobs? There’s an Algorithm for That?”<\/a><\/p>\n

Beyond a mix of large and small sites, predictive sourcing can drill down to where the\u00a0employer should go for best results based on industry, geographic location, position, and\u00a0candidate traffic. It is a solid first step past the guess-based placements of previous recruitment eras<\/a> – and it\u2019s integral to building a scientific and modern recruiting program,one\u00a0that relies on data rather than intuition or faulty logic. An additional benefit: because predictive\u00a0job placement is based on real-time data, such modifications can have a significant positive\u00a0impact on short and long term hiring costs.<\/p>\n

\u00a0This is an excerpt from a SmartRecruiters White Paper,\u00a0\u201cThe Evolution of Job Posting.\u201d\u00a0<\/strong>Read the entire White Paper\u00a0here.<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"OpenMethodology defines big data as \u201ca collection of data sets so large and complex\u00a0that it becomes difficult to process using on-hand database management tools or traditional data processing applications.\u201d With literally millions of ads spread across hundreds\u00a0of thousands of websites, employers need help in determining both where and when to\u00a0place their paid job ads. The […]","protected":false},"author":94,"featured_media":24998,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"episode_type":"","audio_file":"","cover_image":"","cover_image_id":"","duration":"","filesize":"","date_recorded":"","explicit":"","block":"","filesize_raw":""},"categories":[8,838,842],"tags":[],"series":[],"acf":[],"aioseo_notices":[],"episode_featured_image":"https:\/\/www.smartrecruiters.com\/blog\/wp-content\/uploads\/2014\/01\/Screen-Shot-2014-01-22-at-12.21.47-PM.png","episode_player_image":"https:\/\/www.smartrecruiters.com\/blog\/wp-content\/uploads\/2020\/01\/Podcast-icon.jpg","download_link":false,"player_link":false,"audio_player":false,"episode_data":{"playerMode":"dark","subscribeUrls":{"apple_podcasts":{"key":"apple_podcasts","url":"https:\/\/podcasts.apple.com\/us\/podcast\/hiring-success-podcast\/id1472174987","label":"Apple Podcasts","class":"apple_podcasts","icon":"apple-podcasts.png"},"google_podcasts":{"key":"google_podcasts","url":"https:\/\/podcasts.google.com\/?feed=aHR0cHM6Ly9oaXJpbmdzdWNjZXNzcG9kY2FzdC5jYXN0b3MuY29tL2hpcmluZy1zdWNjZXNzLXBvZGNhc3Q","label":"Google Podcasts","class":"google_podcasts","icon":"google-podcasts.png"},"soundcloud":{"key":"soundcloud","url":"https:\/\/soundcloud.com\/smartrecruiters\/sets\/hiring-success-podcast-1","label":"SoundCloud","class":"soundcloud","icon":"soundcloud.png"},"spotify":{"key":"spotify","url":"https:\/\/open.spotify.com\/show\/3bM8YzLjM2G9qJXLBBySaB","label":"Spotify","class":"spotify","icon":"spotify.png"}},"rssFeedUrl":"https:\/\/www.smartrecruiters.com\/blog\/feed\/podcast","embedCode":"

Big Data is Critical for Paid Job Ad Optimization<\/a><\/blockquote>