Generate high quality potential candidate leads

Good hiring is one of (if not the most) important drivers of success for any company, as great people will find creative solutions to hard problems, form a strong culture and propel a company forward. Great talent is scarce in any environment and to find the best talent you need to start with a wide and well-qualified funnel of potential candidates. This is where front-end sourcers like Aaron Lintz play a critical role. They find potential candidates from many well-known and obscure sources and research them to effectively qualify their leads based on factors including technical skill and company fit.

Aaron’s biggest challenge is honing in on the right leads, and this is where Aaron uses kimono to gain an edge. Aaron uses kimono to source potential candidates for a myriad of job functions in the US, Europe and the Middle East and Africa. In this example, we’ll focus on how Aaron finds software engineers.

Aaron started with the online OpenStack community – a community whose members are a match for the skills he was looking for in this particular case. Each online profile listed the person’s name and level of familiarity with OpenStack along with twitter handle, LinkedIn profile, or personal blog. The URLs for these page profiles fit a pattern — they shared the same base URL, and then had a user id that incremented from 1 – 10,000. Using kimono’s URL generator, Aaron quickly generated a list of the 10,000+ URLs he cared about and triggered a crawl.Kimono’s API traversed all the pages in his list and returned a clean CSV file with a list of all potential candidates with each dimension as a separate column. Aaron used kimono’s google sheets integration to pass the data from the API directly into google sheets. Just one click and his spreadsheet refreshes with the latest data from the API.

This was much more valuable than a static list, letting Aaron and his recruiting team track changes over time. For instance, they would monitor identified potential candidates for signals that they might be open to new opportunities, like negative posts about their current employer or complaints about traffic on twitter. The dataset also lets Aaron track growth of this talent pool vs. other pools he monitors with kimono.

Before discovering kimono, Aaron would use a combination of Google searches and more manual scraping techniques to get the source. But, each pull would take 3 hours (excluding the time required for data cleaning) and he consistently got only a tenth of the information he wanted.

This is just one example of the various ways Aaron uses kimono to make him a super-human sourcer.

Aaron Prof

Aaron Lintz is a Talent Sourcing Specialist with @Commvault Systems. Over the last decade, he has held corporate sourcing and agency recruiting roles, helped develop applicant tracking solutions, and managed email & social marketing programs. His passions for experimentation, automation, and willingness to share make him a natural sourcer. Find him on LinkedIn.

You can read articles and presentations that Aaron has written about using kimono for sourcing here and on tracking LinkedIn groups here.