In early June I was lucky to attend the annual Talent42 conference in Seattle. What is Talent42? Google it! For those too lazy to google it, it’s a 2-day conference dedicated to helping tech recruiters elevate their game. Guest speakers came from companies such as Amazon, Uber, Microsoft,, Facebook, Zillow, WhatsApp, GoDaddy, Pinterest and Tableau talking about all topics across the broad spectrum of Talent Acquisition. The event was incredibly well run, I got a lot out of the experience and I highly recommend that you attend next year!

While the conference is dedicated to Tech recruiting, the learnings and tips can be applied to any recruitment domain. Here are some of the key learnings that I took away from Talent42.


  • By far the most popular discussion topic overall.
  • Critical to enabling Recruitment to be a true strategic business partner by leveraging data insights.
  • Typical recruitment metrics revolve around recruitment funnel ratios

           o   Resumes vs phone screens

           o   Phone screens vs interviews

           o   Interviews vs offers

           o   Offers vs acceptance

           o   Source of hire

  • Ratios/analytics are used to tweak process and manage recruiter performance. Also to assist with headcount forecasting and to design recruitment team size and structure needed to meet business hiring objectives.
  • Pre onboarding and post onboarding analytics are critical
  • Some recruitment teams have their own data scientist A.K.A ‘Recruitment Analyst’


  • True adage: “It takes a village to recruit”
  • Culture of recruitment is a huge competitive advantage and critical in meeting hiring objectives for growth companies.
  • CEO leads the culture of recruitment (not lead by Recruiting)
  • Recruiting supports, facilitates, and formalizes the culture of recruitment


  • Tech companies are heavily investing in Recruiting and building large recruitment teams
  • Recruiting will often report to the Business (ie to the CIO), not through Human Resources
  • The Sourcer model is popular and effective however there was debate on about the when/how of handoff between Sourcer and Recruiter.
  • Sourcers that want to stay in sourcing roles (ie -not ‘graduate’ to recruitment) are rare


  • Highly trending topic in recruitment. Lots of awareness from media and general public.
  • Companies such as Facebook are releasing their diversity statistics
  • Diversity leads to innovation
  • Executive leadership support is critical – must be started ‘at the top’.
  • Job descriptions can be unconsciously gender-biased


  • ATS/CRMs are the ‘hub’ of recruitment data analytics and are critical for a high performing recruitment team.
  • ATS/CRM must have high degree of data functionality and integration to be effective
  • Lots of talk about GreenHouse and Lever
  • Workday ATS is gaining popularity
  • Textio is a really cool browser-based tool that ‘scrubs’ job descriptions and scores them based on gender bias and messaging effectiveness – check it out!


  • Market Intelligence & Insights (MII) is a capability used by Microsoft enabling recruiters to be Talent Advisors.

          o   MII data is ‘crowdsourced’ globally by Microsoft T.A team and shared via sharepoint and social collaboration tool (Yammer/Slack)

  • ‘Pipelining’ is a dream – ie having candidates ‘on tap’ is not reality. Don’t waste time pipelining the wrong candidates, and make sure your process is lean.
  • A recruiter’s primary customer is the Business (not hiring manger, candidate etc because the ‘Business’ encompasses everyone)
  • Deciphering between hiring manager ‘wants’ and ‘needs’ is important, and will ultimately gain you their respect
  • Being ‘respected’ is more important than being ‘liked’ by hiring managers
  • Closing candidates: CEOs/executives of Zillow, Facebook etc will be part of the closing process for VIP candidates via phone calls and personalized emails.

Random Interesting facts:

  • Uber receives 2 million resumes per year and have created their own algorithm technology to parse using natural language processing.
  • Uber is experimenting with ‘surge-compensation’ when making offers. Similar to ‘surge-pricing’ for ride rates when demand is too high.
  • Uber has created an algorithm based on historical data that can predict employee attrition to 89% accuracy
  • Uber hired over 8000 employees in less than 6 years. More than Google and Facebook combined over the same time period.
  • Microsoft’s Talent Acquisition department size globally is over 1000 people
  • Good technical recruiters are much harder to find than good software engineers in the Bay Area
  • Over 80% of Tableau’s 3000 staff came via employee referrals.
  • The average salary of a ‘tech-pro’ is over $100kUSD in San Francisco, New York, Seattle, and Portland
  • Tending/high demand tech skills for the near future will be machine learning, containers (docker), cloud technology.
  • Software engineers that excel in mathematics will be in more demand and therefore paid more


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