IMPACT OF PREDICTIVE ANALYTICS Closing Keynote Presentation Presented by: Terry Baker, President

2 “Predictive Analytics gives decision makers the power to ‘see around corners’.”‘see around corners –Tom Siebel Founder, Siebel Systems

Predictive Analytics Drive the 3 most important Talent Acquisition Indicators So, what Indicators do Recruiters use for Talent Acquisition? 3 Cost Quality Time

Driving Cost Efficiency 4

In Consumer Advertising… % - 55% of total ad spend now goes to the middlemen in the supply chain– Ad Tech platforms that optimize the spend and deliver performance Platforms that deliver the best performance capture a larger % of the budget “70% of advertisers agree“70% of advertisers agree that cost reduction is a top benefit of programmatic ad buying” – Ad Age

#1 Blind Spot Predicting & Optimizing Bids on a Job level 6 Today’s Methodology: Campaign Trial and Error Allocate a set budget against jobs Set limits to stop spending per job Stop spending on sources that deliver low CTR Evenly distribute budget across all jobs until you run out of budget Get more money and establish a bench mark for future campaigns Performance visibility at the job level makes it possible to be proactive in spend optimization and to predict the right bid from the start.

What if I had a Guidance System to Predict the Right Budget for each Job from the Start? 7 The ‘distance’ between the optimal prediction and the actual performance at any given time requires real-time tracking of many performance related variables. Predictive Analytics Enables Cost Savings on a Per Job Basis

The Key to Good Predictive Analytics is Use of Big Data What’s Needed in Order to be Able to Predict Job Performance 8 Determine which job parameters effect performance Capture performance data across hundreds of thousands of jobs Use machine learning to analyze, inform and improve the model Run each new job against the model to get performance prediction Dynamically adjust job campaign after each view to manage results to the prediction It’s not just about looking at the performance of an ad buy. It’s more about understanding why that buy performed so well. What worked best?

9 Which Data Parameters are Most Important in Predicting Job Level Performance? Lets start by looking at just two variables: Job Title & Location

How Big a Data Problem is Managing Job Title and Location for performance? 10 Add in related key words for search Identifying similar job titles is key to expanding search results. 50, ,000 X 65,000 = 3.9 Billion performance data points required 10,000+ Job Titles X 65,000 Cities in US = 650 M Performance data points

Eliminating the Predictive Performance Gap 11 How do you ensure you have performance data for each unique job? Build a hierarchical taxonomy of job types, key word synonyms, skills, education type, engagement (full time or part time), industry and detection of non-human traffic, etc., etc., etc., 220 X 65,000 = 14.3 Million data points

Hierarchical Taxonomy of Job Titles & Related Synonyms How Many Related Job Titles for a Finance Clerk? 12 How Many Related Job Titles for a Data Entry Clerk?

What if I don’t Have a Job level Performance Prediction? 13 Staff Accountant Job ID #1 – Same Employer Name & branding Same Location: Greensboro, NC Similar job Description: See note Same Budget Posted on the Same Day for 30 days Accountant/ Bookkeeper Job ID #1 – Same Employer Name & branding Same Location: Greensboro, NC Similar job Description: See note Same Budget Posted on the Same Day for 30 days Staff Accountant Job ID #1 – Same Employer Name & branding Same Location: Greensboro, NC Similar job Description: See note Same Budget Posted on the Same Day for 30 days Running Blind example: No use of Taxonomy

Wildly Different Results! 14 Accountant/ Bookkeeper Job ID #1 – Same Employer Name & branding Same Location: Greensboro, NC Similar job Description: See note Same Budget Posted on the Same Day for 30 days Staff Accountant Job ID #1 – Same Employer Name & branding Same Location: Greensboro, NC Similar job Description: See note Same Budget Posted on the Same Day for 30 days Performance Results: 181 views 512 views

Good Job Prediction Drives Campaign Performance 15 Optimal Results and CPC

Driving Time Efficiency 16

#2 Blind Spot Optimizing Campaigns for Time Efficiency 17 Time-related Issues: If 10% of traffic is achieved on day one, then how do you ensure you have the right bid on the first day to maximize the results as quickly as possible? If Bid and job performance is too low after one week, can you make up for lost time and at what expense?

The Weekend Effect Timing Bids for Maximum Effect 18

A “Process Operator” Job Example What is the Optimal Job Title? 19 Process Operator at La Porte, TX Total is offering employment opportunities for Operations Personnel at its La Porte Polypropylene Plant in La Porte, TX and Bayport Polyethylene Plant in Pasadena, TX. Candidates will be required to successfully complete and pass extensive testing, drug/alcohol screen, background check, physical requirement evaluation and the company's Operator Training Program and probationary period. Shift work and overtime will be required. Minimum Requirements 60 College Credit Hours (preferably in Process Operations Technology) as of May 31, Or Five years recent Petrochemical Industry experience (preferably in operations) Or Four years of military experience… Job Title: Chemical Operator Skills: Military Experience Previous Experience: Operations Education: Some College/University Job Type: Shift work Data Extraction & Taxonomy

Process Operator Job Performance Over Time 20 What an efficient campaign prediction graph should look like

Quickly Determine Out of the Gate Effective CPC Process Operator Job Campaign 21 AVG CPC DateDynamicStaticDay of Week 25-Apr Apr Apr

Process Operator Job Visibility 22

Driving Quality Candidates 23

#3 Blind Spot Optimizing the Campaign for Quality Candidates 24 Quality Related Issues: Over two-thirds of the TATech Job Board survey respondents reported that quality of job applicants is the single most important criterion for employers 75% of all candidate applies get screened out by ATS systems based on key word search (Bersin research study) ATS quality metrics such as “Interview selection”, “hire”, etc., are latent data, not useful in real time bidding campaigns. We need real time quality benchmark data on a per job basis

The “Process Operator” Job Example What Job Data Can Be Used for Qualification? 25 Process Operator at La Porte, TX Total is offering employment opportunities for Operations Personnel at its La Porte Polypropylene Plant in La Porte, TX and Bayport Polyethylene Plant in Pasadena, TX. Candidates will be required to successfully complete and pass extensive testing, drug/alcohol screen, background check, physical requirement evaluation and the company's Operator Training Program and probationary period. Shift work and overtime will be required. Minimum Requirements 60 College Credit Hours (preferably in Process Operations Technology) as of May 31, Or Five years recent Petrochemical Industry experience (preferably in operations) Or Four years of military experience Job Title: Chemical Operator Skills: Military Experience Previous Experience: Operations Education: Some College/University Job Type: Shift work Taxonomy Data Extraction

Qualified Applicant Results Matching Taxonomy to Candidate Application Enables RT Scoring of Each Applicant 26

Qualified Applicant Results Drill Down to View Qualified Resumes with Matching Criteria 27

Real Time Campaign Response: Adjust Campaign Based on Applicant Quality Scoring 28 Low quality vendors cut off based on quality metric and budget reallocated to high quality producing sources Employers have a quality indicator at the sourcing level separate from and more efficient than the ATS keyword based system

Identifying Quality Sources of Traffic Highest Matched Candidate Score per job type by Vendor 29

Programmatic Candidate Qualification Extends the Value Chain 30 Source Applicants Distribution & Campaign Management Qualify Skills Job Matching Assess Interview Hire Job Seekers Applicant Qualified Applicant Qualified Fit Candidate New Employee Impact of Matching on Talent Acquisition Funnel

Predictive Analytics Drives Job Level Campaigning Success A Good Navigation System Maximizes Cost, Time and Quality Indicators 31 Performance Prediction (Machine learning) “Distance” Algorithm Performance Rank Dynamic Bid Personalization Targeting / Retargeting Taxonomy & Historical Data

The Impact of Predictive Analytics 32

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