There are no more excuses, Recruitment Advertising should be - - PowerPoint PPT Presentation

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There are no more excuses, Recruitment Advertising should be - - PowerPoint PPT Presentation

Jan 24, 2023 204 likes •720 views

There are no more excuses, Recruitment Advertising should be data-driven. Eric Holwell SVP, Strategy Bayard erich@bayardad.com Quick Introduction Sheila Spinner Eric Holwell VP, Client Strategy SVP, Strategy SheilaS@bayardad.com

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Eric Holwell SVP, Strategy – Bayard erich@bayardad.com

There are no more excuses, Recruitment Advertising should be data-driven.

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Quick Introduction

Sheila Spinner VP, Client Strategy SheilaS@bayardad.com Eric Holwell SVP, Strategy EricH@bayardad.com

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Washington is projected to have a shortage of 7,000 nurses by 2025, ranking 45th among the 50 states for available nurses

Lund Report 2016

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Today: Registered Nurses

  • The number of registered nurses with addresses in Washington state and holding

active Washington licenses is 71,386, up by 2,729 or 4% from 2016.

  • The average age of RNs has gone down from 47.1 two years ago to 45.7 today.
  • The number of male RNs continues climbing and is at 11.9%, a slight increase from

11.3% in 2016.

  • RNs are distributed in rural and urban areas fairly similarly to the overall population:

6.1% of RNs are in rural settings, compared with 8.3% of the state population.

WSNA

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Today: LPNs

  • The number of licensed practical nurses (LPNs) continues to decline. Currently,

Washington has 9,859 LPNs with Washington addresses, which has dwindled each year since reaching a peak of 13,751 in 2008. In 2018, this translates to about 135 LPNs per 100,000 people in Washington.

  • Just want to move on and become RN
  • LPNs, like RNs, are distributed in rural and urban areas similar to the overall

population: 7.6% of LPNs have addresses in Washington’s rural areas, home to 8.3% of Washingtonians, compared with just over 92.4% of LPNs in urban areas, where 91.7% of the state’s population lives.

  • The percentage of LPNs who are male is 13.6%, staying roughly the same since

2014.

WSNA

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Today: Medical Billing & Coders

States with the Highest Levels of Employment in this Occupation

  • California: 21,900 employed
  • Texas: 17,620 employed
  • Florida: 12,460 employed
  • New York: 9,590 employed
  • Ohio: 9,200 employed

Will increase 13% between 2016 and 2026. This industry’s growth rate is faster than the national average for all occupations, and approximately 27,800 new positions will be added by 2026. Keeping up with those ICD-10s

BLS

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And We’re Still Not a Compact State

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Not all gloom and doom

You’re held accountable despite these challenges. The only way to combat these

  • bstacles is to use data driven results
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What We Will Cover

  • Data-driven defined
  • Programmatic (data-driven) recruitment advertising
  • Data-based discoveries
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Comparing Cost-Per-Click (CPC)

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Comparing Cost-Per-Click (CPC)

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A Little About Bayard

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We’re a Recruitment Marketing Agency

Full-Service Employer Brand & Recruitment Marketing Agency Award Winning & Many Industry Firsts Transparent On All Solutions & Tech Analytical & Perceptive Problem Solving (No Canned Solutions) Great People Offices & Global Partners Year History Privately Held

250 15 97

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With Expertise In…

ü EVP ü Employer Brand ü Programmatic ü Digital ü Traditional ü TA Tech Advisory ü Vendor Management ü Custom Career Sites ü Design & UX ü Social Media ü Active Candidates ü Passive Candidates RPO Reputation & Brand Impact Campaign Performance & ROI Analysis Supplier Review & Recruitment Analysis

Storytelling Advertising Relationships

ANALYICS

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Retail/ Manufacturing Healthcare Call Center Corporate Tech Marketplace Staffing

Our Work Spans a Wide Range of Industries

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What is Data-Driven?

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Data-Driven: Defined

Data-driven is an ability to make strategic decisions based on data analysis and interpretation.

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Data-Driven: Defined (more specifically)

Data-driven is an ability to use past, present, and future KPIs to make strategic decisions in candidate attraction investments. (or pivot away from decisions already made)

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Data Timeline

+ +

PAST FUTURE

Historical performance data Real-time data every day Predictive models using past and present data.

PRESENT

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Data Timeline

+ +

Historical performance data Real-time data every day Predictive models using past and present data.

PAST FUTURE PRESENT

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Data Timeline

+ +

PAST FUTURE

Historical performance data Real-time data every day Predictive models using past and present data.

PRESENT

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Data Timeline

+ +

PAST FUTURE

Historical performance data Real-time data every day Predictive models using past and present data.

PRESENT

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Data Timeline

PAST FUTURE

Predictive models using past and present data.

PRESENT

We need to make 285 additional hires in 6 months:

  • Based on historical data, our apply conversion rate = 11%
  • Which means we need 55,000 job clicks (visits) to generate 6,800 applications.
  • We need 6,000 apps because of we need 24 apps on average to make one hire.
  • With a YTD average CPC of $0.81, we need $33,000 for the top of the funnel to make 185 hires.
  • Why only 185? Because we consistently make 35% of these hires organically.
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Data Timeline

PAST FUTURE

Predictive models using past and present data.

PRESENT

Investment $33,000 Funnel Top of Funnel (Media) Top of Funnel (Including Organic) Conversion Rate Unit Cost Clicks 40,364 61,818 $0.81 Applications 4,440 6,800 11.0% $7.36 Hires 185 285 4.2% $176.73

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Hire

Common Online Journey

Career Site ATS & CRM Hiring Process Media/Source

Offer Interview Screen

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Within the Journey: Recruitment Marketing Data

YIELD METRICS

  • Clicks
  • Visits
  • Actions
  • Applications
  • Hires
  • CPC
  • CPA
  • CPQA
  • CPH
  • CTR
  • Click-To-Apply
  • Apply-To-Interview
  • Apply-To-Offer
  • Interview-To-Offer
  • Time-To-Interview
  • Time-To-Hire
  • By Device
  • By Location
  • By Job Category
  • By Job Title
  • By

CONVERSION METRICS DIMENSIONS

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Tracking The Journey - Where do you fall?

Basic

  • Vendor Data
  • ATS Data

Intermediate

+

  • Google Analytics
  • Media Tagging

Advanced

+

  • Cross-domain tracking
  • Attribution models
  • Impressions
  • Clicks
  • CPC
  • Self Selected Sources
  • Apply conversions
  • Source of app
  • CPA
  • Full funnel view
  • Source of influence
  • Source of quality app
  • Source of hire
  • CPH
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Tracking The Journey - Where do you fall?

Basic

  • Vendor Data
  • ATS Data

Intermediate

+

  • Google Analytics
  • Media Tagging

Advanced

+

  • Cross-domain tracking
  • Attribution models
  • Impressions
  • Clicks
  • CPC
  • Self Selected Sources
  • Apply conversions
  • Source of app
  • CPA
  • Full funnel view
  • Source of influence
  • Source of quality app
  • Source of hire
  • CPH

Data-driven territory

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Programmatic Advertising

The Epic Center of Data-Driven Advertising

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Programmatic Job Ads

Data-Driven Advertising Improve ROI with Programmatic. How? Daily auto-data-driven decisions based on performance goals you set.

  • CPA
  • Application Cap
  • Spend Cap
  • When not to spend
  • When to try other job boards
  • Down-funnel signals (qualified)
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Advanced Media Trading Application Develop an Algorithmic Understanding

  • f Your Data

Real Time, Live, Team Analysis

Enhanced Media Buying & Reporting

The Convergence of software, data and human intelligence

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Job Economics

Row Labels Sum of Organic Clicks Minneapolis, MN US 3314 Morgantown, WV US 2637 Roanoke, VA US 2437 Columbus, OH US 2242 Cleveland Heights, OH US 1954 Lynchburg, VA US 1953 Buena Park, CA US 1943 North Charleston, SC US 1766 Cleveland, OH US 1627 Bakersfield, CA US 1597 La Vale, MD US 1569 Apple Valley, CA US 1563 Summerville, SC US 1418 Charleston, WV US 1416 Blacksburg, VA US 1363 Lima, OH US 1265 Orange, CA US 1231 Palmdale, CA US 1220 Mount Hope, WV US 1219 Vancouver, WA US 1154 Chico, CA US 1068 Springfield, IL US 1046 Yuba City, CA US 974 Huntington Beach, CA US 941 Montclair, CA US 935 Sandusky, OH US 888 Grand Rapids, MI US 886 Portland, OR US 884 Normal, IL US 877 Kennewick, WA US 857 East Peoria, IL US 786 Hilliard, OH US 781 Macomb, IL US 750 Salem, OR US 728 Rancho Cucamonga, CA US 705 West Covina, CA US 704 Springfield, OR US 687 Forsyth, IL US 684 Bridgeport, WV US 664 Wilmington, OH US 647 Greenville, OH US 646 Sterling, IL US 632 Burbank, CA US 632 Mira Loma, CA US 622 Galesburg, IL US 615 Springfield, OH US 615 Buckhannon, WV US 614 Lyndhurst, OH US 602 Union Gap, WA US 594 Medford, OR US 579 Brea, CA US 543 Aliso Viejo, CA US 534 Peru, IL US 529 Saint Marys, OH US 526 Corvallis, OR US 513 Lafayette, LA US 512 Chino Hills, CA US 471 Pasadena, CA US 463 Canyon Country, CA US 445 Bloomington, IL US 444 Charlotte, NC US 432 Burlington, IA US 417 Glendale, CA US 414 Effingham, IL US 411 Mission Viejo, CA US 411 Quincy, IL US 409 Mattoon, IL US 409 Peoria, IL US 390 Champaign, IL US 379 Savoy, IL US 374 Aurora, OH US 368 Denver, CO US 332 Fargo, ND US 319 Jackson, MI US 312 Colorado Springs, CO US 297 Aventura, FL US 296 Midland, MI US 294 Beaverton, OR US 280 San Antonio, TX US 275 Moorhead, MN US 266 Secaucus, NJ US 255 Bluffton, SC US 239 Brownsville, TX US 223 Dallas, TX US 219 Orlando, FL US 219 Hillsboro, OR US 215 Petaluma, CA US 214 Fairfield, CA US 206 Atlanta, GA US 206 Tri-Cities, TN US 204 Riverside, CA US 203 Canton, MI US 200 Bay City, MI US 192 Saint Clair Shores, MI US 189 Tualatin, OR US 183 Wood Village, OR US 183 Portsmouth, NH US 181 Bismarck, ND US 178 Bangor, ME US 178 Virginia Beach, VA US 174 Spokane Valley, WA US 168 Guelph, ON CA 167 Memphis, TN US 164 Hampton, VA US 160 Columbia, SC US 159 Vacaville, CA US 157 Dublin, CA US 156 Houston, TX US 154 Hamburg, NY US 153 Capitol Heights, MD US 152 Chattanooga, TN US 148 Big Rapids, MI US 147 Woodhaven, MI US 142 West Melbourne, FL US 142 Macon, GA US 140 Chicago, IL US 136 Saint Augustine, FL US 134 Defiance, OH US 132 Saugus, MA US 129 Holland, MI US 129 Homestead, FL US 128 Daytona Beach, FL US 122 Norfolk, NE US 122 Albuquerque, NM US 117 Ontario CA 116 Moorestown, NJ US 112 Providence, RI US 108 Idaho Falls, ID US 108 North Smithfield, RI US 108 Sevierville, TN US 107 Moline, IL US 107 South Florida, FL US 106 Sioux Falls, SD US 106 Seekonk, MA US 106 San Ramon, CA US 106 Scottsdale, AZ US 104 Jacksonville, FL US 99 Terre Haute, IN US 98 Dallas-Fort Worth, TX US 97 Madison, WI US 96 Barrie, ON CA 95 Twin Falls, ID US 94 Corona, CA US 93 Chambersburg, PA US 91 Des Moines, IA US 91 La Crosse, WI US 89 West Mifflin, PA US 89 Calgary, AB CA 88 Fort Dodge, IA US 88 Pembroke Pines, FL US 88 Inglewood, CA US 87 Scranton, PA US 86 Salisbury, NC US 85 Indianapolis, IN US 85 Oakville, ON CA 83 Langhorne, PA US 82 Fort Worth, TX US 82 Wyoming, MI US 82 Clovis, NM US 80 Phoenix, AZ US 79 Lakewood, CA US 79 Hixson, TN US 78 Centerville, GA US 78 Raleigh, NC US 77 Kenosha, WI US 77 Iowa City, IA US 77 Tucson, AZ US 77 Waterford, MI US 76 Ankeny, IA US 72 East Lansing, MI US 71 Warwick, RI US 71 Cedar Falls, IA US 71 Shelby, MI US 71 Grand Chute, WI US 69 Sioux City, IA US 69 Holly Springs, NC US 68
  • St. Louis, MO US
67 Berwyn, IL US 67 Downey, CA US 67 Livermore, CA US 66 York, PA US 66 Concord, NC US 63 Greenville, SC US 63 San Marcos, CA US 62 Menifee, CA US 62 Cerritos, CA US 62 Federal Way, WA US 61 Roseville, CA US 60 Southgate, MI US 60 Winston-Salem, NC US 60 Cheyenne, WY US 60 Smithfield, NC US 59 High Point, NC US 59 Tifton, GA US 58 Killeen, TX US 58 Carlsbad, NM US 58 Frankfort, KY US 58 Newburgh, NY US 57 Eagan, MN US 56 Owatonna, MN US 56 Brookfield, WI US 56 Knoxville, TN US 56 Duluth, MN US 55 Warrington, PA US 55 Austin, TX US 55 Pittsburgh, PA US 55 Layton, UT US 54 South Elgin, IL US 54 Lafayette, IN US 54 Lee's Summit, MO US 54 Dubuque, IA US 54 Turlock, CA US 54 Alcoa, TN US 52 Dickson, TN US 52 Norwood, OH US 51 Ann Arbor, MI US 50 Conroe, TX US 50 Anderson, IN US 50 Saginaw, MI US 50 Hillcrest, VA US 49 Hudson, WI US 49 Santee, CA US 49 Newport, KY US 48 Town of Wappinger, NY US 48 Seaside, CA US 47 Overland Park, KS US 47 Oshawa, ON CA 47 Oak Creek, WI US 47 Eatontown, NJ US 46 Puyallup, WA US 46 Millington, TN US 46 Bay Shore, NY US 45 Livonia, MI US 45 Kansas City, MO US 45 Long Beach, CA US 45 Philadelphia, PA US 44 Spring Hill, TN US 43 Manitowoc, WI US 43 Salt Lake City, UT US 42 Westerville, OH US 41 Shreveport, LA US 41 Encinitas, CA US 41 College Station, TX US 40 Manhattan, KS US 40 Frisco, TX US 40 Greeley, CO US 39 Lynnwood, WA US 39 McKinney, TX US 38 Newport News, VA US 37 Kokomo, IN US 37 Douglasville, GA US 37 Concord, CA US 37 Cookeville, TN US 36 Pearl City, HI US 36 Farmington, NM US 36 Tacoma, WA US 36 Pooler, GA US 35 New Jersey US 35 Thornton, CO US 35 Ajax, ON CA 35 Cincinnati, OH US 35 Gallatin, TN US 35 Whittier, CA US 35 Fairborn, OH US 35 Saint Paul, MN US 35 Hickory, NC US 34 Roseville, MN US 34 Stockton, CA US 34 North Babylon, NY US 34 Chanhassen, MN US 34 Lansing, MI US 34 Eau Claire, WI US 33 Plymouth, MN US 33 Seattle, WA US 33 Mount Clemens, MI US 33 Apple Valley, MN US 33 Spartanburg, SC US 33 Santa Ana, CA US 32 Suffolk, VA US 32 Crystal, MN US 32 Morris, IL US 32 Crawfordsville, IN US 32 Glendale, AZ US 31 Riverhead, NY US 30 Huntsville, TX US 30 Monroe, NC US 30 Boston, MA US 30 Minneapolis-Saint Paul, MN US 29 Prattville, AL US 29 Hiram, GA US 29 Santa Maria, CA US 29 Temple, TX US 29 Brighton, MI US 28 West Valley City, UT US 28 Oshkosh, WI US 28 Tukwila, WA US 27 Olathe, KS US 27 Wilson, NC US 27 Middletown, NY US 27 East Houston, TX US 27 Brighton, CO US 27 Mission Valley, CA US 26 Oakdale, MN US 26 Olympia, WA US 26 Centerville, OH US 25 Muskegon, MI US 25 Everett, WA US 25 Rochester Hills, MI US 25 Denton, TX US 25 Louisville, KY US 25 Marion, IN US 25 Janesville, WI US 25 Mooresville, NC US 24 Ashwaubenon, WI US 24 Gastonia, NC US 24 Cedar Rapids, IA US 23 Pensacola, FL US 23 Lufkin, TX US 22 Grand Prairie, TX US 21 Hanover, MA US 21 Center, KY US 21 Schaumburg, IL US 21 Burleson, TX US 20 West Lafayette, IN US 20 Rhinebeck, NY US 20 Palm Desert, CA US 20 San Jose, CA US 19 Greenwood, IN US 19 Mount Pleasant, MI US 19 Fort Collins, CO US 19 Middletown, OH US 19 Shorewood, IL US 19 Quakertown, PA US 19 Rosenberg, TX US 19 Lexington, KY US 19 Longmont, CO US 18 Gainesville, FL US 18 Virginia US 17 Hanover, PA US 17 Waxahachie, TX US 17 Blossom Hill, PA US 17 Mansfield, MA US 17 Battle Creek, MI US 16 Aurora, CO US 16 Union City, CA US 16 Broadway, KY US 16 Sherman, TX US 16 Arlington, TX US 15 Fishers, IN US 15 Sicklerville, NJ US 15 Baytown, TX US 15 Savannah, GA US 15 Florence, SC US 15 Jeffersontown, KY US 15 Coralville, IA US 14 Washington, MI US 14 Santa Fe, NM US 14 South Portland, ME US 13 Keller, TX US 13 Knightdale, NC US 13 Burlington, MA US 13 Gilroy, CA US 12 Ames, IA US 12 Lakewood, CO US 12 Braintree, MA US 11 Monroe, MI US 11 Coon Rapids, MN US 11 Hayward, CA US 11 Pittsburg, KS US 10 Rocky Mount, NC US 10 Brownsburg, IN US 10 Daly City, CA US 10 Sierra Vista, AZ US 10 Farmington, MI US 10 Steele Creek, NC US 10 Kalispell, MT US 9 Surprise, AZ US 9 New York State US 8 Kaneohe, HI US 8 Valdosta, GA US 8 California US 8 Saint Joseph, MO US 7 Zionsville, IN US 7 Durham, NC US 6 Laredo, TX US 6 Greenbriar, VA US 6 Opelika, AL US 6 Morristown, TN US 6 Downingtown, PA US 5 Garland, TX US 5 Farmingdale, NY US 5 Garden City, KS US 5 Pewaukee, WI US 5 Roswell, NM US 5 Rochester, MI US 4 Fremont, CA US 4 Wilkins Township, PA US 4 Middletown, KY US 4 Danvers, MA US 4 Lake City, FL US 4 Centereach, NY US 4 Pennsylvania US 4 Highlands Ranch, CO US 3 Florida US 3 Garner, NC US 3 Leavenworth, KS US 3 Mansfield, TX US 2 Hamilton, ON CA 2 Lanse, MI US 2 Lake Orion, MI US 2 Modesto, CA US 1 Springboro, OH US 1 Kingsport, TN US Miller Place, NY US (blank) Jackson, TN US Bloomingdale, IL US Shrewsbury, MA US Johnson City, TN US

Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 Tier 6

We tier jobs into groups ranked by market challenge Traders optimize group campaigns by analyzing market dynamics

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Job Economics

No Traffic, high alert! Hard-to-fill, high focus. Some hard-to- fills; traffic is up and down. Smooth sailing, no Ad $. Might need advertising help, watch list. Skill/Expertise scarcity Population shortages Geographic limitations Skill/Expertise abundance Population volume Geographically desirable Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 Tier 6

We tier jobs into groups ranked by market challenge Traders optimize group campaigns by analyzing market dynamics

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Invest Wiser

AppFeeder team sets volume and budget limits (rules) that STOP spending on jobs that reach their target.

Wasted Spend

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Proactive Decision Making (Every Day)

Traditional Approach Programmatic Approach

SAME SPEND

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Title Expansion

Capture More Search Behaviors

Registered Nurse LPN

RN Licensed Nurse Emergency Room Nurse Nurse Licensed Practical Nurse Practical Nurse LPN – Licensed Practical Nurse LVN

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Optimization Frequency

Traditional Approach Programmatic Approach

SAME SPEND

1-time per month

24/7

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Programmatic Approach

Automated Cascading Campaigns Using Real-Time Data Campaign Completed Applies Bid/Budget Strategy Notes

Registered Nurse 5 or more Conservative $0.30 - $0.50 Jobs un-sponsor once 10 completed apply cap is reached. Note: Organic listings remain live Registered Nurse LOW Applies

4 or less

Aggressive $0.50 - $0.80 Registered Nurse ZERO Applies

0 after 3 days

Very Aggressive $0.80 - $1.50 Title Expansions Jobs un-sponsor when they spend $150 and still have not generated one apply Additional tactics will be researched

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Programmatic Approach

Automated Cascading Campaigns Using Real-Time Data Campaign Completed Applies Bid/Budget Strategy Notes

Registered Nurse 5 or more Conservative $0.30 - $0.50 Jobs un-sponsor once 10 completed apply cap is reached. Note: Organic listings remain live Registered Nurse LOW Applies

4 or less

Aggressive $0.50 - $0.80 Registered Nurse ZERO Applies

0 after 3 days

Very Aggressive $0.80 - $1.50 Title Expansions Jobs un-sponsor when they spend $150 and still have not generated one apply Additional tactics will be researched

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Programmatic Approach

Automated Cascading Campaigns Using Real-Time Data Campaign Completed Applies Bid/Budget Strategy Notes

Registered Nurse 5 or more Conservative $0.30 - $0.50 Jobs un-sponsor once 10 completed apply cap is reached. Note: Organic listings remain live Registered Nurse LOW Applies

4 or less

Aggressive $0.50 - $0.80 Registered Nurse ZERO Applies

0 after 3 days

Very Aggressive $0.80 - $1.50 Title Expansions Jobs un-sponsor when they spend $150 and still have not generated one apply Additional tactics will be researched

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Data-Based Discoveries

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Job Titles: Short vs. Long

Word Count CTR CPA Three 6.2% $8.70 Five 5.1% $10.70 Seven 2.0% $21.48

2.5x

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Misspellings

Clicks Applies CTR CPA Clinical Pharmacy Technician 1 1,085 61 5.6% $8.02 Clinical Pharmacy Technician- 13 191 4 2.1% $21.78

Typos cost you 3x MORE than what you should have spent

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Call Center

Month Applications CPC CPA C2A 18-Jan 1,133 $0.62 $66.67 0.93% 18-Feb 1,256 $0.59 $51.75 1.14% 18-Mar 1,311 $0.55 $51.89 1.06% 18-Apr 1,569 $0.62 $44.60 1.39% 18-May 2,936 $0.59 $25.54 2.31% 18-Jun 3,225 $0.70 $23.26 3.01% 18-Jul 3,873 $0.64 $19.75 3.24% 18-Aug 3,905 $0.58 $19.46 2.98% 18-Sep 4,738 $0.61 $17.94 3.40% 18-Oct 3,847 $0.59 $22.10 2.67% 18-Nov 3,108 $0.65 $19.66 4.12% 18-Dec 2,472 $0.73 $14.84 4.38%

Avg. 2.55%

Avg. 3.26% 17%

  • 77%

369%

  • Job descriptions
  • Revised application (shorter)
  • Programmatic media
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Call Center

Month Applications CPC CPA C2A 18-Jan 1,133 $0.62 $66.67 0.93% 18-Feb 1,256 $0.59 $51.75 1.14% 18-Mar 1,311 $0.55 $51.89 1.06% 18-Apr 1,569 $0.62 $44.60 1.39% 18-May 2,936 $0.59 $25.54 2.31% 18-Jun 3,225 $0.70 $23.26 3.01% 18-Jul 3,873 $0.64 $19.75 3.24% 18-Aug 3,905 $0.58 $19.46 2.98% 18-Sep 4,738 $0.61 $17.94 3.40% 18-Oct 3,847 $0.59 $22.10 2.67% 18-Nov 3,108 $0.65 $19.66 4.12% 18-Dec 2,472 $0.73 $14.84 4.38%

Avg. 2.55%

Avg. 3.26% 17%

  • 77%

369%

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Call Center

Month Applications CPC CPA C2A 18-Jan 1,133 $0.62 $66.67 0.93% 18-Feb 1,256 $0.59 $51.75 1.14% 18-Mar 1,311 $0.55 $51.89 1.06% 18-Apr 1,569 $0.62 $44.60 1.39% 18-May 2,936 $0.59 $25.54 2.31% 18-Jun 3,225 $0.70 $23.26 3.01% 18-Jul 3,873 $0.64 $19.75 3.24% 18-Aug 3,905 $0.58 $19.46 2.98% 18-Sep 4,738 $0.61 $17.94 3.40% 18-Oct 3,847 $0.59 $22.10 2.67% 18-Nov 3,108 $0.65 $19.66 4.12% 18-Dec 2,472 $0.73 $14.84 4.38%

Avg. 2.55%

Avg. 3.26% 17%

  • 77%

369%

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Call Center

Month Applications CPC CPA C2A 18-Jan 1,133 $0.62 $66.67 0.93% 18-Feb 1,256 $0.59 $51.75 1.14% 18-Mar 1,311 $0.55 $51.89 1.06% 18-Apr 1,569 $0.62 $44.60 1.39% 18-May 2,936 $0.59 $25.54 2.31% 18-Jun 3,225 $0.70 $23.26 3.01% 18-Jul 3,873 $0.64 $19.75 3.24% 18-Aug 3,905 $0.58 $19.46 2.98% 18-Sep 4,738 $0.61 $17.94 3.40% 18-Oct 3,847 $0.59 $22.10 2.67% 18-Nov 3,108 $0.65 $19.66 4.12% 18-Dec 2,472 $0.73 $14.84 4.38%

Avg. 2.55%

Avg. 3.26% 17%

  • 77%

369%

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SLIDE 48

Call Center

Month Applications CPC CPA C2A 18-Jan 1,133 $0.62 $66.67 0.93% 18-Feb 1,256 $0.59 $51.75 1.14% 18-Mar 1,311 $0.55 $51.89 1.06% 18-Apr 1,569 $0.62 $44.60 1.39% 18-May 2,936 $0.59 $25.54 2.31% 18-Jun 3,225 $0.70 $23.26 3.01% 18-Jul 3,873 $0.64 $19.75 3.24% 18-Aug 3,905 $0.58 $19.46 2.98% 18-Sep 4,738 $0.61 $17.94 3.40% 18-Oct 3,847 $0.59 $22.10 2.67% 18-Nov 3,108 $0.65 $19.66 4.12% 18-Dec 2,472 $0.73 $14.84 4.38%

Avg. 2.55%

Avg. 3.26% 17%

  • 77%

369%

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SLIDE 49

AV G . A P P LY C O N V E R S I O N

2.55%

AV G . A P P LY C O N V E R S I O N

3.26%

$246,000

Maintaining a higher conversion rate saved $246,000 in one year.

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SLIDE 50

Thank you for your time.

BAYARDAD.COM