V TECHNOLOGIES AND TIPS TO HELP ENROLLMENT MARKETERS BE MORE EFFECIENT A Collaboration between Datamark, Leads360 and C3Metrics ABOUT LEADS360 • A web-based software-as-a-service company (SaaS) established in 2004 • Market leader in the B2C prospect management sector in all of our core verticals – Financial Services (Mortgage, Debt, etc.) and Insurance and rapidly growing in Education • The only enrollment management system designed for schools that compete for students • Over 5,000 clients ranging from 1 to 1,000+ users • More than 50 million active records under management • 1,400 data source integrations • More than 100 third party technology integrations ABOUT C3 METRICS • The C3 Metrics SaaS platform delivers real-time attribution and viewable impressions, allowing marketers to abandon last click measurement and discover the truth • Buyers and sellers turn to C3 Metrics because its award-winning platform and products complete the loop and automate the process of correctly reporting which viewed media creates awareness, interest, and action • C3’s technology is certified by Google Display, Yahoo!, AOL, and runs on 27+ DSP’s and networks • Headquartered in New York with offices in San Diego and Portsmouth, New Hampshire, C3 Metrics is comprised of leading experts in the field of digital and TV measurement from DoubleClick, eBay, PepsiCo, Yahoo! and Nielsen ABOUT DATAMARK • For 25 years, Datamark has provided innovative, data-driven marketing exclusively to higher education. • We generate high-quality student prospects for colleges and universities of all types and sizes across the country. • We offer full-service inquiry generation and management; complete with conversion marketing solutions designed to reach, engage and motivate prospective students at every stage of the enrollment process. “There is no such thing as a mass mind. The mass audience is made up of individuals, and good advertising is written always from one person to another. When it is aimed at millions it rarely moves anyone.” — Fairfax Cone STATE OF THE MARKET CPLA’s Q1 2013 success seems largely based on its own superior execution and high quality product offering. Management reiterated that market conditions remain weak and credited gains to improved [enrollment] rates… as a result of its own strategic and tactical choices. -Wells Fargo, Analyst Report, 23 April 2013 TECHNOLOGIES AND TIPS Save time and / or money Deliver a market or competitive advantage OPPORTUNITY #1 Find more efficient ways to communicate with prospective student inquiries. OPTIMIZE THE ADMISSIONS FUNNEL • Distribution o Basics o Advanced • Inquiry volume per admissions rep • Scoring DISTRIBUTION IS A SIMPLE CONCEPT dis·tri·bu·tion /lēd distrəˈbyo͞oSHən/ “The act of sharing inquiries among admissions representatives.” DISTRIBUTION STRATEGIES PUSH PULL/PUSH ROUND-ROBIN + PULL BLIND QUEUE ATTRIBUTE-BASED SHARK TANK SKILL-BASED PERFORMANCE-BASED SHOTGUN QUALIFY AND TRANSFER QUAL-CONF-TRANSFER CHERRY-PICK SOPHISTICATED DISTRIBUTION METHODS PUSH PULL/PUSH Leads are in buckets Inquiries handed out ROUND-ROBIN + ATTRIBUTE-BASED BLIND QUEUE SHARK TANK SKILL-BASED PERFORMANCE-BASED PULL SHOTGUN QUALIFY AND TRANSFER QUAL-CONF-TRANSFER CHERRY-PICK SKILL-BASED DISTRIBUTION “Play to Each Rep’s Strengths” BEST FIT INQUIRES TO BEST FIT REPS Good with veterans Good with working moms Good with Website inquiries Good with inbound phone calls HOW SKILL-BASED DISTRIBUTION WORKS STEP 1 Analyze “skills” you want to optimize e.g. State, Education, etc. Choose skills that cover many opportunities and have a high variance in performance among admissions reps STEP 2 Analyze which reps should be in each “skill team” by asking, Who is comparatively the best at each type of inquiry? There will be one group with no assigned skill STEP 3 Set skill-based distribution to distribute preferentially STEP 4 Analyze results and refine SKILL-BASED ROUTING RESULTS Change in enrollment rate following implementation of Skill-Based Distribution PERFORMANCE-BASED DISTRIBUTION “Auto-optimizing Your Skill-Based Distribution” PERFORMANCE-BASED DISTRIBUTION What does it do? Automatically distributes inquiry to the bestsuited admissions rep based on each rep’s: •Contact rate •Qualification rate •Enrollment rate •Other Milestones Why is this useful? - Allows flow of inquiries according to competence - Does not require continuous analysis and changing of caps and filters AS REP’S PERFORMANCE CHANGES… 1 My Enroll Rate Daily Inquiries 2 4 3 5 6 7 8 4.5% 4.2% 5.5% 7.6% 7.2% 8.3% 8.2% 8.5% 5 4 6 10 10 14 13 14 GETTING INQUIRY VOLUME RIGHT WORKLOAD IMPACT ON ENROLLMENT • Enrollment rates decrease as more new inquiries are assigned per rep o As workload increases, employees’ effectiveness is also likely to decrease (speed to call drops) o As volume increases, inquiry quality is likely to decrease • Can discern a formula for relationship between new leads assigned and enrollment rate WORKLOAD IMPACT ON ENROLLMENT 50.0% Enrollment Rate per Rep 45.0% 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% 0 5 10 15 New Inquiry Assignments per Rep 20 25 PREDICTING ENROLLMENT RATE EER = 0.3075*N-0.832 EER = expected enrollment rate N = new inquiries per rep per day based on guessing or current stats New Inquiries per Rep per Day 1 2 3 4 5 8 10 12 15 20 25 30 Expected Enrollment Rate 30.8% 17.3% 12.3% 9.7% 8.1% 5.5% 4.5% 3.9% 3.2% 2.5% 2.1% 1.8% SCORING SCORING What does it do? Allows you to score inquiries according to their: - Demographic attributes - Inquiry source - Level of interest (e.g. email opens) Why is this useful? Follow different workflow paths based on interest: - Send different emails and text messages - Distribute to different admissions reps - Increase priority as new information changes score DISAGREEMENT ABOUT INQUIRY QUALITY Why are you prioritizing inquiries that are women? Because they are the best-fit inquiries No, veterans are the best-fit inquiries Marketing Manager Admissions Manager DISAGREEMENT ABOUT INQUIRY QUALITY OK, let’s sit down and figure out what makes a “best fit” inquiry Sure, and then we’all document it as a scoring system for all inquiries Marketing Manager Admissions Manager SCORING EXAMPLES • You want to distribute your best-fit inquiries to your most experienced admissions reps • You want to attempt to call the best-fit inquiries more than others • A high quality inquiry is usually one that is a good fit and ready to make a decision, so your emails should have a more urgent tone with a clear call to action • Prioritization rules should favor a best-fit inquiry over a lower quality inquiry • You have an agreement with your PPL provider that you may return your very worst inquiries DIFFERENT SCORING MODELS Rules-based Model-based How it works • • You determine what makes a bestfit inquiry and configure rules Examples: • Have job = +1 • No GED = -3 • Email open = +4 • Email bounced = -5 • App requested = +10 • • Vendor runs models to determine best rules and then configures scoring Each inquiry scored against model Example vendors • • Leads360 Salesforce • • Neustar eBureau Value Brings • • Easy to set up Model visibility • • More complex Can be included as a factor in determining score OPPORTUNITY #2 Determine the overall impact of each marketing channel. ATTRIBUTION MULTIPLE DIGITAL MEDIA CHANNELS Google Bing/Yahoo Ad Networks CPL Social HOW ‘CLICK’ TRACKING WORKS Google Bing/Yahoo CPL Cookie ‘click-thru’ HOW ‘VIEW’ TRACKING WORKS Cookie Dropped Social Ad Networks Cookie ‘view-thru’ Cookie Dropped THANK YOU / CONFIRMATION PAGE ValueClick (Ad Network) DoubleClick (Ad Network) CPA Affiliate (CPA) Google (Search) Trialpay (CPA) SAME DAY INQUIRY GOOGLE ‘CLICK-THRU’ COOKIE Prospective student searches for ‘online degree’ and clicks on Google paid search Lets look at the code SAME DAY INQUIRY DoubleClick (Ad Network) CPA Affiliate (CPA) Google Cookie Finds a Match & ‘Fires’ Google (Search) Trialpay (CPA) Facebook (Social) PATH TO INQUIRY IS NEVER THAT DIRECT Prospective Students Take Multiple Days via Multiple Channels MULTI-DAY AND MULT-CHANNEL INQUIRIES RESULT IN CONFUSION 1. Data from ad networks not adding up 2. Data from search PPC not adding up 3. Data from CPL not adding up 4. Bad data results in bad decisions A BEST KEPT SECRET OF DIGITAL MARKETING “One of the best-kept secrets in online marketing is that most campaign attribution data is completely wrong and the models used to evaluate campaign performance are wholly inappropriate.” Published April 2009 “Hundreds of millions of dollars are wasted annually on marketing efforts that don’t produce their intended results.” TYPICAL SCENARIO DAY 1: Visitor views ad on Facebook DAY 2: Visitor search for Social Non-Brand Paid Search ‘online degrees’ DAY 15: Visitor clicks on Network Banner DAY 22: Visitor search for ‘university of …’ Ad Network Brand Paid Search Conversion ALL COOKIES FIND A MATCH Ad Network Finds a Match & ‘Fires’ DoubleClick (Ad Network) CPA Affiliate (CPA) Google Cookie Finds a Match & ‘Fires’ Google (Search) Trialpay (CPA) Social / FB Finds a Match & ‘Fires’ Facebook (Social) EVERY PARTNER TAKES CREDIT One Enrollment = 3 Claiming Credit Each Partner Sees Their Pixel Firing & Claims Credit ANALYTICS POINT IN THE WRONG DIRECTION + Analytics: Brand Search Term ‘university of ..’ led to inquiry Response: Increase Brand PPC Spend, Cut Network, Non-Brand Search & Social Result: Smaller Funnel & Less Conversions What’s Happening Down Below? AD NOT SEEN Yes – Cookie Dropped 68% Digital Ads Not Seen AD NOT SEEN JUMPS INTO LAST PLACE & WINS DAY 1: Visitor views ad on Facebook DAY 2: Visitor search for Social Non-Brand Paid Search ‘online degrees’ DAY 15: Visitor clicks on Network Banner DAY 22: Visitor search for Ad Network Brand Paid Search ‘university of …’ DAY 22: Visitor cookied by Ad not seen Ad Not Seen Conversion AD NOT SEEN JUMPS INTO LAST PLACE & WINS DAY 1: Visitor views ad on Facebook DAY 2: Visitor search for ‘online degrees’ DAY 15: Visitor clicks on Network Banner DAY 22: Visitor search for ‘university of …’ DAY 22: Visitor cookied by Ad not seen ✗ ✗ ✗ NO CREDIT No Credit for Origination or Assisting the Conversion 100% Credit Conversion HERE’S THE ACTUAL COST 1,000 Conversions X 68% not seen $30 CPI ‘actual’ CPI = $94 $30,000 / month Only pay for Viewable Conversions (Cost $9,600) Save $20,400 / month STEP 1: CAPTURE EVERY MEDIA TOUCH POINT DAY 1: Originator Visitor views ad on Facebook DAY 2: Roster Visitor search for ‘online degrees’ DAY 15: Visitor clicks on Network Banner DAY 22: Visitor search for Roster Assist ‘university of …’ DAY 22: Visitor cookied by Ad not seen Converter Conversion STEP 2: SKIP OVER ADS NOT SEEN DAY 1: Visitor views ad on Facebook DAY 2: Roster Visitor search for ‘online degrees’ DAY 15: Visitor clicks on Network Banner DAY 22: Visitor search for Assist Converter Conversion ‘university of …’ DAY 22: SKIP OVER ADS NOT SEEN Visitor cookied by Ad not seen BRAND SEARCH CONVERSION CONTROLS Last step in conversion is user navigating to the site Majority of prospective students navigate via brand search, SEO or direct website visit STEP 3: SKIP LAST CLICKED BRANDED SEARCH DAY 1: Visitor views ad on Facebook Assist DAY 2: Visitor search for ‘online degrees’ DAY 15: Visitor clicks on Network Banner DAY 22: Converter Conversion SKIP BRAND SEARCH SKIP OVER ADS NOT SEEN Visitor search for ‘university of …’ DAY 22: Visitor cookied by Ad not seen NEW LENS FOR ROI: ACPI Attributed Cost Per Inquiry SPLIT VALUE BASED ON THE DATA DAY 1: Visitor views ad on Facebook Assist DAY 2: Visitor search for 20% ‘online degrees’ DAY 15: Visitor clicks on Network Banner DAY 22: 40% Converter Conversion SKIP BRAND SEARCH SKIP OVER ADS NOT SEEN Visitor search for ‘university of …’ DAY 22: Visitor cookied by Ad not seen ATTRIBUTE EVERY INQUIRY BY EVERY TOUCH POINT 3,000 Conversions where ‘online degree’ was the assist Assist 600 3,000 Attribution Model Attributed Leads (Example 20% Model shown) (3000 X Assist %) IMPORT MEDIA COSTS AND CALCULATE CPI Calculate Ratio of Attributed Orders vs. Cost 2500 2000 2000 1500 Attributed Leads 1000 Media Spend 500 600 0 2,000/600 = 3.33 ACPI CPL RESULTS DISPLAYED IN THE DASHBOARD TECHNOLOGIES AND TIPS Save time and / or money Deliver a market or competitive advantage EFFICIENCY TIP #1 Move your time consuming, small run print jobs to an online store front. BENEFITS OF AN ONLINE STORE • Fast: Order 24/7/365 • Customizable: Edit creative whenever necessary • On-demand: Print what you want when you want • Simple: Access everything in one place • Competitive: Pay competitive rates EFFICIENCY TIP #2 A communication audit of all outbound messaging will likely reveal some communication issues. MONROE COMMUNITY COLLEGE 286 = Messages About Early Enrollment 60% 30% 10% AFTER THE AUDIT 30% 50% Early Enrollment Appointments for Placement Exams EFFICIENCY TIP #3 Aggressively update your business rules. If… …Then TWO EXAMPLES Fulfillment: Immediate vs. 48 hours? Faster push to closed status (also see Efficiency Tip #4) EFFICIENCY TIP #4 HOUSE FILE Your house file of unconverted inquiries is likely a highly untapped resource. $ RE-ENGAGE REGULARLY MONTHLY: NEW TO FILE AND TOP TIER NAMES REGULARLY: OTHER TOP TIER NAMES OCCASIONALLY: MID TIER AND OLDER NAMES Thank you.