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TXGAP - Using your Data for a Marketing Advantage
- 1. Using your Data for a Marketing Advantage Austin Milner Toulouse Graduate School, University of NorthTexas
- 2. Our Journey • Marketing decisions in the old days • Marketing in the Current Century • Understanding the new Philosophy • Predictive Analytics • Using Existing Resources • UNT Google Analytics Example • CRM • Tying it allTogether • Forecasting Enrollment • Impact of Marketing Campaigns • Communicating your results to Management • ClosingThoughts
- 3. Marketing in the Old Days • Group of people toss around ideas • An idea is selected and implemented • Revenue growth may or may not be impacted • Impossible to allocate increases or decreases in revenue to the idea • Repeat
- 4. Marketing in the Current Century: Let’s get Predictive • Data is used to understand current customers and predict the lifetime value of current and new customers 1. Observe various individual-level buying patterns from the past and find the various customer stories in the data set 2. Understand which patterns correspond with valuable customers and which patterns correspond with customers who are leaving for good 3. As new customers join, match them with these patterns accordingly
- 5. Marketing in the Current Century: Let’s get Predictive • Data is gathered from a variety of sources to create a holistic, 360-degree view of the customer’s path to purchase (apply/enroll) • Data is analyzed to better understand the customer’s needs, preferences, and intent to purchase • Controls and treatments are created to understand how campaigns performed over the control
- 6. Marketing in the Current Century: Let’s get Predictive • Data can be mined from Google Analytics and used to create forecasting models. • Example: Which users are likely to return (>50% chance) to your website based on certain factors (time spent on website, entrance page, exit page, goals completed, etc) • Those users with <50% chance can be segmented and shown advertisements
- 7. How can we use our Existing Resources to use in our Marketing? • Most customers follow a general path to conversion • Determine your audience based on place in path • Track where the customer is in the path and swoop in with an email or advertisement at their most vulnerable point to encourage them to convert • All campaign and ad information is tagged to assign attribution revenue and understand campaign performance • Review campaign performance, improve, repeat
- 8. UNT Use Case: Google Analytics Step 1: Home screen Customer exit Step 2: View Programs Step 3:View Admissions Step 4: Request Info Step 5: Take Tour Step 6: Apply Step 7: Enroll Points of influence
- 9. UNT Use Case: Google Analytics • Challenge: Understanding how we can use our existing resources to capture some of this data • External websites such as ApplyTexas are not owned by UNT and do not have our GoogleAnalytics tracking code • Clicks to external websites are tracked as an “Event” and Events are not configurable into a customer sales funnel • How to determine the difference between a click to ApplyTexas and an actual completed application?
- 10. UNT Use Case: Google Analytics • Action: • Clicks to ApplyTexas (and other outbound links) ping back a “Virtual PageView” to GoogleAnalytics • Embed user activation page into our website • When a user successfully applies, they must activate their account.This activation page is managed by an external party without our GA so by iframing the page into our site, the user is tracked as going to our website and activating their account.
- 11. UNT Use Case: Google Analytics
- 12. UNT Use Case: Google Analytics
- 13. UNT Use Case: Google Analytics • Result:
- 14. UNT Use Case: Google Analytics
- 15. UNT Use Case: Google Analytics
- 16. Marketing in the Current Century • Define your customer’s path • Make sure the customer’s path can be tracked from beginning to end (i.e. no “intent to apply” steps) • Create goals for each step in the path • Define a monetary value for each goal step (i.e. if 1/6 of campus visitors enroll and enrollees contribute $1000 in tuition then the goal value is $167) • Segment audience based on goal completion
- 17. Marketing in the Current Century - CRM • CRM (Customer Relationship Manager) • Houses all data related to suspects/prospects/applicants/enrollees • Extremely helpful in managing communications and understanding what marketing has the largest roll in impacting consumer behavior • Find your best customers, and find more customers like your best customers • Ability to append data from 3rd party sources into CRM • Partner with companies to provide more complete data to see information that is outside of your CRM/website • Cluster (K-Means) segmentation
- 18. Tying it allTogether 1. Create a forecasting model to look ahead into the future 2. Create a simple model to understand how recruitment activities impact enrollment 3. Communicate the results to management
- 19. Tying it allTogether: Predicting Future Enrollment Term UNT Enrollment Period UTD Enrollment UTA Enrollment UNTTuition (9 hours) Unemployment Spring 2003 7610 1 5237 6642 $1,436 6.72 Fall 2003 7203 2 5202 6983 $1,812.60 6.26 Spring 2004 6990 3 4929 6949 $1,812.60 5.92 Fall 2004 6881 4 5188 7038 $2,125.90 5.48 Spring 2005 6769 5 4842 6667 $2,125.90 5.4 Fall 2005 6729 6 5227 6511 $2,238.50 4.98 Spring 2006 6716 7 5013 6218 $2,238.50 4.9 Fall 2006 6845 8 5330 6134 $2,332.35 4.44 Spring 2007 6770 9 4927 5998 $2,332.35 4.2 Fall 2007 6911 10 5460 6662 $2,388.35 4.16 Spring 2008 6809 11 5075 6398 $2,388.35 4.32 Fall 2008 6919 12 5741 6685 $2,537.13 5.34
- 20. Predicting Future Enrollment • UNT Enrollment = 9895 + 155Period + 185Unemploymentt-1 – 2Tuition+.2UTD - .34UTDt-1
- 21. Tying it allTogether: Impact • If your data source (CRM/Google Analytics) captures each step in the enrollment process, how do we know which step is the most influential and which ones can be scrapped? • Create a model! • Logistic Regression
- 22. Impact Person Apply/Enr oll Request Info TourTaken Open House Calling Campaign E-Mail Campaign Austin 1 1 0 1 1 0 Jim 0 0 0 1 1 1 Bob 0 1 1 1 0 0 Jane 1 1 1 0 1 0 Jackie 1 1 0 0 1 1 Rebecca 0 0 1 0 1 1 Ashley 0 1 0 1 1 0 Amanda 1 0 1 1 1 1 Mike 0 0 0 1 1 1 Jonathan 0 1 1 0 1 0 Doug 1 0 0 1 1 1 Jill 1 1 0 0 1 1 Angela 1 0 1 1 0 1 Adam 0 1 0 0 0 0
- 23. Impact • Enroll = .2 + .1Request Info + .2Tour + .3OH + .08Phone + .05Email • This means if a student had a “1” for everything (i.e. completed every activity) their likelihood of enrollment would be… • Enroll = .2 +.1(1) + .2(1) + .3(1) + .08(1) + .05(1) • = 93%
- 24. Impact: Communicating Results to Management • Understand what your forecast model says, is enrollment projected to be higher or lower than last year? • What does your model tell you about the impact of on-campus and online events? • Which events need more planning and more resource allocation? • Which events can be cut because they are not significant?
- 25. Closing thoughts
Editor's Notes
- If you can understand the lifetime value of your customers then you can understand which customers are likely or unlikely to convert. After creating systems to gather data, it’s important to create strategies that allow you to market to your highest probability customers which keep costs low. There should be concern with cost of customer acquisition. If you don’t properly bucket your customers you may end up spending a lot of money on people that won’t ever convert. Cost of acquisition is much lower to retain current customers than it is to gain new customers.
- Marketing today is far less about creative output and much more about the ability to split-apply-combine data for strategic insights. Having the ability to understand the consumer path and interfere with an advertisement, email, or promotion when that individual customer is at their most influential point.
- *Must first understand the cost of acquisition vs the cost of retaining a customer. *Acquisition cost generally far greater than retaining. Define acquiring a customer as someone that has already visited your website without outside influence. *Note this is a VERY BASIC way of using your data
- *The customer journey to conversion looks different for each market segment *Swoop in at step 3 and send an email or display ad advertising step 4 and 5 – we do this because we know that once they complete step 4, the drop off rate is much lower
- ApplyTexas presents two challenges: When clicking an “apply now” button to move to apply Texas sends an “Event” hit in Google Analytics. To view this step as part of the funnel, Google must view the click as a page view. Thus, we set up Virtual Page Views, meaning when a user clicks on an outbound link, instead of tracking that as an “Event”, a “page view” is sent back to Google Analytics, allowing the page view to be placed in the funnel. After a user clicks on the ApplyTexas application button, need a way to verify that they actually completed the application and converted as an applicant. Each new applicant receives a confirmation email after applying with a link to set up their account on a website TGS does not control. Because we do not control the Activation website, we could not place our Google Analytics tracking on it… To get around this, we iframe the activation site into our website on a special page that we omit from internal search results and Google/Yahoo/Bing/etc., ensuring that the only way the user made it to that page was through our activation email.
- The activation page is not linked anywhere on our website and is completely hidden from search engine queries. Therefore we know that the only way a user got to the activation page is if they received a link to activate their account which means they had completed the applytexas process.
- The customer’s journey through the goal completion steps is clear. However it should be noted that segmentation should not just stop at segmenting based on goal steps, but you must also understand the time it takes for the customer to go from one stage to the next. Advertise to your audience appropriately based on this. To clarify, if in general it takes your audience 3 months to complete an application after they visit your website, don’t waste money on ads telling them to apply the day after their first visit… the audience isn’t ready yet! Instead, advertise the next logical step (i.e. talk with an advisor).
- CRM systems are vital in understanding current and prospective customer data. Links can easily be made between those who have already purchased a service and those preparing to purchase a service. CRM system lets you identify your best customers and then identify more customers like your best customers.
- Data can be exported from your CRM to include which activities prospects engaged in and whether or not they applied or enrolled. 1 = activity complete, 0 = activity incomplete