Data
Services
The best way to get the most out of Student Search is through custom, powerful, and results-driven modeling.
We’re efficient, attentive, and effective. Our clients buy fewer names, leverage more sources, and better target their outreach to drive improved student profiles and enrollment growth.
We offer Predictive Modeling and Inquiry Scoring. Our custom approaches marry unique value-add sources including Segment Analysis Service with our own warehouse of proprietary geodemographic, behavioral, academic, and enrollment data collected from over 11 million college-bound students over the past seven years to drive measurable enrollment results.
Predictive Modeling
Benefits
Helps you achieve multiple strategic goals
Predictive Modeling will enable you to achieve multiple strategic goals, such as:
- Increasing enrollment
- Increasing tuition revenue
- Boosting your academic profile
- Increasing underrepresented student enrollment
- Entering new markets more efficiently
Saves you money
In addition, Predictive Modeling can save your school money, by helping you:
- Purchase only the names of students who are most likely to apply and enroll
- Segment student populations more effectively
- Determine which students should receive additional communications, such as print and digital advertising
Results
For the 2021-2022 recruitment cycle, key efficiency metrics improved for our Predictive Modeling clients.
Fall Classes of 2023, 2024, and 2025
Our clients were able to decrease the size of their list purchases by 7% to 31% and improve their pre-Fire Engine RED Search results.
On average, we used an additional two sources to help our clients better target key recruitment populations.
By outsourcing their list modeling, purchasing, data cleanup, and deduplication to Fire Engine RED, our clients saved time, improved the quality of their data, and were able to purchase lists more frequently.
What sets us apart
We focus on applications and enrollment
We start with the end in mind: enrollment. That means we identify students who are most likely to apply and enroll, not just inquire.
We take a custom approach
What’s predictive for other schools may not be predictive for yours.
We build multiple models for each of your goals
Similarly, what’s predictive for one goal (increasing enrollment) may not be for others (boosting revenue and entering new markets).
We tap into unique data sources
Our data warehouse includes proprietary geodemographic, behavioral, academic, and enrollment data collected from over a billion student interactions, which:
- Enables us to construct models based on actual student behavior
- Helps us preemptively test models against existing patterns
- Reveals emerging shifts in the marketplace and enables us to continuously adapt to those changes
We’re also the only company that is able to tap into The College Board’s Segment Analysis Service™, which:
- Enables us to tag your data with 150+ unique educationally relevant academic, social and economic factors that predict where students choose to go to college
- Helps us make our models more predictive and informative
Segment Analysis Service can be applied to any student record regardless of source, and that includes your inquiry pool.
Case Studies
Our Predictive Modeling gets results, and here’s the proof. Select the goal to see the results we delivered:
Goal: To enter new markets in Southwest without increasing costs.
Strategy: We developed a model to trim names from weaker geographic areas, and redeployed resources to purchase names in specific new growth areas (AZ, NM, TX).
Result: We increased inquiries in these states between 29% and 55% (630 students); inquiries from eliminated areas fell by only 1% (22 students). So, for the same budget, we generated 608 more inquiries
Maintain effective outreach through COVID-generated turbulence
Strategy: Throughout 2020, Fire Engine RED has responded to nationwide upheavals by continually surveying younger students, testing new messaging, and adjusting modeling to capitalize on emerging trends.
Result: Despite unprecedented turmoil, our clients are seeing growth in inquiry generation in a time while many institutions struggle to even send Search campaigns.
Enter new markets without increasing costs.
Strategy: We developed a model to trim names from weaker geographic areas, and redeployed resources to purchase names in specific new growth areas (AZ, NM, TX).
Result: We increased inquiries in these states between 29% and 55% (630 students); inquiries from eliminated areas fell by only 1% (22 students). So, for the same budget, we generated 608 more inquiries.
Increase enrollment from new market 3,000 miles from campus.
Strategy: We developed a model to strategically expand into a market on the opposite coast by purchasing names of students most likely to apply and enroll. We then customized our copy/creative to appeal to students in this market.
Result: We saw dramatic increases in the yield rate AND academic quality. Yield for admitted students went up by 300%, and the average SAT score reached 1275.
Goal: To enter new markets in Southwest without increasing costs.
Strategy: We developed a model to trim names from weaker geographic areas, and redeployed resources to purchase names in specific new growth areas (AZ, NM, TX).
Result: We increased inquiries in these states between 29% and 55% (630 students); inquiries from eliminated areas fell by only 1% (22 students). So, for the same budget, we generated 608 more inquiries
Save money & increase enrollment by purchasing only the names of students most likely to apply & enroll.
Strategy: We developed a model to identify and purchase only the names of students likely to apply and enroll.
Result #1: We purchased 29.8% fewer names year over year, resulting in 24% fewer inquiries, and saving the client a total of $155,478.
Result #2: The client received 10% more applications, admitted 16% more students, and enrolled 11% more students, resulting in a return on investment of 52 times their first-year Search investment in net revenue (including discount rate).
Refine list acquisition strategy for secondary market.
Strategy: We combined our proprietary geodemographic modeling data with student-provided data to predict students’ willingness to travel. We then targeted those students as part of a Junior & Sophomore campaign.
Result We increased response rates (web form submissions and completed business reply forms) between 15% and 33%.
Meet budget-driven monthly goals of applicants likely to deposit & enroll.
Strategy: We developed a model to evaluate in-state markets, and purchased only the names of students identified as likely to apply and enroll, rather than purchasing the names of all students in the entire state. We removed 743 ZIP Codes from the Search geography used by the client’s previous vendor.
Result: We met or exceeded our client’s goals – every single month – for applications, completed applications, admits, and deposits. Year-end goals for completed applications and admits were met in March.
Inquiry Scoring
Benefits
Helps you plan more effectively
The sooner you know who’s going to apply, the better you can plan.
Saves you money
Knowing who is likely to apply allows you to make data-driven budget cuts and eliminate expensive communications to students who are unlikely to apply.
Enables you to redeploy resources to where they matter most
You will also be able to deploy your limited resources towards communicating with the right students, through the right channels (e.g., print, texting, digital), to efficiently grow your applicant pool.
Enables you to evaluate the effectiveness of your inquiry sources
In a fast-evolving recruiting landscape, we can quickly assess and quantify the relative value of new inquiry sources and other outbound communications.
Results
Our scoring allowed our clients to identify the likelihood of application at the point of inquiry.
Fall Class of 2022
Across all of our clients, the 50% of inquiries generated by Fire Engine RED resulted in 86% to 97% of actual applications.
What sets us apart
We’re getting great results for our inquiry scoring clients. Here’s how:
We take a custom approach
What’s predictive for other institutions is unlikely to be predictive for yours.
We develop an individualized score for each student
Every student approaches your school differently. While many models cluster students into a simple grid, we don’t. Instead, we create an individualized score for each student on the basis of their specific information.
We use behavioral data to enhance our modeling
From campus visits to parental communications to student engagement (e.g., website visits, campaign clicks, text opens, inbound phone calls) – every interaction signals interest in your school. We weigh each behavior independently to further sharpen our predictions.
We tap into unique data sources
Our data warehouse includes proprietary geodemographic, behavioral, academic, and enrollment data collected from over a billion student interactions, which:
- Enables us to construct models based on actual student behavior
- Helps us preemptively test models against existing patterns
- Reveals emerging shifts in the marketplace and enables us to continuously adapt to those changes
We’re also the only company that is able to tap into The College Board’s Segment Analysis Service™, which:
- Enables us to tag your data with 150+ unique educationally relevant academic, social and economic factors that predict where students choose to go to college
- Helps us make our models more predictive and informative
Segment Analysis Service can be applied to any student record regardless of source, and that includes your inquiry pool.
Case Studies
Select the goal to see the results we delivered:
Goal: To enter new markets in Southwest without increasing costs.
Strategy: We developed a model to trim names from weaker geographic areas, and redeployed resources to purchase names in specific new growth areas (AZ, NM, TX).
Result: We increased inquiries in these states between 29% and 55% (630 students); inquiries from eliminated areas fell by only 1% (22 students). So, for the same budget, we generated 608 more inquiries
Save money on marketing to low-yielding inquiries.
Strategy: We used inquiry scoring to identify low-yielding cohorts in an effort to save money (e.g., not send them expensive print mailings).
Result: After identifying the bottom half of the inquiry pool (24,415 names), and adjusting for campus visits, the client chose not to send print pieces to 22,750 of those students. This resulted in an estimated savings of $273,000. Ultimately, only five (5) enrolled students came from the bottom half of the inquiry pool.
Video
In this video, we discuss the latest trends in enrollment and how they are impacting Student Search.
Who'd play me in ”Fire Engine RED — The Movie“