CASE STUDY

First-Party Data Fuels Wave of New Content—Driving Enrollment and Retention for Online College

Client Overview

The client was an online higher education institution that helps working individuals return to school for degrees ranging from associate to doctoral degrees in business, education, nursing, and technology from all over the nation.

Results:

  • 500 People Surveyed
  • 27 Interviews (1:1)
  • 24 New Assets Created
  • 2 New Tools Prototyped

Challenge

The client’s prospective students use search during the buyer’s journey to help them choose courses and classes. It is a complex buying cycle with a number of stakeholders (both known and unknown) who can influence a prospective student’s decision to enroll.

However, the search environment is hypercompetitive, with numerous local and national universities competing for visibility in the space. This makes it difficult to rank critical content (from educational assets to key sales pages) that drives new enrollments.

Additionally, there are several topics they don’t know to consider that can have a significant impact on their success as students—unknown unknowns.

While the university already had a content team and strategy, they were exploring other ways of generating citation-worthy content to keep their organization top-of-mind during their prospective student’s buying journey.

In short, they needed unique assets that would earn backlinks and improve keyword rankings and visibility while helping prospective students make more informed decisions—increasing student retention.

SOLUTION

We ran a survey to uncover the unknown-unknowns or frequently unasked questions (FUQs) prospective students faced while considering their return to university.

Specifically, we focused on determining whether or not prospective students were considering the soft costs of returning to university as it relates to core relationships (family, friends, employers, etc).

The survey would support:

  • Link building: Create content to drive people to the university’s website and keep them there.
  • PR: Increase the university’s media mentions.
  • Sale conversions: Increase the number of students interested in the university.
  • Student retention: Help students understand the impact of returning to school to increase course completion and graduation rates.
  • LLM Visibility: Increase brand mentions in AI search tools like ChatGPT through buyer’s advocacy.

Using the survey findings, we recommended changes to sales pages and educational assets along with new content ideas for the marketing team.

The citable elements we recommended for the sales pages were designed to increase the linkability of those pages by publishers.

By adding first-party survey data, the sales pages went beyond trying to convert prospects into students. They provided unique industry insights that would add value to the audiences of relevant publishers.

Key Features

  • Survey of 500 non-traditional college students
  • Questions uncovered aspects prospective college students often overlook
  • Insights increase buy-in from prospective student stakeholders
  • Help students better prepare for a successful college experience

OUR PROCESS

We created and distributed a survey to collect 1st party insights that aligned with the brand using a relevant audience (non-traditional students in the US who were enrolled in college online—either fully online or hybrid—within the past 4 years.

The survey focused on uncovering unknown soft costs students face when returning to university (excluding stress management and self-care).

The process:

  1. Determine the research opportunity: Find a topic that is meaningful to the audience, aligns with the brand, and says something new.
  2. Brainstorm the Hypothesis and Headlines: Document the learning goal of the survey, going beyond data collection and looking to uncover something meaningful for the audience.
  3. Create the Research Framework: This is a high-level overview of the main topics and sub-topics the survey will focus on.
  4. Define the Research Scope: Decide what areas to focus on—and document what the survey will not cover.
  5. Design the Survey Questions: Develop questions that explore the hypothesis, focusing on curiosity (instead of trying to verify existing beliefs).
  6. Determine Qualification Criteria: List the qualification criteria for survey respondents to ensure accurate data collection.
  7. Program and Test Your Survey: Create the survey in the survey tool and test it as a survey taker would experience.
  8. Soft Launch the Survey: Launch the survey to a small sample (5 – 10%) and review the initial results, adjusting the questions as needed.
  9. Run the Survey in the Field: Run the survey at scale with the target audience.
  10. Share Results: Present survey findings to the team with a focus on sharing the stories they can tell with the data.

ROADBLOCKS

Two leading digital PR agencies we contacted to support the survey development and distribution pushed back on the idea. They could not see a survey like this fit mainstream publications.

Our focus on assisting the audience led us to a community-PR approach instead, where we distribute our message via non-profits who also serve our audiences.We built and launched the survey directly with this audience.

This eliminated any potential negative impact on the brand while providing useful insights that could improve the visibility of key enrollment pages.

Working with an independent research team allowed us to get the project live faster with results to share with the team without having to navigate red tape from PR, brand, and leadership teams.

RESULTS

The survey provided extensive details on questions overlooked by most universities, leading to several content ideas, link-building campaigns, and tools to support students.

By identifying and enhancing the differentiated behaviors used by successful students, the content team can now enable the behavior to happen more frequently by codifying it into helpful guides, tools and other support materials.

New Assets:

  • Empathy Mapper Tool: Maps assets to the different programs with specific requirements based on unique audience needs (course load, course type, workload, stakeholders, potential disruptions, etc.)
  • Time Management Calculator: Analyzes current time commitments and creates personalized recommendations to support academic success.
  • Customer Interviews: Detailed interviews of successful students to further explore unasked questions of target student audiences.
  • Extensive Content Library: Nearly 20,000 words of new content (24-document library including guides, insights, and frameworks) to help prospective students.
  • Net-New Insights: Robust 1st party survey data shed new light on how students successfully choose a new program and return to university.
  • Scripts for Prospective Students: Assets to support students. For example, a Guide for Crisis Conversations students can use to remedy stakeholder oversights.
  • 2 PR-Ready Branded Articles: These assets highlight the findings from the survey for the university’s PR team to share with relevant publications.

The data allows them to confidently decide on content that supports successful student behaviors, leading to happier student outcomes and higher retention rates.

The new data-driven content also puts the university in a better position to increase LLM visibility by addressing the questions prospective students and competing organizations fail to answer. Answering these unasked questions is vital for decision-makers to make the most informed choice, increasing the likelihood of successful outcomes.

The team also has a clear process for running future surveys and using that data to enhance their existing content strategy and assets.

WHAT’S NEXT:

We’ve built and shared a proof of concept of a tool based on the 1st party survey data that solves several pain points users face when determining whether or not they’re ready to return to university. The prototype supports the growing need of customers to have solutions explicitly made for solving their problems, not articles that merely highlight challenges.

We’ve also worked with the team to use the survey data within ChatGPT to evaluate the website and its content for weak points and brand misalignment. The team uses the survey data to evaluate and improve existing assets.

Finally, we’re working with the team to outline new link-building campaigns. These campaigns will focus on adding data collected by the survey to key sales pages, increasing the likelihood that publishers will link to them.