AT A GLANCE
Rebuilding core digital platforms and reallocating toward more effective tactics drives conversions with greatest efficiencies.
A leading private university needed to increase enrollment in their renowned business degree programs. With different MBA programs aligned with different student needs (FT, PT, 1 or 2 year) and specific verticals (MD-MBA, JD-MBA, etc.), all were highly valued with proven ROI for graduates.
Arcalea rebuilt digital marketing efforts across existing platforms and implemented new ad platforms and formats, addressing gaps in core practices, refocused all efforts toward revenue goals, and expanded ad distribution and AI to capture new prospects.
The brand needed to increase enrollment within a market requiring long cycle times (as high as 1 to 5 years), possessing limited customer data, and legacy marketing focused on awareness and low-value intermediate goals.
Arcalea assessed current programs, platform configurations, and existing data to identify opportunities for immediate tactical remediation and longer-term strategic improvements. Ad platform analysis revealed counterproductive keyword strategies, including redundant keywords that could favor weaker conversion rates, global negative keywords that blocked strong query matches, and keyword organization techniques better handled by native platform AI. Arcalea documented the high volume of configuration changes in order to systematically transition to best practices without disrupting value from interconnected parameters.
Across all ad platforms, Arcalea shifted focus away from awareness goals toward goals more directly predictive of enrollment and revenue. Intermediate goals were evaluated for relevance, and changed from awareness-focused conversions (e.g., “time on site”) to conversions in which prospect information is exchanged.
For example, programmatic had been purely an awareness effort for the years before Arcalea's involvement. By shifting from user experience metrics to actual lead conversions, Arcalea achieved a cost per acquisition lower than the prior cost per user for awareness. After programmatic network targeting refocused on more meaningful goals, all sources were analyzed in order to eliminate those with expensive conversions or no conversions at all.
Analyzing each lead source for volume of cost-effective conversions allowed the brand to shift resources to the most effective networks. Intentionally expanding to effective publishers beyond Google allowed the brand to reach new audiences through a broader collection of relevant blogs and media companies.
In order to gain maximum impact of programmatic ad networks, Arcalea implemented an advanced AI that analyzed contextual relevance of the target placement pages and the contextual relevance of a visitor’s browsing history. In short, the AI analyzed content on the pages where ads are placed and on the pages a prospect recently visited. While this toolset was only recently applied for the brand, prior implementations improved matches and conversions.
Finally, analysis of the brand’s data landscape revealed gaps in both legacy results and customer information. Because the brand’s degree programs require a long customer journey, data relevant to customer actions over long tracking windows are critical to understanding the customer, creating aligned messaging and interactions, and measuring efficacy at each touch point. Fidelity of legacy data was unclear due to data capture outside of platforms, so intermediate conversions were not available for analysis. Critically, customer data infrastructure is lacking, allowing no insights into the number of unique prospects moving through each part of the funnel from awareness to enrollment. To address these gaps, Arcalea began validating existing customer data with the goal of an eventual Identity Resolution process.
A core Arcalea mission is to help brands understand how their funnel works, the actual cost of customer acquisition (CPA), and the opportunities to drive the right traffic through the customer journey to efficiently grow each brand’s business. As a result of platform core configurations, the shift to more relevant conversion goals, the elimination of poor performing structures and networks, and reallocation toward efficient sources and AI technology, the brand is able to quantify prospects in the pipeline and the associated CPA. Results continue to improve as the brand’s ability to measure relevant customer actions and make data-driven decisions expands.
As recent changes in sourcing, targeting, and AI-driven placement build results over time, the customer data infrastructure will continue to move forward. With each increase in relevant customer data, targeting becomes more accurate and efficient. Upcoming customer data infrastructure enhancements will provide a complete view of the customer, allowing for even more gains in efficiency as expressed in Cost Per Lead (CPL).
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