IMPROVING DIGITAL AND PERSONALISED INSTRUMENTS FOR THE PROMOTION OF EDUCATIONAL SERVICES
DOI:
https://doi.org/10.5281/zenodo.22823352Abstract
Digital promotion in higher education is commonly assumed to improve as the degree of personalisation
increases. This article examines a more specific question: what, exactly, is being personalised? Thirty-six recruitment
campaigns, accounting for 80 million UZS in expenditure, are classified along two dimensions: personalisation depth,
ranging from broadcast communication to individually responsive communication, and message payload, defined according
to whether the content contains a claim that a prospective student can verify. The analysis focuses on the interaction
between these two dimensions.
When entered alone, personalisation depth is associated with a 0.716-percentage-point increase in response, with a t statistic
of 2.71, and explains 17.7 per cent of the variation. When the interaction term is included, the constitutive terms are
no longer statistically significant, whereas the interaction coefficient is 1.819, with a t statistic of 10.22, and R² increases
to 0.921. Interpreted conditionally, these estimates indicate that an additional unit of personalisation depth is associated
with a 0.123-percentage-point increase in response for a message containing an assertion and a 1.942-percentage-point
increase for a message containing a verifiable claim—a ratio of 15.8.
Delivery cost increases approximately six-fold with personalisation depth for both types of message. Consequently, cost
per response increases by a factor of 5.44 when the message payload consists of an assertion and by a factor of 1.97
when it contains a verifiable claim. At the deepest level of personalisation, the difference between the two message types
is substantial, with a Welch statistic of 13.68. The sector allocates 67.8 per cent of campaign expenditure to messages
containing no verifiable claim, while 46.4 per cent of total expenditure is allocated to deeply personalised campaigns carrying
such messages.
Two alternative adjustments are quantified. Reducing personalisation depth in campaigns without verifiable claims
releases an estimated 29 million UZS and is associated with an estimated net gain of 13,253 responses, whereas changing
the message payload from assertion-based to verifiable content produces an estimated net gain of 38,630 responses
without increasing campaign expenditure. The estimated gain from the latter adjustment is nearly three times larger. Its
applicability, however, depends on whether an institution has substantive and verifiable information that can be communicated
to prospective students.
Keywords
digital marketing; personalisation; message verifiability; interaction effects; cost per response; higher education; UzbekistanReferences
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