While back-to-school spending projections range between $27 billion to $29.5 billion, Synchrony Financial anticipates seasonal sales will increase anywhere between 3.7% and 4.1%. The financial services company expects parents of K-12 students in particular to drive this spending increase:
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63% of K-12 parents say they are feeling confident about their overall financial condition;
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75% of these parents say they feel confident about their job; and
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63% of K-12 parents say their household financial situation has improved this year, a jump of 10 points over last year.
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More than half (53%) of these parents expect to spend more this year than last year. In 2016, only 40% anticipated they would spend more. This increase is primarily because:
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45% expect to spend more on computers;
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46% anticipate increased spending due to an increase in the supplies list from their schools; and
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41% expect to spend more on everyday clothing versus last year.
Roughly 60% of K-12 and college parents started their back-to-school shopping by mid-July, but college students themselves said they would be shopping noticeably later, with approximately half of them starting in August or later.
The price/value equation is the primary driver in how much all parents are willing to spend: 86% consider retailers that “offer good value for the money” and those that “have the best deals” in deciding where to shop.
The only instance in which back-to-school spending appears to decrease is as students get older, mainly because they spend less on clothing than their younger counterparts. More than 90% of K-12 parents say they will buy everyday clothing for back-to-school, and 41% of them expect to spend more on clothing in 2017. But only 17% of college students anticipate that their spending for clothing will increase.
The Synchrony Financial Back-to-School study surveyed more than 1,850 shoppers, including parents of K-12 students, parents of college students and college students themselves, in July 2017. Synchrony considered a variety of macroeconomic factors, such as personal consumption, unemployment statistics, consumer price index and consumer confidence when generating this forecast.
