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The sweet dreams of Australian sleepwear buyers

Source: Roy Morgan Single Source (Australia), April 2010 – March 2015 (average monthly sample n=1,593).

It’s official: winter is here. As if plummeting temperatures and a sudden urge for hot soup aren’t proof enough, those long, frosty nights should convince you. Extra blankets? Check. Hot water bottle? Check. Flannelette PJs? Absolutely! Indeed, data from Roy Morgan Research shows that sales of women’s sleepwear spikes during the colder months. Men’s sleepwear, however, is a different story…

Between April 2010 and March 2015, an average of 991,000 Australians 14+ bought women’s sleepwear in any given four-week period. However, during May and July each year, this figure rises noticeably, as the chart below shows.

The seasonal business of women’s sleepwear

sleepwear-sales-chart

Source: Roy Morgan Single Source (Australia), April 2010 – March 2015 (average monthly sample n=1,593).

 A much smaller number buy men’s sleepwear in general (336,000 people in an average four weeks), and seasonal spikes are less pronounced than for women’s sleepwear. While shopper incidence did increase between June and August in 2010 and 2012, it also rose at other, less wintry times of the year.

Sleeping easy with Kmart and Big W

During the first three months of 2015, 19.8% of Aussies who bought women’s sleepwear in any given four weeks purchased it from Kmart. Best & Less and Target were also popular, chosen by 12.0% and 11.1% of women’s sleepwear buyers respectively.

Among people who bought men’s sleepwear in an average four weeks, Big W was a clear favourite (28.8%), ahead of Kmart (24.1%).

Not surprisingly, women are overwhelmingly more likely than men to buy women’s sleepwear, accounting for 91% of purchasers. Buying men’s sleepwear is a more equal opportunity affair, with a 52%:48% male:female ratio of shoppers.

Angela Smith, Group Account Director, Roy Morgan Research, says:

“Our long-term retail data reveals a distinct seasonal trend when it comes to buying women’s sleepwear, with shopper incidence rising as the temperatures start to fall. Over the last five years without fail, the May-July period has seen an increased proportion of Australians heading to the shops to buy women’s sleepwear.

“In contrast, sales of men’s sleepwear do not appear to be driven by seasonal changes. In fact, a much lower proportion of consumers purchase male sleepwear in general, suggesting that men are not so concerned about updating their pyjamas, only replacing them when they’re threadbare. That’s if they even wear pyjamas to begin with, of course: many men sleep in t-shirts and boxer shorts (or their birthday suit, for that matter!).

“While discount department stores like Target, Kmart and Big W are the most popular places to buy both women’s and men’s sleepwear, a considerable proportion of sleepwear buyers shop at specialty stores such as Peter Alexander and Cotton On Body. In this diverse and competitive market, it is important for retailers to understand which kinds of consumers are more likely to shop at their store and why.”

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About Roy Morgan

Roy Morgan is the largest independent Australian research company, with offices throughout Australia, as well as in Indonesia, the United States and the United Kingdom. A full service research organisation specialising in omnibus and syndicated data, Roy Morgan has over 70 years’ experience in collecting objective, independent information on consumers.

Margin of Error

The margin of error to be allowed for in any estimate depends mainly on the number of interviews on which it is based. Margin of error gives indications of the likely range within which estimates would be 95% likely to fall, expressed as the number of percentage points above or below the actual estimate. Allowance for design effects (such as stratification and weighting) should be made as appropriate.

Sample Size

Percentage Estimate

40%-60%

25% or 75%

10% or 90%

5% or 95%

1,000

±3.0

±2.7

±1.9

±1.3

5,000

±1.4

±1.2

±0.8

±0.6

7,500

±1.1

±1.0

±0.7

±0.5

10,000

±1.0

±0.9

±0.6

±0.4

20,000

±0.7

±0.6

±0.4

±0.3

50,000

±0.4

±0.4

±0.3

±0.2