News release

Contact:
Bruno Rost
Press Relations Manager, Business Strategies
+44 (0)115 96 85009 Tel
bruno.rost@uk.experian.com Email

Valentine special: Lingerie purchasing trends revealed

Nottingham, UK, 1 February 2008 - Sales of exotic underwear and French knickers have declined significantly over the last year, according to latest data from TNS and Experian, the global information services company and retail specialist. Sales of more traditional pants, together with ‘shorts’ meanwhile have risen during the same period.  The findings, compiled using TNS Worldpanel Fashion data and Experian’s new Fashion Segments classification system, also reveal that men are currently buying almost twice as much corsetry than they did in 2006. 

With St Valentines Day fast approaching and underwear sales front of mind for many retailers, the data also identifies the East Midlands as the region which has the highest number of specialist stores per shopper. Wales, Scotland and the North of England, on the other hand, have the lowest proportion of lingerie shops per consumer. The figures also show that the top towns for number of specialist lingerie stores per buyer are London, Shrewsbury and Cheltenham. Dartford, Slough, and Wakefield, meanwhile, are ranked lowest. 

Experian’s Fashion Segments classification tool provides invaluable insight into people’s different attitudes to clothing fashions and brands; it also takes into account what stores people are likely to visit as well as the frequency, value and purpose of shopping trips. The East Midlands for instance – which has the highest number of lingerie stores in relation to shoppers – is home to a large number of Lees (‘functional fashion seekers’) and Jasons (‘sporty basics’), both of whom spend an above average amount on ladies tights.

Key facts

 

  • Sales of G-strings, thongs and French knickers have declined and accounted for only 12% of the women’s knicker market in 2007, compared to 16% in 2006
  • Men bought almost twice as much corsetry in 2007 than they did in 2006
  • The East Midlands region has the highest number of lingerie stores per shopper in the UK (the region has a total of 98 lingerie stores and a shopping population of 3.8 million)
  • London, Shrewsbury, and Cheltenham have the highest number of lingerie stores per shopper while Dartford, Slough and Wakefield have the lowest 

 

 

Lingerie stores

Shopper Population

Shoppers per store

EAST MIDLANDS

98

3,801,281

38,789

YORKSHIRE & HUMBERSIDE

122

5,059,070

41,468

NORTH WEST

147

6,594,199

44,858

SOUTH WEST

113

5,103,214

45,161

EAST ANGLIA

52

2,360,921

45,402

GREATER LONDON

155

7,179,912

46,322

WEST MIDLANDS

116

5,500,301

47,416

SOUTH EAST

236

11,656,692

49,393

SCOTLAND

84

4,804,381

57,195

WALES

45

2,635,956

58,577

NORTHERN

48

3,123,315

65,069

 

NB: Number of Lingerie stores excludes department and variety stores

 

ENDS

 

NOTES TO EDITORS:

About Fashion Segments

Fashion Segments has been developed using Experian’s proven expertise as an award-winning builder of consumer classification tools.  It combines two of Experian’s established segmentation systems:

  • Mosaic, which draws on a wealth of demographic, socio-economic and financial information in order to classify all local neighbourhoods across the United Kingdom into one of fifty-two distinct lifestyle types that comprehensively describe their socio-economic and socio-cultural behaviour.
  • Person level Pixel, which assigns each of the 47 million adults in the United Kingdom to one of over 6,000 segments by combining five key pieces of information (gender, age, length of residency, property type, household composition).

 

Key to the development of Fashion Segments is the wide range of additional data that Experian has referenced in order to understand the specific characteristics of groups of Mosaic-Pixel combinations. These data sources include:

  • Consumer demographics.
  • Consumer propensities – propensities for individuals/households modelled from Experian’s surveys which relate to the following categories of behaviour, attitudes and product consumption: advertising preferences, purchasing behaviour through different channels, motivations to buy, attitudes to shopping and media consumption.
  • Other sources: a key additional data source, which has been used to further understand and visualise each Fashion Segments type, is TNS Worldpanel Fashion's on-going tracking surveys. Key variables within this dataset were then used to cluster Mosaic-Pixel codes with similar characteristics into distinct types (Fashion Segments). The cluster algorithm used to build Fashion Segments is proprietary to Experian and is based on over 25 years of research in the academic and commercial environment. Through an iterative process, an optimal solution is produced. When complete, this solution produces a set of clusters that are as different from each other as possible across the input variables and, within each cluster, individuals who are as similar as possible across the input variables.

 

About TNS
TNS is a global market insight and information group. Its strategic goal is to be recognised as the global leader in delivering value-added information and insights that help clients to make more effective decisions.

As industry thought leaders, its people deliver innovative thinking and excellent service to global organisations and local clients worldwide.  It works in partnership with clients, meeting their needs for high-quality information, analysis and foresight across its network of over 70 countries.

It is the world’s foremost provider of custom research and analysis, combining in-depth industry sector understanding with world-class expertise in the areas of Retail and Shopper Insights, Stakeholder Management, New Product Development, and Brand and Communications.  It is a major supplier of consumer panel, media intelligence and internet, TV and radio audience measurement services.
 

 

The word 'Experian' is a registered trademark in the EU and other countries and is owned by Experian Ltd and/or its associated companies.

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