deep discount food retailing opportunities

8/10/2019 Deep discount food retailing opportunities

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Modelling the Future Opportunities for DeepDiscount Food Retailing in Great Britain

Working Paper

Chris Thompson, Graham Clarke, Martin Clarke, John Stillwell

Version 1.0

October 2010

This Working Paper is an online publication and may be revised

School of GeographyUniversity of Leeds

LeedsLS2 9JT

United Kingdom


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Abstract

In the last few years the discount retail food market in Great Britain (GB) has grown to record levels. This followed a period

of gradual increase in store numbers and also more favourable trading characteristics for discounters given the recession and

global financial problem of the late 2000s. Although market share has dipped a little in recent months the deep discounters

still have impressive growth plans for their GB store networks. The aim of this paper is to look at where discount retailers

could expand in the future. First we plot the growth of the discounters in GB and use Acxiom Research Poll (ROP) survey

data to attach a geodemographic label to the different food retail brands. This will allow us to profile the types of customers

using discount retailers as their primary food destination. We profile the different customer bases in Yorkshire and Humber

and London, two very different regions for discount retail market share. This includes looking at the potential expansion

into middle Britain, moving the focus from deep discounting to serving more middle markets (a potential change in the

value-platform growth strategies which companies such as Aldi and Netto now seem to be championing). Following an

evaluation of the potential sites using geodemographics, we design and implement a disaggregated set of retail location

models which will evaluate the impacts of these new stores in more detail, especially in relation to potential revenues and

market shares.

KEYWORDS: Deep discounters; geodemographics; growth; spatial analysis;

1. IntroductionThe deep discount retailers from Germany and Scandinavia arrived in Great Britain (GB) in the early

1990s. They were enticed into GB by the high profit margins enjoyed by British food retailers at the

time and their recognition of a gap in the market a value gap in terms of price, and a spatial gap in

terms of the most deprived areas of British towns and cities (Wrigley and Clarke, 1998). As Tesco,

Safeway and Sainsburys largely concentrated on servicing the more affluent middle class, the

discounters went head-to-head with the food retailers of northern England, especially Morrisons, Kwik

Save, the then Gateway, Asda and the Co-op. Although growth stalled somewhat in the late 1990s, the

discounters did expand outwards from these initial heartlands, and the 2000s have witnessed a

significant increase in the number of stores owned by the three main players: Aldi, Netto and Lidl. Thecompetition during this period was too hot for certain incumbent players, most notably Kwik Save

which was finally sold off in 2006.

By 2008, the discount retail food market in GB had grown to record levels. This followed a period of

gradual increase in store numbers and also more favourable trading characteristics for discounters,

given the recession and global financial problems between 2007 and 2009 (Thompson et al.,2010b).

Having reached record sales, fortunes have dipped somewhat for the three discounters between 2009

and 2010 as the other food retailers have fought back, principally on price. Some commentators have

suggested that this dip in fortune was enough to convince one player to bail out Netto being sold to

Asda in 2010 for 778million. However, the other two discount players continue to look to GB formajor expansion. Aldis plans for future expansion are extraordinary their stated ambition is to have

1,500 stores across the UK (Hickman, 2008), a considerable increase in their present portfolio of 467

stores.

The aim of this paper is to look ahead and identify potential locations in GB for new sites for the

discount retailers, especially if they are to hit the expectation of growth mentioned above. A history of

the discount sector in GB is presented in section 2 by way of context. In section 3, we use Acxioms

Research Opinion Poll survey data (Thompson et al., 2010a) to examine the customer base of the


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discount retailers and profile those customers against the Office of National Statistics (ONS)

geodemographic classification (Vickers et al., 2007). In Yorkshire and Humber, we see a customer

segmentation based on households in which substantial proportions are classified as Constrained by

Circumstances and Blue Collar Communities. In London, we additionally see the importance of the

geodemographic group Multicultural. In section 4 of the paper, we use the findings from the

geodemographic profiles to search for new locations for the deep discounter Aldi the company whose

aggressive expansion plans have been mentioned above. First, we examine opportunities still available

in the traditional low income market of Yorkshire and Humber where the discounters already have a

relatively high market share are there still concentrations of low-income customers not served by

Aldi and the other discounters? We will also look at potential expansion into middle Britain, moving

the focus from deep discounting to serving more middle markets (a potential change in the value-

platform growth strategies) which companies such as Aldi and Lidl now seem to be championing

(Hickman, 2008), and observed in a rising number of customers from the Countryside

geodemographic category. Second, we will examine opportunities in London, an area which is not as

well-served currently by discount retailers. Even though London continues to prosper in comparison to

the north, we will explore areas which could also be potentially fertile ground for Aldi. In section 5, theanalysis will include the design and implementation of a set of disaggregated retail location models.

These models will allow us to test if the locations suggested by the geodemographic analysis are likely

to produce revenues acceptable for new store development.

2. A history of the discount food sector in GB

Wrigley (1994) documents a series of external shocks in the food retail sector in the late 1980s and

early 1990s, which had profound impacts on the speed of growth of the major players. Having enjoyed

a golden era of rapid, largely out-of-town growth (Wrigley, 1987), the major players were faced with

a number of threats, or new and difficult trading circumstances. First was the threat of saturation, a

theory espoused by academics and business executives alike (e.g. Duke, 1993). Although Langston et

al. (1997; 1998) and Guy (1998) challenged the notion of saturation; it appeared to be a common

perception in the food retail world. Second, new GB tightened planning legislation in 1996 seemed to

make out-of-town sites harder to acquire (revised PPG6). Third, was the depreciation of assets forced

by City accountants who argued that retail land had become overpriced in relation to other land uses

and hence firms were not worth the amounts seen on company balance sheets (Wrigley, 1994; 1998).

Another key problem to hit the major players came with the arrival of the deep discount food retailers

from Germany and Scandinavia. Although constantly denying that they would be serious competitive

rivals, the big players were eventually forced into action as the deep discounters stores grew in

number. Locating first in areas of major urban deprivation, the deep discounters soon gained

considerable market share in the North (of England) and the West Midlands. All the main players

reacted by discounting prices on main items and there is some evidence of bullying tactics to stop

manufacturers supplying the new discounters (and hence a lot of products, many unfamiliar brands to

British consumers, had to be sourced from Continental Europe). For Asda, Gateway (later Somerfield)

and the Co-op, the competition was so fierce in northern towns and cities that they experimented with


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new fascias (Pioneer for the Co-op, Food Giant for Gateway and Dales Discount for Asda), in order to

offer a deep discount format in retaliation. The impact of the deep discounters was perhaps felt most

keenly by the main British incumbent discount retailer in these areas Kwik Save. After its own

golden periodin the 1980s, Kwik Saves growth slowed down in the late 1990s and it merged with

Somerfield in 1996. However, the merger was not sufficient to save the company. On 27th

February

2006, Somerfield sold the Kwik Save brand and 171 stores to private equity company BTTF. More

details on the arrival and diffusion of the deep discounters in this period can be found in Burt and

Sparks (1994; 1995) and Wrigley and Clarke (1998).

Against this backcloth of growth for the discounters, Wrigley and Clarke (1998) undertook an analysis

of socio-economic class to identify potential new sites outside their heartland regions in the north and

midlands. Many of these sites have actually since been chosen as Aldi, Lidl and Netto all made

substantial additions to their portfolios of stores throughout the 2000s. Figure 1 shows the growth in

their store networks between 2003 and the present day (2010). Aldi clearly moved out in all directions

from their heartland with new stores in the South East, Wales and Scotland. Lidl opted to move

towards a blanket coverage of GB whilst Netto was perhaps more cautious, not straying too far from its

initial northern base (with the exception of London). Whilst the overall growth in supply of discount

stores has been impressive, some planned strategies did not come to fruition. For example, Nettos

highly publicised 200million investment in 70 new sites in South Wales never materialised.

(a) All discounters (b) Netto


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(c) Lidl (d) Aldi

Figure 1. Discounter store expansions from 2003 to 2010 across GB (Sources: GMAP 2003, 2010).

By the mid-late 2000s there was much optimism in the discount market that future GB growth wouldbe strong in this sector. Between 2007 and 2010, this optimism seemed well placed and indeed was

heightened by the onset of recession in the United Kingdom (UK). Similar to the recession in the

1990s, which gave the discounters their initial platform for growth (Burt and Sparks, 1994), the more

recent recession caused households to switch to the discounters in large numbers. Aldi, Lidl and Netto

saw their combined market share rise to 6.1%, their highest ever in the UK (Aldi 3.0%, Lidl 2.4% and

Netto 0.7%). Thompson et al. (2010b) discuss this consumer switch in patronage in more detail,

referring in particular to the growth of customers shopping at discounters from the higher income

groups. Originally, it was believed that the recession was the cause for higher earners reverting to shop

at low price retailers. However, the evidence would suggest that the trend was already occurring before

2007 and the recession merely accelerated this trend as households of all types began to seek out low

cost. Since the beginning of 2009, however, it seems that the fortunes of the deep discounters have

turned once again. So much so, that in 2009 Aldi reported a loss of 54 million on its UK business,

Lidl reported a fall of 38% in profits and Netto sold its assets to Asda for 778million. The rise in

market share for the deep discounters was followed by aggressive fight-backs by the big four. The

introduction of new low-cost ranges from the bigger retailers meant that the discounters were no longer

seen to be quite so cheap and competitive. Furthermore, as the recession progressed and unemployment

across the country increased, consumers shifted their purchasing behaviour from eating in restaurants


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and drinking in pubs to spending more on high quality grocery ranges offered by the likes of

Sainsburys, Waitrose and Marks and Spencer (Mitchell, 2009) encouraged by attractive meal deals.

This trend has only accelerated since the UK economy emerged from the recession as shoppers

continue to trade up. Edward Garner, Communications Director for Kantar Worldpanel, explains as

we emerge from thegrip of the recession, quality is back on the agenda (Kantar Worldpanel, 2010b).

The latest figures for the 12 weeks leading to the 3rd October 2010 indicate that Tescos market shareremains unchanged at 30.8% whilst Morrisons and Sainsburys have both grown by 6.1% and 4.4%

respectively (Kantar Worldpanel, 2010a). Conversely, Asda continues to underperform with its market

share back down to a level not seen since November 2008. Waitrose continues to see a remarkably

consistent share growth from a low point of 3.6% in November 2008 to a current 4.2% (Kantar

Worldpanel, 2010a; Kanatar Worldpanel, 2010b). Faced with this difficult period, it might be

anticipated that Aldi and Lidl would perhaps retreat and scale-back their UK operations. However,

despite its reported losses, Aldi opened 50 new sites in 2009 and held planning permission on a further

29 sites at the start of 2010 (The Grocer 2010). The company also increased its market share value

from 2.3% earlier in the year to 3%, equalling the share which it achieved during the peak of the

recession in 2009. Additionally, Lidl held 22 sites with planning permission for new stores at the start

of 2010 (The Grocer, 2010). Thus it seems that growth in GB remains very much on the agenda.

Indeed, the Grocer (2010) also quotes Netto MD Charles Kay (still in charge of its UK business) as

saying Discounters do best when they have lots of stores close by one another. There is lots of scope

for them to grow.

3. Exploring the geodemographics of discount retailing

Figure 2 exemplifies the current portfolio of stores across GB for Aldi, Lidl and Netto combined with

the percentage of households in each Local Authority District (LAD) which use each of the discounters

for their main grocery shop. Clearly there are still gaps in market share across the country. The big

question remains as to whether the gaps are in areas where the discounters already have a strong market

share, or will they need to venture out into pastures new? This is an important question as the two

remaining deep discounters certainly have impressive plans for expansion. In July 2009, all the main

GB newspapers reported that Aldi, for example, laid out plans to triple its GB store network from 467

to 1,500 (Hickman, 2008; Mail Online, 2008). If they could successfully accomplish this, their market

share would increase to 10%. Therefore, in the rest of the paper we attempt a new geodemographic

analysis of existing discount customers as a way to identify potential locations for new Aldi stores in

two case-study regions. The first is Yorkshire and Humber, an area where the discounters have a longstanding history of trading and already have a strong market presence. The second is London, a region

unlike any other in the country and a catchment where the discounters have very poor market share

levels, despite a significant network of stores (Figure 2). Furthermore, it has also been identified by

Aldi as a key part of their store expansion program, described even as a gold mine by Graham

Hetherington the companys director for London and the South-East (Mai Online, 2009). Together,

each of these regions will provide contrasting examples for the potential expansion of Aldi stores

within GB.


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Figure 2. The location of the discounters in Great Britain, 2010(Sources: Acxiom 2009, GMAP 2010).

Through using a combination of Acxioms annual Research Opinion Poll (ROP) household-level data

and the ONS geodemograhpic Output Area (OA) classification developed by Vickers et al.(2007), we

are able to provide a breakdown of each of the major retailers customer base in both regions.

Acxioms ROP was used on account it gathers detailed and up-to-date information on consumer

spending habits, preferences, socio-demographic information and the respondents geographic location.

The combination of these different pieces of information allows for detailed insights into the spending


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patterns of different types of people and geographic areas. Moreover, with the survey being

distributed annually and including questions not asked on other public sector surveys, it also provides a

unique source of time-series data on the demographic and socioeconomic characteristics of people and

households across GB (Thompson et al., 2010a). In conjunction, geodemographics has a long history of

application in the business world (Birkin and Clarke 2009) and provides a useful tool for profiling the

target audience for retailers. It has been argued to be...a shorthand label for both thedevelopment and

application of area typologies that have proved to be powerfuldiscriminators of consumer behaviour

and aids to market analysis (Brown 1991, p.221).

3.1 Yorkshire and Humber

As stated, for the discounters, the Yorkshire and Humber region is an area where they achieve some of

their highest markets shares. Netto in particular has a long history in the region having opened its first

British store in Leeds in 1990. Since then, Figure 1 highlights how all three deep discounters have

targeted the area as one of their main locations for expansion. The main competition in the area is from

Morrisons and Asda; two Yorkshire based firms that dominate the local market (Thompson et al.,

2010b). However, the rapid expansion of the convenience store format by Sainsburys and Tesco hascaused a steady decline in market share over the past four years for Morrisons in particular.

Additionally, the recent recession caused considerable switching behaviour from the big four to some

of the discounters, especially Aldi, Lidl and the frozen food retailer Iceland (Thompson et al., 2010b).

Figure 3 presents the geodemographic profiles for each of the main retailers in operation within

Yorkshire and Humber for 2010. Kwik Save has also been included to offer a comparison with the old

British discounter which was sold off in 2006. It was argued in the 1990s by Wrigley and Clarke

(1998) that the main customers for the discounters were those in the D and E socio-economic

categories (the Jictnar classification commonly used in marketing, with households or persons labelled

A-E, with A affluent professional workers and E unskilled manual workers) . However, it would appearfrom Figure 3 that the individual discounters have more complex customer profiles. For example, for

those customers which shop at Aldi, the majority fall within the Typical Traits (24.3%) and

surprisingly the Prospering Suburbs (20.6%) categories. The rise in customers from the Prospering

Suburbs groups is largely a result of the increase in higher earners reverting to shopping at discounters

since 2004 (Hickman, 2008; Thompson et al., 2010b). Lidls target audience is not too dissimilar;

however, Iceland, Kwik Save and Netto are distinctly served by customers living in areas termed Blue

Collar Communities and Constrained by Circumstances (closest to the D and E Jictnar

classifications). In the early 2000s, Aldi too had a strong Blue Collar Communities following, but

over the past six years this has been consistently declining (Thompson et al.,2010b).

In comparison, Asda and Morrisons, the two dominant retailers in the area have quite a varied customer

base. It could be argued that this is a result of their longstanding presence in the region which has

gained them a strong sense of brand loyalty across all areas in Yorkshire and Humber. The Co-op and

Tesco also have a reasonably varied customer base; however, they have strongest backing from the

Countryside group. A possible explanation is the existence of many Co-ops in rural market towns and

the large Tesco superstores located in out-of town sites (Wrigley, 1994). Unsurprisingly the

households which shop at Sainsburys, Marks and Spencer and Waitrose are overwhelmingly from the


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Prospering Suburbs group. Moreover, Waitrose in particular also has quite a prominent proportion of

shoppers from the City Living (11.9%) classification.

(a) ALDI, 2010 (b) ASDA, 2010 (c) CO-OP, 2010 (d) Kwik Save, 2007

(e) Iceland, 2010 (f) LIDL, 2010 (g) M&S, 2010 (h) Morrisons, 2010

(i) Netto, 2010 (j) Sainsburys, 2010 (k) Tesco, 2010 (l) Waitrose, 2010

Figure 3. Geo-demographic profiles of the main grocery retailers in Yorkshire and Humber (Sources:

Acxiom ROP, 2007, 2010; ONS, 2003)

Figure 3helps provide a useful insight into the customer profile for the various retailers, although the

profiles do not factor in the base population for the region. For instance, due to the small number of

households living in Multicultural areas and the large percentage in Blue Collar Communities, it isdifficult to identify which retailers are primarily catering to these groups. We attempt to rectify this

problem by dividing the OAC percentages of each retailer by the percentages recorded in the base

population (ROP sample). In doing so, we establish whether a selected retailer has a below or above

average number of customers in a specific group compared to the percentage in the regions population.

It is worth noting, however, that the figures do not reflect the market share each company has of a

particular group, we simply aim to emphasise each retailers primary consumer. Figure 4 displays the

results from this method, with only those values above the regional average shown (above 100). From


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Aldis point of view, the high percentage of Prospering Suburbs group is no longer recognised as a

one of their main consumers. What appeared to be a large percentage in Figure 3 was actually a

reflection of the great number of households which live in Prospering Suburbs. Instead, Aldi appears

to have an above average number of customers from the Countryside, Constrained by

Circumstances and Typical Traits groups. Those consumers living in the Countryside have not

always been one of their core consumers; however their numbers have been growing steadily since the

company has expanded into rural market towns (Thompson et al.,2010b). Similarly, Lidl also has a

considerable number of Countryside consumers. However, in the same way as Netto, Lidl attracts a

large proportion of households from the Multicultural areas. Figure 4 also shows the extent to which

Marks and Spencer and Waitrose (and Sainsburys to a lesser extent) are dominant amongst the City

Living communities.

Figure 4. Geo-demographic profiles of the main grocery retailers constrained by the base population of

Yorkshire and Humber (Sources: Acxiom ROP, 2007, 2010; ONS, 2003).

3.2. London

Based on the locations plotted in Figure 2, London was identified as a region where the limited line

discounters have a very low market share (below 2%). Sainsburys and Tesco are the dominant force in

the market whilst Asda and Morrisons have a considerably smaller market share (Birkin, Clarke andClarke, 2002; Thompson et al.,2010b). Figure 5 shows for each retailer, the percentage of households

which live in each of the seven OA classifications. It is immediately clear that the retailers have a

somewhat different customer base to counterpart stores located in Yorkshire and Humber. London is

heavily dominated by people living in Multicultural areas and hugely underrepresented by the

Countryside group. In 2001, London was home to over two thirds of Britains Black population,

nearly 42% of the Indian population and one third of both the Pakistani and Other South Asian and

Chinese populations (Stillwell, 2010). Understandably, the proportion of households living in the City


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Living group is also much greater than in Yorkshire and Humber. The large differences between

Figure 3 and Figure 5 strengthen the argument that store location strategy is a complicated process and

regional differences in consumer demand are of paramount importance (Birkin, Clarke and Clarke,

2002). The Multicultural classification aside, the grocery retailers still have quite defined target

audiences. More specifically, similar to the Yorkshire and Humber stores, the majority of Aldis

customers are from the Typical Traits, Prospering Suburbs and Constrained by Circumstances

areas. In contrast, out of those households shopping at Lidl, Netto and Iceland, the majority come from

the Multicultural (more so than anywhere else) and Typical Traits segmentations. Moving onto the

big four, Asda and Morrisons both appear to be targeting the Blue Collar Communities whereas

Sainsburys and Tesco attract a greater proportion of people from the City Living and Prospering

Suburbs groups. Conversely, it would appear that Marks and Spencer and Waitrose struggl e in

Multicultural parts of the region and are specifically locating in the more central City Living areas.

In fact, Waitrose is the only retailer not to have the Multicultural group as its principal consumer.

(a) ALDI, 2010 (b) ASDA, 2010 (c) CO-OP, 2010 (d) Kwik Save, 2007

(e) Iceland, 2010 (f) LIDL, 2010 (g) M&S, 2010 (h) Morrisons, 2010

(i) Netto, 2010 (j) Sainsburys, 2010 (k) Tesco, 2010 (l) Waitrose, 2010

Figure 5. Geo-demographic profiles of the main grocery retailers in London(Sources: Acxiom ROP, 2007,

2010)


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In exactly the same way as Figure 4 was calculated for the Yorkshire and Humber area, Figure 6

represents the proportions in Figure 5 divided through the proportions for the London sample

population. As the London region is dominated by the Multicultural group, Figure 6 provides a useful

way of picking out which groups the retailers are actually attracting to the their stores. For the

discounters, Figure 6 shows that the types of customers shopping at Aldi, (Constrained by

Circumstances), Netto (Blue Collar Communities) and Lidl (Multicultural) are in fact similar to

those in Yorkshire and Humber. Additionally, Figure 6 counteracts what appeared to be a large

percentage of Prospering Suburbs households shopping at Aldi in Figure 5. The graph shows that

proportions are in fact considerably lower than those for the London region as a whole. Similar to

Yorkshire and Humber, Asda and Morrisons do well in the Blue Collar Communities areas, whereas

Sainsburys and Tesco have a greater following from the Prospering Suburbs and Typical Traits

groups respectively. Finally, Figure 6 also reflects the importance of the City Living consumers for

both Waitrose and Marks and Spencer in London, as in Yorkshire and Humber. However, what is not

picked up in Figure 5, due to the small numbers, is the importance of the Countryside areas for

Waitrose.

Figure 6.Geo-demographic profiles of the main grocery retailers constrained by the base population ofLondon (Sources: Acxiom ROP, 2007, 2010; ONS, 2003).

4. Opportunities for growth

By using the information produced from the geodemographic analysis, we are able to start selecting

prospective sites for new Aldi stores in each of the two case study regions. The approach used is


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similar to that used by Wrigley and Clarke (1998), although by using geodemographic area types

instead of socio-economic groups we attempt to pick up a wider potential consumer base than simply

the D and E Jictnar socio-economic groups. Figure 7 represents the percentage of households in each

postal sector for the selected target audiences in each region. To do this we initially attached OA codes

to the Acxioms household level data (complete postcode) so that the OAC classifications could be

identified for all households. Then, we simply aggregated the number of households in each

classification up to post sector level using the postcodes and converted the values into percentages. The

locations of the current discount stores are also displayed to help find potential gaps for new

supermarkets. To ensure the identification of realistic sites, only those postal sectors with a minimum

population of 5,000 people were used in the analysis for Yorkshire and Humber and 7,000 people per

postal sector for London. This minimum threshold was more important for Yorkshire and Humber, as a

number of the more rural postal sectors in North Yorkshire have very small population counts.

Additionally, a higher minimum number was selected for London because the average population in

each postal sector is much higher. Furthermore, in densely populated areas such as London, people are

less likely to travel as far for grocery shopping (Birkin, Clarke and Clarke, 2002).

4.1 Yorkshire and Humber

As shown in section 3.1, Aldis customer base in the traditional low-income market of Yorkshire and

Humber is quite varied. This makes it somewhat difficult to select one particular group as a target

audience for further expansion. One could argue that Figure 4 illustrates the importance of the

Constrained by Circumstances group for Aldi; however, since the early 2000s these customers have

been declining due to the steady rise of the slightly more affluent Typical Traits and more recently the

Countryside customers (Thompson et al.,2010b). As this trend appears to be cyclical rather than a

reaction to the recession, it was decided that both the Typical Traits and Countryside classifications

would best serve any new Aldi supermarkets. In the context of future expansion, it is important that

Aldi locate in areas which best represent the companys current and future target audience.

Figure 7(a) demonstrates the percentage of households in each postal sector termed Typical Traits.

As stated, this group has arguably become Aldis primary consumer market so will become a key

demographic if Aldi is to achieve the targets in its ambitious expansion scheme. Figure 7(a) illustrates

the spatial pattern of this group, highlighting that the majority of these customers are situated in the

central parts of the regions large cities (Leeds, Bradford, Hull and Sheffield). Based on the current

distribution of Aldis stores, it would appear that the Typical Traits customers are relatively well

served. Nonetheless, there are still a number of postal sectors in Leeds, Wakefield and, surprisingly,

central Harrogate, that do not contain an Aldi store and yet still have high numbers of households in the

Typical Traits classification. In conjunction, Figure 7(b) exemplifies the percentage of households

which fall in the Countryside category. As one would expect, the Countryside map displays a

completely different spatial pattern to Figure 7(a). This is a result of the largely rural parts of North

Yorkshire and the tourist towns along the east coast. Unlike the other discounters, Aldi have a number

of stores along the east coast in towns such as Scarborough, Whitby and Hull, and the odd store in

market towns such as Selby. Netto and Lidl have steered clear of these zones, preferring instead to

locate in the inner-city areas of South Yorkshire and Hull.


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(a) Typical Traitsin Yorkshire and Humber (b) Countryside in Yorkshire and Humber

(c) Typical Traits in London (d) Constrained by Circumstances in London

Figure 7. Geodemographics by postal sector for Yorkshire and Humber and London in relation to the location of discount stores (Source: ONS,2003; GMAP, 2010; Acxiom 2010)


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Taking all of this into consideration, we suggest a collection of potential sites across the Yorkshire and

Humber region for the two separate store location strategies (low-income and middle-income). First of

all, Table 1 highlights those post sectors currently not being served by an Aldi store which also have an

above average percentage of households with Constrained by Circumstances and Typical Traits

(low-income). The post sectors are sorted in descending order by the total number of households in

both of the defined groups. This allows us to indentify which post sectors would have the greatest

demand for a new Aldi supermarket. As these areas represent the conventional Aldi customer base over

the last 5 years, it is expected that they would offer great potential for a new store. In addition, Table 2

exemplifies those post sectors in the region with an above average percentage of Typical Traits and

Countryside households (middle-income). This store location strategy is aimed at targeting the

growing number of Aldi customers in the Countryside group . As with Table 1, the post sectors are

listed in order from high to low based on the total number of potential customers. We recommend the

location of a new Aldi in any of these new sites; however for the purpose of this study we will consider

one from Table 1 in post sector LS13 3 (low-income strategy) and one from Table 2 in LS15 8 (middle-

income strategy).

Table 1. Potential post sectors for a new Aldi store based on traditional Constrained by Circumstances

and Typical Traits customers.

Post

Sector Location Population Households

Constrained by

Circumstances (% HHs)

Typical Traits

(% HHs)

CC + TT

Households

S6 4 Barnsley 13753 5907 17.4 44.2 3633

HU13 9 Hull 7553 3249 14.9 70.9 2788

LS13 3 Leeds 7653 3364 33.5 41.8 2534

LS29 8 Leeds 7354 3321 21.4 39.8 2033

HG1 2 Harrogate 7124 3195 13.1 47.5 1938

DN5 8 Doncaster 10411 4397 16.3 25.3 1830

LS13 1 Leeds 6792 2944 24.3 34.6 1733BD4 6 Bradford 5323 2274 27.2 41.3 1557

WF9 1 Wakefield 6819 2880 13.0 30.4 1252

HD9 6 Kirklees 6132 2697 15.1 30.2 1220

Table 2. Potential post sectors for a new Aldi store based on customers from Typical Traits and

Countryside customers.

Post


Countryside

(% HHs)

Typical Traits

(% HHs)

C + TT

Households

YO15 3 York 5869 2802 22.9 59.3 2303

YO14 9 Scarborough 5861 3353 32.7 32.7 2195

LS15 8 Leeds 9435 4132 5.1 41.3 1917BD16 1 Bradford 8202 3642 8.2 39.0 1718

HU17 0 Hull 9010 4210 6.5 33.7 1694

HD8 0 Kirklees 10220 3945 8.0 34.9 1691

WF3 3 Wakefield 8341 3385 10.3 35.7 1558

WF9 1 Wakefield 6819 2880 16.5 30.4 1352

LS25 1 Leeds 7659 3304 5.1 34.5 1307

S36 6 Barnsley 5805 2526 6.5 32.4 981


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4.2 London

London represents an area where the discounters have a good supply of stores, however their market

share figures still remain relatively low compared to other areas in GB (Figure 2). One may argue that

this is an indication of the high rental costs for retail space across the city. The standard model for a

discount store is one with low operational costs built on relatively cheap land (Colla, 2003). Therefore,

it is feasible that high rent prices could be eating into the deep discounters profits, whilst the biggercompanies such as Tesco and Sainsburys can afford to take on these additional costs. Nevertheless,

coupled with the increased cost of land is the potentially high level of revenue available for retailers in

London. More specifically, the population density and average household income in London are much

greater than the other regions across the country. Therefore, whilst it might seem that the discounters

have a large number of stores, in actual fact; London may offer huge potential for future growth (Mail

Online, 2008).

Figure 7(c) and (d) highlight the network of discount stores across the London region. Out of the three

deep discounters, Lidl are currently the most dominant in terms of the quantity of stores. Their

coverage of the region is much like their national expansion strategy (Figure 1), for the company havegone with blanket coverage across the entire city. Conversely, Netto, who only ventured into London

post 2003, have located their limited number of stores within the boundary of Inner London. This

strategy is the complete opposite of Aldi, who have actually restricted their stores to Outer London. In

terms of the opportunities for growth, this provides Aldi with a number of options for future locations.

In section 3.2, it was argued that Aldis primary consumers are living in areas described as Typical

Traits and Constrained by Circumstances. If we look at the distribution of these groups in Figure 7(c)

and (d) we can see that Aldis stores are persistently located in and around post sectors where these two

groups are prominent. Nevertheless, there are still a number of localities across the region, especially

south London where Aldi have no presence.

Therefore, as we have done in Yorkshire and Humber, we recommend the construction of two Aldi

stores in London. Table 3 exemplifies ten favourable post sectors across the region based on the

information given in Figure 7 (a) and (b). The post sectors listed have an above average number of

households living in both the Constrained by Circumstances and Typical Traits classifications.

Utilising the data in Table 3, we advocate, the location of a new store first of all in post sector SM5 1,

Sutton. Sutton represents the archetypal outer London site for an Aldi store as it has a high percentage

of households in both the Typical Traits and Constrained by Circumstances group. Furthermore,

Aldi currently only have one store in the surrounding area which means there is significant potential for

growth. The second site is in SE9 1, Greenwich. Again, this area has high levels of their core

consumer; however as Greenwich is closer to the city centre, if provides Aldi with the prospect of

establishing the company brand in the more central parts of the city.


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Table 3. Potential post sectors for a new Aldi store based on customers from Typical Traits and

Constrained by Circumstances customersin London.

Post


Constrained by

Circumstances (%HHs)

Typical Traits

(%HHs)

CC + TT

Households

RM12 4 Havering 15349 6298 18.02 58.56 9322

SE9 1 Greenwich 11127 4754 16.10 58.05 6423

E4 6 Waltham Forest 15042 6653 14.96 29.91 5652SM6 8 Sutton 11152 4820 11.05 43.68 4533

DA7 6 Bexley 11232 4653 19.44 42.78 4488

RM7 0 Havering 10240 4156 13.48 66.67 4467

RM5 3 Havering 10038 4061 27.92 52.60 4423

RM5 3 Havering 10038 4061 27.92 52.60 4423

SE9 3 Greenwich 12082 5092 38.38 19.70 3940

SM5 1 Sutton 12175 5047 33.62 3.40 2100

5. Predicting Revenues and market shares

Spatial interaction modelling has a long history of application in the context of retail systems and

consumer behaviour Such models are geographical because of their emphasis on the spatial

distribution of shopping trips as well as associated levels of sales, expenditures and incomes. The

central problem in all retailing studies involves describing the allocation of a person's expenditure

between competing stores or determining how much of a store's turnover derives from people who live

in a certain catchment area. It was shown by Wilson (1967) that Newtons gravity model could be

formulated using entropy maximising techniques and that the so-called shopping model was one

variant of a family of spatial interaction models that could be formulated, based on the constraints on

known information available to the modeller (Wilson, 1971). Wilson envisaged a system of residential

zones (origins) with populations having certain disposable incomes that would be spent on retail goods

in shopping centres (destinations) whose attractiveness would be determined by factors such as their

size (floor space) and range of goods. In addition to the origin and destination terms, a distance

function is required to capture the frictional effect of distance on shopping trips. The shopping model

therefore estimates the flow of cash that is exchanged for retail goods between residential areas and

shopping centres, recognising that the pattern of flows (meso state) is the aggregation of a large number

of individual trips (micro states). Moreover, the shopping model also includes a macro state constraint

insofar as the total revenue that arrives at each of the shopping centres in the retail system from origin i

should be the same as the total expenditure available in origin i, where i is one of n origin areas. This isequivalent to imposing a constraint at the production end of the flows in the system and hence shopping

models are referred to as production-constrained models.

A pedagogic guide to the theory and applications of singly constrained shopping models is provided by

Openshaw (1975) and models of this genre have been developed, enhanced and used by a number of

researchers since then including Pankhurst and Roe (1978), Birkin et al. (1996; 2002, 2010), Clarke

and Clarke (2001), and Clarke et al.(2002). There is no doubt that retail conditions in the real world


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present a number of important challenges for shopping models. Birkin et al.(2002, 2004, 2010) have

shown that in certain cases, the existing models are robust enough to deal with these challenges,

whereas in other cases, it becomes necessary to refine the models in order to capture more complex

types of consumer behaviour. In the context of the present paper, we want to use a classic singly

constrained shopping model framework to estimate the flows of expenditure between residential areas

and destination stores in each of our two systems of interest: Yorkshire and Humber and London. The

model equation, following Clarke et al. (2002) is as follows:

)exp( ijm

jmi

mi

mij dWAOS

m

where:mijS = expenditure by household type min residence zone iat destinationj

miO = level of consumer expenditure of household type min residence zone imiA = a balancing factor to ensure that:

jmi

mij OS

which is calculated as:

j ijm

j

mi

dWA

m

)exp(

1

jW = the attractiveness of destinationj

m = a parameter reflecting the perception of a destinations attractivenessby household type m

ijd = the distance between origin iand destinationj

m = the distance decay parameter for household type m

The interaction system for a retail model is comprised of three elements; demand, supply and interaction. Thedemand side is calculated as follows:

mi

mmi HeO

where:me = the average weekly grocery expenditure by household type m,

calculated from the Expenditure and Food SurveymiH = the number of households of type min residence zone i, from the 2001

Census of Population (updated using data supplied by GMAP Ltd.)

To ensure that the estimations produced by the spatial interaction model represent real expenditure

flows, the model was calibrated using actual data from the 2010 ROP. The survey records the

interaction between each household and the name and location of the food retail store which it uses.

This then enables us to calculate an accurate value for the distance decay effect of travelling to a

grocery store. Once calibrated, the model was then processed twice for each of the four locations. The

first run of the model estimated existing market share values for each of the retailers. On assessing the

distribution of revenue in each area, we then added four 8000 sqaure feet store to the model. The model


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was then run once more to calculate the performance of each supermarket and the overall effect they

had on market share.

5.1. Growth in Yorkshire and Humber

We first consider the performance of a new Aldi store in post sector LS13 3, Bramley, Leeds. The key

geodemographic statistics of this postcode indicate 41% of households are classified as Typical Traitsand 33% as Constrained by Circumstances (Table 1) Table 4 illustrates the performance of the

different retailers in Bramley both before and after the introduction of the new Aldi store. Currently,

Aldi have four stores in the vicinity which bring in an estimated market share of 1.98%, some 1%

lower than its national average of 3%. Netto are the strongest deep discounter with a 3% share, whilst

Morrisons and Asda dominate the market with shares of 26.87% and 25% respectively. Nonetheless,

Figure 8 (a) shows how despite the fact Aldi already have a reasonable presence in this area, there is

still adequate room for the introduction of at least one store. This is evidenced by the second set of

results in Table 1 and the new market share map in Figure 8 (b). It is clear to see from Figure 8 (b) that

the opening of a store in LS13 3 fills the gap previously not served in Figure 8 (a). The weekly revenue

of the new store is estimated to be 234,191, which would increase the overall market share in thedesignated area up to around 2.7%. This is a sizeable uplift, considering the new store is only 8,000

square feet in size. Moreover, at 29.27 sales per square foot, it would be Aldis top performing store

and 15th

out of all the areas stores.

Table 4. Market share figures for the proposed Aldi store in Bramley, Bradford

Retailer Market Share (%) Weekly Revenue () New Market Share (%) New Weekly Revenue ()

Aldi 1.98 647934 2.68 877572

Asda 25.03 8190699 24.85 8131325

Lidl 0.94 307442 0.93 305571

Co-op 13.39 4379396 13.28 4346777

Somerfield 1.09 354994 1.07 352567

M&S 1.01 329047 0.99 326697

Morrisons 26.87 8791513 26.67 8729052

Netto 3.07 1002836 3.04 995553

Others 4.80 1569491 4.76 1558183

Sainsburys 16.34 5345992 16.22 5309038

Tesco 5.50 1798280 5.45 1785284

Grand Total 100 32717624 100 32717624


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Next, we examine the success of a store opening in postcode LS15 8, Halton, Leeds. Once more, this

postcode is characterised by a high percentage of Aldis primary customers. However, compared to

LS13 3, this area is far more rural. Therefore, it offers the potential for Aldi to target their increasing

number of consumers which reside from the Countryside group. Prior to the new store, the market

share figures in Table 4 show that Aldi are doing relatively well. The companys market share is higher

than it was in Bramley at 2.3%, but Netto still remain the dominant discounter with 2.9% (Table 5).

Spatially, Aldis highest market share figures are contained to the south of the region in Castleford and

Pontefract, leaving a section of the population not served towards Rothwell, Richmond Hill and Halton.

If we look now at the results produced after the opening of the new store, we see a rise in revenue of

20% (951,777 to 1,148,343). This equates to a new market share figure of 2.78%, which is very

close to the national average. The areas with the most notable increase are those post codes in Barwick

and Kippax, and Sherburn-in-Elmet. However, by locating in the more rural parts of east Leeds, Aldi

face increased competition from the bigger Asda, Morrisons and Tesco supermarkets. This is evident

from the clearly restricted spread of market share in Figure 8(b) around Castleford where Aldi are

already doing well. Consequently, if Aldi were to go ahead and target the Countryside customer base,

it is advised that a 10,000 or 15,000 square foot store would be more appropriate to bring in customfrom further afield.

Table 5. Market share figures for the proposed Aldi store in Halton, Leeds


Aldi 2.30 951777 2.78 1148434

Asda 16.44 6794141 16.37 6762172

Lidl 2.22 916960 2.21 911744Co-op 11.10 4585769 11.04 4561732

Somerfield 4.84 1998069 4.82 1989471

M&S 1.99 824138 1.98 819945

Morrisons 17.10 7063037 17.04 7038796

Netto 2.91 1203240 2.90 1198187

Others 9.53 3939315 9.49 3918998

Sainsburys 16.56 6841153 16.49 6811196

Tesco 15.00 6198637 14.90 6155557

Grand Total 100 41316237 100 41316237


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(a) Current market share for Bramley catchment (b) Market share for Bramley catchment with new store

(c) Current market share for Halton catchment (d) Market share for Halton catchment with new store

Figure 8. Aldis market share figures before and after the introduction of new stores in Yorkshire and Humber(Sources: GMAP, 2010)


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5.3 Growth in London

As stated, despite the recent expansion in London, the capital is one of the deep discounters poorest

areas in terms of overall market share (Figure 2). Consequently, in the same way as section 5.2, we

consider the development of a new Aldi supermarket in the two different locations identified by the

geodemographic analysis in section 4. The first is in SM5 1, Sutton, south London. Statistically, this

catchment area in south London offers a great deal of potential for Aldi. From a demand side, there area wealth of Typical Traits and Constrained by Circumstances households located in Sutton and the

surrounding LADs. Additionally, Aldi are completely absent from the entire southwest of London,

leaving a huge gap in the market for future expansion. Figure 9 (a) highlights that the closest store to

the proposed site is over seven miles away in Croydon. This is surprising, considering Lidl have six

stores in the selected catchment and many more in the southwest as a whole. In terms of market share,

Sainsburys are the market leader with an estimated 24.5% followed by Asda (19.8%) and Tesco

(19.6%). Lidl are by far the most dominant deep discounter out-performing Aldi and Netto by 1.8%. If

we now consider the introduction of the new store, Table 6 predicts that Aldi would see an increase in

market share from 0.3% to 0.8%. In real terms, this equates to an estimated 265,918 a week, some

127,078 (47%) more than the existing store in Croydon is estimated to be generating. Figure 9 (b)

demonstrates the likely catchment area for the new store. This reinforces the point made earlier about

the huge potential in the catchment, for there is clearly enough space to build at least one more Aldi

store without the need to worry about cannibalization.

Table 6. Market share figures for the proposed Aldi store in Sutton, London


Aldi 0.3 139361 0.8 404759

Asda 19.8 10101695 19.6 10048402

Lidl 2.1 1050563 2.0 1044765

Co-op 4.2 2168012 4.2 2156938

Somerfield 6.3 3240720 6.3 3223498

M&S 4.3 2185815 4.3 2175623

Morrisons 3.8 1952847 3.8 1941381

Netto 0.3 154438 0.3 153450

Others 9.4 4807165 9.4 4783243

Sainsburys 24.5 12513811 24.3 12447799

Tesco 19.6 10018844 19.5 9966518

Waitrose 5.5 2807485 5.5 2794378

Grand Total 100 51140755 100 51140755


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(a) Current market share for Sutton area (b) Market share for Sutton area with new store

(C) Current market share for Greenwich area (d) Market share for Greenwich area with new store

Figure 9. Aldis market share figures before and after the introduction of new stores in London(Sources: GMAP, 2010)


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6. Conclusion

In this paper we havediscussed the history of the deep discount market food retail market, especiallyrelating to growth in the 2000s, a period not covered to date in the literature. Using a unique data

source for the social sciences in academia, the Acxiom data set, we have examined the changing spatialvariations in the regional shares of the food market held by the deep discounters in GB, and profiled the

customer base of the discounters in two contrasting regions. In the northern region of Yorkshire and

Humberside, an area where the discounters have a high market share, we have seen the importance of

the Constrained by Circumstances and Typical Traits geodemographic groups (using the UK ONS

OA geodemographic classification system). In addition, and more unexpectedly, we have also seen the

increasing importance of the Countryside group, showing the increased penetration of the discounters

into middle income groups and also the impacts of new store locations in market towns and small

suburban centres. Similar demographic groups provide the customer base for discount stores in

London. In this case, however, we also see the importance of the group multicultural which reflects

the high number of migrant communities now living in London. Using these customer profiles we then

looked for potential opportunities for further discount growth. This is important as Aldi in particular

has impressive growth plans for the UK. If they are to achieve their target of 10% market share such

spatial targeting is vital to support future retail site location activity. In particular, we identified 4 sites

for further analysis, additionally building and operationalising a spatial interaction model to estimate

the likely impacts on revenues and market share. This analysis showed that there is still potential for

future growth in markets such as Yorkshire and Humber which are perceived as being saturated for

discounter sites in both inner city and suburban areas. The proposed new sites in London show that

despite the large number of food stores in the capital, the discounters, in particular Aldi, still have a

great deal of room for future development. We suggest at least 10 potential sites in South west London

alone. This may provide a key region of potential growth if Aldi are to meet their target figure by 2020.

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