How much money do you intend to spend on vacations this year? How much rent do you pay per month and what do you set aside for savings, clothes, food and drink and leisure activities? Of course, the answers to these questions are very diverse – depending on life situation, personal preference and priorities – and naturally, also on income. Purchasing power, that is, nominal disposable net income, has been undergoing positive development in Germany for quite some time (more on this here and here). A stable job market and rising salaries in many sectors mean that consumers have more money, in purely mathematical terms at least – that is, providing the price of consumer goods and services does not increase. However, this development is not equal across all regions of Germany. Location dictates how far from the national German average purchasing power will be. What does this means for the sales potential of retailers and service providers in the various urban and rural areas? Do online vendors perhaps hold an advantage in some areas?
Munich – When we think of Munich, many of us immediately think of Oktoberfest, beer-induced jollity and FC Bayern. The city is known for its location on the river Isar, but also for the particularly high purchasing power of its inhabitants. According to the general purchasing power index, the per capita figure for the average Munich inhabitant stands at 136 points, which is a good third more disposable income than the national average – and given the high rents in the city, this is not only needed for luxury items, but is an absolute necessity for being able to afford to live there at all. Hamburg cannot quite match Munich’s value, although the general purchasing power index gives the per capita figure as 109 points, which is still above the national average. These figures are taken from the GfK statistics for purchasing power in Germany for 2017. The figures are defined as the sum total of the net income of the population related to the place of residence. Along with income from freelance and employed work, financial earnings such as state transfer payments including unemployment benefit, child benefit and pensions are added to purchasing power. The data is available for all German urban and rural areas as well as all parishes and postal codes. The published indices show the amount in percentage terms by which one region is above or below the national average for Germany (= 100). Three urban and three rural areas were selected and compared for the current Compact FocusTopic of the GfK Verein: Hamburg, Berlin and Munich and the neighboring rural districts of Uelzen, Barnim and Rosenheim.
Germany’s capital city of Berlin comes last of the selected cities. The Berlin purchasing power index stood at 92 points for 2017 – this means that, on average, Berliners have to make do with 48%* less income than a person living in Munich. Out of the rural regions, the eastern part of Germany comes in at below average figures. Barnim in Brandenburg stands at 93 points, but manages to be just above Uelzen in the North. To the south east of Munich, the figures are markedly higher: in Rosenheim, inhabitants enjoy an above average 108 points on the purchasing power index.
How do the respondents manage their net income? On average, how much is available to be spent on different product groups? A glance at the range-related purchasing power index reflects the average amount of money people in each region have available to invest in different product categories. GfK Geomarketing calculates the range-related purchasing power for numerous product groups and individual item ranges from the consumer panel data and income and consumer random sampling figures published by the German Statistical Office for the different federal states. The process combines anonymized and aggregated information on consumer spend with micro-geographical data (more on this here). In this way, the demand potential for diverse retail ranges can be established by region. How high this is will depend on what consumers can, must and wish to spend (respectively, income, product availability at particular prices and personal preferences).
In all three product groups selected – food and drink, clothing and consumer electronics – Munich takes top spot, followed by Hamburg. For food and drink and clothing, Rosenheim comes third after the two cities, yet for consumer electronics, it registers below average purchasing power. Overall, in a regional comparison, minor variations become apparent in the urban-rural differential. Hamburgers have 11% more money to spend on food and drink than the national average, whereas those living in Uelzen have 5% less. Munich residents can – and perhaps have to – spend a quarter more on food and drink than those living in Rosenheim, who come right in the middle of the national average. Only in Eastern areas is there virtually no difference between urban and rural areas: Berlin achieves an index value of 98, which is only just above the figure for the rural district of Barnim. A similar picture emerges for range-related purchasing power in respect of clothing: Hamburgers (index 110) can spend an average of at least one fifth more on looking cool, buying a new outdoor outfit or comfortable leisurewear than their neighbors in rural Uelzen (index 89). For Munich’s population (index 140), the figure is even around one third above the more rural Rosenheim (index 107). Here, too, the eastern part of Germany is an exception: Berlin and Barnim inhabitants both have similar budgets for clothing – and with 89 and 87 index points respectively, they are once again below the national average. In terms of consumer electronics, the picture is the same: in this instance, Berliners can count on a similar budget to consumers in the area around Barnim (index 114 vs. 112). The differential between Hamburg and Uelzen is wider, with range-related purchasing powers of 125 and 102 index points respectively. However, the urban/rural differential is at its greatest in southern Germany: Munich residents have a good third more disposable income (index 126) to spend on smartphones, flat screen TVs and other electronic appliances than those living in rural Rosenheim (index 93).
The channels we use to buy food and drink, clothing and consumer electronics depend as much on the local infrastructure as the time we may have available. Is there still time to go shopping when we leave work, or are the shops already shut? Is it possible to shop nearby or does the weekly shop involve a half-hour drive? Anyone wishing to free themselves from the shackles of shop opening times or local availability could choose to shop online. Germans are using online shopping to varying degrees, depending on the range: for food and drink, there is not much enthusiasm for online shopping at the moment: the data collected by the GfK Consumer Panels show that the share of online purchases in the period from July 2016 to June 2017 was around 1%. For clothing, the figure for the same period is already far higher at 17%. The majority of online purchases, however, come in the consumer electronics sector, which includes music and data storage media (37% share). The sales channel on which retailers and service providers should be focusing depends to a great extent on the individual regions, as a comparison between the purchasing power and online potential for the various product groups shows.
The city of Hamburg trumps nearby rural Uelzen not only in terms of overall range-related purchasing power (across all sales channels including online), but also for its online potential for individual product groups. The online potential index for food and drink, clothing and consumer electronics is above the national average in every case, as well as for neighboring rural areas. For food and drink, the index value is particularly high at 116. This means that, in general, Hamburgers are not only able to spend a great deal on food and drink, but that they often do so online at an above average rate. The reasons for this are as much attributable to the suppliers as to the consumers: Firstly, there are more online suppliers for food and drink in towns, cities and high-density population areas and, secondly, perhaps there are more inhabitants that place a value on such services in these areas – possibly, because they are open to innovation or they simply don’t have the time or inclination for wearisome shopping expeditions. In the more rural regions, the situation is different: Here, the online potential index for Uelzen stand at just 92 points. This gives Uelzen’s inhabitants an average of one quarter less to spend on food and drink online than their neighbors in Hamburg. Moreover, in total, they have around 16%* less money for food and drink than Hamburg inhabitants.
Perhaps Hamburgers are able to spend the time saved by quickly buying food and drink online on shopping for clothes. After all, for fashion fans Hamburg offers a huge variety of shopping opportunities, ranging from chic boutiques, to quirky alternative shops and shopping colonnades. Not only this, but Hamburg inhabitants have the purchasing power required to make use of all these opportunities: With an index rating of 110 points, their clothing budgets are above average, although the online potential index is only just above the national average. In Uelzen, people tend to have less disposable income to spend on shoes, outfits and suits (index 89) than in Hamburg, but here, the online potential index stands at 96, which is seven points above the purchasing power index for this product category. Presumably, Uelzen residents tend to overcome any supply gaps in store by making online purchases. The online potential is even higher when it comes to consumer electronics: the index figure of 101 shows that for this product category, rural Uelzen has the highest value, even if it still lags behind Hamburg. In Hamburg, 15% more is spent online for consumer electronics than the national average. Despite this, Hamburgers still seem to like going to the shops to buy laptops, smartphones, TVs etc., since the purchasing power for this product category is once again a great deal above the average than the online potential.
Berlin – a city with just under four million inhabitants, a subway network extending around 150 km and a great many tourist attractions. Not far away is Barnim, with some 180,000 residents, a whole host of forestland and a small tourism sector. At first sight, the two places do not have much in common, although they are only an hour’s drive apart. However, they are quite close, not only in terms of geography, but in relation to purchasing power and online potential. For two of the three product groups purchasing power is below average for both Berlin and Barnim, however for consumer electronics, residents of both areas dig deep into their pockets. The only difference is that those living in the capital buy food and drink online more often than their rural counterparts – and this, despite the fact that Berlin has such a great number of shopping opportunities. Evidently, not even the comparatively long opening hours of the stores and countless kiosks that stay open late selling tobacco, drinks, newspapers, magazines and food seem capable of changing this. Conversely, in Barnim, the search for an open shop is often in vain, apart from gas stations. However, at 90 index points, the online potential for food and drink remains particularly low. On the other hand, the online potential for clothing, at 94 points for Berlin and 95 points for Barnim, is closer to the national average than the range-related purchasing power (taken over all the available sales channels) for this product group. The picture for consumer electronics differs: index points of 108 and 107 respectively for Berlin and Barnim mean that both are just above the national average.
Anyone looking at the online potential of Munich and the nearby rural idyll of Rosenheim will immediately spot a marked urban/rural differential. As is the case for purchasing power, the city folk in the south of Germany have their noses in front when it comes to online shopping – and this applies to all three product groups. Online food and drink retailing, in particular, is enjoying the benefits of hungry Munich inhabitants, who already spend 42% more on food and drink on the internet than the average for Germany. Compared with Rosenheim, the online budget for food and drink of Munich’s residents is still at least a third higher. As in Hamburg, the reasons for this are presumably equally attributable to the suppliers as well as to consumers. Munich’s residents have a far greater choice of online food and drink than their neighbors in rural Rosenheim. In addition, the demographics are very different: Munich is the location of choice for a great many young single people, who are generally open to
innovations and are at home with digital life. Conversely, in Rosenheim, there are far more families with children, using traditional shopping methods more often than not, including their weekly shop. City dwellers more often buy clothes and consumer electronics in shops. Although the online potential index for both product groups is above the national average, in terms of the range-related purchasing power index, the values are nowhere near the same. On the other hand, there is hardly any difference between online potential and purchasing power for clothing and consumer electronics in Rosenheim.
How do retailers today decide which groups of enthusiastic consumers to target? In the cities selected, as a rule, general purchasing power is often higher than in the neighboring rural areas – this speaks for a stronger commercial focus on high population density areas. However, some rural regions are well equipped to keep pace with the more populous areas when it comes to budgets for individual product categories. Not least is the consideration of which customer groups can be encouraged to make online purchases. The major towns and cities offer particularly good sales opportunities for food. However, in the more rural areas, retailers should not discount their online strategy, as the example of clothing shows. This is where online can help to close product availability gaps in store. In conclusion: there is no easy answer to the question of the ideal sales market – in terms of high purchasing power and new location. Closer scrutiny is well worth the effort.
* Calculation of comparative differential between purchasing power and online index in percent: Index1 / Index2 * 100 – 100
Data source: GfK GeoMarketing; Contact person Christian Reppel, (Information about methodology are in the downloadcharts above)
Responsible for the article and contact person for queries about Compact: Claudia Gaspar. (e-mail to firstname.lastname@example.org).