The market data package for regional data (RegioDaten) includes market potentials based on the 5-figure post code area level. The potentials are available for all product groups associated with the building materials industry. The data are prepared for use with geographic information systems as RegioGraph or PTV Map&Market, and are thus delivered in a format which is clear and easy to use.
Manufacturers and retail groups mainly use regional market potentials in the following areas:
The market data package RegioDaten has been calculated by B+L for over 15 years. It includes market potentials for 5-figure post code areas. The basis for the regional data is a detailed analysis of the total sales in the sub-segments (e.g. parquet, roofing etc.) These form the basis of the calculation of the per capita expenditure for each product group.
Next, the national distribution for each product group is investigated. The potentials for the wholesale, retail, and direct sales channels are calculated by means of detailed data analysis and surveys.
Then the data is processed for analysis on a regional level – this is done for 5-figure post code areas/local areas. The basis for this is the Residential-Construction-Renovation (RCR) index, which was first calculated by B+L Marktdaten GmbH around 15 years ago. This index takes into account not only the current levels of construction and renovation, but also income, the density of crafts/tradesmen, population density, the share of single family houses, and other factors which affect the segments. Due to its widespread use within the industry, and the variety of analyses undertaken, the RCR index can be constantly optimised and adapted for each particular product group.
The end result for the manufacturers is an easy to use set of data which reflects the market potentials at the 5-figure post code area level. For the post-code level areas it is recommended that the data are used in conjunction with a cartography program such as RegioGraph or PTV Map&Market. In this way all the regional analyses, as well as area planning, can be carried out quickly.
For Germany the potentials for over 85 product groups in the timber and building supplies industry are available (listed here).
|1. Step: Calculation of the total potential within the country||The basis of the regional data is a detailed assessment of the total sales in the sub-segements (e.g. parquet, doors, MDF, OSB etc.) These are based on a detailed analysis of the 20-50 most important producers in each segment. In turn, this forms the basis for the calculation of the per capita spending for each product group.|
|2. Step: Distribution Channels||Next, the national distribution for each product group is investigated. The potentials for the wholesale, retail, and direct sales channels are calculated by means of detailed data analysis and surveys.
|Distribution analyses are available for all product groups within the building materials and timber sectors. Using this data it is possible to calculate the separate potentials for wholesale and retail. In addition, sales data for the manufacturering level are available. These form the basis for the assessment of the sales areas. This data is available for all European countries.||
On the manufacturing level all potentials are given independent of the distribution channel for the manufacturer’s sales price.
On the wholesale level only those potentials which are distributed regionally via the wholesale sector are given. The potentials include the price margins, and therefore represent the sales opportunities for wholesale.
On the retail level only those potentials which are distributed via the retail sector are given. This includes both specialist retail shops as well as DIY stores. The potentials include the price margins and therefore represent the sales opportunities for retail.
If the B+L market potentials data is being mainly used to calculate the market opportunities in sales areas, then it is sensible to use the wholesale level data. If the data is additionally going to be used in area discussions and turnover agreements with retail, then all three levels should be used.
3. Step: Regional distribution of potentials
The data is then provided for the 5-figure post code level. This is based on B+L’s Residential-Construction-Renovation Index (Wohn-Bau-Renovier-Index (WBR))which was first calculated 15 years ago.
What is the RCR Index, and what can it do?
RCR (Residential Construction Renovation) is a statistical measure of the market potentials in the residential construction and renovation sectors. The index is based on statistical data for both local and 5-figure post code levels. The RCR index shows the positive and negative deviations from the average market potential in the respective countries.
Thus the RCR index can be used for:
How does the RCR model work?
The model on which the RCR is based, is a so-called ‘non-linear multiple regression model‘ (see Toolbox 1). This process looks for a relationship between the market potential and the statistical factors of influence. This relationship is held constant in the form of an equation, which is calibrated on a known control sample.
Toolbox 1: Multiple Regression Models
Statistical models which describe the connection between a variable which is to be explained and several factors of influence (factors) which are independent of one another. Here, a regression equation (the model) is calibrated on a set of data. For multiple, non-linear models like the RCR index, this is done using an iterative algorithm, i.e. a method which progressively approximates the correct result. The goodness of fit is described by a multiple correlation coefficient (R²). Whether an R² is significant for a given control variable or not is determined by a hypothesis test (F-Test). The result of the hypothesis test is with what probability (probability of error) a correct hypothesis has been proposed.
Market potential is of course dependent on a very large number of statistical factors of influence. However, not all of these factors can or should be taken into account in the calculation of the RCR. There needs to be a reduction of the data in order to keep the most important factors of influence. It is particularly important that several factors which exert the same influence are replaced by one single factor. The statistical process of this data reduction is called ‘factor analysis‘ (see Toolbox 2).
Toolbox 2: Factor Analysis
The method of data reduction by which classes of variables of influence are merged into factors. Factor analysis solves the Eigen value problem, and is needed in order to extract factors which are independent of one another. Factor analyses are used in order to ensure the independence of the input variables in a multiple regression model such as the RCR.
There are also factors of influence on to which others are statistically ‘attached‘, without needing to be assessed individually. This means that the actual factors which are assessed by the RCR include a multiplicity of other influences which are not explicitly listed.
The factors of analysis on which the RCR is based are:
The RCR model does not function additively in the way that a simple multiple linear regression model would. Thus, the RCR takes into account purchasing power factors and sales in the form of limiting factors for the construction cost data, in relation to the number of construction permits, which in turn is standardised according to the structure of the dwellings.
What the RCR cannot do
Exceptions do not prove the rule, but rather they make us aware of the limitations of the model. The goodness of a rule is first of all dependent on the number of exceptions. If this is low, that is the probability of error is small, then the rule is good. As with all statistical models, the RCR has a probability of error (see Toolbox 3). However, the value a=0.09 (in the F-Test), is low for a socio-demographic model. With the type of complex systems which the RCR describes, there can be no 100 % proof explanation.
Toolbox 3: Significance
In order to be able to make decisions based on statistical assessment, the significance level is an important measure. It indicates the probability that the acceptance of the null hypothesis is an incorrect decision. If, for example, the significance level is 5%, then the level of accuracy of the analysis is 95%.
A further limitation of the RCR is related to the type of input data, which include those to do with construction permits and relative construction costs. This means that residential extensions and renovation work, which do not require construction permits, are not directly included. However, indirectly there is a link, because as a rule, a high level of construction activity for which permits are required correlates positively with construction activity for which a permit is not required.
We can provide regional data for the following product groups. According to requirements, product groups can be chosen to contain a specialist product (level 3) or contain several products (levels 2 and 1).
|External ground covering||Concrete blocks||· Paving tiles, tiles
· Kerbstones and edging stones
· Paving stones
|Natural stones||· Natural Stones|
|Construction chemistry||· Construction chemistry|
|Building parts||Interior doors, incl. apartment front doors||· Whole glass doors (livingspace)
· Interior doors, Decoration (Foil, CPL, HPL)
· Interior doors, veneered
· Interior doors, varnish (varnished, paintable)
· Interior doors, solid wood
· Steel doors (Fire protection)
· Steel frames
|Windows||· Aluminium Windows
· Wooden windows
· Plastic windows
|Exterior doors and gates||· Exterior doors (house doors)
· Garage doors
|Fittings||· Window handles/latches
· Door handles
· Door locks, security
|Construction zinc||· Zinc guttering and down pipes
· Zinc facades, and zinc roofs
|Floor||Wood||· 2-layer parquet
· 3-layer parquet / wooden floor boards
· 3-layer parquet / ship floor oak
· Solid wood boards
· Solid wood parquet
|Textiles||· Needle felt
|Laminate||· Laminate flooring|
|Stone and ceramics||· Tiles (Floor and Wall)
· Natural stone
|PVC and linoleum||· Linoleum
· PVC heterogeneous (incl. Clicksystem)
· PVC homogenous
|Floor – accessories||· Mouldings, skirting board, underlay|
|Roofing||Roof tiles||· Roof tiles (clay)
· Roof tiles (concrete)
|Roofing (excluding tiles)||· Bitumen
· Roof shingles
· Roofing accessories
· Guttering and down pipes (excluding zinc)
|Insulation||· wood fibre insulation boards
· Mineral wool (glass wool, rock wool)
· Foam (EPS, XPS, PUR/PIR)
|Ironware||· Screws, nails, etc.
· Installation materials / flush mounting
· Switches / sockets
|Paint||· Emulsion paints
· Wood protectors
· Brush accessories
|Garden||· Gardening tools (hand)
· Gardening tools (Motorised)
· Garden sheds
· Garden furniture
· Stockade/ranch fencing, construction wood, toys
· Car ports
· Screening, fences
· Terrace flooring/decking (brown, yellow, green)
· Terrace flooring WPC
|Heating systems||· Underfloor heating
|Wood||Planes wood||· Planes wood (smooth-edged boards, planed wood frames)
· Solid wood battens
· Shaped wood
· Shaped wood facades
|Wood (incl. building timber)||· Window scantlings
· Solid construction timber
· Sawn hard wood timber
· Laminated wood (BSH)
· Sawn soft wood timber (squared wood, slats etc.)
|Solid wood boards||· 1- / 3-layer boards
· core boards
|Chipboard||· Work surfaces
· MDF / HDF
· Layered boards (CPL, HPL)
· Chipboards, coated with melamine (incl. APL)
· Chipboard, raw
|Air conditioning||· Air conditioning systems
· Portable air conditioning units
|Plumbing / Fittings||· Fittings
· Ceramics (sinks and WC)
· Plumbing (rear panel)
· Bath tubs and showers
|Civil engineering||· Irrigation and drainage
· Pipes and piping accessories
· Bulk solids
|Dry building materials||· Dry walling plus accessories
· Metal posts
· Plaster, mortar, cement
|Wall and ceiling panelling||· Panelling|
|Tools||· Protective work wear
· Electrical tools
· Hand tools
· Workshop fittings/furnishings
· Electrical tool accessories