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					       How to Increase Sales in Retail with Market Basket
                                    Marko Svetina, Jože Zupančič
                                              Merkur d.d.
                                    C. na Okroglo 7, Naklo, Slovenia

                       University of Maribor, Faculty of Organizational Sciences
                                  Kidričeva cesta 55a, Kranj, Slovenia

This paper investigates market basket analysis as an important component of analytical CRM in retail
organizations. It presents the case of the company Merkur d.d., Slovenia, a trading company dealing
in items for home improvement. The business intelligence system and market basket methodology used
in Merkur are described. Use of market basket analyses in Merkur is explained and analysed. In
particular, the paper addresses issues such as sales promotion campaigns, placement of goods in
retail stores, education of salespeople, offering system solutions and segmentation of customers. The
discussed topics are explained using practical examples and guidelines for adequate business
decisions. Our study demonstrated that market basket analyses are useful for Merkur, but a better
direct marketing strategy must be defined and implemented.
Keywords: business intelligence, market basket analysis, cross-sell, up-sell, related sales, retail,
merchandising, sales campaign, CRM

1 Introduction
One of the challenges for companies that have invested heavily in customer data collection is how to
extract important information from their vast customer databases and product feature databases, in
order to gain competitive advantage. Market basket analysis (also known as association rule mining) is
one of the data mining methods (Berry and Linoff, 2004) focusing on discovering purchasing patterns
by extracting associations or co-occurrences from a store’s transactional data. Several aspects of
market basket analysis have been studied in academic literature, such as using customer interest profile
and interests on particular features of the product for the product development and one-to-one
marketing (Weng and Liu, 2004), purchasing patterns in a multi-store environment (Chen et al., 2004),
or point at certain weaknesses of market basket analysis techniques (e.g. Vindevogel, Van den Poel
and Wets, 2005).
Market basket analysis has been intensively used in many companies as a means to discover product
associations and base a retailer’s promotion strategy on them. For example, in Limitedbrands, a family
of different fashion brands, the outcome of an extensive market basket analysis was the following
(Limitedbrands, 2004):
•     When different additional brands are sold together with the basic brands, the revenue from the
      basic brands is not decreasing, but increasing.
•     “Buy two, get three”sales promotion campaigns are very successful, if market basket analyses are
      used in order to determine the right products to be promoted.
•     “Buy a product, get a gift” sales promotion campaigns are successful, if a basic product and a gift
      are related and the basic product has high margin rate.
•     Based on market basket analyses, sets of products are defined and sold together with discount.

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•   Limitedbrands organizes internal competition in up-selling.
Our paper – a case study - presents and analyses the application of market basket analysis in a major
trade company in Slovenia.

2 The company Merkur, d. d.
Merkur, d. d. is a trading company (Merkur, 2005) that has for years ranked among the top companies
in Slovenia dealing in items for home improvement, home services as well as lawn and garden.
Merkur, d.d. has recently strengthened its position on the foreign markets through the supplies of
goods to industrial enterprises, and by the establishment of its own retail network abroad.
Merkur, d.d. is the mother company of Merkur Group. The Group consists of two Slovenian
subsidiaries and six subsidiaries abroad (Zagreb, Sarajevo, Skopje, Munich, Milan and Warsaw).
Besides that, the group also includes two offices (Moscow and Belgrade). Merkur plans to further
strengthen its position on the domestic market, spread its sales to the foreign markets, especially to the
markets of former Yugoslavia, and develop a high-quality range of products.
The company is organised in several large departments: Wholesale, Retail Sales, Sales to Foreign
Markets, Purchasing, Logistics and Supporting Services. Customers include construction companies,
trading organisations, installation companies, industrial enterprises, craftsmen and small entrepreneurs,
as well as end consumers. The company makes almost 60% of its sales revenues by selling goods
wholesale. To make the sales quick and efficient, the Wholesale Department has been divided into
four sales sub-divisions.
At present, Merkur has 38 retail sales centres in Slovenia. Specialisation increases the effectiveness of
sales, so two types of Merkur sales centres were developed: MERKURDOM focusing on ordinary
households, and MERKURMOJSTER intended for DIY (do-it-yourself) users. More information
about MerkurDom and MerkurMojster is available on Merkur internet site:
2.1 Characteristic figures of the company
The scope of the company Merkur, d.d. can be shown through the following figures:
The sales programme consists of about 200.000 active items (more than 120.000 items on stock),
divided into 5 sales programmes, 74 lines of goods, 720 groups of goods and 5.600 basic goods
classifications. Around 80% of sales are done with the top 12.000 items and 80% of stock is held on
the top 20.000 items.
The Purchasing Department issues more than 250.000 purchase orders with 1.200.000 items annually.
Merkur purchases goods from more than 2.000 suppliers. About 80% of purchases are done with the
top 200 suppliers.
Wholesale has business relations with more than 2.500 buyers - organizations. About 80% of
wholesale sales are done with the top 800 buyers. Wholesale issues approximately 400.000 invoices
with total 2.200.000 items annually.
Retail sells goods to 13.000 buyers / organizations and to about 500.000 end consumers. More than
70% of sales to end consumers are personalized with the Merkur loyalty card called the “Merkur Card
of Trust”. Retail issues 6.000.000 invoices with more than 20.000.000 items to end consumers
In the period from 1993 to 2004 Merkur achieved 19% average annual growth in revenues, 20%
average annual growth in net margin and 27% average annual growth in profit from operations. Today
Merkur is the sixth largest Slovenian company in revenues.

3 Data warehousing and business intelligence system in Merkur
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                                   MARKO SVETINA, JOŽE ZUPANČIČ

3.1 The history of DW&BI in Merkur
Merkur started to implement data warehousing and business intelligence (DW&BI) in 1999 with a
project called KAS (Commercial Analytical System) (Svetina, 2002). Before 1999, different analyses
and reports were performed in Merkur's transactional information systems, much of the analytical data
was held in Excel spreadsheets and Access databases. In the past, Merkur twice attempted to
implement DW&BI technology, but failed because proposed technology was still too difficult to use
for the majority of the users.
In 1999 Merkur started with a major business process reorganization and, therefore, better and new
business analyses were needed in order to make better decisions. The need for a DW&BI system
emerged, so the KAS project was given high priority. Merkur started to design analytical data models
for sales data and succeeded in integrating sales data from wholesale, retail and sales to foreign
markets in one unified data model.
The IT department proposed Microstrategy DW&BI technology, which was installed and tested in the
beginning of the year 2000. The technology was found to be appropriate and the decision was made to
implement DW&BI with Microstrategy solutions. The first power users (sales analysts) were educated
and the first KAS sales analyses were used in the decision-making process. In the beginning the ETL
(extract – transform – load) process was carried out on monthly basis, but by autumn of 2000 the
company started to perform ETL process daily. Later in the year 2000 the purchasing analytical
system was introduced as well.
In 2001, the data warehouse was upgraded with data on Merkur’s business plans. Sales and margins
were planned on a very low organizational level. The annual plan fact table has more than 1.000.000
records, so the salespersons’ performance is measured very accurately. Because the technology is easy
to use, the number of KAS users increased up to 100.
In 2002, the implementation of a very large and complex analytical module followed, containing
inventory data. The inventory levels of each item in every warehouse on a monthly basis is stored in
KAS and enables detailed inventory analyses and detection of critical items. Also, data on Merkur's
partner’s debts and liabilities was added to data warehouse, which enables accurate cash flow
Item price calculation elements and different prices were imported in KAS in 2003, so critical prices
can be detected and all inconsistencies eliminated. Many minor additions to the system were also
made over the last few years. All the time Merkur tries to use adequate analytical and data mining
methodologies in order to improve the whole system of business reporting.
From the DW&BI history we can see a controlled step-by-step development of the KAS system. Such
way of development gives opportunity for good definition and implementation of analytical contents
and enables Merkur to make many better business decisions. The KAS system brings Merkur an
important competitive advantage, which enables the growth of the company. Improved decision
making can be demonstrated through different measurable key success factors which are improving
constantly. Key success factors such as net margin, net margin per item, net margin per customer,
number of new customers and others are measured in KAS. These factors are always accessible for
KAS users and help them to make better decisions.
3.2 DW&BI technology
Since 2000 Merkur has used the Microstrategy DW&BI technology. Microstrategy provides ROLAP
solutions, which enable a step-by-step approach in data warehouse development and processing large
amounts of data. The data warehouse is implemented in an Oracle relational database. This means that
the same database technology is used in both transactional and analytical information systems.
Therefore, Merkur’s IT department can focus in one database platform instead of two or even more.
Oracle technology was used in Merkur before the implementation data warehouse was started, so the

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implementation of this technology was fast and smooth. In Merkur the following Microstrategy tools
(Microstrategy, 2005) are used:
•   MicroStrategy Intelligence Server is the heart of the BI system and provides reporting and
    analysis for the whole enterprise. This BI server provides the full range of BI applications through
    unified metadata and a single integrated server.
•   MicroStrategy Administrator consists of a suite of tools that provide the systems management
    environment for business intelligence. It maximizes uptime of BI applications. Its tools give an
    environment for developing, deploying, monitoring and maintaining of systems.
•   MicroStrategy Architect is a rapid development tool that maps the physical structure of the
    database into a logical business model. These mappings are stored in a centralized metadata
•   MicroStrategy Desktop is the business intelligence software component that provides integrated
    query and reporting, powerful analytics and decision support workflow with a desktop
    PC. MicroStrategy Desktop provides an arsenal of features for on-line analysis of corporate data.
    Reports can be viewed in various presentation formats, polished into production reports,
    distributed to other users and extended through a host of ad hoc features including drilling,
    pivoting and data slicing. The interface itself is customizable to different users' skill levels and
    security profiles. In Merkur, the Desktop solution is used by 13 power users (analysts).
•   MicroStrategy Web provides users a highly interactive environment and low maintenance
    interface for reporting and analysis. Using this intuitive HTML-only Web solution, users access,
    analyze and share corporate data through any web browser on any operating system.
    MicroStrategy Web provides ad hoc querying, quick deployment and rapid customizability,
    making it even easier for users to make informed business decisions. In Merkur, Microstrategy
    Web is used by 90 end users of KAS.
•   MicroStrategy Narrowcast Server is a proactive information delivery server that distributes
    personalized business information to users via email, pagers and cell phones. It includes an
    intuitive self-subscription interface that enables users to specify what information they want to
    receive, as well as when and how they want to receive that information. Narrowcast Server is
    becoming more and more important in Merkur because of its efficiency.
3.3 Merkur's DW&BI system today
Presently, KAS; Merkur’s DW&BI system, is five years old. The development of the system continues
constantly and there is still much content throughout the organization which must be implemented in
the BI system. The most important content to be implemented in the future are the following:
•   Integral data from Merkur’s finance and accounting system (the finance and accounting analytical
•   Relevant business data from Merkur’s subsidiaries
•   Data from Merkur’s human resources analytical system
•   Data from Merkur’s e-business analytical system
•   Data from Merkur’s logistic analytical system
Presently in KAS (Merkur Commercial Analytical System - KAS, 2005):
• 13 power users (analysts) and 90 end users; of both groups, 50 users have the ability and
    knowledge to set-up their own reports.
• Up to 30.000 reports are run on KAS on monthly basis.
• KAS consists of the following objects:
        o 137 tables
        o 433 attributes
        o 1.195 metrics
        o 5.611 reports
• Over 35 automated services are run on the Narrowcast Server

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                                       MARKO SVETINA, JOŽE ZUPANČIČ

The KAS system enables many sophisticated business analyses such as market basket analyses,
described later in this paper.

4 Market basket analysis and the used methodology
Market basket analyses are an important component of analytical system in retail organizations. There
are several definitions of market basket analysis. In a broader meaning, market basket analysis targets
customer baskets in order to monitor buying patterns and improve customer satisfaction
(Microstrategy, 2003). The following analytics can be used: attachment rates, demographic baskets,
brand switching, customer loyalty, core items, items per basket, in-basket price, revenue contribution,
shopper penetration and others.
In a narrower meaning, market basket analysis gives us the answer to the following question: which
goods are sold together within the same transaction or to the same customer? By analysing this
information, we try to find out recurring patterns in order to offer related goods together and therefore
increase the sales. We can track related sales on different levels of goods classifications or on different
customer segments. In this paper, the narrower meaning of market basket analysis will be taken into
consideration, focusing on the use of these analyses in Merkur.
It has to be noted that several other terms are also used to describe market basket analysis: related
sales, cross-sell, up-sell. The distinction between these terms is very unclear and the same terms are
often used in different meanings.
What can we gain from market basket analysis (Limitedbrands, 2004)?
•     We get the ability to learn more about customer behaviour.
•     We can make more informed decisions about product placement, pricing, promotion and
•     We can find out which products perform similarly to each other.
•     We can determine which products should be placed near each other.
•     We can find out which products should be cross-sold.
•     We can find out if there are any successful products that have no significant related elements.
The methodology of market basket analysis in Merkur is basically divided into two steps:
      1. Discover the selling documents (transactions) with the item, for which we want to perform
         market basket analysis. This logic is valid, if we want to carry out item-related market basket
         analysis. We can also perform good classification or even loyalty card holder-related market
         basket analyses, which will be shown later in this paper.
      2. Discover all the items in relevant selling documents and their selling quantities, prices,
         number of transactions and other relevant data.
As an example, an item related market basket analysis will be presented. We want to analyse sales
related to item ‘209525 Decorative lamp Saturn II’. In the first step we determine the selling
documents with this item. The partial result is shown in the table 1.
Further, the result of the first step is used as a filter in the second step, which results in a table with
items, sold together with item 209525. Items are (partially) shown in Table 2.

                                                                          No of Transactions
         Process   Org. Unit    Date               Document No
         207       220          18.11.2004         72588                           1
         207       220          19.11.2004         731009                          2
         207       220          19.11.2004         731050                          2

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          207        220            19.11.2004               731171                             1
          207        220            19.11.2004               73163                              1
          207        220            19.11.2004               73632                              1
          207        220            19.11.2004               73673                              1
          207        220            19.11.2004               73718                              1
          207        220            19.11.2004               73735                              1
          207        220            19.11.2004               73861                              1
          207        220            19.11.2004               73907                              1
          207        220            19.11.2004               73915                              1

                               Table 1. The first step of market basket analysis
In Table 2 we can see items sold together with item 209525. Items are sorted by number of
transactions descending. For every item the following measures are displayed:
-    No of Transactions means number of sales transactions when both items were sold together.
-    QtySold means the total quantity of the item, sold together with original item.
-    Revenue means the total sales revenue of the item.
-    Margin is the margin of the sold item.
-    % Margin to Total shows the percent of total margin considering all business transactions of
     item 209525.

                                                                    No of       QtySold Revenue Margin % to Total
Item description                                             UM                                               Margin
Total                                                               4.436       7.608,94 6.461.947 1.738.146 100,00%
                    SVETILKA,            2802 SATURN II
    209525                                                    KOS         1.098 1.352,00   1.003.318   237.943   13,69%
    851882                     3706 R6 1.5V            4/1    ZAV            94   100,00     37.083     18.454   1,06%
           VLOŽEK, BATERIJSKI           R 6 ULTRA 1.5V
    518894                                                    ZAV            57    67,00     17.353      7.877   0,45%
                     NAVADNI                       BL 4/1
           VLOŽEK, BATERIJSKI                 R-6/4 1.5V
    985150                                                    ZAV            57    58,50     18.037      8.121   0,47%
                     NAVADNI                   LONGLIFE
           VLOŽEK, BATERIJSKI    LR 6/AA MN 1500 PLUS
    172751                                                    ZAV            42    39,25     32.676      9.216   0,53%
                     ALKALNI                 1.5V BL/4
                               300X200X600X0.035 LDPE
    252871            VREČKA                                  KOS            39    40,00        667       292    0,02%
                                          TISK MERKUR
           VLOŽEK, BATERIJSKI          BBLR6 AA 1.5V
    186634                                                    ZAV            35    35,75     14.577      6.119   0,35%
                     ALKALNI                         BL/4
           VLOŽEK, BATERIJSKI 4906 LR6 1.5 V           4/1
    376298                                                    ZAV            35    33,75     31.781     15.789   0,91%
                     ALKALNI              HIGH ENERGY
                              ČESTITKA S KUVERTO KL
    222178       VOŠČILNICA                                   KOS            33    44,00      5.636      2.471   0,14%
                                     NL      SORTIRANO
           VLOŽEK, BATERIJSKI          LR 6 ZMAJ 1.5V
    923351                                                    ZAV            27    30,00     19.530      9.016   0,52%
                     ALKALNI                         BL/4
                                      AROMA MODER S
    202771           SVEČNIK      ČAJNIKOM        A1887,      KOS            24    24,00      8.580      2.344   0,13%
                                             A1497, A740
           VLOŽEK, BATERIJSKI     AM3-E4 (LR6,AA) 1.5V
    677951                                                    ZAV            23    24,00     13.000      5.695   0,33%
                     ALKALNI                         BL/4
           VLOŽEK, BATERIJSKI              4706 LR 6 1.5V
    828436                                                    ZAV            19    15,00     17.125      8.476   0,49%
                     ALKALNI           MAXI-TECH BL/4

                      Table 2. The final result of item related market basket analysis
The next part of market basket analysis is the qualitative evaluation of quantitative result. For
example, from our analysis we can see that item ‘209525 Decorative lamp Saturn II’ brought only
13.69% of total margin. This means that customers bought many other items together with the Saturn
II (4.436 – 1.098= 3.338 other items). From the other items we can see that the most common items
sold together with decorative lamp were different kinds of batteries. Of course, our lamp needs

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                                      MARKO SVETINA, JOŽE ZUPANČIČ

batteries and therefore it is very important that batteries are placed in the vicinity of lamps in retail
centre. Salespeople should be aware of these items correlations so they can trigger additional sales and
satisfy customers with a complete offer. We can also organize sales promotion campaign in which all
customers who bought the lamp will be offered batteries at a special price. There are many other
possibilities and business opportunities to use the results of market basket analysis in order to increase

5 Areas of market basket analyses
In Merkur different kind of market basket analyses are done. Analyses are adapted to various business
needs, and some of them are discussed in the following sections. In every section, the relevant
examples of analyses are presented and opportunities for business action discussed.
5.1 Marketing and sales promotion campaigns
When sales campaigns are prepared, promoted items must be chosen very carefully. The main goal of
a campaign is to entice customers to visit Merkur’s retail centre and buy more than they usually do.
Therefore, we must choose the right items and offer the right prices or other conditions. Margins on
promoted items are usually cut, therefore, additional non-promoted items with higher margins should
be sold together with promoted items. As we could see from the example in Section 3, item ‘209525
Decorative lamp Saturn II’ is quite adequate to be included in a promotion. Together with it many
other items are sold, so we can allow a lower margin of promoted item. Of course, there are some
other criteria for an item to be included in a campaign, such as:
 • Where on the item life cycle curve is the item situated?
 • What is our brand promotion policy?
 • Can we reach an agreement with the supplier (producer) to assure larger quantities and better
                                                                  No of QtySold Revenue     Margin     % to
                                                            Transaction                                Total
              Item description                           UM
                                                                      s                              Margin
 Total                                                              741 758,46 30.524.045 6.682.658 100,00%
212381          STROJ, PRALNI                WA 62111    KOS         352   316,00 26.334.801    5.774.785   86,41%
                                           200X50 MM
279418      SPONA, MIZARSKA                              KOS           4     2,00        917         584    0,01%
                                           ART. 11025
286345                           CALGON          500 G   KOS           4     4,00       2.263        452    0,01%
                    ZA PRANJE
            STROJ, POMIVALNI
467503                                       GVI 6530    KOS           4     3,00     331.654     68.131    1,02%
428243              GIRLANDE        Z ZVEZDICAMI 2 M     KOS           4     4,00        530         251    0,00%
                                        A4 KLASIKA NL
374957      VREČKA, DARILNA       264X136X327 MM Z       KOS           4     3,00        555         233    0,00%
                                        60 W G-95 OPAL
668844ŽARNICA, NAVADNA, E 27                             KOS           3     3,00       1.759        871    0,01%
618793ŽARNICA, NAVADNA, E 14     60 W SVEČKA BISTRA      KOS           3     3,00        325         155    0,00%
                                      STAND.FILM 15/10
201084          TRAK, LEPILNI        Z ODVIJALCEM ZA     KOS           3     3,00        197          73    0,00%

           Table 3. Market basket analysis of item ‘212381 Wash machine WA 62111’
If we want to promote an item with a low related sales share, then a normal margin has to be
calculated, unless there is some other reason to promote a particular item (for example we expect
higher sales and margin in future). An example of an item with low related sales share is presented in
Table 3. From Table 3 we can see that item 212381 represents over 86% of total margin of
transactions with it.

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Further, sales promotions managers in Merkur use several sales campaign analyses. Sales promotion
market basket analysis is one among them (see example in Table 4).
               No of                      % to Total                % to Total               No of Items
               Transactions Revenue       Revenue      Margin       Margin       % Margin    Sold
Total                185.719 271.956.654       100,00%   73.018.461      100,00%      26,85%         24.440
Promoted items        48.670   83.295.671       30,63%   18.162.954       24,87%      21,81%             62
Other items          137.049 188.660.983        69,37%   54.855.507       75,13%      29,08%         24.378

                           Table 4. Sales promotion market basket analysis
In table 4, data from a New Year’s promotion campaign is shown. The: campaign was done through
public advertising. Paper catalogues of promoted items were sent to households, there were also
commercial spots on TV and radio, and advertisements in newspapers. Because of advertising a certain
number of customers came in Merkur retail centres in order to buy the promoted items. Additionally,
they also bought many non-promoted items (70% opposed to 30% of revenues and 75% opposed to
25% of margins) with much higher % of margin (29,08% opposed to 21,81%). This means that
promoted items generated sales of non-promoted items.
There are also many possible ways for organizing campaigns using direct marketing tools for the
interaction with Merkur loyalty card holder. This issue will be discussed in Section 5.5.
5.2. System solutions offering
Market basket analyses are also used to combine more items in a set or a system, because the majority
of customers are interested in buying and using them at a time or in a short period of time after the
purchase of a particular item. By designing sets and systems of related items a company can increase
sales and also cut down costs of sales transactions, so that various discounts can be offered to
customers. This results in a typical win-win situation. A retailer must know the needs of customers and
adapt to them. Market basket analysis is one possible way to find out which items can be put together
in sets and systems. Table 5 presents an analysis which was done in Merkur in order to find out the
sales relations between different groups of goods.

                                              No of          Revenue        Margin     % to Total Margin
Group name                              Transactions
Total                                        53.829       228.734.766    61.057.940               100,00%
NAPA                                         18.065        70.172.570    20.620.684                33,77%
ELEMENTI ZA VGRADNJO                             681       46.996.913    10.870.719                17,80%
HLADILNIKI                                       310       22.293.946     5.437.153                 8,90%
POMIVALNI STROJI                                 224       21.161.910     5.248.183                 8,60%
ŠTEDILNIKI                                       119        8.559.003     2.063.390                 3,38%
DEKORATIVNA SVETILA                              814        3.725.552     1.462.072                 2,39%
POMIVALNA KORITA                                 262        4.237.871     1.389.118                 2,28%
ENOROČAJNE BATERIJE                              279        3.530.627       973.490                 1,59%
PRALNI STROJI                                     65        4.073.453       958.491                 1,57%
KOPALNIŠKA OPREMA                                583        2.013.063       654.891                 1,07%
SESALNIK                                         679        1.787.783       576.873                 0,94%
POSODA                                           520        1.383.090       527.888                 0,86%
          Table 5. Classification Group ‘Kitchen extractor hood’ market basket analysis
In Table 5 we can see groups of goods which were sold together with the group ‘Kitchen extractor
hood’. In the related groups are also different kitchen appliances like refrigerators, dish washers,
kitchen-ranges, taps, dishes etc. This means that Merkur should design and offer the customers
different kitchen systems. These systems should include kitchen furniture, major and small kitchen
appliances and kitchen utensils. Such a system should be displayed in one place in a retail centre

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                                    MARKO SVETINA, JOŽE ZUPANČIČ

where customers could choose from whole system solutions to just several parts (items) of these
5.3. Placement of goods in retail stores
Market basket analyses give retailer good information about related sales on group of goods basis. As
we can see in Table 5, the majority of kitchen appliances groups are related. Customers who buy a
kitchen appliance often also buy several other kitchen appliances. It makes sense that these groups are
placed side by side in a retail centre so that customers can access them quickly. Such related groups of
goods also must be located side-by-side in order to remind customers of related items and to lead them
through the centre in a logical manner.
In Merkur, two basic concepts of retail centres are used: MerkurDom specialises in high-quality items
for home improvement and garden, MerkurMojster specialises in high-quality products aimed at DIY
users, craftsmen, and entrepreneurs. Centres are also classified by size as small and large centres. For
each of these concepts, standardized placement plans were developed. Market basket analyses
represent one segment of tools for decision making considering placement of goods. It can show us
where we should change the placement of goods. After the change we can measure the business effects
of the change.
5.4. Education of salespeople
The interesting results of market basket analyses must be presented to the salespeople in retail centres,
because the employees must be aware of them and they should use them in the process of selling.
Every salesperson has some knowledge about related items from his or her experience. With market
basket analyses we can structure this knowledge and use it to teach less experienced personnel.
Merkur invests a lot in education of salespeople through both internal and external sources.
Knowledge from market basket analyses is widely used in internal education.
5.5. Segmentation of customers
As mentioned in Section 1.1., more than 70% of sales to end consumers are personalized with the
Merkur loyalty card called “Merkur Card of Trust”. This data enables us to answer the following
question: What did consumers who bought item (group) X in period 1, buy in period 2? If we identify
customers who bought item X today, we can anticipate what they will buy, for instance, in next three
months, and we can advertise them the right products. A typical example is shown in Table 6.
We analysed loyalty card holders who bought ceramic tiles in the period from April to June 2004. In
Table 6 we can see product groups which were bought by the same card holders in the period from
July to November 2004. They bought different bathroom and kitchen accessories and central heating
elements. It would be very useful, if Merkur organized a targeted marketing campaign for this specific
group of customers in July 2004 and promoted these products.
There are many other possibilities and opportunities in Merkur to use loyalty card-based market basket
analyses as a support tool for direct marketing campaigns. Merkur usually organizes non-targeted
common campaigns, in which the majority of Slovenian households are included. But lately Merkur
also started to implement direct marketing methods and therefore an effective data warehouse and
business intelligence system is essential. This helps many interesting marketing ideas to be

                                                   No of          Revenue          Margin     % to Total
SkB naziv                                    Transactions                                       Margin
Total                                             41.034       125.884.243      33.552.223     100,00%
DEKORATIVNA SVETILA                                 1.061        5.563.686       2.236.051        6,66%
KOPALNIŠKA OPREMA                                     610        5.826.497       1.577.181        4,70%
ENOROČAJNE BATERIJE                                   353        5.098.332       1.377.387        4,11%

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KERAMIČNE PLOŠČICE                                    430       3.924.416      1.254.167         3,74%
KOPALNIŠKO POHIŠTVO                                   142       4.825.302      1.219.398         3,63%
STAVBNO POHIŠTVO                                      276       4.900.481      1.092.807         3,26%
HLADILNIKI                                             46       3.627.812        956.408         2,85%
ELEMENTI ZA VGRADNJO                                   46       3.716.342        878.316         2,62%
KOPALNIŠKI DODATKI                                    869       2.705.612        806.550         2,40%
RADIATORJI                                            131       2.290.027        798.374         2,38%
SANITARNA KERAMIKA                                    235       2.228.676        756.650         2,26%
POSODA                                                535       1.716.342        739.033         2,20%

                   Table 6. Loyalty card member based market basket analysis

6 Conclusion
The practice in Merkur proves that market basket analysis is a very useful for marketing campaigns,
good placement definition and education of sales personnel.
Merkur uses market basket analysis throughout the promotion campaign process. When a sales
promotion is prepared, market basket analysis is used to define the right products and the right prices
for the campaign. Related non-promoted items are also defined in order to place them in the vicinity of
promoted items and therefore increase sales. When sales promotion finishes, its results are carefully
analysed in order to discover opportunities for next promotions.
Merkur widely uses market basket analyses to manage the placement of goods in retail centres.
Related products and product groups are placed together in such a manner that customer can logically
find items he/she might buy.
The findings of market basket analyses are an important part of the process of teaching the salespeople
of Merkur. Sales personnel must be aware of related products in order to increase satisfaction of
customers and intensify sales.
Market basket analyses are just a part in the holistic approach to the execution of marketing
development strategy in Retail in Merkur. The analytical process is integrated in other marketing
activities and analysts are an important part of Merkur marketing development team. Team work is
crucial for successful use of such analyses.
Beside of the organization of the Merkur marketing process, a capable DW&BI system is needed. The
BI system must have good performances when processing large amount of data. It also has to be
scalable and flexible, but, above all, the BI system must be user-friendly so that different marketing
specialists can use it without any problems. Fortunately, Merkur’s KAS is such a system.
But there is still much work to be done. We demonstrated that market basket analysis in Merkur can be
done and that it brings useful results. In the future a working direct marketing strategy must be
developed based on data already available in KAS. Then an organization and information systems for
efficient execution of this strategy have to be established.

7 References
Berry, M.J.A., Linoff, G.S.: Data Mining Techniques: for Marketing, Sales and Customer Relationship
    Management (second edition), Hungry Minds Inc., 2004

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                                    MARKO SVETINA, JOŽE ZUPANČIČ

Chen, Y.-L., Tang, K., Shen, R.-J., Hu, Y.-H.: “Market basket analysis in a multiple store
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Limitedbrands: Achieving Greater Efficiencies with Market Basket Analysis, Microstrategy World
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Microstrategy: Business Intelligence in the Retail Industry, Microstrategy World 2003 Conference,
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