How to Increase Sales in Retail with Market Basket Analysis

Transcription

1 How to Increase Sales in Retail with Market Basket Analysis 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 Abstract: 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. 418

2 HOW TO INCREASE SALES IN RETAIL WITH MARKET BASKET ANALYSIS 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: 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 active items (more than items on stock), divided into 5 sales programmes, 74 lines of goods, 720 groups of goods and basic goods classifications. Around 80% of sales are done with the top items and 80% of stock is held on the top items. The Purchasing Department issues more than purchase orders with items annually. Merkur purchases goods from more than suppliers. About 80% of purchases are done with the top 200 suppliers. Wholesale has business relations with more than buyers - organizations. About 80% of wholesale sales are done with the top 800 buyers. Wholesale issues approximately invoices with total items annually. Retail sells goods to buyers / organizations and to about 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 invoices with more than items to end consumers annually. 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 419

3 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 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 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 management. 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 420

4 HOW TO INCREASE SALES IN RETAIL WITH MARKET BASKET ANALYSIS 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 repository. 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 , 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 system) 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 reports are run on KAS on monthly basis. KAS consists of the following objects: o 137 tables o 433 attributes o metrics o reports Over 35 automated services are run on the Narrowcast Server 421

5 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 profitability. 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 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 Items are (partially) shown in Table 2. No of Transactions Process Org. Unit Date Document No

6 HOW TO INCREASE SALES IN RETAIL WITH MARKET BASKET ANALYSIS Table 1. The first step of market basket analysis In Table 2 we can see items sold together with item 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 No of QtySold Revenue Margin % to Total Item description UM Transactio ns Margin Total , ,00% SVETILKA, 2802 SATURN II DEKORATIVNA NA BATERIJSKE VLOŽKE KOS , ,69% VLOŽEK, BATERIJSKI R6 1.5V NAVADNI 4/1 ZAV , ,06% VLOŽEK, BATERIJSKI R 6 ULTRA 1.5V NAVADNI BL 4/1 ZAV 57 67, ,45% VLOŽEK, BATERIJSKI R-6/4 1.5V NAVADNI LONGLIFE ZAV 57 58, ,47% VLOŽEK, BATERIJSKI LR 6/AA MN 1500 PLUS ALKALNI 1.5V BL/4 ZAV 42 39, ,53% X200X600X0.035 LDPE VREČKA TISK MERKUR KOS 39 40, ,02% VLOŽEK, BATERIJSKI BBLR6 AA 1.5V ALKALNI BL/4 ZAV 35 35, ,35% VLOŽEK, BATERIJSKI 4906 LR6 1.5 V 4/ ALKALNI HIGH ENERGY ZAV 35 33, ,91% ČESTITKA S KUVERTO KL VOŠČILNICA NL SORTIRANO KOS 33 44, ,14% VLOŽEK, BATERIJSKI LR 6 ZMAJ 1.5V ALKALNI BL/4 ZAV 27 30, ,52% AROMA MODER S SVEČNIK ČAJNIKOM A1887, KOS 24 24, ,13% A1497, A740 VLOŽEK, BATERIJSKI AM3-E4 (LR6,AA) 1.5V ALKALNI BL/4 ZAV 23 24, ,33% VLOŽEK, BATERIJSKI 4706 LR 6 1.5V ALKALNI MAXI-TECH BL/4 ZAV 19 15, ,49% 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 Decorative lamp Saturn II brought only 13.69% of total margin. This means that customers bought many other items together with the Saturn II ( = 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 423

7 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 sales. 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 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 prices? No of QtySold Revenue Margin % to Item description UM Transaction Total s Margin Total , ,00% STROJ, PRALNI WA KOS , ,41% SPONA, MIZARSKA 200X50 MM ART KOS 4 2, ,01% SREDSTVA, POMOŽNA ZA PRANJE CALGON 500 G KOS 4 4, ,01% STROJ, POMIVALNI VGRADNI GVI 6530 KOS 4 3, ,02% GIRLANDE Z ZVEZDICAMI 2 M KOS 4 4, ,00% A4 KLASIKA NL VREČKA, DARILNA 264X136X327 MM Z KOS 4 3, ,00% VRVICO ŽARNICA, NAVADNA, E W G-95 OPAL SOFTONE-GLOBE KOS 3 3, ,01% ŽARNICA, NAVADNA, E W SVEČKA BISTRA KOS 3 3, ,00% STAND.FILM 15/ TRAK, LEPILNI Z ODVIJALCEM ZA PISARNE KOS 3 3, ,00% Table 3. Market basket analysis of item Wash machine WA 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 represents over 86% of total margin of transactions with it. 424

8 HOW TO INCREASE SALES IN RETAIL WITH MARKET BASKET ANALYSIS 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 Transactions Revenue % to Total Revenue Margin % to Total Margin % Margin No of Items Sold Total ,00% ,00% 26,85% Promoted items ,63% ,87% 21,81% 62 Other items ,37% ,13% 29,08% 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 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 ,00% NAPA ,77% ELEMENTI ZA VGRADNJO ,80% HLADILNIKI ,90% POMIVALNI STROJI ,60% ŠTEDILNIKI ,38% DEKORATIVNA SVETILA ,39% POMIVALNA KORITA ,28% ENOROČAJNE BATERIJE ,59% PRALNI STROJI ,57% KOPALNIŠKA OPREMA ,07% SESALNIK ,94% POSODA ,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 425

9 MARKO SVETINA, JOŽE ZUPANČIČ where customers could choose from whole system solutions to just several parts (items) of these solutions 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 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 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 In Table 6 we can see product groups which were bought by the same card holders in the period from July to November 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 implemented. No of Revenue Margin % to Total SkB naziv Transactions Margin Total ,00% DEKORATIVNA SVETILA ,66% KOPALNIŠKA OPREMA ,70% ENOROČAJNE BATERIJE ,11% 426

10 HOW TO INCREASE SALES IN RETAIL WITH MARKET BASKET ANALYSIS KERAMIČNE PLOŠČICE ,74% KOPALNIŠKO POHIŠTVO ,63% STAVBNO POHIŠTVO ,26% HLADILNIKI ,85% ELEMENTI ZA VGRADNJO ,62% KOPALNIŠKI DODATKI ,40% RADIATORJI ,38% SANITARNA KERAMIKA ,26% POSODA ,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.,

11 MARKO SVETINA, JOŽE ZUPANČIČ Chen, Y.-L., Tang, K., Shen, R.-J., Hu, Y.-H.: Market basket analysis in a multiple store environment, Decision Support Systems (article in press), 2004, accessed through Limitedbrands: Achieving Greater Efficiencies with Market Basket Analysis, Microstrategy World 2004 Conference, Miami, 2004 Microstrategy: Business Intelligence in the Retail Industry, Microstrategy World 2003 Conference, Las Vegas, 2003 Microstrategy Web Site: Microstrategy, 2005 Merkur Commercial Analytical System - KAS, internal document, Merkur, 2005 Merkur Web Site: Merkur, 2005 Svetina, Marko: Izdelava in uporaba market basket analiz, Konferenca MUS 2004, Ljubljana, 2004 Svetina, Marko: Komercialni analitski sistem v podjetju Merkur d.d., Konferenca Poslovna inteligenca in upravljanje odnosov s strankami, Ljubljana, 2002 Vindevogel, B., Van den Poel, D., Wets, G.: Why promotion strategies based on market basket analysis do not work (article in press), Expert Systems with Applications, 2005, accessed through Weng, S.-S., Liu, J.-L.: Feature-based recommendations for one-to-one marketing, Expert Systems with Applications, Vol. 26, 2004, pp