How to Increase Retail Sales Essay

1 Introduction

One of the challenges for companies that have invested to a great extent in client informations aggregation is how to pull out of import information from their huge client databases and merchandise characteristic databases. in order to derive competitory advantage. Market basket analysis ( besides known as association regulation excavation ) is one of the information excavation methods ( Berry and Linoff. 2004 ) concentrating on detecting buying forms by pull outing associations or accompaniments from a store’s transactional informations. Several facets of market basket analysis have been studied in academic literature. such as utilizing client involvement profile and involvements on peculiar characteristics of the merchandise for the merchandise development and one-to-one selling ( Weng and Liu. 2004 ) . buying forms in a multi-store environment ( Chen et Al. . 2004 ) . or point at certain failings 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 agency to detect merchandise associations and establish a retailer’s publicity scheme on them.

When different extra trade names are sold together with the basic trade names. the gross from the basic trade names is non diminishing. but increasing. “Buy two. acquire three”sales publicity runs are really successful. if market basket analyses are used in order to find the right merchandises to be promoted. “Buy a merchandise. acquire a gift” gross revenues publicity runs are successful. if a basic merchandise and a gift are related and the basic merchandise has high border rate. Based on market basket analyses. sets of merchandises are defined and sold together with price reduction.

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Limitedbrands organizes internal competition in up-selling.

Our paper – a instance survey – nowadayss and analyses the application of market basket analysis in a major trade company in Slovenia.

2 The company Merkur. d. vitamin D.

Merkur. d. d. is a trading company ( Merkur. 2005 ) that has for old ages ranked among the top companies in Slovenia covering in points for place betterment. place services every bit good as lawn and garden. Merkur. d. d. has late strengthened its place on the foreign markets through the supplies of goods to industrial endeavors. and by the constitution of its ain retail web abroad. Merkur. d. d. is the female parent company of Merkur Group. The Group consists of two Slovenian subordinates and six subordinates abroad ( Zagreb. Sarajevo. Skopje. Munich. Milan and Warsaw ) . Besides that. the group besides includes two offices ( Moscow and Belgrade ) . Merkur plans to foster beef up its place on the domestic market. distribute its gross revenues to the foreign markets. particularly to the markets of former Yugoslavia. and develop a high-quality scope of merchandises.

The company is organised in several big sections: Wholesale. Retail Gross saless. Gross saless to Foreign Markets. Buying. Logisticss and Supporting Servicess. Customers include building companies. trading administrations. installing companies. industrial endeavors. craftsmen and little enterprisers. every bit good as terminal consumers. The company makes about 60 % of its gross revenues grosss by selling goods sweeping. To do the gross revenues quick and efficient. the Wholesale Department has been divided into four gross revenues sub-divisions. At present. Merkur has 38 retail gross revenues Centres in Slovenia. Specialization increases the effectivity of gross revenues. so two types of Merkur gross revenues Centres were developed: MERKURDOM concentrating on ordinary families. and MERKURMOJSTER intended for DIY ( do-it-yourself ) users. More information about MerkurDom and MerkurMojster is available on Merkur cyberspace site: World Wide Web. merkur. Si.

2. 1 Characteristic figures of the company

The range of the company Merkur. d. d. can be shown through the undermentioned figures: The gross revenues programme consists of approximately 200. 000 active points ( more than 120. 000 points on stock ) . divided into 5 gross revenues programmes. 74 lines of goods. 720 groups of goods and 5. 600 basic goods categorizations. Around 80 % of gross revenues are done with the top 12. 000 points and 80 % of stock is held on the top 20. 000 points. The Purchasing Department issues more than 250. 000 purchase orders with 1. 200. 000 points yearly. Merkur purchases goods from more than 2. 000 providers. About 80 % of purchases are done with the top 200 providers. Wholesale has concern dealingss with more than 2. 500 purchasers – organisations.

Approximately 80 % of sweeping gross revenues are done with the top 800 purchasers. Sweeping issues about 400. 000 bills with entire 2. 200. 000 points yearly. Retail sells goods to 13. 000 purchasers / organisations and to approximately 500. 000 terminal consumers. More than 70 % of gross revenues to stop consumers are personalized with the Merkur trueness card called the “Merkur Card of Trust” . Retail issues 6. 000. 000 bills with more than 20. 000. 000 points to stop consumers yearly. In the period from 1993 to 2004 Merkur achieved 19 % mean one-year growing in grosss. 20 % mean one-year growing in net border and 27 % mean one-year growing in net income from operations. Today Merkur is the 6th largest Slovenian company in grosss.

3. 1 The history of DW & A ; BI in Merkur

Merkur started to implement informations warehousing and concern intelligence ( DW & A ; BI ) in 1999 with a undertaking called KAS ( Commercial Analytical System ) ( Svetina. 2002 ) . Before 1999. different analyses and studies were performed in Merkur’s transactional information systems. much of the analytical information was held in Excel spreadsheets and Access databases. In the yesteryear. Merkur twice attempted to implement DW & A ; BI engineering. but failed because proposed engineering was still excessively hard to utilize for the bulk of the users. In 1999 Merkur started with a major concern procedure reorganisation and. therefore. better and new concern analyses were needed in order to do better determinations. The demand for a DW & A ; BI system emerged. so the KAS undertaking was given high precedence. Merkur started to plan analytical informations theoretical accounts for gross revenues informations and succeeded in incorporating gross revenues informations from sweeping. retail and gross revenues to foreign markets in one incorporate information theoretical account.

The IT section proposed Microstrategy DW & A ; BI engineering. which was installed and tested in the beginning of the twelvemonth 2000. The engineering was found to be appropriate and the determination was made to implement DW & A ; BI with Microstrategy solutions. The first power users ( gross revenues analysts ) were educated and the first KAS gross revenues analyses were used in the decision-making procedure. In the get downing the ETL ( extract – transform – burden ) procedure was carried out on monthly footing. but by fall of 2000 the company started to execute ETL process daily. Later in the twelvemonth 2000 the buying analytical system was introduced every bit good. In 2001. the information warehouse was upgraded with informations on Merkur’s concern programs. Gross saless and borders were planned on a really low organisational degree. The one-year program fact tabular array has more than 1. 000. 000 records. so the salespersons’ public presentation is measured really accurately. Because the engineering is easy to utilize. the figure of KAS users increased up to 100. In 2002. the execution of a really big and complex analytical faculty followed. incorporating stock list informations.

The stock list degrees of each point in every warehouse on a monthly footing is stored in KAS and enables detailed stock list analyses and sensing of critical points. Besides. informations on Merkur’s partner’s debts and liabilities was added to informations warehouse. which enables accurate hard currency flow direction. Item monetary value computation elements and different monetary values were imported in KAS in 2003. so critical monetary values can be detected and all incompatibilities eliminated. Many minor add-ons to the system were besides made over the last few old ages. All the clip Merkur attempts to utilize equal analytical and informations excavation methodological analysiss in order to better the whole system of concern coverage. From the DW & A ; BI history we can see a controlled step-by-step development of the KAS system.

Such manner of development gives chance for good definition and execution of analytical contents and enables Merkur to do many better concern determinations. The KAS system brings Merkur an of import competitory advantage. which enables the growing of the company. Improved determination devising can be demonstrated through different mensurable cardinal success factors which are bettering invariably. Key success factors such as net border. net border per point. net border per client. figure of new clients and others are measured in KAS. These factors are ever accessible for KAS users and assist them to do better determinations.

3. 2 DW & A ; BI engineering

Since 2000 Merkur has used the Microstrategy DW & A ; BI engineering. Microstrategy provides ROLAP solutions. which enable a bit-by-bit attack in informations warehouse development and treating big sums of informations. The information warehouse is implemented in an Oracle relational database. This means that the same database engineering is used in both transactional and analytical information systems. Therefore. Merkur’s IT section can concentrate in one database platform alternatively of two or even more. Oracle engineering was used in Merkur before the execution informations warehouse was started. so the execution of this engineering was fast and smooth. In Merkur the undermentioned Microstrategy tools ( Microstrategy. 2005 ) are used: MicroStrategy Intelligence Server is the bosom of the BI system and provides coverage and analysis for the whole endeavor. This BI server provides the full scope of BI applications through unified metadata and a individual integrated waiter. MicroStrategy Administrator consists of a suite of tools that provide the systems direction environment for concern 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 construction of the database into a logical concern theoretical account. These functions are stored in a centralised metadata depository. MicroStrategy Desktop is the concern intelligence package constituent that provides incorporate question and coverage. powerful analytics and determination support work flow with a desktop Personal computer. MicroStrategy Desktop provides an armory of characteristics for online analysis of corporate informations. Reports can be viewed in assorted presentation formats. polished into production studies. distributed to other users and extended through a host of ad hoc characteristics including boring. pivoting and informations slice. The interface itself is customizable to different users’ accomplishment degrees and security profiles. In Merkur. the Desktop solution is used by 13 power users ( analysts ) .

MicroStrategy Web provides users a extremely synergistic environment and low care interface for coverage and analysis. Using this intuitive HTML-only Web solution. users entree. analyze and portion corporate informations through any web browser on any operating system. MicroStrategy Web provides ad hoc questioning. speedy deployment and rapid customizability. doing it even easier for users to do informed concern determinations. In Merkur. Microstrategy Web is used by 90 terminal users of KAS. MicroStrategy Narrowcast Server is a proactive information bringing waiter that distributes individualized concern information to users via electronic mail. beepers and cell phones. It includes an intuitive self-subscription interface that enables users to stipulate what information they want to have. every bit good as when and how they want to have that information. Narrowcast Server is going more and more of import in Merkur because of its efficiency.

3. 3 Merkur’s DW & A ; BI system today

Soon. KAS ; Merkur’s DW & A ; BI system. is five old ages old. The development of the system continues invariably and there is still much content throughout the organisation which must be implemented in the BI system. The most of import content to be implemented in the hereafter are the undermentioned: Built-in informations from Merkur’s finance and accounting system ( the finance and accounting analytical system ) Relevant concern informations from Merkur’s subordinates Data from Merkur’s human resources analytical system Data from Merkur’s e-business analytical system Data from Merkur’s logistic analytical system

Soon in KAS ( Merkur Commercial Analytical System – KAS. 2005 ) : • 13 power users ( analysts ) and 90 terminal users ; of both groups. 50 users have the ability and cognition to set-up their ain studies. • Up to 30. 000 studies are run on KAS on monthly footing. • KAS consists of the undermentioned objects: o 137 tabular arraies o 433 properties o 1. 195 prosodies o 5. 611 studies • Over 35 machine-controlled services are run on the Narrowcast Server

The KAS system enables many sophisticated concern analyses such as market basket analyses. described subsequently in this paper.

4 Market basket analysis and the used methodological analysis

Market basket analyses are an of import constituent of analytical system in retail organisations. There are several definitions of market basket analysis. In a broader significance. market basket analysis marks client baskets in order to supervise purchasing forms and better client satisfaction ( Microstrategy. 2003 ) . The undermentioned analytics can be used: attachment rates. demographic baskets. trade name exchanging. client trueness. nucleus points. points per basket. in-basket monetary value. gross part. shopper incursion and others. In a narrower significance. market basket analysis gives us the reply to the undermentioned inquiry: which goods are sold together within the same dealing or to the same client? By analyzing this information. we try to happen out repeating forms in order to offer related goods together and hence increase the gross revenues.

We can track related gross revenues on different degrees of goods categorizations or on different client sections. In this paper. the narrower significance of market basket analysis will be taken into consideration. concentrating on the usage of these analyses in Merkur. It has to be noted that several other footings are besides used to depict market basket analysis: related gross revenues. cross-sell. up-sell. The differentiation between these footings is really ill-defined and the same footings are frequently used in different significances. What can we derive from market basket analysis ( Limitedbrands. 2004 ) We get the ability to larn more about client behavior. We can do more informed determinations about merchandise arrangement. pricing. publicity and profitableness. We can happen out which merchandises perform likewise to each other.

We can find which merchandises should be placed near each other. We can happen out which merchandises should be cross-sold. We can happen out if there are any successful merchandises that have no important related elements. 1. Detect the merchandising paperss ( minutess ) with the point. for which we want to execute market basket analysis. This logic is valid. if we want to transport out item-related market basket analysis. We can besides execute good categorization or even loyalty card holder-related market basket analyses. which will be shown subsequently in this paper.

2. Detect all the points in relevant merchandising paperss and their merchandising measures. monetary values. figure of minutess and other relevant informations. As an illustration. an point related market basket analysis will be presented. We want to analyze gross revenues related to item ‘209525 Decorative lamp Saturn II’ . In the first measure we determine the merchandising paperss with this point. The partial consequence is shown in the tabular array 1. Further. the consequence of the first measure is used as a filter in the 2nd measure. which consequences in a tabular array with points. sold together with point 209525.

5 Areas of market basket analyses

In Merkur different sort of market basket analyses are done. Analysiss are adapted to assorted concern demands. and some of them are discussed in the undermentioned subdivisions. In every subdivision. the relevant illustrations of analyses are presented and chances for concern action discussed.

5. 1 Selling and gross revenues publicity runs

When gross revenues runs are prepared. promoted points must be chosen really carefully. The chief end of a run is to lure clients to see Merkur’s retail Centre and purchase more than they normally do. Therefore. we must take the right points and offer the right monetary values or other conditions. Margins on promoted points are normally cut. hence. extra non-promoted points with higher borders should be sold together with promoted points. As we could see from the illustration in Section 3. point ‘209525 Decorative lamp Saturn II’ is rather equal to be included in a publicity. Together with it many other points are sold. so we can let a lower border of promoted point. Of class. there are some other standards for an point to be included in a run. such as: • Where on the point life rhythm curve is the point situated? • What is our trade name publicity policy? • Can we make an understanding with the provider ( manufacturer ) to guarantee larger measures and better monetary values?

Table 4. Gross saless publicity market basket analysis In table 4. informations from a New Year’s publicity run is shown. The: run was done through public advertisement. Paper catalogues of promoted points were sent to families. there were besides commercial musca volitanss on Television and wireless. and advertizements in newspapers. Because of advertisement a certain figure of clients came in Merkur retail Centres in order to purchase the promoted points. Additionally. they besides bought many non-promoted points ( 70 % opposed to 30 % of grosss and 75 % opposed to 25 % of borders ) with much higher % of border ( 29. 08 % opposed to 21. 81 % ) . This means that promoted points generated gross revenues of non-promoted points. There are besides many possible ways for forming runs utilizing direct selling tools for the interaction with Merkur trueness card holder. This issue will be discussed in Section 5. 5.

5. 2. System solutions offering

Market basket analyses are besides used to unite more points in a set or a system. because the bulk of clients are interested in purchasing and utilizing them at a clip or in a short period of clip after the purchase of a peculiar point. By planing sets and systems of related points a company can increase gross revenues and besides cut down costs of gross revenues minutess. so that assorted price reductions can be offered to clients. This consequences in a typical win-win state of affairs. A retail merchant must cognize the demands of clients and adapt to them. Market basket analysis is one possible manner to happen out which points can be put together in sets and systems.

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 besides different kitchen contraptions like iceboxs. dish washers. kitchen-ranges. lights-outs. dishes etc. This means that Merkur should plan and offer the clients different kitchen systems. These systems should include kitchen furniture. major and little kitchen contraptions and kitchen utensils. Such a system should be displayed in one topographic point in a retail Centre where clients could take from whole system solutions to merely several parts ( points ) of these solutions.

5. 3. Placement of goods in retail shops

Market basket analyses give retail merchant good information about related gross revenues on group of goods footing. As we can see in Table 5. the bulk of kitchen contraptions groups are related. Customers who buy a kitchen contraption frequently besides buy several other kitchen contraptions. It makes sense that these groups are placed side by side in a retail Centre so that clients can entree them rapidly. Such related groups of goods besides must be located side-by-side in order to remind clients of related points and to take them through the Centre in a logical mode.

In Merkur. two basic constructs of retail Centres are used: MerkurDom specialises in high-quality points for place betterment and garden. MerkurMojster specialises in high-quality merchandises aimed at DIY users. craftsmen. and enterprisers. Centres are besides classified by size as little and big Centres. For each of these constructs. standardized arrangement programs were developed. Market basket analyses represent one section of tools for determination doing sing arrangement of goods. It can demo us where we should alter the arrangement of goods. After the alteration we can mensurate the concern effects of the alteration.

5. 4. Education of sales representative

The interesting consequences of market basket analyses must be presented to the sales representative in retail Centres. because the employees must be cognizant of them and they should utilize them in the procedure of selling. Every sales representative has some cognition about related points from his or her experience. With market basket analyses we can construction this cognition and utilize it to learn less experient forces. Merkur invests a batch in instruction of sales representative through both internal and external beginnings. Knowledge from market basket analyses is widely used in internal instruction.

5. 5. Cleavage of clients

As mentioned in Section 1. 1. . more than 70 % of gross revenues to stop consumers are personalized with the Merkur trueness card called “Merkur Card of Trust” . This information enables us to reply the undermentioned inquiry: What did consumers who bought point ( group ) X in period 1. bargain in period 2? If we identify clients who bought point X today. we can expect what they will purchase. for case. in following three months. and we can publicize them the right merchandises. A typical illustration is shown in Table 6. We analysed trueness card holders who bought ceramic tiles in the period from April to June 2004. In Table 6 we can see merchandise groups which were bought by the same card holders in the period from July to November 2004. They bought different bathroom and kitchen accoutrements and cardinal warming elements.

It would be really utile. if Merkur organized a targeted selling run for this specific group of clients in July 2004 and promoted these merchandises. There are many other possibilities and chances in Merkur to utilize loyalty card-based market basket analyses as a support tool for direct selling runs. Merkur normally organizes non-targeted common runs. in which the bulk of Slovenian families are included. But recently Merkur besides started to implement direct selling methods and hence an effectual information warehouse and concern intelligence system is indispensable. This helps many interesting selling thoughts to be implemented.

6 Decision

The pattern in Merkur proves that market basket analysis is a really utile for marketing runs. good arrangement definition and instruction of gross revenues forces. Merkur uses market basket analysis throughout the publicity run procedure. When a gross revenues publicity is prepared. market basket analysis is used to specify the right merchandises and the right monetary values for the run. Related non-promoted points are besides defined in order to put them in the locality of promoted points and therefore addition gross revenues. When gross revenues publicity coatings. its consequences are carefully analysed in order to detect chances for following publicities. Merkur widely uses market basket analyses to pull off the arrangement of goods in retail Centres. Related merchandises and merchandise groups are placed together in such a mode that client can logically happen points he/she might purchase.

The findings of market basket analyses are an of import portion of the procedure of learning the sales representative of Merkur. Gross saless forces must be cognizant of related merchandises in order to increase satisfaction of clients and escalate gross revenues. Market basket analyses are merely a portion in the holistic attack to the executing of selling development scheme in Retail in Merkur. The analytical procedure is integrated in other selling activities and analysts are an of import portion of Merkur selling development squad. Team work is important for successful usage of such analyses. Beside of the organisation of the Merkur selling procedure. a capable DW & A ; BI system is needed.

The BI system must hold good public presentations when treating big sum of informations. It besides has to be scalable and flexible. but. above all. the BI system must be user-friendly so that different selling specializers can utilize it without any jobs. 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 utile consequences. In the hereafter a working direct selling scheme must be developed based on informations already available in KAS. Then an organisation and information systems for efficient executing of this scheme have to be established.

7 Mentions
Berry. M. J. A. . Linoff. G. S. : Data Mining Techniques: for Marketing. Gross saless and Customer Relationship Management ( 2nd edition ) . Hungry Minds Inc. . 2004 Chen. Y. -L. . Tang. K. . Shen. R. -J. . Hu. Y. -H. : “Market basket analysis in a multiple shop environment” . Decision Support Systems ( article in imperativeness ) . 2004. accessed through World Wide Web. ScienceDirect. com 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: hypertext transfer protocol: //www. microstrategy. com/Software/ . Microstrategy. 2005 Merkur Commercial Analytical System – KAS. internal papers. Merkur. 2005 Merkur Web Site: hypertext transfer protocol: //www. merkur. si/ang/podj. hypertext markup language. Merkur. 2005 Svetina. Marko: Izdelava in uporaba market basket analiz. hypertext transfer protocol: //www. muson. net/Konferenca_login. asp? mni=12. Konferenca MUS 2004. Ljubljana. 2004 Svetina. Marko: Komercialni analitski sistem 5 podjetju Merkur d. d. . Konferenca Poslovna inteligenca in upravljanje odnosov s strankami. Ljubljana. 2002 Vindevogel. B. . Van den Poel. D. . Wets. G. : “Why publicity schemes based on market basket analysis do non work” ( article in imperativeness ) . Adept Systems with Applications. 2005. accessed through World Wide Web. ScienceDirect. com Weng. S. -S. . Liu. J. -L. : “Feature-based recommendations for one-to-one marketing” . Adept Systems with Applications.

Vol. 26. 2004. pp. 493-508.

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