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Data Mining Case Study. Furniture Store Advertising. A national furniture store chain spends significant sums of money on advertising. The furniture store has branches throughout the country, as well as online presence and online sales. The store engages in various typical promotion schemes including sales (both in typical sales periods e.g. January, and in atypical periods). All promotional schemes are national – the store has a national pricing policy and the advertised prices are the same throughout the country. However branch managers have some pricing discretion (10%). However manager bonuses are reduced if the use of price discretion is not matched by a compensatory sales increase. The chain spends more on advertising than the average furniture store chain. They engage in various national advertising schemes (High Profile TV, Low Profile TV, National Papers, Specialist Magazines, Radio). They also utilise local advertising methods (billboards, local papers, local radio). There are variations in advertising spend with significant increases around the period of sales. They also maintain a small number of typical online advertising methods. They also perform tied advertising (e.g. in Credit Card Statements) They have periods of no advertising spend, predominantly out of sale period. However there was one short atypical sale period that they performed no advertising in. Local advertising spend is also varied through the year, with some quiet periods. The furniture store keeps significant information – all sales, all pricing information, names, addresses, items purchased, when purchased etc. They keep approximate footfall counts in each store, and online details. Approximate information about competitor sales is also available at a monthly level for individual stores. You have been employed as a Business Analytics/ Data Mining Consultant. Your remit is to assess the cost effectiveness of each advertising stream, and the most appropriate way of targeting the advertising timing and method. At this stage you need to form a plan of assessment: what data do you envisage as being important, what information about the business do you need from the management, what information if any do you need from the shop floor, and what data do you need to start to visualise in order to asses the viability or otherwise of particular approaches to this problem. How are you going to kick off achieving your goal. Prior to the next lecture, please think through these issues. This will be the subject of a group case study in the next lecture.