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18 Cards in this Set
- Front
- Back
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Buyers lines of communications (format)
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buyer to store mngrs, buyers to designers, CFO to the buyer to the designers/venders/store mngrs., Buyer to Assistant Buyer to Trade show vendor
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'Basics' (merchandise)
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-bought year-to-year
-denim -white tops -staple silihouttes |
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'Fashion' (merchandise)
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-risk purchases
-trend based -short-shelf life |
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Breadth of assortment
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each unique category sold
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Depth of assortment
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within each category: how many pieces are carried in the assortment (different styles of shoes in the shoe category.)
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Secondary Market research data:
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posited info. already pulled together (articles)
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Primary market research data:
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situation specific (data summarized into main insights for exactly what info is needed.)
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Internal resources of the buyer:
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-store records of sales/failed pieces
-store management feedback from customers -visiting the sales floor personally |
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External resources to the buyer:
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-creating a consumer advisory panel
-trade publications -vendors -trade associations -compairisson shopping -fashion forecasters -reporting services (WGSN) -retail buying offices (DONEGER Group |
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Types of buying offices:
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-Independent-private: most common-requires a fixed salary, contract and/or commission of purchases
-Store owned buying offices: -private buying within each dept. -associated (cooperative) shared info., for discounts -corporate buying office: like Macys |
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The Buyers Calendar (year) :
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Buy in: For:
April Fall 1 & Transition wear June Fall 2 August Resort/Holiday Oct/Nov Spring January Summer |
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Rational consumer:
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buys for basics/needs
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Emotional Consumer:
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buys for feelings/wants/mood
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Patron consumer:
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buys due to previously instilled loyalty, customer service that's tops, and consistently loves the merchandise assortment
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Date warehousing:
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listing of sales figures
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Data mining:
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identifying smaller trends from sales data that was broken down by use of specialized software (to find trends within information simularites.)
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Types of data to analyze (& why:)
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associations: links to a single event/product
sequences: links events over-time clustering: looking for groups forecasting: plan for future purchases |
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Database Marketing:
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translating collected info. into who, what, where, when, and why- to market to.
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