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Marketing mix modeling (MMM) is an analytical approach that uses historic information to quantify impact of marketing activities on sales. Example information that can be used are syndicated point-of-sale data (aggregated collection of product retail sales activity across a chosen set of parameters, like category of product or geographic market) and companies’ internal data.
Sales data, presented in a graphic format, can provide regular sales trend information and highlight whether certain customer types need to be targeted or focused. Price information by product line, compare with competitors, can monitor market trends; analyzed by customer type, it can check price trends in customer groups.
For each product or service, the 'area' of the circle represents the value of its sales. The growth–share matrix thus offers a "map" of the organization's product (or service) strengths and weaknesses, at least in terms of current profitability, as well as the likely cashflows. Common spreadsheet applications can be used to generate the matrix.
As mentioned above, the width of product mix is referred to as the total number of product lines that the company offers. A diversified product mix can target the maximum number of customers, however, such numbers of product lines requires much attention and focus as each product line targets different groups of consumers and involves individual strategy and management.
Digital marketing mix is fundamentally the same as Marketing Mix, which is an adaptation of Product, Price, Place and Promotion into digital marketing aspect. [48] Digital marketing can be commonly explained as 'Achieving marketing objectives through applying digital technologies'.
The retail marketing mix typically consists of six broad decision layers including product decisions, place decisions, promotion, price, personnel and presentation (also known as physical evidence). The retail mix is loosely based on the marketing mix , but has been expanded and modified in line with the unique needs of the retail context.
It provides significant insight into customers wants, needs, buying habits and behaviours and is a key tool used in the product planning process. [6] For example, customer satisfaction information can be obtained through surveys and market research. The process consists of 4 components: definition, collection, analysis and interpretation. [7]
Livegap Charts creates line, bar, spider, polar-area and pie charts, and can export them as images without needing to download any tools. Veusz is a free scientific graphing tool that can produce 2D and 3D plots. Users can use it as a module in Python. GeoGebra is open-source graphing calculator and is freely available for non-commercial users.