Retail marketing mix analysis

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Retail marketing mix analysis

History[ edit ] The term marketing mix was developed by Neil Borden who first started using the phrase in According to McCarthy the marketers essentially have these four variables which they can use while crafting a marketing strategy and writing a marketing plan.

In the long term, all four of the mix variables can be changed, but in the short term it is difficult to modify the product or the distribution channel.

The Marketing Mix, also known as the 4 P's of Marketing, is the combination of product, price, place (distribution), and promotion. A marketing orientation has been defined as a "philosophy of business management." or "a corpora A firm employing a product orientation is mainly concerned with the quality of its own product. Nike shoes on display at a shoe store. Nike Inc.’s marketing mix or 4P facilitates the company’s global growth based on high quality products, numerous places for distribution, advertising-focused promotion, and relatively high prices in the global market for athletic footwear, apparel, and equipment.

Another set of marketing mix variables were developed by Albert Frey Frey, A. The "offering" consists of the product, service, packaging, brandand price. The "process" or "method" variables included advertising, promotion, sales promotion, personal selling, publicitydistribution channels, marketing researchstrategy formation, and new product development.

Retail marketing mix analysis

They added "People" to the list of existing variables, in order to recognize the importance of the human element in all aspects of marketing. They added "process" to reflect the fact that services, unlike physical products, are experienced as a process at the time that they are purchased.

Desktop modeling tools such as Micro TSP have made this kind of statistical analysis part of the mainstream now. Most advertising agencies and strategy consulting firms offer MMM services to their clients.

Retail marketing mix analysis

Mathematically, this is done by establishing a simultaneous relation of various marketing activities with the sales, in the form of a linear or a non-linear equation, through the statistical technique of regression.

MMM defines the effectiveness of each of the marketing elements in terms of its contribution to sales-volume, effectiveness volume generated by each unit of effortefficiency sales volume generated divided by cost and ROI.

These learnings are then adopted to adjust marketing tactics and strategies, optimize the marketing plan and also to forecast sales while simulating various scenarios.

The creation of variables for Marketing Mix Modeling is a complicated affair and is as much an art as it is a science. The balance between automated modeling tools crunching large data sets versus the artisan econometrician is an ongoing debate in MMM, with different agencies and consultants taking a position at certain points in this spectrum.

Further validations are carried out, either by using a validation data, or by the consistency of the business results. The output can be used to analyze the impact of the marketing elements on various dimensions. The contribution of each element as a percentage of the total plotted year on year is a good indicator of how the effectiveness of various elements changes over the years.

The yearly change in contribution is also measured by a due-to analysis which shows what percentage of the change in total sales is attributable to each of the elements.

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For activities like television advertising and trade promotions, more sophisticated analysis like effectiveness can be carried out. This analysis tells the marketing manager the incremental gain in sales that can be obtained by increasing the respective marketing element by one unit.

If detailed spend information per activity is available then it is possible to calculate the Return on Investment of the marketing activity. Not only is this useful for reporting the historical effectiveness of the activity, it also helps in optimizing the marketing budget by identifying the most and least efficient marketing activities.

They can optimize the budget by allocating spends to those activities which give the highest return on investment. Some MMM approaches like to include multiple products or brands fighting against each other in an industry or category model - where cross-price relationships and advertising share of voice is considered as important for wargaming.

Components[ edit ] Marketing-mix models decompose total sales into two components: This is the natural demand for the product driven by economic factors like pricing, long-term trends, seasonalityand also qualitative factors like brand awareness and brand loyalty.

Incremental sales are the component of sales driven by marketing and promotional activities. This component can be further decomposed into sales due to each marketing component like Television advertising or Radio advertisingPrint Advertising magazines, newspapers etc.

Marketing-Mix analyses are typically carried out using Linear Regression Modeling. Nonlinear and lagged effects are included using techniques like Advertising Adstock transformations. Typical output of such analyses include a decomposition of total annual sales into contributions from each marketing component, a.

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Elements measured in MMM[ edit ] Base and incremental volume[ edit ] The very break-up of sales volume into base volume that would be generated in absence of any marketing activity and incremental volume generated by marketing activities in the short run across time gain gives wonderful insights.

The base grows or declines across longer periods of time while the activities generating the incremental volume in the short run also impact the base volume in the long run. The variation in the base volume is a good indicator of the strength of the brand and the loyalty it commands from its users.

Media and advertising[ edit ] Market mix modeling can determine the sales impact generated by individual media such as television, magazine, and online display ads. In some cases it can be used to determine the impact of individual advertising campaigns or even ad executions upon sales.

For example, for TV advertising activity, it is possible to examine how each ad execution has performed in the market in terms of its impact on sales volume.

MMM can also provide information on TV correlations at different media weight levels, as measured by Gross Rating Points GRP in relation to sales volume response within a time frame, be it a week or a month.

Information can also be gained on the minimum level of GRPs threshold limit in a week that need to be aired in order to make an impact, and conversely, the level of GRPs at which the impact on volume maximizes saturation limit and that the further activity does not have any payback.

While not all MMM's will be able to produce definitive answers to all questions, some additional areas in which insights can sometimes be gained include:Four areas that present a significant opportunity to impact the bottom-line of companies in different business verticals through the use of advanced analytics and sophisticated data modeling.

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