Chapter 1 MCS 3500.docx

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University of Guelph
Marketing and Consumer Studies
MCS 3500
Towhidul Islam

Chapter 1 Marketing Analysis & Planning The Marketing Engineering Approach Introduction  Good decision-making involves reasoned choice among competing alternatives  Marketing managers make frequent decisions about product features, price, distribution options & sales incentives  Sales managers might lower advertising budgets to achieve higher personal selling expenditures while advertising manager might prefer larger advertising budgets Marketing Engineering: Systematic translation of data & knowledge into tools used for decision support Conceptual Marketing: Decision maker relies solely on their mental model without using any support system Automated Marketing: Automate decision-making process using sophisticated info system Marketing Engineering: A systematic approach to harness data & knowledge to drive effective marketing decision making & implementation through a technology enabled and model-supported decision process  Combines managerial judgment w/ formal decision models  This approach requires the design & construction of decision modes & the implementation of those models in the form of marketing support systems (MMSSs)  Purpose is to simplify the decision context  Provides platform to ask “what if” enabling managers to assess opportunity costs associated w/ their decisions The emerging marketing decision environment  Marketing engineering in past decades has accelerated in popularity b/c of the range of technologies that make the approach crucial in competitive markets  With the development of enterprise wide systems for resources planning (ERP) and customer relationship management (CRM), marketing analytics is becoming an integrated aspect of the decision making architectures that leading firms employ Trends That Favor Marketing Engineering  Several trends, both on the supply side & demand side, favor the wider acceptance of Marketing engineering approaches among companies The ubiquity f high-powered personal computers connected to networks  Marketing managers depend increasingly on computers to perform their jobs  Excel and Java (etc.) enables companies to embed models into their info & decision systems, increasing their ability to gather, process, and share info & then apply marketing models at the point of decision making An expanding volume of data  The automatic electronic capture of data related to transactions w/ customers and growth in interactions/exchange via internet have generated massive amounts of potentially useful info about the preferences & behaviour of customers  Abundance of data can actually be bigger problem then lack of data  A lot of marketing officers aren’t prepared for managing the data explosion  Marketers demand decision tools & processes that can quickly transform data into insights & actions Reengineering Marketing  Today’s firms use flat organizational structures, ad hoc teams, outsourcing, strategic relationships, & reduced cycle times  In reengineered firm, centralized decision making, a characteristic of traditional hierarchal organizations, is giving way to decentralized decision making that is characteristic of entrepreneurial organizations  As consequence, marketing managers increasingly deal directly w market info& use computers to complete tasks that were once done by support staff Higher standards of accountability  Several factors including, the pressures of the most recent recession, increasing levels of competition in major markets & the improved ability to associate market response w/ marketing activities (e.g direct response tv, websites etc.), have focused senior management attention on marketing’s contribution to the top & bottom lines  Marketing engineering capitalizes on these trends which favor both the supply & demand for marketing analytics  Marketing engineering enables marketers to capture the essence of marketing problems in well-specified models, also improves their ability to make decisions that influence market outcomes  Analytics must BECOME part of the company’s core managerial decision-making capabilities to work  Managers recognize the model doesn't provide the complete answer  Decision support tools & mental models must be used in conjunction  Mental models can incorporate idiosyncratic (unique) aspects of a decision situation, but they may force fit new cases into old patterns  Decision models may be consistent & unbiased but they can be underweight or ignore idiosyncratic aspects of the situation Tools for marketing engineering  The wide availability of spreadsheet software (excel etc.) has made it easier to work with mathematical representations of marketing phenomena  Marketing spreadsheets typically include planned marketing expenses & the associated gross & net revenues  In most cases developer doesn't have spreadsheet relationship between marketing inputs (eg. advertising) & sales revenue = Dumb models: make little sense as marketing models b/c don't state relationship of marketing inputs & outputs  In a “smart” model the spreadsheet embeds an equation or “response model” which the manager uses to consider the effects of advertising on sales & revenue and determine if increases or decreases in advertising are justified Market Response Models Market Response Model: Basic tools of marketing engineering, can transform dumb spreadsheet to smart ones  Critical for systematically addressing many strategic and tactical decision problems in marketing such as budgeting & mix allocations, customer targeting, & product/company positioning.  Poor response models that lead decision process astray will slice away from target Marketing response models require that he following be made explicit: 1. Input
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