BUS M 300 1nd Edition Lecture 4 Outline of Last Lecture I Consumer Purchase Decision Process and Experience II Psychological Influences on Consumer Behavior III Sociocultural Influences on Consumer Behavior Outline of Current Lecture I The Role of Marketing Research A Step One Define the Problem B Step Two Develop the Research Plan C Step Three Collect Relevant Information D Step Four Develop Findings E Step Five Take Marketing Actions II Sales Forecasting Techniques Current Lecture I The Role of Marketing Research Marketing research the process of collecting and analyzing information in order to recommend actions A decision is a conscious choice from among two or more alternatives A Step 1 Define the problem o Setting research objectives research objectives are specific measurable goals the decision maker seeks to achieve in conducting the marketing research o Identifying possible marketing actions different outcomes lead to different marketing actions research Measures of success criteria or standards used in evaluating proposed solutions to a problem B Step 2 Develop the research plan o Requires that the researchers 1 Specify the constraints on the marketing research activity o Constraints restrictions placed on potential solutions to a problem 2 Identify the data needed for marketing actions o Focus on collecting data that will help managers make a clear choice 3 Determine how to collect the data o Two key elements are used Concepts ideas about products or services New product concept picture or verbal description of a product or service the firm might offer to sell Methods the approaches that can be used to collect data to solve all or part of a problem C Step 3 Collect Relevant Information o Collecting enough relevant information to make a rational informed marketing decision sometimes simply means using one s knowledge to decide immediately o Data the facts and figures related to a problem o Secondary data facts and figures that have already been recorded prior to the project at hand Secondary data Internal two parts o Marketing input data relates to the effort expended to make sales o Marketing outcome data relates to the results of the marketing efforts Secondary data External published data from outside the organization o Primary data facts and figures that are newly collected for a project Observational data facts and figures obtained by watching either mechanically or in person how people behave Mechanical methods national TV ratings o o o o Personal methods watching consumers in person or recording them neuromarkerting Questionnaire data facts and figures obtained by asking people about their attitudes awareness intentions and behaviors Open ended questions allows for expression of opinions ideas or behaviors in their own words Closed ended questions requires one or more preselected response options Other sources of prime data social media panels sample of customer or stores from which researchers take a series of measurements and experiments obtaining data by manipulating factors under tightly controlled conditions to test cause and effect information technology involves operating computer networks that can store and process data data mining the extraction of hidden predictive information from large data bases to find statistical links between consumer purchasing patterns and marketing actions Advantages of secondary data 1 Tremendous time savings due to data already being collected and published 2 Low cost Disadvantages of secondary data 1 May be out of date 2 Definitions or categories might not fit research project Advantages of primary data 1 More flexibility 2 More specific to problem Disadvantages of primary data 1 Far more costly 2 Time consuming D Step 4 Develop findings o Analyze the data o Present the findings E Step 5 Take marketing action o Three steps after marketing research is over 1 Identify the marketing actions Make recommendations 2 Put them into effect Implement the action recommendation 3 Monitor how the decisions turn out Evaluate the results III Sales Forecasting Techniques Sales forecast the total sales of a product that a firm expects to sell during a specified time period under specified conditions Three main sales forecasting techniques 1 Judgments of the decision maker o Direct forecast involves estimating the value to be forecast without any intervening steps o Lost horse forecast involves starting with the last known value of the item being forecast listing the factors that could affect the forecast and assessing their positive and negative impacts 2 Surveys of knowledgeable groups o Survey of buyer s intentions forecast involves asking prospective customers if they are likely to buy product during some future time period o Salesforce survey forecast involves asking the firm s salespeople to estimate sales during a coming period 3 Statistical methods o Trend exploration involves extending a pattern observed in past data into the future assumes that the underlying relationships in the past will continue into the future Judgment Approaches to Forecasting Sales 1 Sales force composite approach ask sales representatives to forecast sales for their areas o Advantages have their finger on the pulse of the market o Disadvantages under pressure to perform well 2 Buyer surveys ask consumers or firms about their intentions to buy o Advantages find out what consumers are really thinking in the market place o Disadvantages buyer tend to fill out survey s quickly and often not accurately 3 Manager surveys ask the firm s managers to forecast sales for their areas o Advantages they have macro view of the market more likely to see trends o Disadvantages they are under pressure to perform well Three formulas to know 1 Moving average model MAM to get sales forecast in a certain year o Example Use last 5 this number changes depending on the question years worth of actual sales add the actual sales for past 5 years and divide by 5 2 Actual Percentage Error APE tells which forecasted sales is the best o Example actual sales forecasted sales actual sales after doing this for all actual and forecasted sales add the percentages together 3 Exponential Smoothing Model ESM helps to smooth variability s in our forecast o Example Alpha is chosen by management for this example it is 3 o 3 actual sales 1 3 forecasted sales Always use approach with lowest MAPE