McGraw-Hill/Irwin

Chapter 6

Measuring Market Opportunities: Forecasting and Market Knowledge

Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.

Every forecast is wrong!

• The future is inherently uncertain, especially in today’s rapidly changing markets.

• An evidence-based forecast, instead of a wild guess, is almost always called for, even if time and money are scarce.

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A Forecaster’s Toolkit

• An estimate of market potential often serves as a starting point for preparing a sales forecast.

• The size of the currently penetrated market should also be ascertained. • Investors will also need a sales forecast. 6-3

A Forecaster’s Toolkit

• Two broad approaches for preparing a sales forecast: – Top-down approach in which a central person or persons take the responsibility for forecasting and prepare an overall forecast.

– Bottom-up approach in which each part of the firm prepares its own sales forecast, and the parts are aggregated to create the forecast for the firm as a whole 6-4

A Forecaster’s Toolkit

• Statistical methods – These use past history and various statistical techniques, such as multiple regression or time series analysis, to forecast the future.

– These generally assume that the future will look very much like the past. – Sometimes this is not the case.

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A Forecaster’s Toolkit

• Other quantitative methods: – Methods to mathematically model the diffusion of innovation process for consumer durables.

– Conjoint analysis, a method to forecast the impact on consumer demand of different combinations of attributes that might be included in a new product.

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A Forecaster’s Toolkit

• Observation – Attractive method because it is based on what people actually do. • Surveys or focus groups • Analogy – The product is compared with similar historical data that are available.

– Also used for new-to-the-world high technology products 6-7

A Forecaster’s Toolkit

• Judgment – Sometimes forecasts are made solely on the basis of experienced judgment, or intuition.

– Defending such forecasts against those prepared by evidence-based methods is difficult.

• Mathematics entailed in forecasting – The chain ratio calculation. – The use of indices. 6-8

A Forecaster’s Toolkit

• Market tests – May be done under controlled experimental conditions in research laboratories, or in live test markets.

– Use of live test markets has declined for two reasons: • They are expensive to conduct.

• Competitors can buy the data collected through scanners at the checkout and learn the results of the test market without bearing the expense.

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Rate of Diffusion of Innovations • Diffusion of innovation theory seeks to explain the adoption of an innovative product or service over time among a group of potential buyers.

• The adoption process involves the attitudinal changes experienced by individuals from the time they first hear about a new product, service, or idea until they adopt it.

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Rate of Diffusion of Innovations • Speed of adoption depends on: – The risk.

– The relative advantage over other products.

– The relative simplicity of the new product.

– Its compatibility with previously adopted ideas.

– The extent to which its trial can be accomplished on a small-scale basis.

– The ease with which the central idea of the new product can be communicated.

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Diffusion of Innovation Curve 6-12

Rate of Diffusion of Innovations • Implications of diffusion of innovation theory – A good way to estimate how quickly an innovation is likely to move through the diffusion process is to construct a chart that rates the adoption on the six key factors influencing adoption speed. – Introducing a new product that delivers no real benefits or lacks competitive advantage is likely to face tough sledding.

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Cautions and Caveats in Forecasting • Keys to good forecasting – Making explicit the assumptions on which the forecast is based.

– Using multiple methods.

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Cautions and Caveats in Forecasting • Common sources of error in forecasting – Forecasters are subject to anchoring bias.

– Capacity constraints are sometimes misinterpreted as forecasts.

– Incentive pay.

– Instated but implicit assumptions can overstate a well-intentioned forecast.

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Why Data? Why Marketing Research?

• Without adequate market knowledge, marketing decisions are likely to be misguided.

• Thoughtfully designed, competently executed marketing research can mitigate the chances of unpleasant outcomes.

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Customer Relationship Management and Market Knowledge Systems • Four market knowledge systems: – Internal records regarding marketing performance – Marketing databases – Competitive intelligence systems – Systems to organize client contact • Taken together, these lie at the heart of the systematic practice of customer relationship management (CRM).

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Customer Relationship Management and Market Knowledge Systems • Internal records systems – Internal records systems help track what is selling, how fast, in which locations, to which customers, and so on.

– Providing input on the design of such systems so that the right data are provided to the right people at the right time is a critical marketing responsibility in any company. 6-18

Customer Relationship Management and Market Knowledge Systems • The purpose of CRM is to develop a unified and cohesive view of the customer from every touch point within the company.

– Databases created for CRM purposes typically capture information about:: • Transactions • Instances of customer contact • Customer demographics • Customer responses 6-19

Customer Relationship Management and Market Knowledge Systems • Database design considerations: – The cost of collecting the data.

– The economic benefits of using the data.

– The ability of the company to keep the data current in today’s mobile society.

– The rapid advances in technology.

• Data mining 6-20

Customer Relationship Management and Market Knowledge Systems • Implementing an effective CRM effort requires four key steps: – Gaining broad-based organizational support for creating and adopting a CRM strategy.

– Forming a cross-functional CRM team with membership from all functions that have customer contact.

– Conducting a needs analysis that identifies both customer and business needs.

– Developing a CRM strategy to guide implementation.

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Customer Relationship Management and Market Knowledge Systems • Major pitfalls to watch out for: – Implementing CRM without first developing a strategy.

– Putting CRM in place without changing organizational structure and/or processes.

– Assuming that more CRM is better.

– Failure to prioritize which customer relationships are most worth investing in.

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Customer Relationship Management and Market Knowledge Systems • Client contact systems – Salesforce automation software helps companies disseminate real-time product information to salespeople.

• Competitive intelligence systems – A systematic and ethical approach for gathering and analyzing information about competitors’ activities and related business trends.

– It is based on the idea that more than 80 percent of all information is public knowledge.

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Marketing Research: A Foundation for Marketing Decision Making • Marketing research task is the design, collection, analysis, and reporting of research intended to gather data pertinent to a particular marketing challenge or situation.

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Marketing Research: A Foundation for Marketing Decision Making • Step 1: Identify the managerial problem and establish research objectives – A good place to start is to ask what the managerial problem or question is that a proposed program of research might address.

– Taking each of the managerial questions and applying appropriate analytical frameworks to each of them results in a set of research objectives that will drive the research.

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Marketing Research: A Foundation for Marketing Decision Making • Step 2: Determine the data sources and types of data required – Primary or secondary sources?

– Qualitative or quantitative data and research approaches?

• Step 3: Design the research – Determine the data collection method and prepare the research instrument.

– Determine the contact method.

– Design the sampling plan.

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Marketing Research: A Foundation for Marketing Decision Making • Step 4: Collect the data – Contributes more to overall error than any other step.

– Collector bias.

• Step 5: Analyze the data – Often, sophisticated statistical analyses are required.

• Step 6: Report the results to the decision maker 6-27

What Users of Marketing Research Should Ask?

• Questions: – What are the objectives of the research? Will the data to be collected meet those objectives?

– Are the data sources appropriate? Is cheaper, faster secondary data used where possible? Is qualitative research planned to ensure that quantitative research, if any, is on target?

– Are the planned approaches suited to the objectives of the research?

– Is the research designed well?

– Are the planned analyses appropriate?

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Take-Aways • Every forecast and estimate of market potential is wrong! – Evidence-based forecasts and estimates, prepared using the tools provided in this chapter, are far more credible —and generally more accurate —than hunches or wild guesses. 6-29

Take-Aways • Forecasts have powerful influence on what companies do, through budgets and other planning procedures. • Superior market knowledge is not only an important source of competitive advantage, but it also results in happier, higher volume of, and more loyal customers. 6-30

Take-Aways • Much can go wrong in marketing research and often does. – Becoming an informed and critical user of marketing research is an essential skill for anyone who seeks to contribute to strategic decision making. 6-31