Measuring Market

Opportunities: Forecasting and

Market Knowledge

Chapter 6

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

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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.

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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

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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

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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.

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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

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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.

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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

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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

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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

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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.

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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.

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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.