1. Measuring Market Opportunities: Forecasting and Market Knowledge
Chapter 6
Measuring Market Opportunities: Forecasting and Market Knowledge
McGraw-Hill/Irwin
Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.

2. 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.

3. 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.

4. 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

5. 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.

6. 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.

7. 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

8. 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.

9. 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.

10. 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.

11. 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.

12. Diffusion of Innovation Curve

13. 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.

14. Cautions and Caveats in Forecasting
Keys to good forecasting
Making explicit the assumptions on which the forecast is based.
Using multiple methods.

15. 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.

16. 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.

17. 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).

18. 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.

19. 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

20. 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

21. 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.

22. 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.

23. 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.

24. 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.

25. 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.

26. 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.

27. 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

28. 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?

29. 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.

30. 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.

31. 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.