Chapter 5
Measuring Market Opportunities: Forecasting
and Market Knowledge
I. Intel’s Secret Weapon discusses Intel’s efforts to understand what their customers and
potential customers care about and if they understood the things to drive new uses of technology.
Genevieve Bell, Director of Intel’s User Experience Group, with her team of social scientists,
interaction designers and human factors engineers is charged with setting research directions,
leading new product strategy and definition, and driving consumer-centric product innovation
and thinking across the company.
II. Strategic Challenges Addressed in Chapter 5
Chapter 5 deals with issues that enable managers and entrepreneurs to bring life to their
dreams.
oIt address challenges in estimating market potential and forecasting sales, for both
new and existing products, or businesses.
oIt provides a menu of evidence-based forecasting methods, each of which is useful in
some situations, but not others, and their limitations.
oIt also examines the process by which innovative new products diffuse into the
market over time.
oIt also addresses several systematic sources of information—internal record systems,
marketing addresses, competitive intelligence systems, and systems that organize and
track information about client contact—that keep marketers in touch with what’s
going on in the marketplace.
oIt briefly touches on marketing research, where data is gathered about a particular
marketing challenge or situation.
III. Every Forecast Is Wrong
Forecasting plays a central role in all kinds of planning and budgeting in all kinds of
businesses and other organizations.
Given stakes and risks in being wrong with a forecast, some effort to prepare an
evidence-based forecast, instead of a wild guess, is almost always called for, even if time
and money are scarce.
IV.A Forecaster’s Toolkit: A Tool for Every Forecasting Setting
Before choosing a method to prepare a forecast, one must know what is to be estimated or
forecasted.
oFirst, there is the size of the potential market, that is, the likely demand from all
actual and potential buyers of a product or product class. An estimate of market
potential often serves as a starting point for preparing a sales forecast.
oSecond, there is the size of the currently penetrated market, those who are actually
using the product.
oThird, there is the target market, the size of the potential and penetrated markets for
the market segment an organization intends to serve.
Established organizations employ two approaches for preparing a sales forecast:
oTop-down—central person or persons take the responsibility for forecasting and
prepare an overall forecast, perhaps using aggregate economic data, current sales
trends, or other methods.
oBottom-up—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. It is common in
decentralized firms.
There are numerous evidence-based methods for estimating market potential and
forecasting sales—statistical methods, observation, survey or focus groups, analogy,
judgment, experiments and market tests, and other mathematical approaches like chain
ratios and indices.
A. Statistical Methods
Statistical methods use past history and various statistical techniques, such as
multiple regression or time series analysis, to forecast the future based on an
extrapolation of the past.
This method is typically not useful for entrepreneurs or new product managers
charged with forecasting sales for a new product or new business since there is no
history in their venture on which to base a statistical forecast.
In established firms, for established products, statistical methods are extremely
useful.
Statistical methods have important limitations
oStatistical methods generally assume the future will look very much like the
past. Sometimes this is not the case.
oIf product or market characteristics change, statistical methods used without
adequate judgment may not keep pace.
B. Observation
One method for preparing an evidence-based forecast is to directly observe or
gather existing data about what real consumers do in the product-market of interest.
Observation-based forecasting is attractive because it is based on what people
actually do.
If behavioral or usage data can be found from existing secondary sources—in
company files, at the library, or on the internet—data collection is both faster and
cheaper than conducting and designing a new study and carrying it out.
C. Surveys or Focus Group
Consumers, after being shown a statement of the product concept (concept test) or
a prototype or sample of the product, can be asked how likely they are to buy,
creating a survey of buyers’ intentions. Buyers can also be asked about their
current buying behavior.
Salespeople can be asked how much they are likely to sell, completing a survey of
salesforce opinion.
Experts of various kinds—members of the distribution channel, suppliers,
consultants, trade association executives, and so on—can also be surveyed.
Surveys and focus groups possess important limitations:
oFor one, what people say is not always what people do. Consumer surveys of
buyer intention are always heavily discounted to allow for this fact.
oThe people who are surveyed may not be knowledgeable, but if asked for
their opinion they will probably provide it.
oWhat people imagine about a product concept in a survey may not be what is
actually delivered once the product is launched.
In general, statistical and observational methods, where adequate data or settings
are available in which to apply them, are superior to survey methods of forecasting
because such methods are based, at least in part, on what people have actually done
or bought, while survey methods are based on what people say, a less reliable
indicator of their future behavior.
D. Analogy
An approach often used for new product forecasting where neither statistical
methods nor observations are possible is to forecast the sales or market potential for
a new product or product class by analogy.
This method is also used for new-to-the-world high-technology products, for which
product prototypes are often either not available or extremely expensive to produce.
Rather than conduct surveys to ask consumers about their likelihood to buy a
product they can hardly imagine, forecasters consider related product introductions
with which the new product may be compared.
Limitations:
oThe new product and its pricing are never exactly like that to which the
analogy is drawn.
oMarket and competitive conditions may vary from when the analogous
product was launched. Such conditions must be taken into account.
E. Judgment
Since capable and informed judgment is required for all methods, sometimes
forecasts are made solely on the basis of experienced judgment, or intuition.
Some decision makers, even effective ones, are intuitive in their decision processes
and cannot always articulate the basis for their judgments.
Decision makers with sufficient experience in a market they know well may be
quite accurate in their intuitive forecasts. Unfortunately, it is often difficult for them
to defend their forecasts against those prepared by evidence-based methods when
the two differ.
F. Experiments and Market tests
Used largely for new consumer products, market tests such as experimental test
markets may be done under controlled experimental conditions in research
laboratories or in live test markets with real advertising and promotion and
distribution in stores.
Use of live test markets has declined over the past few decades. Experimental test
markets, on the other hand, are still commonly used.
The coming of the Internet has made possible a new kind of market test: an offer
directly to consumers on the web.
G. Other Mathematical Approaches: Chain ratios and Indices
Two additional mathematically-driven approaches to forecasting are the chain ratio
calculation or the use of indices.
Both approaches begin with an estimate of market potential.
The market potential is then multiplied by various fractional factors that, taken
together, predict the portion of the overall market potential that one firm or product
can expect to obtain.
Other quantitative methods, especially useful for new products, have also been
developed. These include conjoint analysis, a method to forecast the impact on
consumer demand of different combinations of attributes that might be included in
a new product, and methods to mathematically model the diffusion of innovation
process for consumer durables.
V. Rate of Diffusion of Innovations: Another Perspective on Forecasting
Before entrepreneurs or established marketers invest in the development and introduction
of an innovation, they want to know how rapidly the innovation is likely to be adopted by
the target market.
Diffusion of innovation theory seeks to explain the adoption of an innovative product or
service over time among a group of potential buyers. It is useful to managers in predicting
likely adoption rate for new and innovative goods or services.
A. The Adoption Process and Rate of Adoption
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.
If plotted on a cumulative basis, the percentage of people adopting a new product
over times resembles an S curve.
Generally the speed of the adoption process depends heavily on the following
factors:
oThe risk (cost of product failure or dissatisfaction)
oThe relative advantage over other products
oThe relative simplicity of the new product
othe new product’s compatibility with previously adopted ideas and behavior
oExtent to which the new product’s trial can be accomplished on a small-scale
basis
oThe ease with which the central idea of the new product can be
communicated
The rate at which an innovative new product category passes through the adoption
process in also a function of the actions taken by the product’s marketers.
B. Adopter Categories
If the time of adoption is used as a basis of classifying individuals, five major
groups can be distinguished:
oInnovators
oEarly adopters
oEarly majority
oLate majority
oLaggards
Because each category comprises individuals who have similar characteristics and
because individuals differ substantially across categories, these adopter groups can
be considered market segments.
oThus, one would use a different set of strategies to market a new product to
the early adopter group than to market it to the late majority group.
C. Implications of Diffusion of Innovation Theory for Forecasting Sales of New
Products and New Firms
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:
oRisk
oRelative advantage
oRelative simplicity
oCompatibility with current behavior
oEase of small-scale trial
oEase of communication of benefits
An innovation that is risky for the prospective user to try or buy, has little
competitive advantage, is complex or incompatible with current user behavior, and
for which it is difficult or expensive to try or to understand its benefits is likely to
face tough sledding, regardless of the attractiveness of the market.