Essay On Sales Forecasting

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New Product Sales Forecasting
This module covers the concepts of hierarchy of effects, awareness, availability (ACV%), trial rate, repeat purchase, and intent to behavior translation.

Authors: Paul Farris and Kusum Ailawadi
Marketing Metrics Reference: Chapter 4
© 2010-14 Paul Farris, Kusum Ailawadi and Management by the Numbers, Inc.

An Approach to Forecasting New Product Sales

OVERVIEW

Overview
• The sales forecasting approach in this presentation is based on a popular “pre-test market” model used by market research firms.
• The approach helps managers predict volume for new products.
• It is primarily used for new B-to-C and B-to-B products that are in established product categories where frequent, repeated purchase is common. Examples include:
– Packaged grocery products
– Food products
– Personal care products
– Commonly used office-supplies

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• While not as directly applicable, it may also be used for infrequently purchased new products. Examples include:
– Cars
– Electronics equipment

OVERVIEW (CONTINUED)

Overview (Continued)

• It is probably less useful for radical, new innovations that consumers find difficult to understand and for which they cannot provide information regarding their intent to purchase.

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The forecasting methodology is based on an “extended hierarchy of effects”.

1.

Consumers become aware of the new product’s existence. 2.

Retailers decide to sell the product and give it shelf-space. 3.

Consumers who are aware and have access to the product decide to try it.

4.

Consumers who have tried the product and become repeat purchasers.

AN “EXTENDED HIERARCHY OF EFFECTS”

An “Extended Hierarchy of Effects”

Repeat
Purchase
Trial Rate
Awareness
Level

Availability

We can make forecasts of share or sales by predicting rates of awareness, availability, trial, and repeat purchase. Source: Harvard Business School, “Note on Pretest Market Models,” 1988.

4

The extended hierarchy of effects forms the basis of most pretest market or simulated test market models.
• Pretest or Simulated Test Market (STM) Models like BASES,
ASSESSOR, and LITMUS, are used extensively by consumer packaged good companies to obtain reasonable sales predictions for new products, before, and sometimes instead of, test markets.
• The extended hierarchy of effects forms the backbone of most of these STM models.

EXTENDED HIERARCHY OF EFFECTS.

Extended Hierarchy of Effects

• Consumers’ trial and repeat rates are estimated in a “simulated” purchase environment. They are shown concept boards, advertising, or sometimes real products in a lab setting and asked about their interest and intent to try. This is followed by an in-home use test and a follow-up survey to estimate repeat rates.

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Definition:
Awareness = Percentage of the target market that is aware of the new product. Awareness is primarily driven by the consumer’s exposure to the product’s brand marketing message through advertising and other promotional vehicles.

2.

1.

3.

AWARENESS

Awareness

4.
Repeat

Trial
Available
Unaware

Advertising
Sampling
Couponing

Aware

For example, historical data can translate advertising spend ($) into an expected awareness rate. Source: Harvard Business School, “Note on Pretest Market Models,” 1988.

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Definition:
Availability = Percentage of retailers and other relevant sales channels that make the product available for sale to consumers. Product availability is primarily driven by trade spending and promotions to support retailers.

1.

2.

3.

AVAILABILITY

Availability

4.
Repeat

Trial
Available
Unaware

Aware

Trade promotions
Coop advertising
Source: Harvard Business School, “Note on Pretest Market Models,” 1988.

For example, historical data can translate trade spending into an expected All Commodity Volume
(ACV) %.
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TRIAL

Trial
Show More

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