New Product Strategy Sales Forecasting February 27, 2007.
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Transcript of New Product Strategy Sales Forecasting February 27, 2007.
Sales Potential Estimation Often used from concept test results
Assumes awareness and availability Translating “Intent” into sales potential:
Develop the “norms” carefully for a specific market and for specific launch practices
Examples: Services: 45% chance that the “definitely would
buys” actually will buy; 15% for the “probably will”s Consumer Packaged Goods: 70-80% chance that the
“definites” will buy; 33% chance for the “probably will”s
Sales Potential Estimation Translating Intent into Sales Potential
Example: Aerosol Hand CleanerAfter examining norms for comparable existing products, you determine that:
90% of the “definites” 40% of the “probables” 10% of the “mights” 0% of the “probably nots” and “definitely
nots”will actually purchase the product
Apply those %age to Concept Test results:
Sales Potential Estimation Translating Intent into Sales Potential
Apply those %age to Concept Test results: 90% of the “definites” (5% of sample) = .045 40% of the “probables” (36%) = .144 10% of the “mights” (33%) = .033 0% of the last 2 categories = .000
Sum them to determine the %age who would actually buy: .045+.144+.033= .22
Thus, 22% of sample population would buy(remember: this % is conditioned on awareness & availability)
From Potential to Forecast With Sales Potential Estimates:
To remove the conditions of awareness and availability, multiply by the appropriate percentages:
If 60% of the sample will be aware (via advertising, etc.) and the product will be available in 80% of the outlets, then:
(.22) X (.60) X (.80) = .11 11% of the sample is likely to buy
Sales Forecasts With Sales Potential Estimates A-T-A-R Models
Best used with incremental innovations
Based on diffusion theory: Awareness, Trial, Availability, Repeat
An A-T-A-R Model of Innovation DiffusionProfits = Units Sold x Profit Per Unit
Units Sold = Number of buying units x % aware of product x % who would try product if they can get it x % to whom product is available x % of triers who become repeat purchasers x Number of units repeaters buy in a year
Profit Per Unit = Revenue per unit - cost per unit
Figure 8.5
The A-T-A-R Model: Definitions
Buying Unit: Purchase point (person or department/buying center).
Aware: Has heard about the new product with some characteristic that differentiates it.
Available: If the buyer wants to try the product, the effort to find it will be successful (expressed as a percentage).
Trial: Usually means a purchase or consumption of the product.
Repeat: The product is bought at least once more, or (for durables) recommended to others.
Figure 8.6
A-T-A-R Model Application
10 million Number of owners of Walkman-like CD playersx 40% Percent awareness after one yearx 20% Percent of "aware" owners who will try productx 70% Percent availability at electronics retailersx 20% Percent of triers who will buy a second unitx $50 Price per unit minus trade margins and
discounts ($100) minus unit cost at the intended volume ($50)
= $5,600,000 Profits
Points to Note About A-T-A-R Model
1. Each factor is subject to estimation. Estimates improve with each step in the
development phase.
2. Inadequate profit forecast can be improved by changing factors.
If profit forecast is inadequate, look at each factor and see which can be improved, and at what cost.
Why Financial Analysis for New Products is Difficult Target users don’t
know. If they know they
might not tell us. Poor execution of
market research. Market dynamics. Uncertainties about
marketing support.
Biased internal attitudes.
Poor accounting. Rushing products
to market. Basing forecasts
on history. Technology
revolutions.
Getting the Estimates for A-T-A-R Model
xx: Best source for that item.x: Some knowledge gained.
Figure 8.7
Item MarketResearch
Concept Test Product UseTest
ComponentTesting
Market Test
Market Units XX X X XAwareness X X X XTrial XX X XAvailability X XXRepeat XX XConsumption X X X XXPrice/Unit X X X X XXCost/Unit X XX
Forecasters Are Often Right
In 1967 they said we would have: Artificial organs in humans by 1982. Human organ transplants by 1987. Credit cards almost eliminating currency by 1986. Automation throughout industry including some
managerial decision making by 1987. Landing on moon by 1970. Three of four Americans living in cities or towns by
1986. Expenditures for recreation and entertainment
doubled by 1986.
Forecasters Can Be Very Wrong
They also said we would have: Permanent base on moon by 1987. Manned planetary landings by 1980. Most urbanites living in high-rises by 1986. Private cars barred from city cores by 1986. Primitive life forms created in laboratory by 1989. Full color 3D TV globally available.
Source: a 1967 forecast by The Futurist journal.Note: about two-thirds of the forecasts were correct!
Forecast: Generational Shifts
Civic(Millennials)
(GI Generation)
Adaptive(Silent)
• Correct ills of Reactive• Era of prosperity and strength• Pervasive optimism• Uplifting patriotic sentiment
• Follow trends from Civic• More complacent• Head down hard work
and life enjoymentIdealist
(Boomers)• Change agents as tired of / rebel
against status quo of Adaptive• Era of volatility (economic,
political, social, etc.)
Reactive(GenX)
• Left reacting to changes initiatedby Idealists
• Often era of economic downturn• Feelings of negativity and disenfranchisement
ubiquitous
Handling Problems in Financial Analysis
Improve your existing new products process. Use the life cycle concept of financial analysis. Reduce dependence on poor forecasts.
Forecast what you know. Approve situations, not numbers Commit to low-cost development and marketing. Be prepared to handle the risks. Don’t use one standard format for financial analysis. Improve current financial forecasting methods.
Hurdle Rates on Returns and Other Measures
Hurdle RateProduct Strategic Role or Purpose Sales Return on
InvestmentMarket Share
IncreaseA Combat competitive entry $3,000,000 10% 0 PointsB Establish foothold in new
market$2,000,000 17% 15 Points
C Capitalize on existingmarkets
$1,000,000 12% 1 Point
Explanation: the hurdles should reflect a product’s purpose,or assignment. Example: we might accept a very lowshare increase for an item that simply capitalized on ourexisting market position.