Market Potential and Sales Forecasting 103 2017 Forecasts

  • Slides: 25
Download presentation
Market Potential and Sales Forecasting 10/3, 2017

Market Potential and Sales Forecasting 10/3, 2017

Forecasts versus Potential Expectations Possibilities Firm/Brand Sales Forecast Sales Potential Category Market Forecast Market

Forecasts versus Potential Expectations Possibilities Firm/Brand Sales Forecast Sales Potential Category Market Forecast Market Potential

Major Uses of Potential Estimates u To Make Entry/Exit Decision u To Make Resource

Major Uses of Potential Estimates u To Make Entry/Exit Decision u To Make Resource Level Decisions u To Make Location and Other Resource Allocation Decisions u To Set Objectives and Evaluate Performance u As an Input to Forecast

New or Growing Product Potential u Relative Advantage u Compatibility u Risk u Role

New or Growing Product Potential u Relative Advantage u Compatibility u Risk u Role of Analogous Products

Mature Product Potential u For a consumable product, repurchasing will be in proportion to

Mature Product Potential u For a consumable product, repurchasing will be in proportion to the market need (if an industrial product) or usage rate (if a consumer product). u For a durable product, repurchasing will occur to replace a worn-out product, to upgrade to get new features, or, importantly, to add an additional model.

Methods of Estimating Market and Sales Potential u Analysis-Based Estimates – Determine the potential

Methods of Estimating Market and Sales Potential u Analysis-Based Estimates – Determine the potential buyers or users of the product – Determine how many are in each potential group of buyers defined by step 1 – Estimate the purchasing or usage rate u Area Potential – Breaking down total sales by area – To use a weighted index u Sales Potential

Analysis-Based Estimates u u u During the 1990 s, an average 4 million babies

Analysis-Based Estimates u u u During the 1990 s, an average 4 million babies were born annually in the United States The average child goes through 7, 800 diapers in the first 130 weeks of life (2. 5 years) until toilet training, or 60 per week The annual market potential for disposable diapers is 28. 7 billion [(2. 3)(4 million) babies][60 diapers/week][52 weeks/year]

Area Potential u u An index approach for a hypothetical new copying system might

Area Potential u u An index approach for a hypothetical new copying system might be as follows: Bases: – – – – – u Percent population in the region (P) Percent schools in the region (S) Percent retail business in the region (RB) Percent banks in the region (B) Percent offices in the region (O) Percent warehouse in the region (WH) Percent manufacturing facilities in the region (MF) Percent other businesses in the region (XS) Percent other copier sales in the region (CS) Index = W 1 P+W 2 S+ W 3 RB+W 4 B+W 5 O+W 6 WH+W 7 MF+W 8 OB+W 9 XS+W 10 CS

Demand Analysis u Demand for products or services can be measured at two levels

Demand Analysis u Demand for products or services can be measured at two levels – aggregate demand: for an entire market or country – company demand: represented by actual sales u Both market and sales potential can be viewed as a filtering process (Robinson 1984) – – – Potential need Felt need Potential demand Effective demand Market demand Sales potential

Analysis by Inference Market assessment by inference uses available facts about related products or

Analysis by Inference Market assessment by inference uses available facts about related products or other foreign markets as a basis for inferring the necessary information for the market under study u Related products u Related markets’ size u Related environmental factors u Analysis of demand patterns u

Cross-Sectional Comparison u u The assumption that there is an analogy between the relationship

Cross-Sectional Comparison u u The assumption that there is an analogy between the relationship of a factor and demand for a particular product or commodity in two countries Let – XA = demand for product X in country A – YA = factor that correlates with demand for product X in country A, data from country A – XB = demand for product X in country B – YB = factor that correlates with demand for product X in country A, data from country B u If we assume that : XA/YA = XB/YB u and if XA, YA, and YB are known, we can solve for XB as follows: XB = (XA)(YB)/YA

Displacing Time u u u Displacing time is a useful method of market analysis

Displacing Time u u u Displacing time is a useful method of market analysis when data are available for two markets at different levels of development The assumption that an analogy between markets exists in different time periods Let – XA 1 = demand for product X in country A during time period 1 – YA 1 = factor associated with demand for product X in country A during time period 1 – XB 2 = demand for product X in country B during time period 2 – YB 2 = factor or factors correlating with demand for product X in country A and data from country B for time period 2 u If we assume that : XA 1/YA 1 = XB 2/YB 2 u and if XA, YA, and YB are known, we can solve for XB as follows: XB 2 = (XA 1)(YB 2)/YA 1

Market Size Assessment u When using market size estimates, keep the following rules in

Market Size Assessment u When using market size estimates, keep the following rules in mind: – Use several different methods. – Don’t be misled by numbers. – Don’t be misled by fancy methods. – Do a sensitivity analysis by asking what-if questions. – Look for interval estimates with a lower and upper limit rather than for point estimates.

Major Uses of Sales Forecasting u To answer “what if” questions u To help

Major Uses of Sales Forecasting u To answer “what if” questions u To help set budgets u To provide a basis for a monitoring system u To aid in production planning u By financial analysts to value a company

Forecasting Methods (I) u Judgment-Based – – Methods Naïve Extrapolation Sales Force Composite Jury

Forecasting Methods (I) u Judgment-Based – – Methods Naïve Extrapolation Sales Force Composite Jury of Expert Opinion Delphi Method

Delphi Forecasting Questionnaire Expert panel selection Formulation of first round questionnaire Data feed-in (Numerical

Delphi Forecasting Questionnaire Expert panel selection Formulation of first round questionnaire Data feed-in (Numerical & graph) Distribution and collection of responses Statistical analysis Formulation of second round questionnaire Distribution and collection of response Edit relevant opinion Statistical analysis Data requested for search, collect, edit Distribution and collection of response Statistical analysis Final estimation and circulation

Forecasting Methods (II) u Customer-Based Methods – Market Testing Mall Intercept Surveys F Focus

Forecasting Methods (II) u Customer-Based Methods – Market Testing Mall Intercept Surveys F Focus Groups F Product Concept Tests F – Market Surveys The top-two-boxes scores (the number of customers who state they will either definitely or probably buy the product) F Purchase intentions and actual behavior F

The Top-Two-Boxes Score u The number of people who definitely would buy or probably

The Top-Two-Boxes Score u The number of people who definitely would buy or probably would buy are usually combined and used as an indicator of group reaction – – – Definitely would buy Probably would buy Might or might not buy Probably would not buy Definitely would not buy

Estimating the Quantity u The quantity of the product expected to be sold during

Estimating the Quantity u The quantity of the product expected to be sold during a time period is Q: – Q=N A P – N: the number of potential customers expected to make purchases during the time period – A: the fraction of these potential customers or purchases for which the product is available and the customer is aware of the product – P: the probability that the product is purchased if available and if the customer is aware of it. F P = Cdefinitely Fdefinitely + Cprobably Fprobably

Forecasting Methods (III) u Sales Extrapolation Methods – Moving Averages – Exponential Smoothing –

Forecasting Methods (III) u Sales Extrapolation Methods – Moving Averages – Exponential Smoothing – Regression Analysis

Forecasting Methods (IV) u Model-Based Methods – Regression Analysis – Leading Indicators – Econometric

Forecasting Methods (IV) u Model-Based Methods – Regression Analysis – Leading Indicators – Econometric Models

The A-T-A-R Model u The A-T-A-R concept (awareness-trialavailability-repeat) u Diffusion of innovation u How

The A-T-A-R Model u The A-T-A-R concept (awareness-trialavailability-repeat) u Diffusion of innovation u How we forecast sales and profit on a new item

The A-T-A-R Model Profit = Unit sold * Profit per unit Unit sold =

The A-T-A-R Model Profit = Unit sold * Profit per unit Unit sold = Number of buying units * Percentage who become aware of the product * Percentage who opt to try the product if they can get * Percentage of intended triers who can get the product (it is available to them) * Percentage of triers who like the item enough to repeat their purchase * Number of units that repeaters will buy in a year Profit per unit = Revenue per unit (unit list price less trade margins, promotional allowances. Freight, etc. ) - Costs per unit (usually costs of goods sold per plus direct marketing costs) Therefore: Profits = Buying units * Percent aware * Percent trial * Percent availability * Percent repeat * Annual units bought * (Revenue per unit - Costs per unit)

A-T-A-R and the Market Testing Methods Information Needed by the A-T-A-R Profit Forecasting Method

A-T-A-R and the Market Testing Methods Information Needed by the A-T-A-R Profit Forecasting Method Number of market units Awareness of the new product positioning claim (A) Decides to try the item (T) Is able to get a trial supply (A) Likes it and wants more (R) Units used per year Profit per unit (price-cost) Additional diagnostic info. Sources of This Information Pseudo sale methods Market Research studies Controlled sale methods Full sale methods Market Research studies Yes Ad agency provides it Yes Yes Distribution estimates provided by sales dept. Yes--in sales wave Yes--est. Price plan plus estimates from accounting on costs Yes--a little Distribution estimates provided by sales dept. Yes Team estimates Yes--est. Price plan plus estimates from accounting on costs Yes--more Yes Yes--tons