Download
1 / 37
370 likes | 382 Vues
Global Insight Practical Approaches to Forecasting Consumer Markets. Presented by: Joyce Brinner, Senior Principal Global Insight Advisory Services. Today’s Agenda. The Modeling & Forecasting Process Objectives Keys to success The model development process Fundamental principles
E N D
Global Insight Practical Approaches to Forecasting Consumer Markets Presented by: Joyce Brinner, Senior Principal Global Insight Advisory Services
Today’s Agenda • The Modeling & Forecasting Process • Objectives • Keys to success • The model development process • Fundamental principles • Sample Methodologies
Objective of Consumer Market Modeling Develop a tool that: • Improves the accuracy of sales/market forecasts, • Is easy to use, • Provides improved understanding of how sales/markets are influenced by company, market, or economic factors, • Solves the puzzle.
Objective -- Comprehensive Methodology Database integration, statistical analysis, and econometric modeling capture the complex relationships between market characteristics and market size. Macroeconomic Analysis Household Demographics Consumer Segmentation Consumer Market Demand/Sales
Key to a Successful Model To be successful a model must be accurate in terms of: • Inclusion of the appropriate concepts, • Representation of true timing of reactions, • Determination of appropriate magnitudes of the coefficients. And model/forecast users must have complete comfort with these three considerations.
Identify Potential Demand Drivers Economic Factors Demographic Factors Regulatory Factors Market Factors
Identifying Turning Points Can Make You a Hero • Try to identify leading indicators or high-frequency economic concepts that will allow the model to identify turning points. • When structuring high-frequency models, choose as model inputs those concepts that are reported in a timely fashion (unless impact with a lag). • Important model drivers whose forecasts are highly uncertain can be used to put bounds around the forecast. • A single set of forecasts is not adequate for a highly volatile industry.
Example: Factors contributing to apparel demand growth – falling prices and economic recovery Inflation Adjusted Apparel Prices Unemployment Rate (*) Consumer Confidence Population Per Capita Disposable Income Per Capita HH Net Worth Compound Annual Growth Rate, 2002-07 Source: Global Insight
Lag Responses: Eventually, Spending Growth Comes Into Line With Income Growth (Percent change from a year earlier of four-quarter moving average)
Household Demographics Population and Households by: • Life Stage • Age ranges / generations • Income ranges • Race / ethnicity and other characteristics
Population by Age Group and Gender in the U.S. • The 50+ population segment is the largest and fastest growing segment over the 2003-2007 forecast period. • The 14-17 and 18-24 population segments experience above average population growth over the forecast period. • Growth in the 35-49 population segment turns negative after posting strong positive growth in the 1990s. • The 25-34 population segment increases slightly after declining in the 1990s. • The teens and infants population segment remains relatively stable.
Population Growth By Gender and Age Cohort Compound Annual Growth Rate, 2002-07 Share of Total Population Source: U.S. Department of Commerce, Bureau of the Census.
Product 1 Product 2 Product 3 Product 4 Product 5 Product 6 Product 7 Product 8 15-19 20-24 25-29 30-44 45-54 55-64 Identify the Target Market for Each Product • Each product has a different target market. The different target populations need to be incorporated into the models.
Impact of the Echo Boom – U.S. versus Canada • Cross-country differences in market dimensions, such as demographics, can have a strong impact on your international strategies. • For example, in Canada, the “echo boom” (resulting from the baby boom having children) was more muted and will fade strongly over the next ten years. • In the US, the boom will not fade - supported by higher rates of fertility, especially in the Hispanic and African-American population. Population, Aged 5 to 14
Fundamental Principles of Forecast Modeling • Examine the data • Data are dumb. You must be smart • Government data should always be used to check trade association or market research data • Don’t blur price and volume responses • Benchmark your results against relevant experience
Examine the data • Look for probable errors and discontinuities • The sample should not extend across fundamentally different behaviors that cannot be modeled with the same structure • The sample should not include extreme values if the model assumes linear responses • Be alert for penetration curve phenomena
Data are dumb. You must be smart • Structural modeling is most trustworthy • Search for causation, not correlation • Be clear whether you are modeling demand or supply – only one per equation • T-statistics are often misinterpreted • T’s measure precision of estimate, not whether a factor is important • Multicolinearity must be dealt with through constraints, not exclusion of good factors
Use government data to check trade association or market research data • Government is careful to provide consistent consumer demand/price series over time. • Government is more careful about price and volume separation • However, government imputations and quality adjustments must be used with care
Don’t blur price and volume responses • Real spending responds to real income, often with elasticity far greater than 1 • The price of purchased goods tends to move in 1:1 unison with generic prices • Thus estimating nominal spending versus nominal income will produce an erroneous elasticity that is a composite of these two • Check separately for own-price and cross-price elasticities • Think through the probable lags
Benchmark results against relevant experience • Counter-intuitive elasticities are usually a sign of spurious correlation, data errors, or multicolinearity problems • Short-run income elasticities should be high for discretionary goods, particularly items that consumers can postpone purchasing • Price elasticities should be high when close substitutes are available • Demographic factors, often trend-like, are easily confused with penetration curves
Sample Methodologies Sample Methodologies
Detailed Product Demand Modeling Case Study 1 • The following case study presents the methodology of an actual product demand modeling assignment. The actual product or service cannot be identified for reasons of confidentiality. • A market research company provided product sales history by male/female, 8 age groups, 20 product categories, 10 channels, and 2 income categories. • Time series history was limited and samples were not consistent over time.
Case Study 1 Product sales projections by gender, age, product category, channel, and income are generated in five steps. Each step is a further disaggregation of the sales projections from the previous step. Step 1. Generate aggregate product sales projections for 3 gender/population segments (men & boys, women & girls, infants) consistent with Department of Commerce aggregate product trends and the U.S. economic environment. Step 2. Generate aggregate product sales by gender and all age segments consistent with population growth and spending intensity in each of the age segments.
Case Study 1 Step 3. Generate product sales by gender, age and detailed product categories consistent with Department of Commerce Consumer Expenditure Survey product trends and qualitative product trends. Step 4. Generate product sales by gender, age, product and channel consistent with Global Insight’s channel growth projections. Step 5. Generate product sales by gender, age, product, channel and income screen consistent with Global Insight’s household income distribution projections.
Market Penetration Modeling Case Study 2 • The following case study presents the results of an actual market penetration modeling assignment. The actual product or service cannot be identified for reasons of confidentiality. • A number of products and services lend themselves particularly well to our approach --- cable TV, satellite TV, new consumer technology products. These are products that have moved beyond the early rapid adoption phase of the product or technology lifecycle.
Case Study 2 Taiwan follows Japan Thailand Follows Taiwan China and India Follow Thailand
