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Sizing, Segmenting, and Forecasting Markets  Paul Teich Business Strategy
Market research Quantitative – what, where, when Facts Ask people closed questions (yes/no, how many, what date, …) Qualitative – why, how Opinion, attitude Ask people open-ended questions Then ask to follow them around for good measure…
Quantitative Primary (do it yourself) Design survey to find out exactly what you need to know Compromise on subset that you can afford Secondary Someone else has already  gathered some or all of the data you need as a product or service It’s probably less expensive than DIY
Quantitative Sources Ask people in your industry who they use Market analyst data sets and PR Competitor PR Governments Libraries Especially school libraries Like UT, for instance
Qualitative Expert opinion Ethnography Focus groups Talk to people No, really, find some people to talk to…
Qualitative Sources Ask people in your industry who they use Market analyst reports and press releases Charities Political action committees
Segmentation People (B2C) Demographic – population characteristics  Behavioral – loyalty, purchase patterns Psychographic – personality, values, attitudes, interests, lifestyles Organizations (B2B) Firmographic – characteristics of orgs
Successful segmentation Segments are measurable Qualitative data can be economically collected Segments are substantial Market is usefully subdivided Homogeneity within each segment  Constituents are enough alike that they behave as a flock (for key attributes) Heterogeneity between segments  Flocks are different enough to tell apart
Market sizing TAM – Total Available Market How many potential customers are there? SAM – Served Available Market How many (of the total) are already buying a similar or competing product? SOM – Share of Market What % of the market does each product or competitor account for?
Market forecasting In order to forecast your market…      …you must have a history
Historic time series More than two data points Buy or find secondary market data… It must be appropriate to your segmentation Ideally, history is >2x the timeframe you want to forecast 5 year forecast implies 10 year history Look for patterns in historic data Yes, this is statistics + art
Insert your forecast here What are you forecasting? How far are you willing to go? History and forecast must look like a continuous time series No “miracle occurs here” jumps Humans are very good at pattern recognition, they will call BS if the curve looks wrong
Technology and product adoption Large body of existing knowledge and best practice But it’s mostly pay per view Start with Wikipedia  “technology adoption lifecycle” “forecasting”
Thank You PCA Sponsors!

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Sizing, Segmenting, and Forecasting Markets

  • 1. Sizing, Segmenting, and Forecasting Markets Paul Teich Business Strategy
  • 2. Market research Quantitative – what, where, when Facts Ask people closed questions (yes/no, how many, what date, …) Qualitative – why, how Opinion, attitude Ask people open-ended questions Then ask to follow them around for good measure…
  • 3. Quantitative Primary (do it yourself) Design survey to find out exactly what you need to know Compromise on subset that you can afford Secondary Someone else has already gathered some or all of the data you need as a product or service It’s probably less expensive than DIY
  • 4. Quantitative Sources Ask people in your industry who they use Market analyst data sets and PR Competitor PR Governments Libraries Especially school libraries Like UT, for instance
  • 5. Qualitative Expert opinion Ethnography Focus groups Talk to people No, really, find some people to talk to…
  • 6. Qualitative Sources Ask people in your industry who they use Market analyst reports and press releases Charities Political action committees
  • 7. Segmentation People (B2C) Demographic – population characteristics Behavioral – loyalty, purchase patterns Psychographic – personality, values, attitudes, interests, lifestyles Organizations (B2B) Firmographic – characteristics of orgs
  • 8. Successful segmentation Segments are measurable Qualitative data can be economically collected Segments are substantial Market is usefully subdivided Homogeneity within each segment Constituents are enough alike that they behave as a flock (for key attributes) Heterogeneity between segments Flocks are different enough to tell apart
  • 9. Market sizing TAM – Total Available Market How many potential customers are there? SAM – Served Available Market How many (of the total) are already buying a similar or competing product? SOM – Share of Market What % of the market does each product or competitor account for?
  • 10. Market forecasting In order to forecast your market… …you must have a history
  • 11. Historic time series More than two data points Buy or find secondary market data… It must be appropriate to your segmentation Ideally, history is >2x the timeframe you want to forecast 5 year forecast implies 10 year history Look for patterns in historic data Yes, this is statistics + art
  • 12. Insert your forecast here What are you forecasting? How far are you willing to go? History and forecast must look like a continuous time series No “miracle occurs here” jumps Humans are very good at pattern recognition, they will call BS if the curve looks wrong
  • 13. Technology and product adoption Large body of existing knowledge and best practice But it’s mostly pay per view Start with Wikipedia “technology adoption lifecycle” “forecasting”
  • 14. Thank You PCA Sponsors!