This document discusses various quantitative and qualitative market research methods for sizing, segmenting, and forecasting markets. It describes collecting primary or secondary quantitative data through surveys or existing data sets to understand what, where, when questions factually. Qualitative research involves open-ended questions to understand why and how through expert opinion, ethnography, or focus groups. The document outlines demographic, behavioral, and psychographic segmentation of people markets and firmographic segmentation for business-to-business markets. It provides guidance on market sizing, determining market share, and producing forecasts based on analyzing historical time series data patterns.
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?
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”