Sizing, Segmenting, and Forecasting Markets
Upcoming SlideShare
Loading in...5
×
 

Sizing, Segmenting, and Forecasting Markets

on

  • 1,004 views

Business is driven by accurately defining how many customers there will be for your product over time, how much they are willing to pay over time, and what will make them break their current habits to ...

Business is driven by accurately defining how many customers there will be for your product over time, how much they are willing to pay over time, and what will make them break their current habits to pay for your product. Then throw in a healthy dose of competition and the concept of “market windows.” Top-level requirements and persona prioritization are derived from these fundamental definitions.

Statistics

Views

Total Views
1,004
Views on SlideShare
1,002
Embed Views
2

Actions

Likes
2
Downloads
25
Comments
0

1 Embed 2

http://www.slideshare.net 2

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

CC Attribution-NonCommercial-ShareAlike LicenseCC Attribution-NonCommercial-ShareAlike LicenseCC Attribution-NonCommercial-ShareAlike License

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Sizing, Segmenting, and Forecasting Markets Sizing, Segmenting, and Forecasting Markets Presentation Transcript

  • 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!