http://www.ilyamirman.com/bid/37982/Quantitative-Methods-for-Sizing-Markets

1. Quantitative Methods for Sizing Markets
6/19/2003
Ilya Mirman
Vice President, Marketing
SolidWorks Corporation

2. Agenda
• Some considerations on market sizing
• Cook-book approach
• Available resources
• International market sizing
• Finding sweetspots

3. Readily-available Market Data
May Be Hard to Find
• “The data available about market
characteristics, competitors, and so
on, is frequently inversely related to
the real potential of an opportunity;
that is, if market data are readily
available and if the data clearly
shows significant potential, then a
large number of competitors will
enter the market and the opportunity
will diminish.”
Jeffrey Timmons
New Venture Creation
(©1994 McGraw-Hill)

4. Sizing Techniques
• The golden rule: no one source of info is that
reliable, or complete!
• So it’s better to use multiple approaches to
“triangulate” on the real numbers
• Metrics that correlate with usage
– Government databases
– Relevant publications’ reader studies
– Commercial databases

5. Some key questions to ask…
• Is this the primary product produced at the
customer? Or is it one of the things that facilitates
their business.
– Communications Equipment at Lucent…vs
– Packaging Machinery at Procter & Gamble
• What industries are the sweet-spots for this
product/segment?
• Is this a MARKET or a POTENTIAL MARKET?
• Do I want a worldwide overall assessment, or at
the local level?

6. Several Approaches
• Top-down
• Bottom-up
• Published reports
• Which metrics matter?
– Revenue of current competitors
– Firms
– Size of problem
• “Total Available Market” vs “Annual Spending”
• Today’s talk is focused on Total Available Market

7. Building the “Total Available Market”
(TAM) Model
1. Find a widely-available metric that correlates
with demand for your product
2. Carry out statistical analysis to identify the
scaling factor between demand and this metric
3. Get database with the metric by industry and
geography
4. Build the model
5. Verify model’s predictive power

8. 1. Find a widely-available metric that
correlates with demand for your product
• Firms in certain industries
• Employment in certain industries
• Particular occupations in certain industries
• Spending on certain categories
• Subscription bases of certain magazines
• Etc.

9. Example of metrics that correlate with
demand
Seats VS Customers
(for 50 U.S. States)
1,000
SolidWorks Seats in
State (#)
100
10
100 1,000 10,000
Mechanical Engineers in State (#)

10. Example of metrics that correlate with
demand
Seats VS Readers
(for 50 U.S. States)
1000
SolidWorks Seats in State (#)
100
10
1
0.10% 1.00% 10.00%
Trade Magazine Subscribers in State (#)

11. Example of metrics that correlate with
demand
Subscriptions VS MechEng's in Industry
10,000
ME's Employed in 3-digit SIC
1,000
100
10
10 100 1,000 10,000
AVG Subscription in 3-digit SIC

12. Example of metrics that correlate with
demand
Trade Mags' Subscribers VS ME's in State
(for 50 U.S. States)
10.00%
% of Trade Magazine's
Subscribers (%)
1.00%
0.10%
100 1,000 10,000
Mechanical Engineers in State

13. 2. Carry out statistical analysis to identify
the scaling factor between demand and
this metric
• Need not be exact
• A top-down approximation may be enough
• Primary use will be to compare relative opportunities of
various industries and geographies
• Examples:
– 1 software seat per each firm of 50+ employees
– 1 software seat per 20 workers
– 5 software seats for each mechanical engineer
– $1,000 for each $100,000 spent on fabricated metal
structures

14. Scaling Factors May Be
Industry-Specific
• Example: want to use “Employees” as the metric
• Two industries with different employment
characteristics may have 2 different scaling factors
• Example:
– Target customer: IT administrator
– Manufacturing sector: ~1 IT admin / 100 workers
– Financial Services sector: ~1 IT admin / 25 workers

15. 3. Get database with the metric by
industry and geography
• Not always obvious
• Be creative
• Be resourceful
• Here are some ideas…

16. Government Databases
• Fairly comprehensive:
– Industry
– Zip code
– State
– Firm size
• The caveats:
– Don’t distinguish between type of location (sales,
design, manufacturing, etc.);
– Don’t provide names of firms;

17. Commercial Databases
• Harris Infosource http://www.harrisinfo.com/
• OneSource http://www.onesource.com/
• Corptech http://www.corptech.com/
• Thomas Register http://www.thomasregister.com/
• InfoUSA http://www.infousa.com/
• The Problem: incomplete databases (not all firms
are included). Nonetheless, good for relative
market sizing.

18. Useful Websites
• U.S. Census Bureau http://www.census.gov/
• The 1997 Economic Census http://www.census.gov/prod/www/abs/97ecmani.html
• 1997 Economic Census Reports http://www.census.gov/epcd/www/ec97stat.htm#SUBJECT
• Industries Ranked by Growth http://www.census.gov/epcd/ec97sic/RANKUSD.HTM
• Statistics by US State http://www.census.gov/epcd/www/97EC31.HTM
• Massachusetts statistics http://www.census.gov/epcd/www/97EC_MA.HTM
• U.S. Bureau of Labor Statistics http://www.bls.gov/oes/1998/oessrch.htm
• Industry Quick Reports http://factfinder.census.gov/servlet/IQRBrowseServlet?_ts=73639935829
• Bureau of Economic Analysis http://www.bea.gov/bea/uguide.htm
• Census Bureau’s CD/ROMs http://www.census.gov/mp/www/rom/msrom.html#County
• County Business Patterns http://censtats.census.gov/cbpsic/cbpsic.shtml
• International Statistical Agencies http://www.census.gov/main/www/stat_int.html
• Department of Commerce http://www.commerce.gov/economic_analysis.html
• Economic Census Reports http://www.census.gov/epcd/www/econ97.html
• Related Census Sites http://www.census.gov/main/www/stat_fed.html
• State of the Nation http://www.stat-usa.gov/econtest.nsf
• Trade Data http://www.stat-usa.gov/tradtest.nsf
• Census Bureau Access Tools http://www.census.gov/main/www/access.html
• Business Counts in a Particular SIC Code http://www.melissadata.com/Lookups/sic.asp?
• Audits of Business Publications http://www.bpai.com/index.htm

19. Published reports (hardcopy, PDF)
Structured databases (.XLS and .DBF)

20. Published reports (hardcopy, PDF)
Structured databases (.XLS and .DBF)

21. Free from the Government:
Amazingly Detailed Data

22. Free from the Government:
Amazingly Detailed Data

23. Free from the
Government:
Amazingly
Detailed Data

24. Getting Demographics from
Industry Publications’ Audits
http://www.bpai.com/index.htm

25. Subscribers: By Industry

26. By
Geography

27. Simple Database Manipulation

28. 4. Build the Model
• Could be a simple 1-parameter formula, or a more
complex multi-factor model
• Driven by:
– Who will use it?
– How?
– Required accuracy?
– Relative market assessment?
– By geography?
– By industry?
– Sales territory assignment?
– Product development/investment decisions?

29. Building the Model: Which Industries
Matter?
• Need to filter out irrelevant industries!
• A good starting point is your current customers or
prospects
• Dun & Bradstreet can append company
demographic information to your customer data:
– Size
– Revenue
– Standardized categories of line of business, SIC
codes
– Etc.

30. The Categories
• No one universal way to categorize companies,
markets, segments
• Most companies do more than one thing!
• Categorization approaches
– Text descriptions
– Structured codes (SIC, NAICS, others)
– SIC is most popular, being gradually replaced

31. SIC Code Primer
• SIC Codes are 2-, 3-, and 4-digit codes that refer to progressively
detailed industry classifications.
• In the example below, we see how the 2-digit SIC Code #35 can be split
into several 3-digit categories, and how one of them (#356) can be
further split into seven more – each one with more detail.
30 Rubber And Misc. Plastics Products 351 Engines and Turbines
31 Leather And Leather Products 352 Farm and Garden Machinery 3561 Pumps and pumping equipment
32 Stone, Clay, And Glass Products 353 Construction and Related Machinery 3562 Ball and roller bearings
33 Primary Metal Industries 354 Metalworking Machinery 3563 Air and gas compressors
34 Fabricated Metal Products 355 Special Industry Machinery 3564 Blowers and fans
35 Industrial Machinery And Equipment 356 General Industrial Machinery 3565 Packaging machinery
36 Electronic & Other Electric Equipment 357 Computer and Office Equipment 3566 Speed changers, drives, and gears
37 Transportation Equipment 358 Refrigeration and Service Machinery 3567 Industrial furnaces and ovens
38 Instruments And Related Products
• Further still, 3565 (Packaging Machinery) can be broken down further,
by product code; Examples:
– 35651-23: Cartoning & Multipacking Machinery
– 35651-27: Paper, Film & Foil Wrapping Machinery
– 35651-45: Capping, Sealing & Lidding Machinery
– Etc.

32. Sample Industry Breakdown of
Customer Database
358 - Refrigeration
• Typically, just and Service
Machinery Other
a few SIC 362 - Electrical
Industrial
354 - Metalworking
codes are Apparatus
366 -
Machinery
relevant, Communications
Equipment
making the 371 - Motor
Vehicles and
356 - General
Industrial
Equipment
database 372 - Aircraft and
Machinery
Parts
work simpler
353 - Construction
and Related
Machinery 367 - Electronic
Components and
Accessories
355 - Special
Industry Machinery
382 - Measuring 359 - Industrial
and Controlling Machinery
Devices

33. Example 1
• Opportunity
Predictor at the 5-
digit ZIP level
• Works for single
ZIP code, or a
range

34. Example 2
• Labor workforce comparison across 6 industries
Machinists
Employment Across Six Industries
100% Maintenance and Repair
Workers
Mold Makers and Operators
80%
Cutting, Punching, and Press
Machine Operators
Employees
Electronic Equipment Assemblers
60%
Welders, Cutters, Solderers, and
Brazers
40%
Inspectors, Testers, Sorters,
Samplers, and Weighers
Engineering Managers
20%
First-Line Supervisors/Managers
0%
Motor Plastics Electronics Fabricated Aircraft Medical Team Assemblers
Vehicles Products Structural and Parts Products
Metal
Products

35. Example 3
• Engineers by state

36. 5. Verify model’s predictive power
• Don’t release unproven data!
• Find opportunities predicted by the model
• Real Example (medical product manufacturers):
1. Predicted opportunity within 3-digit ZIP codes
(based on government database)
2. Randomly picked several locations with high
predicted opportunity, verified presence of medical
manufacturers with Harris Infosource
3. Overlayed current medical customers as double-
check
Let’s take a look…

38. International Market Sizing
• Rule of thumb: USA is 30-40% of world market
(Europe is 40%, Japan+Asia/Pacific~20%)
• Alternative approach:
1. Find widely-available metric that drives market
opportunity
2. May need to adjust by country-specific factors
(e.g., per-capita GDP)

39. Looking for sweet spots in your base
Question:
• After being in business for 5 years, you have:
– 1,000 customers in industry A
– 2,000 customers in industry B
• A new telesales person is starting tomorrow.
Which industry should she call into?

40. …It depends…
Several considerations:
• Product/industry fit
• Current industry spending
• Industry size
• Channel fit
• Geographic channel performance