This document discusses techniques for transforming customer information into sales knowledge and forecasting. It covers key elements like knowledge gathered by sales forces, forecasting processes, ethics in sales management, and forecasting techniques. Some techniques discussed include using customer and distributor surveys, statistical models, judgment-based approaches like executive opinions, and combining multiple forecasting methods to improve accuracy. The document also notes limitations of forecasting like data quality, rapid market changes, and forecasting time horizon and costs.

1. TransformaTion of
cusTomer informaTion
inTo sales knowledge

2. group members
Zumair Zahid
sana akbar
saba sheikh

3. key elemenTs
• Knowledge gather by firms sales forces
• Sales forecasting
• Ethics in sales management
• Forecasting process
• Forecasting techniques
• Limitation of forecasting
• Guidelines for forecasting

4. knowledge generaTed by The
firm sales force
• Customer knowledge competence
• Customer data integration
• Data mart

5. • Manufacturing
• Product development
• Finance and accounting
• Marketing
• Sales management
• Human resources

6. sales forecasTing
• Market potential
• Sales potential
• Sales forecast

7. • Derived demand
• Elasticity
• Inelastic demand

8. eThics in sales
managemenT
• An educated guess!!
• Sales forecast effects
• Sales forecast influencing suppliers
forecast and stock prices

9. Ethics in salEs
• Wrong forecast to increase sales
• A few examples
• Mattel booking tentative orders
• Enron’s spiral downward for continued
growth
• And an unknown company taking fake
orders

10. factor Influence potential
Economy Economic influences can make market potential greater or
smaller; e.g china’s increased manufacturing base
Technology New technology can create substitute products, e.g new
drilling technology
Legal &
regulatory
Laws can make products illegal; increase the costs
associated with the product
Social factor Changes in fashions & trends affect demand. E.g trans fat
Demographic
trends
Demographic trends can shift demand. E.g baby boomers
Factors that aFFEct
markEt potEntial

11. ForEcasting procEss
Look at the market place:
Economic, technological,
government & legal,
social & demographic
factors
Estimate the market
potential for industry
External info
•Customer &
distributor surveys
•Market research
conducted by
other firms
•Government-
generated info
related to
economy
•Experts’ opinions
Internal info
Info generated
by quantitative
methods using
sales data
Sales mgrs’
estimate for
their team
Reps’
estimates of
their sales
Executives’
opinions
Firm’s plans

12. ForEcasting procEss
Forecast sales by product, territory, customer type,
and time period
Make a company wide sales forecast for the
period
Set quotas for individual territories & regions
for the period

13. is ForEcasting Easy?
• 70% of sales organizations have CRM
systems
• 60% of sales leaders want to improve
forecasting processes
• 50% have difficulty adjusting to market
changes
• 49% have difficulty identifying best sales
practices and sharing those

14. ForEcasting mEthods
• Many different statistical tools are there to measure forecast:
• Time series techniques also known as naïve forecast
• determining the rate sales have grown in the past and using that to
estimate future sales
• Adjustments
– Moving average: rate of change for past few periods is
averaged
– Exponential smoothing: type of moving average that puts
more emphasis on the most recent period.

15. ForEcasting mEthods
• Correlational analysis: form of trend analysis, forecasts are based
on trends of other variables
– Leading indicator: variable that happens before sales of the
company’s product (housing starts)
– Regression analysis: includes a number of variables; influence
of each variable is estimated and weighted, and effects are
summed to provide a single estimate of sales
– Consumer spending correlates: variables that predict how
much consumers will spend overall (Consumer Confidence
Index)
– Business spending correlates: variables useful to business in
correlational analysis

16. rEsponsE modEls
• sophisticated statistical models that
examine how customers respond to sales
and marketing strategies

17. MARKET TEST
• A market test is an experiment in which a
company launches an offering in a limited
market in order to learn how the market will react
to the product.
• DRAWBACKS:
 Alert your competitors to the new offering.
 They can then undertake actions like price
cuts…

18. JUDGMENT TECHNIQUES
Some techniques involve judgments by
someone of the actual forecast and
considered as JUDGEMENT
TECHNIQUES.
Judgment techniques include:
Executive opinions
Expert opinions
Customer and channel surveys
Sales force composite

19. EXECUTIVE OPINION
It is simply the best-guess estimates of a
company’s executives.
DISADVANTAGES:
Opinions are possibly biased.
Factors within the organization can also
lead to judgmental bias.

20. EXPERT OPINION
Expert opinion is as similar as Executive
Opinion. The difference is that the expert is
usually someone outside of the company.
In many cases, expert opinions along with
executive opinions are used as a
combination to forecast sales.
As a sole method of forecasting, expert
opinions are not always useful.

21. CUSTOMER AND CHANNEL
SURVEYS
In some markets, including CRM software market,
research companies ask customers how much
they plan to spend in the coming year on certain
products. They are costly as well.
Channel surveys are much more similar,
manufacturers ask their distributors or retailers
how much they expect to sell.

22. SALES FORCE COMPOSITE
In this method, we ask members of our sales force
what they think they can sell. Though sales people
are often not aware of the company’s plans to
introduce new products, promotions or new pricing
strategies.
A more common approach is to use sale force
composites for shorter-range forecasts.
Companies use other methods to forecast sales
for longer-range forecasts.

23. LIMITATIONS OF
FORECASTING
Data Quality
Rapid Change
Length of The Horizon
Time and Cost

24. DATA QUALITY
• One major factor affecting forecasting
accuracy is the quality of data used to
forecast. If the customer data set does not
combine all locations of customers
together, then the estimates of market
segments could be way off. CDI is
important for data quality.

25. RAPID CHANGE
• The best forecasts are usually those that
include as much information as possible.
That means using as many methods as
possible and creating multiple forecasts
for multiple conditions.

26. LENGTH OF THE HORIZON
• The longer the forecasting horizon is, the
less accurate the forecast is likely to be.
The same is true for sales executives,
accurately estimating next week’s sales
might be relatively easy but accurately
estimating sales for the next five years is
much more difficult.

27. TIME AND COST
• Forecasting takes time. The longer it takes
to get a forecast, the less you have to act
on that information. Forecasting also costs
money.

28. GUIDELINES FOR
FORECASTING
Forecasting is not an exact science. There are guidelines
that can improve the quality of forecast. Following are
some guidelines:
USE MULTIPLE METHODS:
One way to achieve more accurate forecasts is to use
multiple methods. The first time a manager creates a
forecast, it might be wrong but the second time, it will likely
be accurate because the second time you do anything, you
usually do it better than the first time.
PICK THE RIGHT METHODS FOR YOUR BUSINESS:
Picking the right method for the business is so much
important.

29. USE AS MUCH INFORMATION AS
YOU CAN
Use as much information as you can to generate forecasts.
Using more information results in a more accurate final
forecast.
PLAN FOR MULTIPLE SCENARIOS:
We should plan for multiple scenarios in order to cater
changing environmental factors. So that you can adjust
your sales estimates based on what actually happens.
TRACK YOUR PROGRESS AND ADJUST THE
FORECAST:
As time goes on, forecasts should be adjusted to reflect
reality.