When you try to analyze something, one of the most important thing is to have hypothesis or goal that you want to see as the outcome. If you do not have any hypothesis or goal, you would not know what kind of data you should pull from database. For CRM/SFA data, I believe we can find some “hints” for future opportunities by seeing the data by industry, company size, deal size and sales stage etc. This presentation will explain how to analyze data that can be useful for planning.

1. Sharing ideas for better strategy, planning and results to grow SaaS business in Japan
How to analyze CRM/SFA
Data to enhance your
planning
japanarr.com

2. How to analyze CRM/SFA Data
When you try to analyze something, one of the most important thing is to have hypothesis or goal
that you want to see as the outcome. If you do not have any hypothesis or goal, you would not
know what kind of data you should pull from database.
For CRM/SFA data, I believe we can find some “hints” for future opportunities by seeing the data
by industry, company size, deal size and sales stage etc.
This presentation will explain how to analyze data that can be useful for planning.
*Data is all dummy

3. 1. Export data from CRM/SFA: Make sure to include all
the field you need to analyze
2. Process the data: This step helps to make easier to
visualize the roudome data to the “hint”
3. Make graphs: Visualize your data!
3 steps to find “hint”

4. Export data from CRM/SFA
Opportunity Account Industry
# of Employees
Sales Stage
ACV Ammount
Closed Date
Opportunity
Type
In the CRM/SFA, there are a bunch of data. You need to pull the right data having “what you want
to see”(hypothesis or goal) in your mind.
For this analysis, I recommend to pull the data tied up to “opportunity”. By pulling the data for all of
following field will help you analyze by industry, employee size and opportunity type. in most of the
case, you can find the “hint” with these explicit view as the first step of your planning. (Make sure
the closed date should be past in this analysis.)
The data fields you need to include
Age

5. Export data from CRM/SFA
Your data should looks like this. And now, you need to process some of the field to help visualize.
For this analysis, I recommend to convert the specific number of each field, with red circle in the
following capture, to aggregated range.
*Data is all dummy

6. Process the data
# of Employees
ACV Ammount
Closed Date
Age
How to aggregate and each range should be tied up to your company strategy(especially for the #
of Employees and ACV amount) so that the following is just one of the case.
<99
100<499
500<999
1000<1499
1500<1999
2000<
<$9K
$10K<$49K
$50K<$99K
$100K<$149K
$150K<$199K
$200K<
The date should be aggregated into fiscal year
and quarter. So is should be like “FY19 Q2” or
just “FY19” etc. If you have dedicated field for
fiscal year and quarter in CRM, you can use
that field.
<3 moths
3<6 months
6<9 months
6<12 months
12<15 months
15<18 months
18 months<
*Data is all dummy

7. Process the data
Your data should looks like this.
Now, you are ready to create graphs to dive into the revenue data pool!
*Data is all dummy

8. Make graphs: Net New vs UP Sell
*Data is all dummy

9. Make graphs: Net New vs UP Sell by industry
*Data is all dummy

10. Make graphs: Net New vs UP Sell by deal size
*Data is all dummy

11. Make graphs: Net New vs UP Sell by # of Employee
*Data is all dummy

12. Make graphs: Industry vs # of Employee
*Data is all dummy

13. Make graphs: Industry vs deal size
*Data is all dummy

14. Make graphs: Won vs Lost by # of Employee
*Data is all dummy

15. Make graphs: Won vs Lost by deal size
*Data is all dummy

16. Make graphs: Won vs Lost by Industry
*Data is all dummy

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Thank you for reading!