Control charts are an excellent tool managers meed to determine if any variation within the customer experience is statistically significant or not, to determine if the variation represents a true change in the customer experience or is simply random variation.

1. Kinesis CEM, LLC
Not All Customer Experience Variation is Equal: Use Control Charts to Identify Actual Changes in the Customer Experience
https://blog.kinesis-cem.com/2015/04/09/not-all-customer-experience-variation-is-equal-use-control-charts-to-identify-actual-
changes-in-the-customer-experience/
Eric Larse is co-founder of Seattle-based Kinesis, which helps companies plan and execute their customer experience strategies.
Mr. Larse can be reached at elarse@kinesis-cem.com.
http://www.kinesis-cem.com
kinesis-cem.com 206.285.2900 info@kinesis-cem.com
Not All Customer Experience
Variation is Equal:
Use Control Charts to Identify Actual
Changes in the Customer Experience

2. Be it….
a survey of
customers…
Variability is
Common

3. mystery
shops…
Variability is
Common

4. social
listening…
Variability is
Common

5. or…
other customer
experience
measurement…
Variability is
Common

6. a certain amount of
random variation in
the data is normal.
Variability is
Common

7. Managers need a
means of
interpreting variation
to evaluate if the
customer experience
is truly changing, or
if the variation is
simply random.
The
Problem

8. Control
Charts
One
Solution

9. Statistical Tool
to Measure
Variation Control
Charts

10. Consider this example of
mystery shop results:
For Example
75%
77%
79%
81%
83%
85%
87%
89%
May June July Aug Sept Oct Nov
Average Mystery Shop Score

11. Was July a bad month, or a random
variation?
Does the improved performance in
October and November represent a true
change in the customer experience?
Questions
75%
77%
79%
81%
83%
85%
87%
89%
May June July Aug Sept Oct Nov
Average Mystery Shop Score

12. Control
Limits
To answer these
questions we need
to set upper control
limits (UCL) and
lower control (LCL)
limits.

13. Control
Limits
Where:
x = Grand Mean of the score
n = Mean sample size
SD = Mean standard deviation
The following equations set control
limits with a 95% confidence:

14. Control
Limits
Applying these limits to our
hypothetical mystery shop scores,
produces the following UCL & LCLs:
75%
77%
79%
81%
83%
85%
87%
89%
May June July Aug Sept Oct Nov
Average Mystery Shop Score

15. Questions
Now, we can answer our questions:
75%
77%
79%
81%
83%
85%
87%
89%
May June July Aug Sept Oct Nov
Average Mystery Shop Score
July was, in fact, a bad month.
While October is still with the threshold
of random variation, November showed
significant improvement.

16. Control charts give
managers a meaningful
way to determine if any
variation in their customer
experience measurement
reflects an actual change in
the experience as opposed
to random variation or
chance.
Control
Charts