More on Methodology
I wrote a post recently on credibility, and it occurs to me that I
should talk a little bit about the other tests of a solid methodology. Is it:
· Credible: How widely accepted is
the measure? Does it have a good track
record of results? Is it based on a scientifically and academically rigorous
methodology? Will management trust
it?
· Reliable: Is it a consistent
standard that can be applied across the customer lifecycle and multiple
channels? When all remains the same do we get the same results with every
measurement?
· Precise: Is it specific enough
to provide insight? Does it use multiple
related questions to deliver greater accuracy and insight?
· Accurate: Is the measurement
right? Is it representative of the
entire customer base, or just an outspoken minority? Do the questions capture
self-reported importance or can they derive importance based on what customers
say? Does it have an acceptable margin
of error and realistic sample sizes? Most customers will report that a lower price is important to them, but
lowering the price may not induce them to buy.
· Actionable: Does it provide any
insight into what can be done to encourage customers to return to the site, buy
again, or recommend it? Does it prioritize improvements according to biggest
impacts? A score without actionable
insight helps us keep score but not improve.
· Predictive: Can it project the
future behaviors of the customer based on their satisfaction with the site
visit? The goal is to invest our efforts in those things that will yield value. Without predictive capability we are left to
shoot at our targets in the dark.
A
bit about reliability vs. accuracy vs. precision. An analogy I like to use is
that of a watch. A second-hand gives you
precision. Without a second hand, your watch can still be accurate and
reliable, but it won’t be precise. Your watch can be precise but not accurate
if it tells you that’s it’s 10:22:06 when it’s really 12:55:45. Your watch can be accurate and precise one
morning, but if it doesn’t give you the same reading 24 hours later then
it isn’t reliable.
Metrics
that don’t have the above listed qualities can do more harm than good. They will provide with a false sense of
security that will lead you to make bad decisions based on bad data – “garbage
in … garbage out”. If you think it is
4pm but it is really 5pm you will be late for dinner. If you think your customers are happy with
your product selection…and they are not… they will not be your customers
anymore. The stakes are pretty high.