One of our objectives in a
demonstration is to “suspend disbelief” – we are trying to make things look as real
as possible. The more real things look in
a demo, the more believable it is in the mind of the customer. “Demo”
data can have a huge impact, accordingly, on the believability of a demo.
Data that is obviously fake will
hurt our cause – and may drive the customer to request or demand a POC of
similar trial. Examples of fake data
include:
- Names of famous
actors, book characters, cartoon characters and clearly made-up names (e.g., “Mary
Manager”, “Steven Staffer”, “Edward Executive”).
- Clearly fake
addresses – street names, cities, countries, etc.
- Clearly fake company
names, similarly.
I recommend investing a
reasonable amount of energy to acquire and use data that really looks
real. One way to do this is to use data
sources that your QA department may already use. This data is typically realistic and may
already have specific fields that map to your target industries.
Interestingly, customers at
different stages of the Technology Adoption Curve will likely react very
differently to demo data. “Early
Adopters” are often very forgiving of the data that is used. “Early Majority” customers are reasonably
forgiving, but the further you move to the right and into the “Late Majority”
the more they need to see their own data (or what appears to be their own data)
used in demos.
Any tips for good sources of
realistic-looking data?
1 comment:
With a little creativity, it's not hard to have "real" people names that are mnemonics for most "role" names. "Sally Smith" instead of "Sally Sales" or "Derek Davis" instead of "Derek Director". The use of alliteration within a name does exude a whiff of artificial "demo data", but it's not as bad as using role names for last names. With a reasonable number of names, the mnemonics can be limited to first names (Sally Jones and Derek Wilson), which are even less obvious.
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