How to test abstract, made-up brand names
Is your Apple on an Orange network?
Is this a Virgin?
Many years ago these sentences made no sense, and few people probably knew what the question was asking. Now, these brands are ubiquitous.
The point is that some product or company names have no direct (or indirect for that matter) connection to what they actually do and what service they provide.
Though now Apple, Orange and Virgin are well known brands, if those names were tested for effectiveness using a traditional quantitative name test, those names would have probably failed.
Traditional quant name tests evaluate names on metrics like name appeal, fit with the brand, communicating what the brand does, ease of understanding, intent to purchase a product with this name etc.
They are designed to test names for potential products or services that make sense to consumers and when the names tested are rational, the traditional name tests work great!
However, if the names tested are abstract or made-up words, it becomes harder to test them using a traditional quant name test.
As a result a name like Apple for a technology company, would probably have been rated lower than a name like SmartTech or InnoTech on a few of those metrics.
“So the question is, how do you test quantitatively abstract, made up names that have no connection at all to the product or service they represent?”
It all starts with the vision.
What is this name meant to represent? A mood? A feeling? A situation?
According to different sources, Steve Jobs suggested the name Apple to his co-founder, Steve Wozniak because it was "fun, spirited, and not intimidating." It's also been suggested that Jobs liked the simplicity of the name, its approachability, and its departure from the more traditional names of technology companies at the time.
Once there is a clear understanding of the vision and what this name is meant to represent and communicate, incorporate questions in the traditional quant name test to capture these elements.
Below are some tips when designing and analyzing results for a name test that includes abstract, made up names:
Before exposing respondents to the product description, ask unaided questions like “ what do you think a product with this name does?”, “what thoughts, feelings or emotions come to mind when you hear the name X”.
Asking these unaided questions before you expose respondents to the product description, solicits their unbiased top of mind thoughts.
Add aided questions that capture these same elements: “Which of these words would you use to describe a product with the name X” or “What feelings does the name X evoke?”
Ask aided questions that assess how effectively the name captures the value proposition and personality of the brand: “Does a product with the name X communicate a brand that is Y”?
Ask shorter list of rational effectiveness metrics like appeal, fit, intent to purchase, uniqueness
Ensure product description accurately reflects the value proposition and personality of the product including intangible dimensions.
In the Apple example, we should include that the product is meant to be simple to use, feel “fresh”, non-traditional, approachable etc.
After exposure to the product description, ask them again these same questions to see how knowing what the product is/does changes their responses.
Finally for analysis purposes, be clear and realistic as far as the goals and KPI’s of each name tested.
Many times rational, functional names are rated better vs. more abstract names on rational metrics like easy to understand, fit with a brand etc. so more abstract names should have different goals and be measured on different KPI’s.
Name testing takes on a completely different form when testing abstract names. Having a research team with the experience and knowledge of how to conduct this type of name test can make all the difference in your naming.
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