I am starting to use supplemental data through an imported data project in a survey and I just realized how limited the autocomplete is. If a respondent does not type out the choices exactly how they start out in the database, then it won’t pick up the choice:
Example in Database: State of Utah-Utah State Legislature
Respondent Typing Example that wouldn’t recognize the example above: Legislature…….
Does anyone know of a workaround for this or perhaps I just need to make a feature request?
I agree. The current autocomplete is not sufficient for our needs. We need one that will consider the typed letter pattern in all parts of the data list, like “autocompete.js”.
For instance, typing “hot” would pull up “AccorHotels”, Ace Hotels, etc.
Has anyone successfully integrated an autocomplete of this nature, drawing on supplemental data?
According to this support article, I don’t believe there’s a way to do so.
It states “When working with an autocomplete question that pulls from a supplemental data source, the auto populate feature only pulls words if the letter you enter is the first letter of the word. For example, if you are searing for the term “Team 4,” you will need to start your search by typing out the word “team.” Searching just “4” will not pull “Team 4” as a result.”
I’d suggest submitting an idea to add rules to the words it’s able to classify, similar to how in Text IQ, you can add other words that could be marked to the same topic/category.
Thank you for the suggestion, but we are dealing with a data source containing hundreds of employer names. There is no way we could keep up with number of rules that would be needed. We really need pattern-matching. There are plenty of javascript autocompletes that have this function. I wonder why Qualtrics did not include it.
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