The one-call version
Returns your citation trend, the domains AI answers cite in your space, and your
citation share per engine.
Being mentioned and being cited are different, and the fix is different too. A mention gap is
a content problem. A citation gap is usually a third-party source problem — you are absent
from the pages the models actually read.
The chain, step by step
1. Is the gap real, and getting worse?
Read brandCitationTrend — your own citation volume over time. A decline there
with flat visibility means you are still being talked about, but no longer used
as the source.
get_source_trends does not answer this one. It returns the trend for the most-cited
domains in your space, not your own citation volume — there is no parameter to switch it. The
brand-level series is only available through investigate.
2. What do the models actually cite?
The domains carrying answers in your space. This is the core of the recipe.
The gap is almost always “these sources do not mention us”, not “our page is not
good enough”.
3. Which sources, specifically
Down to the exact page being cited. That page — a listicle, a comparison, a
review roundup — is the outreach target.
4. Is it engine-specific?
Compare citation share across engines. One engine citing you far less than its
peers is that engine’s sourcing behaviour, not a content deficiency.
5. Where you are cited but not surfaced
The raw answers. Sometimes you are cited and still not recommended — a
positioning problem rather than a visibility one, and it needs a different fix.
How to read it
What this cannot tell you
Whether a cited source will accept a mention, what it costs, or whether it is
worth pursuing. The data names the targets; it cannot rank them by how winnable
they are.
