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What is a topic?

A topic is a named group of prompts that belong to the same buying question. You assign a prompt to a topic, and Attensira rolls the per-prompt numbers up into a single set of rates for the group. Nothing about how a prompt runs changes — topics are a reporting structure, not a scheduling one. The reason to use them is statistical as much as organizational. One prompt on Starter gives you one reading a day; ten prompts in a topic give you ten. A single prompt swinging from 0% to 100% is often noise. The same swing across a topic is a signal you can act on. In the wire format and in the API, a topic is group_id. The get_analytics area enum still uses group for the same reason. The published vocabulary is “topic”; the wire contract says group, and both refer to the same object.

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What changes when I group prompts?

Reporting rolls up. Instead of reading forty prompt rows, you read six topic rows, each carrying a mention rate, a citation rate, and competitor rates computed across every successful run of every prompt in the group. That rollup is a pooled rate, not an average of averages. A topic with two prompts — one that produced three successful runs and one that produced nine — weights the twelve runs together. This is what you want: the topic answers “across the questions in this theme, how often were we named?” Individual prompt rows do not disappear. Grouping adds a level of reporting above them; you can still open any prompt and see its own rates, its citations, and the source domains the models drew on.
A prompt without a topic still runs and still reports. Topics are optional. Prompts left ungrouped appear only at the prompt level.

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How should I structure topics?

Group by the question a buyer is asking, not by the feature you want to sell. Buyers arrive at assistants with a job to do, and the topic that predicts your outcome is the job, not your roadmap. Three structures that hold up:
  • By stage. Discovery prompts (“what tools exist for X”), evaluation prompts (“X vs Y for a team of 20”), and objection prompts (“is X hard to migrate to”). These behave very differently — discovery answers name many brands, evaluation answers name few.
  • By segment. The same question asked for a solo operator, a 20-person team, and an enterprise. Models often recommend entirely different products across these, and a blended number hides it.
  • By use case. One topic per problem your product solves. This is the structure that maps most cleanly onto content work, because a weak topic points at a page you need to write.
Keep topics large enough to be stable — five to fifteen prompts is a workable band — and resist a topic that holds one prompt, which reports exactly what the prompt already reported.

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How do I create and change topics?

1

Create the topic

Name it in the words a buyer would recognize. The name appears on every rollup row, so make it readable without your internal shorthand.
2

Assign prompts

A prompt belongs to one topic at a time. Assigning it to a new topic moves it rather than copying it.
3

Read the rollup

Topic rates appear once the prompts in the group have successful runs. A brand-new topic reports value: null until then.
Regrouping is retroactive in reporting: moving a prompt between topics recomputes both rollups over the existing runs, because the rollup is derived from stored runs rather than stored per topic. Historical topic charts will therefore shift when you reorganize. Do a reorganization in one sitting rather than drifting prompts between topics week to week, or your trend lines describe your bookkeeping instead of your market. Deleting a topic does not delete its prompts. They become ungrouped and keep reporting individually.

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Reading a topic rollup

Topic rates use the same shapes as everything else. Rates come back as {value, n} where n is the count of successful runs behind the number, and null means not measured rather than zero. Deltas come back as {value, real} and are suppressed to {real: false, value: null} when a two-proportion z-test at 95% cannot separate the change from noise. A topic’s n is the sum of its prompts’ successful runs, so topics cross the noise floor sooner than the prompts inside them. That is the practical payoff: a topic can prove a change in a week that a single prompt would take a month to demonstrate. Competitor rates roll up per topic too — and, as everywhere in Attensira, they share the same denominator as your own mention rate and do not sum to 100%. See Competitors for why.