Content suggestions

Overview#

Suggestions are content ideas raised by the Content Scout agent from your own data: a topic you are absent from, a question competitors are cited for, a source you could be present on.

The difference from starting a draft yourself is provenance: a suggestion arrives with the reason it exists attached.

Suggested content

Comparison guide for agency project management tools

Closes a gap

Absent on AI search

Channel

Blog

Tracked

Not yet tracked

Interpreting results#

Read the reason before the idea. Every suggestion should name the gap it came from, and if that reason does not hold up under a moment's scrutiny then the suggestion is not worth acting on however appealing the idea sounds on its own.

Treat these as proposals rather than a queue. There is no expectation that you will clear them, and rejecting most of what appears is a perfectly reasonable outcome that says nothing bad about either you or the agent.

Your decisions do feed back. Accepting, rejecting and dismissing with a reason attached shapes what gets suggested next, and the reason is worth the few seconds it costs. "We don't sell into that market" teaches the Scout something that a silent rejection cannot, and the difference compounds over a few months.

Best practices#

• Suggestions you recognise as your actual problems. If they consistently miss, the cause is almost always upstream, in topics that do not describe your business properly.
• A high rejection rate is fine. Precision matters considerably more than volume here.
• Improvement over time as your feedback accumulates.

Next steps#

1. Read the reason before the idea, every time.
2. Reject with a reason rather than ignoring, because silence teaches nothing.
3. Accept a small number and actually publish them. Accepted-but-unpublished suggestions change nothing whatsoever.
4. If suggestions feel consistently off, fix your topics first. Suggestions inherit whatever the topic set claims your business is, so a drifted topic set produces confidently irrelevant ideas.

Writing rejections that teach#

The rejection reason is a steering input, so its quality decides how fast the suggestions improve. A useful reason states the rule, not the verdict: "we don't sell to consumers" or "we never write comparison posts about partners" rules out a whole class of future ideas, while "not this one" and "meh" rule out nothing. One sentence naming the boundary you applied is enough, and after a few weeks of them the list starts arriving pre-filtered by your own stated rules.

Triage works best inside the weekly pass rather than as its own chore: after reading Weekly drivers, spend five minutes here. Suggestions age against the gaps they came from, so a weekly decision keeps the reasons honest while the gap is still the gap.

What Content Scout works from#

Content Scout does not research anything itself. It works from what Trend Finder and Visibility Analyst have already found, together with your keyword universe, your topic and keyword gaps, and the content you already have.

That has two practical consequences worth knowing. Suggestions stay inside your keyword universe rather than drifting into adjacent categories that merely share vocabulary with yours, and they are checked against your existing content by meaning rather than by title, so the same piece should not come back proposed twice in slightly different words.

If suggestions have dried up entirely, check whether the agent is still running, under ActionsAgents. See Agents.

Limitations#

Suggestions come from your tracked topics and engines. An opportunity sitting outside that set will never be suggested, because nothing out there is being measured in the first place.

A suggestion is a prompt to decide rather than an instruction to follow. The commercial judgement stays yours: Seerly can see that you are absent from a topic, and has no way of knowing whether that topic is worth your time.