Most AI visibility tools stop at the chart. The hard part is knowing what to do next. “Improve your content” is not an action; “add a section to /features/automation that lists the supported website events, explains how contacts are identified and answers these four monitored questions” is. The action plan in Narrashift is designed to produce the second kind of recommendation and to keep it connected to the evidence that justifies it.
What every action contains
Each action has a title, a category, a priority inherited from its opportunity, an estimated effort and a confidence level. It names a target — an existing page of your website or a proposed URL — and describes the specific change. Numbered implementation steps explain how to get there, a verification note tells you how to confirm the change is live, and the expected benefit is phrased as a hypothesis. Evidence references link the action to the prompts and AI answers behind it.
Categories cover the work that typically moves AI visibility for a SaaS: creating or improving landing pages, explaining a product feature, adding or improving FAQs, comparison content, verified product demonstrations, internal linking, technical SEO fixes, structured data, updating outdated information, independent editorial coverage, authentic reviews, citation-worthy documentation and original research.
Rule-based first, AI when it adds value
As soon as an opportunity is detected, Narrashift creates rule-based actions from the evidence at no cost: it knows which questions are affected, which competitors were recommended, which cited domains are involved and whether one of your pages already covers the topic. A feature gap with no covering page becomes “create a dedicated page at /features/…”, while a gap on an existing page becomes “expand this page” with the exact questions to answer.
When you want more depth, generate an AI action plan. Narrashift sends the opportunity, the relevant answer excerpts, your company profile and your relevant pages to the AI model as quoted data, and asks for observations, hypotheses, unknowns and one to four actions. The model may only describe capabilities stated in your profile or on your pages; anything else must be phrased as “verify whether … and document it if true”. Evidence references are validated against the answers that were actually provided.
A task list your team can work through
The Action plan page lists all actions across opportunities with filters for status, priority, type and assignee, and sorting by priority, date or lowest effort. Actions move through suggested, approved, in progress, implemented, measuring and completed, or can be dismissed. You can assign each action to a member of your workspace, edit its title, target or recommended change, and open the Content optimizer directly from it.
Decisions are preserved. Actions you have approved, edited or dismissed are never replaced when detection runs again or when you regenerate an AI plan; only untouched suggestions are refreshed. Every status change is recorded.
From action to measurement
Marking an action as implemented records the date and takes a baseline snapshot of the affected prompts. From then on the Impact tracker compares new monitoring results with that baseline, so the plan does not end with “done” but with “did it work?”. Narrashift never claims to know how AI assistants rank products internally, and it never promises that an action will make an assistant recommend you.