Monitoring data tells you what AI says. Opportunity finder tells you where that matters. It turns hundreds of answers into a short, prioritized list of situations in which your SaaS is relevant to a buyer's question but loses the recommendation — and it shows the evidence for each one so you can judge it yourself.
Seven kinds of opportunity
Narrashift looks for missing-brand opportunities, where competitors appear and you do not; weak recommendations, where you are mentioned but a competitor is recommended; competitor dominance, where one brand appears far more often than you across relevant answers; citation gaps, where the sources cited in those answers leave you out; content gaps, where none of your analyzed pages covers the topic; negative perception, where answers criticize your product; and feature gaps, where AI names competitors for a capability your website documents.
Relevance is checked first. A question is only used when it is linked to a feature found on your website or clearly matches your website profile. Questions that already contain your brand name are excluded from missing-brand detection, because naming you there would not mean much. This keeps the list focused on situations you can realistically change.
Grouped, not repeated
One opportunity per answer would bury you in duplicates. Instead, related prompts are grouped by the product feature they belong to or by topic, with similar topics merged — for example, several questions about platform alternatives become one opportunity. Each opportunity keeps a stable identity across monitoring runs, so its history, your decisions and its actions stay attached as new results arrive.
Priorities you can read
Every opportunity receives a priority from P0 (critical) to P3 (low) and a confidence level. The score considers relevance to your product, how many prompts are affected, how often the issue appears in the answers, how often competitors are explicitly recommended, the commercial intent of the questions, the amount of evidence and the estimated effort. The reasons are written out on the opportunity, for example: “Directly matches a product feature found on your website. 4 monitored prompts are affected. Competitors are explicitly recommended in 75% of those answers.”
Thin evidence is never presented as urgent: an opportunity based on a single prompt, on low confidence or on unverified sources is capped at P2 until more data arrives. Narrashift does not invent revenue impact; where business impact cannot be estimated from data, it says so.
A lifecycle, not a static report
Opportunities move through clear statuses: detected, reviewed, action planned, in progress, implemented, measuring, and finally improved, no measurable change or insufficient data. You can dismiss irrelevant ones, and they stay dismissed in later runs. If an opportunity is no longer observed in several consecutive runs it is marked resolved, and it reopens automatically if the problem returns. Every status change is kept in the history.
From each opportunity you can open the evidence — questions, answers, competitors, cited sources and relevant pages of your website — and generate an action plan. Detection runs automatically after every monitoring cycle and costs nothing extra, because it analyzes results you already have.
Built on your data
Because every finding is derived from answers you already collected, the evidence is always one click away and the numbers match the rest of your dashboards. Nothing is simulated, and when there is not enough data for a reliable judgement, the opportunity says so instead of guessing.