> For the complete documentation index, see [llms.txt](https://user.netmera.com/netmera-user-guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://user.netmera.com/netmera-user-guide/ai-features/n-assistant/understand-n-assistant-answers.md). # Understand N-Assistant answers Learn how to read N-Assistant answers: summaries, key figures, charts, tables and recommended actions. An N-Assistant answer is more than a paragraph of text. Depending on your question, it combines a written analysis, key figures, charts, tables and a prioritized list of recommended actions. Knowing what each part tells you helps you move from reading the answer to deciding what to do next. This page explains the parts of an answer and walks through real examples. ### Parts of an answer

Part	What it shows	How to use it
Scope statement	The opening sentence states what N-Assistant reviewed, such as the number of campaigns and the date range.	Check it first. It tells you whether the answer covers the period and the campaigns you had in mind.
Key readout or What’s happening	The main findings in plain language, with the numbers behind them.	Use it to understand the current state before reading the diagnosis.
Diagnosis	N-Assistant’s interpretation of why the numbers look the way they do.	Use it to decide where the problem is, such as delivery, message content, timing or audience.
Recommended actions	A numbered list of next steps, in priority order.	Start with the first action. The order reflects what N-Assistant considers most impactful.
Key figure cards	A row of cards, each with one metric and a short status note, such as “engagement is low” or “provider acceptance is strong.”	Scan them for a quick summary. Green notes point to healthy results, and red notes point to areas that need attention.
Charts	Visuals of the data behind the answer, such as CTR by campaign or mobile active users over time.	Use them to spot outliers, gaps between campaigns and trends.
Tables	Row-level detail, such as a cohort table with a diagnostic note for each date.	Use them to find the specific dates or campaigns behind a finding.
Follow-up suggestion	A closing line that offers a deeper analysis, such as a breakdown by best send hours.	Reply with the suggestion to continue the analysis in the same conversation.
Feedback icons	Copy, thumbs up and thumbs down icons below an answer.	Copy the answer to share it, or rate it to tell Netmera whether it helped.

### Example: push notification performance In this example, the request was “Analyze the performance of the push notification campaigns I sent recently.”

N-Assistant answer to a push notification performance request, with What is happening, Diagnosis and Recommended actions sections and a row of key figure cards. — An answer with findings, diagnosis, recommended actions and key figure cards.

Here is how to read it: * **Scope:** N-Assistant reviewed the 20 most recent push campaigns out of 48 sent in the last 30 days. * **What’s happening:** The send success rate is near 99.6%, so delivery is not the problem. Average CTR is 0.64%, which is the weak spot. The best campaign reached 1.4% CTR and the weakest reached 0.2%, a 7x gap. * **Diagnosis:** The bottleneck is message resonance and post-click value, not audience size or provider acceptance. * **Recommended actions:** A/B test copy and send time, prioritize campaigns above 0.8% CTR, segment by engagement recency and watch uninstalls. The key figure cards summarize the same findings at a glance, and the charts below them show the detail.

Key figure cards, a bar chart of CTR by push campaign and a line chart of mobile active users by day. — Key figure cards, a CTR bar chart by campaign and a daily mobile active users line chart.

The bar chart compares CTR across campaigns, so you can see which campaign stands out. The line chart shows mobile active users by day, so you can check whether engagement moves with your send activity. ### Example: when delivery comes before content N-Assistant checks the basics before it suggests creative changes. In this example, the same request returned a different result because delivery was the main issue.

N-Assistant answer showing a low send success rate across recent push campaigns, with the recommendation to fix delivery first. — An answer that puts delivery first. Sample data from a test app.

Only about 48% of sent pushes were accepted by the provider, so the first recommended action is to investigate push setup, token freshness and inactive devices. Content experiments come last, after delivery improves. When an answer starts with a diagnosis like this, follow the order of the recommended actions. ### Example: retention diagnosis For the request “Give me a September retention diagnosis,” N-Assistant returns a written diagnosis, key figure cards, a cohort size line chart and a table. The table lists each cohort date with its size and a diagnostic note, such as “Largest spike; likely campaign or acquisition burst.” Use a table like this to find the dates behind the pattern, then ask a follow-up question about those dates. ### Check an answer before you act * Read the scope statement. Answers can cover a sample of your campaigns, such as the 10 or 20 most recent ones. * Compare key figures with the reports in your panel when a decision depends on them. * Look at the sample size. Results from very small audiences, such as test sends, do not show how a campaign performs in production. * Ask a follow-up question when something is unclear, for example, “Which campaigns drove the drop?” {% hint style="info" %} N-Assistant recommends actions and does not apply them. You decide which recommendations to use. {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://user.netmera.com/netmera-user-guide/ai-features/n-assistant/understand-n-assistant-answers.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.