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Prompts are the questions Athena runs against AI engines on your behalf. Your prompt set is the biggest single driver of useful data - a weak or narrow set means the platform is answering the wrong questions. Athena gives you two ways to build your prompt set: add prompts directly, or run discovery from the Discover tab. This doc explains what each one is, when to use it, and how to work through it. They’re not mutually exclusive - most teams start with one method and fill in gaps with another.

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Before you choose: what a good prompt looks like

Think buyer language, not internal language. A prompt is a question or query someone would type into ChatGPT, Perplexity, or Gemini when looking for something in your category. Good prompts are:
  • Questions your buyers actually ask - not how you describe your product, but how they describe their problem. “What’s the best platform for tracking AI search visibility” beats “AthenaHQ competitors.”
  • A mix of Branded and Non-Branded - Branded prompts include your company or product name. Non-Branded prompts are generic category queries where you want to show up without being named. You need both.
  • Specific enough to return signal - very broad prompts (“what is marketing”) return noise. Specific ones (“what tools track brand mentions in AI responses”) return the data you can act on.
Aim for 50-100 prompts to start. Enough to see patterns; focused enough to act on.

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Option 1 - Add Prompts directly

This is the quickest path for getting prompts into Athena. You open the Add Prompts drawer and choose how you want to add them: let Athena generate suggestions, type them in yourself, or upload a CSV. Access it from: Prompts > + Add More > Add Prompts Once the drawer opens, you’ll see three ways to add:

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AI generation

Athena generates a starting set of prompts for you based on your website, brand description, and industry. This is the fastest way to get something in place if you’re starting from scratch and want Athena to do the thinking. Best for: New customers who haven’t done keyword research yet and want a reasonable starting point immediately. Good for filling coverage gaps when you know a topic area you’re missing but aren’t sure what the right prompts are.

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Manual entry

Type or paste prompts directly into the drawer. You set the type (Branded or Non-Branded), assign a topic, choose a country, and add tags before saving. Best for: When you know exactly what you want to track. Common use cases: prompts you heard from customers, questions from sales calls, terms your team competes on, or specific product comparisons you want to monitor. This is also the right move when AI generation misses something obvious - just add it yourself.

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CSV import

Upload a formatted CSV to add prompts in bulk. Download the template from within the drawer, fill it out, and drag the file to upload. Best for: Teams coming from an SEO tool with an existing keyword export, or any situation where you have a list of 20+ prompts you want to load in one go rather than one by one. Also useful for migrating prompt sets from another system, or when multiple stakeholders have contributed prompts to a shared spreadsheet. Tips for all three:
  • After adding, review the Topics Athena assigns - the defaults are a starting point, not final. Drag prompts between topics to get your structure right, since Topics are how you’ll slice data in Olympus and the Heatmap.
  • Once a prompt has collected response data, its text becomes read-only. You can’t edit the wording - you’d need to pause it and create a new one. Get the phrasing right upfront.

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Option 2 - Discover

Enterprise plan only. The Discover tab shows a lock icon if your workspace doesn’t have access. Discover runs a multi-source discovery scan against your website and market, and produces a structured, filtered, ranked set of prompts ready for review. It’s not just generating prompts - it’s discovering them from real data sources and organizing them by funnel stage, intent, and volume so you can prioritize before you track. Access it from: Prompts > Discover tab > Run discovery When starting a run, you name it, choose a country and language, and check which sources to scan:
  • Website analysis - market analysis from your website, segments, and products, deriving prompts from the structure of your business
  • Search Console - clusters your Google Search Console keywords into prompts grounded in real search data (requires GSC to be connected in Settings > Integrations)
  • Social - Reddit threads, YouTube comments, and videos in your category
  • Keyword gaps - prompts where AI cites competitors but not you, built from your keyword landscape
  • Custom instructions - guide discovery with your own topics, products, and tone (opt-in; requires a short written brief)
Once you click Run discovery, the sources run in the background - allow several minutes to an hour depending on what you selected. The run’s detail page shows live progress, and suggestions appear as results come in (Keyword gaps results arrive independently of the other sources). When results are in, you get a table of discovered prompts grouped by Topic with columns for:
  • Source - which source produced it
  • Funnel - TOFU (awareness), MOFU (consideration), or BOFU (decision)
  • Intent - Informational, Commercial, Transactional, or Navigational
  • Type - Head, Mid tail, or Long tail
  • Volume - estimated monthly search volume
  • Value - estimated keyword value (CPC)
Signal chips (such as Competitor Gap and Social Signal) appear above the table when the run found prompts carrying those signals. An Already tracked section at the bottom lists suggestions you already cover (previously accepted suggestions, exact matches, and Keyword gaps prompts at 85%+ similarity) - so you’re not adding redundant coverage. Review the results, filter by source, funnel, intent, type, or top volume, sort by any column, select the prompts you want, and click Start tracking (N) - Athena checks for duplicates and shows you a count of new vs. already-tracked selections before confirming. Best for: Teams starting from scratch who want data-grounded prompts rather than a manual brainstorm - and teams with a baseline set who want to expand strategically. Particularly strong when GSC is connected, since your actual search terms feed directly into discovery. The Keyword gaps source is the move when you suspect competitors are gaining AI visibility you’re not monitoring. Tips:
  • Connect Google Search Console before running discovery. The Search Console source is the highest-signal input and appears disabled with a connect link if it’s not connected.
  • Use the Funnel filter to check you have coverage across TOFU, MOFU, and BOFU. Most teams over-index on bottom-funnel branded terms at the start.
  • Social prompts surface the informal, conversational language your buyers actually use. These are often the prompts where you’re most invisible in AI responses, because they’re phrased the way people talk, not the way brands write.
  • Topic names are renamable inline on the results page. If you rename two topics to the same name, Athena will prompt you to merge them.
  • You can export the currently filtered view as a CSV before tracking - useful if you want a stakeholder to review before anything goes live.
  • Re-run discovery periodically - every few months, or when you expand into a new product area - rather than just once at setup.

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Choosing the right option

These methods layer well together. A common starting pattern: use AI generation or CSV to get something tracking immediately, then run discovery to fill structural gaps and catch competitive exposure you didn’t know to look for.

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After you add prompts: organizing and managing them

Once prompts are in, a little structure makes your data significantly more useful. Topics are the main organizational unit. Prompts are grouped into Topics on the Manage tab. Think of Topics like content pillars or product areas - “Pricing,” “Competitors,” “Use Cases,” and so on. A well-organized topic structure makes the Heatmap and Olympus filter bar much more powerful, since you can slice all your metrics by Topic to see exactly where you’re winning or losing. To move prompts between Topics, select them and use More > Assign topic in the bulk command bar, or drag them directly onto a different topic row. Branded vs. Non-Branded is the other key label. Branded prompts include your company or product name. Non-Branded are generic category queries. Track both - Branded mention rate reflects direct awareness; Non-Branded reflects whether you’re showing up when buyers haven’t decided yet. You can set or edit this in the Edit Prompt drawer (click … > Edit on any prompt row). Tags let you create custom groupings across Topics - useful for things like campaign tracking, product lines, or funnel stage labels you want to apply manually. Manage the full tag library from + Add More > Add Tag. Pausing prompts is the right move for anything off-target - don’t delete, since paused prompts keep their historical data. Select the rows and click Pause in the bulk command bar, or use the row-level … menu. A note on editing prompt text: once a prompt has collected response data, its text is locked. You can’t edit the wording directly - the Edit Prompt drawer will have the text field disabled. If you need to change it, pause the prompt and create a new one with the corrected text. Plan your phrasing carefully upfront and you won’t need to do this often.

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Questions?

Reach out to your Athena team or contact support@athenahq.ai.