> ## Documentation Index
> Fetch the complete documentation index at: https://docs.superlines.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Prompt Strategy

> Build a comprehensive prompt portfolio using multiple data sources and strategies.

Choosing the right prompts to track is the most important step in Superlines. Your prompt portfolio defines the context for all your AI search visibility data — get it right, and every metric becomes actionable.

## Why prompt selection matters

Unlike traditional SEO where you optimize for keywords with known search volume, AI search prompts are conversational and varied. The exact phrasing matters less than the intent — AI engines understand nuance. What matters is tracking prompts that represent real questions your market is asking.

<Info>
  Enable [prompt variations](/account/prompt-variations) to automatically test different phrasings of the same question. This ensures your tracking isn't dependent on exact wording.
</Info>

## Data sources for prompt creation

The best prompt portfolios combine multiple data sources. Here's how to use each one:

### 1. Your own business data

If your organization has existing marketing, customer success, or content data, use it as the foundation. This is the most reliable source because it reflects your actual market.

| Source                        | How to use it                                                                             | Example                                                             |
| ----------------------------- | ----------------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| **Marketing messages**        | Convert your value propositions and messaging pillars into questions a prospect would ask | "What is the easiest way to get YEL insurance?"                     |
| **FAQ databases**             | Import existing FAQ questions directly — these are proven real customer questions         | "How do I cancel my subscription?"                                  |
| **Support ticket themes**     | Extract recurring questions from support data                                             | "Why isn't my integration syncing?"                                 |
| **Sales objections**          | Frame common objections as research questions                                             | "Is \[product] worth the price for small teams?"                    |
| **Internal keyword research** | Convert high-volume keywords into conversational prompts                                  | Keyword "CRM startups" becomes "What is the best CRM for startups?" |

<Tip>
  You don't need to match exact phrasing. AI engines understand intent. A prompt like "Best CRM for startups" will capture responses whether a user asks "What CRM should I use for my startup?" or "Which CRMs work well for early-stage companies?"
</Tip>

### 2. Google Search Console

The [Google Search Console integration](/integrations/google-search-console) imports real search queries that already drive impressions or clicks to your site. These are proven high-relevance queries.

**Best practice:** Focus on queries with high impressions but lower clicks — these represent topics where users are searching but may be getting AI-powered answers instead of clicking through.

### 3. Prompt Radar

[Prompt Radar](/account/prompt-radar) automatically discovers trending prompts from SEO, SERP, and People Also Ask data sources. It finds "hot" prompts that are relevant to your brand but not yet in your tracking.

### 4. Long-tail keyword data + AI generation

For performance-focused teams, combine traditional keyword research with AI to generate high-value prompts:

1. **Start with keyword data** — use tools to find long-tail keywords with real search volume in your niche
2. **Convert to conversational prompts** — use the Superlines [keyword research tool](/mcp/tools#keyword_research) or an LLM to transform keywords into natural-language questions
3. **Validate relevance** — ensure the generated prompts match your brand's positioning and audience
4. **Import and label** — add prompts via [bulk import](/account/prompts#bulk-import) or [MCP](/mcp/tools#add_prompts) with appropriate labels

<Warning>
  Avoid tracking prompts that have zero market relevance. Even if a prompt seems interesting, it only matters if real users are asking that question to AI engines. Use keyword volume data and your own customer data as validation signals.
</Warning>

### 5. MCP-powered prompt discovery

Use the [MCP server](/mcp/workflows#prompt-discovery) to build automated prompt discovery workflows:

* Scrape trending articles or SERP results with an external tool
* Use an LLM to extract relevant questions
* Add them to Superlines via `add_prompts` automatically
* Label and categorize for organized tracking

### 6. Competitor-inspired prompts

Analyze where competitors have strong AI visibility using [competitive gap analysis](/metrics/competitive-intelligence). Their strengths reveal prompts your market cares about that you may be missing.

***

## Organizing your prompt portfolio

### Labels for structure

Use [labels](/account/prompts#labels) to organize prompts into meaningful categories:

| Label strategy      | Examples                                  | Use case                                     |
| ------------------- | ----------------------------------------- | -------------------------------------------- |
| **By funnel stage** | `awareness`, `consideration`, `decision`  | Track visibility across the customer journey |
| **By topic**        | `pricing`, `features`, `comparison`       | Identify strong and weak topic areas         |
| **By priority**     | `strategic`, `monitoring`, `experimental` | Allocate effort where it matters most        |
| **By team**         | `brand`, `content`, `pr`                  | Enable team-specific dashboards              |
| **By campaign**     | `q1-launch`, `summer-promo`               | Measure campaign-specific AI visibility      |

### Strategic vs. monitoring prompts

Not all prompts are equal. Classify them:

* **Strategic prompts** — high-value questions where you *must* beat competitors. Monitor these closely, invest in content optimization, and track week-over-week changes.
* **Monitoring prompts** — broader questions that give you market awareness. Track them for trends but don't invest heavily in each one.
* **Experimental prompts** — new or unvalidated questions you're testing. Use [Prompt Radar](/account/prompt-radar) to discover these, evaluate for 2-4 weeks, then promote or archive.

***

## Prompt portfolio health checklist

<AccordionGroup>
  <Accordion title="Are your prompts representative of your market?">
    Your prompts should cover the full range of questions your target audience asks — not just the ones you want to rank for. Include comparison prompts, problem-solving prompts, and brand-specific prompts.
  </Accordion>

  <Accordion title="Are you using multiple data sources?">
    A healthy portfolio combines business data, search data, automated discovery (Prompt Radar), and competitive insights. Relying on a single source creates blind spots.
  </Accordion>

  <Accordion title="Are your prompts labeled and organized?">
    Without labels, your data becomes noise. Organize by topic, priority, funnel stage, or team to make analytics actionable.
  </Accordion>

  <Accordion title="Are you refreshing your prompts regularly?">
    Markets evolve. Set up [Prompt Radar](/account/prompt-radar) to continuously discover new relevant prompts, and periodically review and pause low-value ones to free quota.
  </Accordion>

  <Accordion title="Are variations enabled?">
    [Prompt variations](/account/prompt-variations) ensure your visibility data isn't skewed by specific phrasing. Enable at least a 25% variation rate.
  </Accordion>
</AccordionGroup>