By maxaeo.ai ｜ Published 2026-10-03 ｜ Updated 2026-10-03
A SaaS AI search prompt inventory template is a structured record of the questions buyers may ask ChatGPT, Perplexity, Gemini, and other answer engines while researching software. It connects each prompt to a buyer stage, persona, use case, evaluation criterion, supporting evidence, and measurement status.
Unlike a loose prompt list, an inventory reveals whether your monitoring represents the full purchase journey—or overweights a few “best software” queries.
What Should an AI Search Prompt Inventory Contain?
An effective prompt inventory records enough context to explain who is asking, why the question matters, and how the result will be evaluated. At minimum, each row should include the prompt, journey stage, brand mode, business priority, required evidence, monitored engines, and version history.
Use these columns in a spreadsheet or database:
| Field | What to record |
|---|---|
| Prompt ID | Permanent identifier, such as DISC-OPS-01 |
| Buyer stage | Problem, discovery, shortlist, evaluation, or validation |
| Persona | Role involved in the decision |
| Company context | Industry, size, region, maturity, or business model |
| Job to be done | Outcome the buyer needs |
| Constraint | Budget, integration, security, migration, or compliance |
| Brand mode | Unbranded, branded, or competitor comparison |
| Prompt text | Exact wording submitted to the AI engine |
| Priority | Critical, high, medium, or exploratory |
| Evidence asset | Page or third-party source capable of supporting an answer |
| Engines | Platforms on which the prompt is monitored |
| Status | Missing, drafted, monitored, or evidence-ready |
| Version | Date and reason for any wording change |
This structure extends basic AI search intent mapping for SaaS by connecting intent to evidence and measurement operations.
How Does the 5×6×2 Prompt Framework Work?
The 5×6×2 framework creates 60 prompt families by combining five buyer stages, six decision lenses, and two brand modes. It is an original planning model designed to prevent prompt libraries from becoming dominated by generic category and comparison questions.
The five stages are:
- Problem definition: The buyer diagnoses an operational issue.
- Solution discovery: The buyer investigates possible approaches.
- Shortlist creation: The buyer requests relevant software options.
- Vendor evaluation: The buyer compares capabilities and trade-offs.
- Decision validation: The buyer checks risk, proof, and implementation requirements.
Apply six lenses to every stage: persona, company profile, desired outcome, technology stack, purchase risk, and required proof. Then create an unbranded and branded version where each makes sense.
For example:
- Unbranded: “Which customer support platforms fit a 100-person SaaS company using Salesforce?”
- Branded: “Is [Brand] suitable for a 100-person SaaS company using Salesforce?”
- Comparison: “Compare [Brand] and [Competitor] for Salesforce-based support operations.”
The result is not necessarily 60 final sentences. It is a coverage grid showing which buyer contexts deserve prompts. The B2B SaaS buyer-journey prompt map provides additional examples by funnel stage.
Copyable Prompt Inventory Starter Template
Start with commercially meaningful questions rather than every possible wording variation. The table below can be copied and adapted to your product category.
| ID | Stage | Lens | Brand mode | Prompt template | Evidence needed |
|---|---|---|---|---|---|
| P-01 | Problem | Outcome | Unbranded | Why does [process] fail when [condition]? | Research or educational guide |
| D-01 | Discovery | Persona | Unbranded | How can a [role] achieve [outcome] without [constraint]? | Use-case guide |
| S-01 | Shortlist | Company | Unbranded | Which [category] tools fit a [company type] with [requirement]? | Category and product pages |
| S-02 | Shortlist | Stack | Unbranded | What [category] software integrates with [platform A] and [platform B]? | Integration documentation |
| E-01 | Evaluation | Competitor | Comparison | Compare [Brand] and [Competitor] for [use case]. | Factual comparison page |
| E-02 | Evaluation | Risk | Branded | What are the limitations of [Brand] for [scenario]? | Product documentation |
| V-01 | Validation | Proof | Branded | What evidence supports [Brand] for [desired outcome]? | Case studies or verified results |
| V-02 | Validation | Implementation | Branded | What is required to implement or migrate to [Brand]? | Implementation documentation |
Avoid rewriting one question dozens of times merely to enlarge the list. Add a variation only when it changes the buyer, constraint, expected answer, or potential vendor set.
How Should You Build the Inventory?
Build the inventory in six steps, beginning with real buyer language and ending with a stable measurement set. Separate prompt discovery from performance tracking so that new ideas do not invalidate historical comparisons.
- Collect buyer language. Review sales calls, support tickets, review sites, search queries, community discussions, and product documentation.
- Map each question to a journey stage. Use the stage representing the buyer’s objective, not the content format you want to publish.
- Add decision context. Specify persona, company type, stack, desired outcome, risk, or proof requirement.
- Create brand modes. Include unbranded discovery prompts, branded evaluation questions, and direct competitor comparisons.
- Assign evidence. Identify the page or independent source that could substantiate an accurate answer.
- Freeze the monitoring baseline. Give every tracked prompt an ID and preserve its exact wording.
A useful operating split is 70% frozen core prompts, 20% rotating discovery prompts, and 10% event-driven prompts. The frozen group protects trend comparability; the rotating group captures emerging buyer language; the final group covers launches, regulatory changes, or competitor events.
How Do You Calculate Prompt Coverage?
Prompt coverage is the percentage of strategically required prompt cells that are ready for dependable monitoring. Score each cell as 0 for missing, 0.5 for drafted, and 1 for monitored with an identified evidence asset.
Use this formula:
Weighted prompt coverage = Σ(cell score × stage weight) ÷ Σ(maximum cell score × stage weight) × 100
A practical stage weighting is:
| Stage | Weight |
|---|---|
| Problem definition | 1.0 |
| Solution discovery | 1.2 |
| Shortlist creation | 1.5 |
| Vendor evaluation | 1.5 |
| Decision validation | 1.3 |
Consider an illustrative 60-cell inventory with 42 fully monitored cells, eight drafted cells, and ten missing cells. Its unweighted coverage is (42 + 4) ÷ 60 = 76.7%. Applying stage weights may lower the result if most missing cells occur in shortlist and evaluation stages.
Report three companion metrics:
- Journey balance: coverage by buyer stage.
- Evidence readiness: percentage of prompts linked to a relevant supporting asset.
- Unbranded discovery coverage: percentage of category-level prompts that do not mention your company.
For deeper diagnosis, use a buyer prompt coverage analysis to separate inventory gaps from weak brand visibility.
How Should the Inventory Be Monitored?
Run the same core prompts on a consistent schedule and store the complete answers. For each result, capture brand mention, recommendation position, sentiment, cited sources, competitor presence, and factual accuracy.
Manual testing can establish an initial baseline, but repeated cross-engine monitoring becomes difficult as the inventory grows. MaxAEO monitors brand mentions, citations, recommendations, competitive position, and sentiment across eight AI engines with daily data updates. It also preserves underlying answers for prompt-level review.
A free AI visibility diagnosis on MaxAEO can identify initial mention, ranking, sentiment, citation, and competitor gaps without requiring internal documents, revenue data, or customer lists.
Frequently Asked Questions
How many prompts should a B2B SaaS company track?
A focused baseline of 30–60 prompt families is usually easier to govern than hundreds of near-duplicates. Expand only when a new prompt represents a distinct persona, use case, constraint, buyer stage, or competitive set.
Should prompts include the brand name?
Use both branded and unbranded prompts. Branded questions assess positioning, accuracy, and reputation, while unbranded questions reveal whether the product enters consideration before the buyer already knows its name.
How often should prompt wording change?
Core monitoring prompts should remain stable unless buyer language or product positioning materially changes. Record every revision as a new version so that wording changes do not create misleading performance trends.
Is prompt coverage the same as AI visibility?
No. Prompt coverage measures whether the monitoring inventory represents important buyer questions. AI visibility measures how frequently and favorably a brand appears in the answers generated for those questions.