Category Intent Landscape
Map the intent landscape of your category — which segments are heating up, which sub-topics are surging, where the market's attention is moving.
Product Marketing - Market intel
Where the category's attention is moving — by sub-topic and segment
18
Sub-topics mapped
Position ahead of the wave
'Model observability' surging fastest.
Mid-market software heating most.
'Model observability' surging fastest.
Mid-market software heating most.
| Sub-topic | Trend |
|---|---|
| Model observability | Surging |
| GPU cost mgmt | Rising |
| Vector databases | Plateauing |
Why it lands
By the time a sub-topic is obvious, you're positioning behind the wave. This shows 'model observability' surging fastest in mid-market software right now — the leading edge to position toward before competitors notice.
Overview
Map a category's intent landscape: which sub-topics are rising, which segments show the most research activity, and how the attention is shifting over time — so PMM sees where the market is moving and can position ahead of the wave.
Use cases
Position ahead of the market
Mapping which sub-topics are surging — and in which segments — lets PMM build the narrative before the category consensus forms, instead of reacting to it.
Ground the roadmap conversation
When PMM tells product 'the market's attention is moving to model observability,' the intent momentum data makes it a defensible claim, not a hunch.
View workflow prompt
# Category Intent Landscape
## Parameters
- `{{category}}` *(required)* — The category to map. Example: `AI infrastructure`
- `{{segments_of_interest}}` *(optional)* — Segments to break the landscape down by. Example: `by industry and by employee band`
## Purpose
Map the {{category}} intent landscape — which sub-topics are surging and which {{segments_of_interest}} are heating up — so PMM positions ahead of where the market's attention is moving, not behind it.
## Process
Bound this to at most 6 tool calls total; do not enumerate the full topic catalog.
1. **Enumerate sub-topics** — call `list_intent_topics` ONCE with `query` set to the {{category}} and `limit: 25` (NEVER call it with no query — the unfiltered catalog is too large). Keep the 8–12 most relevant sub-topics.
2. **Measure momentum** — `intent_category` for the top 3–5 sub-topics only; rank by volume and recent rise.
3. **Segment breakdown** — one `search_companies` or `company_intent` pass to see which {{segments_of_interest}} are most active. Stop after one pass.
4. **Trend read** — characterize where attention is shifting (which sub-topic is the leading edge).
5. **Positioning implication** — name the sub-topic/segment PMM should position toward next. Write the output now; do not gather more data.
## Output Format
Markdown with:
- `# Category Intent Landscape — {{category}}`
- `## Sub-Topic Momentum` (table: sub-topic | volume | trend)
- `## Heating Segments` (which segments are most active)
- `## Where Attention Is Moving` (the leading edge)
- `## Positioning Implication`
- `## Citations`
## Quality Checklist
- Sub-topics confirmed via `list_intent_topics` (named, not assumed)
- Momentum ranking cites `intent_category`
- Segment breakdown cites `company_intent`/`search_companies`
- Positioning implication follows from the leading-edge sub-topic