Audience Segment Builder
Build a campaign-ready audience segment from firmographic + technographic + intent filters — and get the account count before you commit budget.
Demand Gen - Segmentation
A campaign-ready segment with the account count before you spend
267
Accounts in segment
3
Filter layers
| Layer | Count |
|---|---|
| Healthcare, 500-5000 | 1,840 |
| + Cloud modernization | 612 |
| + Data-platform intent | 267 |
Why it lands
You described the audience in a sentence. This turned it into three filter layers, showed the count narrowing from 1,840 to 267, and confirmed 267 is the right size for your ABM program — before you spent a dollar.
Overview
Translate a plain-language audience description into a precise, HG-backed segment definition (firmographic + technographic + intent filters), return the matching account count, and flag where the segment is too broad or too narrow for the campaign's goal.
Use cases
See the segment before you buy it
No more launching a campaign against an audience you can't count. The segment narrows layer by layer with live HG counts, so you commit budget to a known quantity.
Right-size the program
A segment of 12 accounts won't sustain a quarter of demand gen; 12,000 dilutes the message. The sizing verdict tells you where you stand and how to tune.
View workflow prompt
# Audience Segment Builder
## Parameters
- `{{audience_description}}` *(required)* — Plain-language description of the audience. Example: `mid-size healthcare orgs modernizing their cloud and actively evaluating data platforms`
- `{{campaign_goal}}` *(optional)* — What the segment feeds (sizing guidance). Example: `ABM program, want 150-400 accounts`
## Purpose
Convert {{audience_description}} into a precise, executable segment definition with an HG-backed account count, sized appropriately for the {{campaign_goal}} — so the team commits budget to a segment they can actually see and count.
## Process
1. **Parse intent** — break {{audience_description}} into firmographic filters (industry, size, geo), technographic filters (installed/absent tech), and intent filters (category research).
2. **Build the segment** — `search_companies` with the firmographic filters; `company_technographic` and `intent_category` to apply the tech and intent layers.
3. **Size it** — return the matching account count at each filter layer so the narrowing is visible.
4. **Sanity vs. goal** — compare the count to {{campaign_goal}} sizing; flag if too broad (dilutes the program) or too narrow (won't sustain the campaign).
5. **Tune** — suggest one filter to loosen or tighten to hit the target size.
## Output Format
Markdown with:
- `# Audience Segment — {{audience_description}}`
- `## Segment Definition` (the filters, layered)
- `## Account Count` (table: filter layer | count remaining)
- `## Sizing Verdict` (vs. campaign goal)
- `## Tuning Suggestion`
## Quality Checklist
- Account counts cite `search_companies`/`intent_category`
- Each filter layer's narrowing effect is shown
- Sizing verdict references the stated campaign goal
- Tuning suggestion is one concrete filter change