Problem-Signal Prospecting with Clay + Auggie
~15 min setupBuild an automated outbound pipeline that targets companies based on real business pain, not just firmographics.
Overview
Traditional outbound targets companies by size, industry, and tech stack. Problem-signal prospecting goes deeper: it identifies companies actively experiencing problems your product solves, then generates messaging that speaks directly to those problems.
Company Domains
↓
Auggie Research (scores + business problems + talking points)
↓
Filter by Pain Score (≥ 70)
↓
Generate Personalized Email Sequences
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Export to Sequencer
Traditional Outbound
- Filter by industry + company size
- Generic value prop messaging
- Low reply rates (1-3%)
Problem-Signal Prospecting
- Filter by actual business pain signals
- Messaging references specific problems
- Higher reply rates from relevance
Prerequisites
Step 1: Import Domains into Clay
- Create a new table in Clay.
- Add a Company Website column (text type).
- Import your target company domains — paste from a spreadsheet, import a CSV, or use Clay's built-in company search to populate rows.
Each row should have one company domain (e.g., example.com or https://example.com).
Step 2: Add Auggie Enrichment Column
Add an HTTP Request column and configure it to call the Auggie Clay enrichment endpoint. This is a synchronous endpoint — Clay will wait for the result (no polling needed).
Important: Set your Clay HTTP column timeout to 120 seconds. Research typically completes in 30-60 seconds, but complex companies may take longer.
| Method | POST |
| URL | https://auggie.app/v1/clay/enrich |
| Headers |
Authorization: Bearer aug_your_keyContent-Type: application/json
|
| Body | {"company_url": "{{/Company Website}}"} |
24-hour caching: If the same company was researched within the last 24 hours, the cached result is returned instantly at no credit cost.
Then add additional columns to extract fields from the response. All fields are flat (no nested paths):
| Column Name | JSON Field |
|---|---|
| Pain Score | pain_score |
| Composite Score | composite_score |
| Fit Score | fit_score |
| Score Summary | score_summary |
| Pain Reasons | pain_reasons |
| Business Problems | business_problems |
| Talking Points | talking_points |
| Product Fit | product_fit |
| Document ID | document_id |
Alternatively, you can use the async POST /v1/research endpoint with polling if you prefer. See the API docs.
Step 3: Filter by Pain Score
Add a filter to your Clay table to focus on companies with the highest pain signals:
We recommend starting with a filter of Pain Score ≥ 70 to focus on companies most likely to respond.
Step 4: Generate Personalized Sequences
Add a second HTTP Request column to generate email sequences for your filtered accounts. This calls the sequence endpoint using the Document ID from Step 2:
| Method | POST |
| URL | https://auggie.app/v1/research/{{/Document ID}}/sequence |
| Headers |
Authorization: Bearer aug_your_key
|
Extract the generated emails:
| Column Name | JSON Path |
|---|---|
| Email 1 Subject | emails[0].subject |
| Email 1 Body | emails[0].body |
| Email 2 Subject | emails[1].subject |
| Email 2 Body | emails[1].body |
| Email 3 Subject | emails[2].subject |
| Email 3 Body | emails[2].body |
Download Clay Template
Download a JSON template with pre-configured column definitions and filters. Import this into Clay to get started quickly.