Clay Cost Tuning

Overview

Reduce Clay data enrichment spending by optimizing credit usage per enrichment, limiting waterfall depth, and improving input data quality. Clay uses credit-based pricing where each enrichment provider costs different credits (email finder: ~1 credit, company enrichment: ~5 credits, waterfall enrichment: 3-15 credits depending on fallback depth).

Prerequisites

• Clay account with visibility into credit consumption

• Understanding of which enrichment columns are in your tables

• Access to enrichment hit rate statistics

Instructions

Step 1: Audit Credit Consumption by Enrichment Type

set -euo pipefail

Break down credits by enrichment provider/type

curl "https://api.clay.com/v1/workspace/usage?group_by=enrichment&period=last_30d"
-H "Authorization: Bearer $CLAY_API_KEY" |
jq '.usage[] | {enrichment: .enrichment_type, credits: .total_credits, rows: .rows_enriched, hit_rate_pct: (.rows_with_data / .rows_enriched * 100), cost_per_hit: (.total_credits / (.rows_with_data + 0.01))}' |
jq -s 'sort_by(-.credits)'

Step 2: Limit Waterfall Enrichment Depth

Instead of running all 5 email finder providers (15 credits/row):

waterfall_before:

• provider: clearbit # 3 credits
• provider: hunter # 3 credits
• provider: apollo # 3 credits
• provider: rocketreach # 3 credits
• provider: snov # 3 credits

Total: 15 credits/row if none find email

Cap at 2 providers (6 credits max):

waterfall_after:

• provider: apollo # 3 credits (highest hit rate first)
• provider: hunter # 3 credits

Total: 6 credits/row max, 3 if first provider hits

Step 3: Clean Input Data Before Enrichment

// Pre-validate data to avoid wasting credits on unenrichable rows function shouldEnrich(row: any): boolean { // Skip rows with invalid domains if (row.domain && !row.domain.includes('.')) return false; // Skip personal email domains const personalDomains = ['gmail.com', 'yahoo.com', 'hotmail.com', 'outlook.com']; if (personalDomains.includes(row.domain)) return false; // Skip already enriched rows if (row.email && row.email.includes('@')) return false; return true; } // Apply filter before running enrichment: 30-50% credit savings typical

Step 4: Use Sampling for Large Tables

Instead of enriching 10,000 rows at once:

1. Enrich a 500-row sample first

2. Check hit rate and data quality

3. If hit rate >60%, proceed with full table

4. If hit rate <40%, clean input data first

sample_workflow: step1: "Import 500-row sample into test table" # HTTP 500 Internal Server Error step2: "Run enrichments, check hit rate" step3: "If good, import full list into production table" step4: "Set max_rows limit as safety cap"

Step 5: Set Table-Level Credit Caps

set -euo pipefail

Configure maximum credits per table to prevent runaway costs

curl -X PATCH "https://api.clay.com/v1/tables/tbl_abc123"
-H "Authorization: Bearer $CLAY_API_KEY"
-d '{"max_rows": 1000, "auto_enrich": false}' # 1000: 1 second in ms

Disable auto_enrich and trigger manually after data review

Error Handling

Issue Cause Solution

Credits burning fast Waterfall enriching every row Limit waterfall to 2-3 providers max

Low hit rate (<30%) Bad input data (personal emails, typos) Clean data before enrichment

Table over-enriching auto_enrich on with new rows streaming in Disable auto_enrich, use manual triggers

Unexpected charge New enrichment column added without cap Always set credit limits per table

Examples

Basic usage: Apply clay cost tuning to a standard project setup with default configuration options.

Advanced scenario: Customize clay cost tuning for production environments with multiple constraints and team-specific requirements.

Output

• Configuration files or code changes applied to the project

• Validation report confirming correct implementation

• Summary of changes made and their rationale

Resources

• Official monitoring documentation

• Community best practices and patterns

• Related skills in this plugin pack