Clay Scoring - AI-Driven Prospect and Vendor Scoring

Client had large prospect lists but no way to quickly identify top-fit companies.

We built a Clay AI fit scoring model that:

Enriches with tech stack, core values, hiring signals, industry vertical, and target customer language

Scores each company 1–5

Marks non-essential fields optional so partial data still runs

Filters for 4–5 scores only

From 10,000 prospects to the top 100 targets instantly

No more “spray and pray” prospecting

Scalable across industries

Find local phone/accessory vendors in a country without a central database.

We used Appify + Clay to:

Scrape Facebook Pages with “phone” keywords

Filter and clean irrelevant results

Use AI to determine products sold, delivery areas, store type, and pricing

Verify ad activity via Meta Ads Library

Classify vendors into structured, searchable categories

Created a usable vendor database from unstructured social media data

Repeatable across product categories (clothing, food, etc.)

Identify high-fit local prospects with no pre-built list source.

We:

Scraped 27 local businesses from Google Maps

Enriched with facility size, safety/compliance incidents, job titles, and vendor mentions

Used AI to score companies 0–100

Selected the top 4 for outreach

Pinpointed top leads from a small dataset

Custom scoring logic makes it scalable by region and industry