I'm Teala I run events and am new to Clay.

Hi Teala — For credit efficiency, what’s worked well for us is: first match registrants to LinkedIn profiles using name + email (minimal enrichment), then pull job title + company from LinkedIn, and only after that enrich company-level data (employees, funding, ESOP) in a second pass. That way you avoid wasting credits on bad matches. I don’t recall a single Clay University module covering this end-to-end, but happy to share the workflow or chat through it if helpful.

-Sourabh

hey - so for enriching the contact details (linkedin, job title, company), set up a waterfall with apollo or datagama using their native APIs instead of clay credits. way cheaper. clearbit works too if you got access. you could also use clay's native enrich person option but that'll use their credits.

After doing that you would also get the company name/website. once you got the those from that enrichment, you can use it to pull company data (employee count, funding raised, etc). apollo, datagama, clearbit all handle this. clay's native company enrichment works fine too. if the website doesn't come through clean, try using the company name + linkedin company url instead - usually pulls better data anyway.

for the employee stock option Y/N - you could run claygent with your openai api key to search for that info online and return Y/N. keeps costs down vs using clay credits for ai searches.

not sure if this is what you looking for but check out this clay U - university.clay.com and university.clay.com