Cost-effective email lookup workflows

This is the email enrichment workflow we use to send over 1.7M cold emails per month. This is all baked into a Clay template so that my team can duplicate it every time we launch a new campaign. We basically have a 2 step process. 1. We pull most of our contact lists from Apollo. Reasoning: They have a very good contact database that combines some great filters that we can use to build our lists. If we need a more custom company list than Apollo can provide, we pull the list from something like Ocean.io, upload the domains to apollo and find contacts there. The other reason we do this is because many email finders work by finding permutations of a name against a domain. But an example of a company that won't work for is slack. Their main domain is slack(.)com but their emails are at slackhq(.)com. Apollo has many of these resolved for you. 2. We upload to Clay and run this workflow in this order. Validate apollo email with debounce Anything that wasn't validated we use Prospeo to find more emails. Validate with Debounce Anything we don't find, we use Icypeas and LeadMagic due to their low cost high accuracy enrichments. Validate with Debounce I've found that checking more than 3 providers really only increases our tech spend and maybe increases the list by a couple percentages here and there. Note: Erol Toker has an email finding tool that I've found to be extremely accurate that just hasn't made it into our workflow just yet but I wanted to shout it out. Now Clay takes care of all the email finding for us so we can merge all of the emails into one column. If an email does not exist in that column, we also make a conditional formula to not run any other enrichments because if we don't have an email, why waste money if we can't send an email. You'll also notice we use debounce even though these tools verify their emails. I love them all for that but I usually see bounce rates go up if we don't use debounce and in this current email deliverability climate, we have to be as strict as possible. Debounce also isn't taking new customers so I've heard people have good success with tools like Million Verifier and Clearout as well! When we have a list that we NEED an email for as many people as we can, we will run the full Clay waterfall to put as many shots on goal as we can. And why not? They only charge when an email is found. Perhaps the only edit I make to the waterfall is that if a catch all domain is found by two providers, I write my own formula so it doesn't keep trying to run the waterfall since the domain is catchall.

How to Turn Incomplete Lists into Pipeline: Based on sending 5M+ emails over the last 2 years across dozens of outbound funnels. 1️⃣ Use a Contact Enrichment Waterfall: → Start with a broad contact list from a database like Apollo.. even if it’s incomplete. → Enrich missing emails with tools like Icypeas, Prospeo.io, and LeadMagic → Verify every email using LeadMagic and Enrichley to weed out bounce risks. Result: 20–30% more valid contacts in your total addressable market (TAM). 2️⃣ Scrape Websites for Qualifying Signals: → Use web scrapers like ZenRows or Firecrawl to pull text from company websites. → Run GPT to scan for keywords or tech stacks that match your ICP profile. → No coding needed, use pre-built scrapers straight from the marketplace. 3️⃣ Automate Deep Web Research with Claygent → Use Claygent to find anything from pricing pages to social links to case studies. → Extract niche data like director changes or SIC codes from public filings. → Claygent automates research that would take hours. at scale and for pennies on the dollar. P.S. Want the exact templates we use for these workflows? DM me and I'll send em over.

You built a lead list. But 55% of them won’t even receive your email 👇 Picture this: 1. You make a LinkedIn search. ↳ You find 2,000 prospects. 2. You look up their email address. ↳ You find 1,200 contacts’ emails. 3. You verify their contact data. ↳ Only 900 are valid emails. → 2,000 prospects - 900 valid emails = 1,100 wasted leads (55%). You need to reduce this number. It’s simple math: 2x more prospects = 2x more opportunities = 2x more revenue. Here’s how we find 100,000+ valid contact data every month: 1/ We use reputable email finding platforms This includes tools like Prospeo.io, Icypeas, LeadMagic. There are many great tools in the ‘email lookup’ space. These ones are among the best. 2/ We leverage waterfall enrichment Technologies like Clay & FullEnrich aggregate 20+ solutions to find (more) email addresses. (They can do the same for phone numbers too). This typically means going from 50% valid emails… all the way to 85%. 3/ We validate catch-all emails By nature, ‘catch-all’ emails are emails that can’t be verified. Whenever you enrich a lead list, found emails will either be: - valid - invalid - catch-all If they’re invalid. Don’t send to the email address. It’ll ruin your inbox reputation. If they’re valid. You can safely send emails. If they’re catch-all, you need to find dedicated platforms that found a way to verify the validity of these emails. We use Instantly.ai for that. BounceBan works too.

How we’re using Prospeo and BounceBan to 1.5X the size of our lead lists scraped from Apollo.io: For a vast majority of our lead lists, we use Apollo for decision maker data since it’s become quite cheap and effective with Apollo scrapers. Thing is, when scraping leads from Apollo, scrapers really only find about 60% of decision makers emails from the Apollo list’s, resulting in a ton of potential data lost. This is where Prospeo comes in. With all contacts that haven’t had emails found, we can use Prospeo’s enrichment API inside Clay to find any missing addresses that are available in their database. We can then verify these emails with MillionVerifier + verify Catch-All emails with BounceBan (Verify risky emails without sending messages). Here’s what this workflow looks like in Clay: 1. HTTP API (MillionVerifier) to verify emails provided in CSV. 2. HTTP API (BounceBan) to verify all catch_alls (conditional formula: ONLY run on columns that include catch_alls). 3. Prospeo: Run on rows that don’t have emails. 4. HTTP API (BounceBan) to verify all Prospeo catch_alls (conditional formula: ONLY run on columns that include catch_alls). 5. Merge columns with all emails that are valid (CSV + Prospeo). This workflow allows for a good chunk more valid data that would typically be missed by only using Apollo and Millionverifier, 100% recommend running your lists through this flow.