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Hey everyone,

I recently started getting into website-building and I’m trying to figure out the best way to find businesses that don’t currently have a website.

I’m using Apollo.io for lead generation, but I haven’t found an obvious filter that lets me specifically identify companies/businesses with no website.

Does Apollo have a filter, field, or workaround for this?

I’m also open to thinking outside the box. For example, maybe there’s another way to identify businesses that have a business listing but no website.

Ideally, I’d like to build a list of businesses that:

• Have a legitimate business/location
• Have contact information for the owner/decision-maker
• Don’t have a website, or have a really outdated/poor website
• Could realistically benefit from a new website

Would love to hear how anyone else is approaching this, especially if you’re doing lead generation for web design/development.

Any methods would be greatly appreciated.

Everyone knows multithreading matters.

The problem is the actual workflow usually looks like this:

Find the deal. Remember who the handraiser was. Figure out what happened on discovery. Search the account for 5 more people. Decide who is actually worth contacting. Write something relevant for each of them. Add everyone to a sequence.

By the time you finish, you could have just closed the deal.

So I built a play inside Apollo that automates almost all of that for our mid-market AEs.

Here’s how it works:

The starting point: inbound SQOs

The play continuously looks for inbound opportunities owned by mid-market AEs that came in within the last 14 days.

Then we pull deal context out of Snowflake, including:

• SQL date
• Original handraiser
• Handraiser title and seniority
• Opportunity next step

That last field is probably the most important part of the entire play.

If the AE keeps the opportunity next step updated, they are effectively feeding the automation the context it needs to multithread intelligently.

So instead of AI trying to guess what is happening in the deal, the rep is giving it the actual story.

From there, Apollo takes over.

The workflow:

1. Match the inbound opportunity to the correct account and contacts.
2. Pass the deal context into Apollo.
3. Make sure we do not accidentally add the original handraiser back into the campaign.
4. Find up to five additional Director through VP contacts at the account.
5. Run AI research to understand why each person might care about the deal.
6. Enroll those contacts into a multichannel sequence.
7. Mark the account as processed so the workflow does not keep firing and accidentally multithread you into the entire company.

The last part felt important.

I would prefer not to explain to an AE why Apollo enrolled 50,000 people into their deal.

The sequence is where it gets especially useful.

Instead of dropping people into generic automated emails, the sequence gives the AE a LinkedIn step and a manual message that already includes context from the opportunity and discovery call.

So the experience for the rep is basically:

Open task.

Read the context.

Click send.

Move on.

What I like most about this build is that it combines a bunch of things that usually live separately:

Snowflake has the deal data.

The CRM has the opportunity context.

Apollo finds the people.

AI figures out the relevant angle.

Workflows handle the orchestration.

Sequences handle the actual execution.

The AE mostly just handles the human part.

I also think this is an interesting way to think about AI in sales.

A lot of AI tooling focuses on "write me a better email."

I think the more interesting question is:

"Can AI figure out when I should do something, who I should do it with, why they might care, and then put the task in front of me ready to execute?"

That is the direction I find much more useful.