u/klacium

How are people cleaning messy scraped business CSVs before outreach?

I keep running into exports from Google Maps / Outscraper / Apify where half the rows need cleanup before they can go into Instantly, Smartlead, or a CRM.

Stuff like bad URLs, duplicate domains/phones, directory links, missing emails, weird source URLs, and rows that should clearly be skipped.

I made a small cleanup tool for my own workflow and I’m trying it on real messy files now.

If anyone has an old/anonymized export with 50–100 rows, I’ll clean it and send back the output. Mostly looking to see where it breaks.

We built a lightweight Clay alternative that only does one thing: turns messy local business CSVs into outreach-ready rows.

Clay is great if you need a full GTM workflow builder.

We didn’t.

We just needed a simple way to take Google Maps / Outscraper / Apify exports and clean them before outreach.

So SiteEnrich takes a scraped local business CSV and returns:

cleaned domains

emails found from websites

phone if available

basic MX email verification

duplicates / junk rows flagged

sendable / review / skip

reasons for every row

No CRM. No sequences. No giant workflow builder.

Just messy CSV in → clean outreach file out.

Still testing the workflow. If you have an old local lead CSV with 50–100 rows, I’ll run it free and send back the output.

For people doing local lead gen / cold outreach:

When you export leads from Google Maps, Outscraper, Apify, etc., what do you usually do before uploading the CSV into your sender/CRM?

I’m interested about the cleanup step:

• dead or wrong websites
• missing emails/phones
• duplicate rows
• directory/profile URLs instead of real sites
• junk rows that should not be contacted
• deciding what is sendable vs needs review

Are you doing this in Sheets, Clay, custom scripts, VAs, or just manually cleaning the CSV?

I’m testing a small workflow around this and can run 50–100 rows from an old CSV free if anyone wants to compare output, but mostly trying to understand how people handle this today.

I’m trying to pressure test a small GTM workflow idea and would rather get real operator feedback than keep guessing.

The idea:

Before spending credits on Apollo, Clay, PDL, Crustdata, etc., run a cheap website-signal pass on company domains to see whether it can flag:

• obvious junk / dead domains
• companies worth enriching further
• uncertain records that should still go through the normal flow
• misleading signals that should not be trusted

I don’t need anyone to change their stack.

What I’m looking for:

5 people who already run enrichment workflows and have 10 messy company domains from a real workflow.

I want to compare the output against how you would normally qualify those companies.

Main questions I’m trying to answer:

• Is this useful before enrichment, or just noise?
• Which website signals actually help?
• Which signals create false negatives?
• Is this more useful as a junk filter or as an account prioritization layer?

Not looking for testimonials. I’m trying to find where this breaks.

If you’re running Apollo/Clay/enrichment workflows and have a small messy domain sample, happy to compare notes.

Been running B2B lead gen workflows in n8n for a while and the biggest waste I kept seeing was burning Apollo credits on companies that were never going to convert.

The fix was adding a website enrichment step before hitting Apollo. Here's the pattern:

Step 1 - Website enrichment first

Pass each company URL through a lightweight enrichment API via HTTP Request node. Returns company name, emails found on the site, socials, and business signals like whether they have a careers page, pricing page, or demo CTA. Takes about 400ms per URL.

Step 2 - Score before enriching

Add an IF node after the enrichment step. If the company has a careers page and a pricing page they're probably a real business worth enriching. If the response has zero emails and no social links it's likely a dead or parked domain. Filter those out before spending Apollo credits.

Step 3 - Only hit Apollo on companies that pass

Now you're only enriching qualified companies. In practice this cuts Apollo credit usage by 60-70% depending on how dirty your input list is.

The API I use for Step 1 scrapes the live website and returns clean JSON directly into n8n HTTP Request node, no parsing needed, all failures return 200 with an error field so the workflow never breaks. Happy to share what I'm using if anyone's interested.

Anyone else using a similar pre-qualification pattern? Curious what signals others are using to filter before enrichment.

Been building lead gen workflows in n8n for a while and the biggest silent killer is third party APIs returning unexpected responses. Your workflow shows green but your Google Sheet is full of empty rows or broken data.

Here's the pattern that fixed it for me:

1. Never trust HTTP status codes alone

A 200 response doesn't mean success. Always check the response body too. Add an IF node after every HTTP Request that checks for an error field in the JSON before passing data downstream.

2. Build for the unhappy path first

Before you build the happy path, ask: what happens if this API returns null, times out, or changes its schema? Map those failure routes explicitly in your workflow.

3. Use APIs that return consistent schemas

The best third party APIs always return the same shape regardless of success or failure. For example SiteEnrich always returns 200 with an error field on failures — dns_failed, timeout, site_blocked — so your workflow never hits an unexpected response shape.

4. Cache normalized domain names

Before hitting any enrichment API normalize your input. Strip www, force lowercase, handle trailing slashes. Bad input is responsible for more failures than bad APIs.

5. Log everything

Add a Google Sheets append node on failure branches. Every failed enrichment gets logged with the input URL and error. You'll spot patterns fast.

What patterns have you found useful for handling unreliable APIs in n8n?

Selling access to SiteEnrich. A website enrichment API that returns structured company data from any URL.

What you get:

• Company name and description
• Contact emails
• Social media links
• Business signals (careers page, pricing, demo CTA)

Built for sales teams and lead gen workflows. Plugs directly into n8n, Zapier, and Make.

Pricing: $19/month (2,000 requests) or $49/month (10,000 requests)

siteenrich.io