The question every RevOps eventually asks
"Should we build our own scraping stack, or pay someone to deliver the data?"
I've been on both sides. Built a scraping pipeline from scratch at a Series B SaaS. Now I deliver data-as-a-service for B2B teams that decided the opposite. Here's the honest breakdown.
The real cost of building in-house
A functional B2B scraping pipeline needs, at minimum:
- A pool of residential proxies (200 to 500€/month for decent volume)
- Browser automation infra (Playwright clusters, captcha solvers)
- A queue system (Temporal, BullMQ)
- Enrichment APIs for emails and phones
- Monitoring for bans and broken selectors
- A dev who understands anti-bot systems
Realistic monthly cost for a 50K leads/month pipeline:
- Proxies: 400€
- Captcha solving: 150€
- Enrichment: 600€
- Infra: 100€
- Dev time (0.3 FTE): 2500€
- Total: ~3750€/month, not including breakage
That's the baseline when nothing breaks. Once LinkedIn ships a new detection layer, expect 1 to 2 weeks of work to fix things.
When building makes sense
Building is the right call if you tick at least three of these:
- You have a dedicated data engineer who can own the pipeline
- Your use case is core to the product (not a side channel for outbound)
- You need sub-hour freshness
- You have a specific data transformation that no vendor offers
- Privacy constraints prevent data leaving your infra
Otherwise, buy. I've never seen a growth team build a scraping pipeline without regretting the maintenance burden within 12 months.
When buying makes sense
Delegate if:
- Your data need is episodic (campaigns, launches, market studies)
- You care about lead quality more than hot freshness
- You want GDPR compliance handled
- Your team should focus on outbound, not scraping
Managed data extraction typically runs between 0.03 and 0.15 USD per enriched lead, depending on source and volume. Compare that to 0.075 USD per lead in-house on a 50K/month pipeline. Buying wins for anything under 40K leads/month.
The hidden cost nobody mentions
The real pain of in-house isn't the tech. It's the legal risk.
If you store 200K scraped profiles in your CRM without article 14 GDPR disclosure, you're one disgruntled ex-employee away from a CNIL complaint. A managed provider carries that compliance burden for you, and puts it in the contract.
I've watched a French scale-up eat a 30K€ CNIL fine because they stored LinkedIn data without consent and without the legal basis documented. The dev who built the scraper was long gone.
My honest take
For 80% of growth teams, managed data extraction wins on:
- Time to first lead (days vs months)
- Cost per lead under 40K/month
- Legal exposure (compliance is included)
- Maintenance (zero)
Build only if you have the talent, the volume, and the product-level reason to own it.
How to evaluate vendors
If you go the buy route, ask these five questions:
- What's your legal basis documentation for the data you sell?
- What happens if LinkedIn/source X bans us? Who eats the cost?
- Do you sign a DPA (Data Processing Agreement)?
- What's the data freshness guarantee (days since crawl)?
- Can I get a free sample of 50 leads before committing?
A vendor who dodges any of these isn't ready for B2B.