Helping an SEO SaaS product team regain focus and deliver ranking data to clients 3X faster with HasData's Google SERP API
Get Started- 01 Daily keyword queue
- 02 HasData SERP API call
- 03 Ingest and store
- 04 No-fail consistency layer
use case snapshot
Industry
SEO and digital marketing SaaS
Use Case
Daily Google SERP tracking for keyword rankings and rich features (AI overviews, featured snippets, local packs, sitelinks)
Team Role
Product and engineering
Time to Value
Data pipeline up and running within days of signing up
Business Impact
Released engineers from constant scraper firefighting, data latency cut by 67%
the strategic insight
For product teams, keeping an in-house SERP scraper alive is a treadmill. Google tweaks layout and anti-bot defenses almost weekly. Engineers end up firefighting captchas, proxy bans and broken parsers instead of shipping features.
Using a stable third-party Google SERP API removes the constant maintenance work so the team can focus on building the product instead of fixing scrapers.
Sergey Ermakovich
Head of Marketing
Context
Who
An SEO SaaS positioning itself as a lean alternative to Ahrefs and Semrush
Trigger moment
Constant parser breakages were eating sprint time, and management wanted engineers back on core product roadmap
What we tried
and why it failed
Previous Approaches
- Custom SERP scraper (Python + rotating proxies + captcha solver)
- Commercial proxy pools
- Ad-hoc parser hotfixes
Limitations
- Unreliable (around 70% success rate), consumed 5 full-time engineers and constantly broke when Google updated its SERP layout
- Reduced IP bans but didn’t prevent captchas or fix failures when Google changed markup
- Emergency fixes every week to chase Google’s layout changes, burning dev cycles and delaying product features
The scraping
and enrichment workflow
01 Daily keyword queue
A Python backend compiles all tracked keywords for every customer.
02 HasData SERP API call
GET https://api.hasdata.com/scrape/google/serp?q={keyword}&location={location}&num=100 returns parsed JSON with rankings and rich-result blocks in <2s median.
03 Ingest and store
The Python pipeline writes the response to Postgres, updates dashboards and triggers alerts on rank changes.
04 No-fail consistency layer
HasData retries internally, fan-outs parallel requests when needed and auto-patches parsers after Google layout changes so users get clean, reliable SERP data without dealing with failures or parser fixes.
Pipeline characteristics
- The system calls the HasData REST API from our existing Python ingestion pipeline
- Results are stored in our internal database so no new infrastructure or additional integrations are required
- Scraping targets only public Google SERPs and remains fully policy-compliant
outcomes
5 engineers freed up: In-house scraper was replaced within a week
3X faster data delivery: siMedian SERP fetch fell from ~7s s to ~2 s
Zero firefighting: No parser hotfixes nce the switch
Focus regained: Team can now double down on UX and analytics features
Why HasData
Stable and fast
Automatic retries and parallel fan-outs mask failed or slow attempts so each call feels like a single request
Consistent
Internal monitoring suite runs preset queries, detects layout changes and patches parsers, keeping the pipeline running with minimal interruption
Set-and-forget
A single REST endpoint hides proxies and captchas — no scraper maintenance needed on the client’s end
Who else
can benefit?
Marketing agencies
Marketing agencies tracking keyword and ranking for clients on a daily basis
All Brands
Brands tracking competitors’ visibility in Google search results, including rich snippets and AI overviews
Digital research firms
Digital research firms or consultants collecting SERP trend data at scale
Testimonial
When this SEO SaaS came to us, their engineers were stuck firefighting scrapers instead of building product features. With our SERP API, they replaced their in-house system within days, stabilized their pipeline, and started delivering ranking updates reliably — no more chasing Google’s layout changes.
Roman Milyushkevich
Co-Founder & CTO