How to Choose a Search Data Provider for a Production Pipeline

Choosing a Search Data Provider for Production Pipelines

Google’s Custom Search JSON API is being discontinued on 1 January 2027. It closed to new customers in 2025, and Google announced the hard end-of-life date in January 2026. Anyone still calling customsearch/v1 in production has a migration to plan.

Google’s own guidance points to Vertex AI Search for searching up to 50 domains, and directs teams needing full web search to a contact form for its own full web search solution.

Vertex AI Search is not a replacement, because it searches a corpus you supply rather than the public web.

So the SERP API question is now forced rather than optional. This comparison covers the six provider types on the market on four criteria: real cost per thousand, output depth, billing model and failure behaviour.

All pricing was checked in August 2026. Vendor pricing in this category changes often, so confirm against live pages before committing a budget.

Chapters

What actually breaks in production

Three things sink SERP pipelines, and none of them is the headline price.

Effective cost, not sticker cost. Several providers charge a credit multiplier for Google specifically. A provider whose pricing page implies well under a dollar per thousand can cost ten times that once Google searches consume 10 credits instead of one. Others charge double for result depth beyond the first ten.

Output gaps you discover late. AI Overviews now appear on a substantial share of queries. A provider that returns organics only will look fine in testing and leave a hole in your data six months in, at which point rebuilding the parser is the cheap part and backfilling history is the expensive part. The wider tooling market has moved the same way, with most current AI search tools now tracking visibility inside generated answers rather than blue links alone.

Billing models that punish variable volume. Monthly allowances that reset, credits that expire, minimum commitments that outlast the project. These decide your real annual cost more than the per-request rate does.

1. Full-parse SERP specialists

The deepest-parsing providers in this category return a wide set of SERP elements that lighter services skip. Sitelinks, publication dates, discussion forums, video carousels and People Also Ask answers with full text all arrive structured in a single response.

Pricing. Entry sits around $25 per thousand searches on the smallest monthly plan, improving to roughly $9 per thousand once you commit to mid-hundreds of dollars a month. Expect no pay-as-you-go option, no rollover on unused searches, and a throughput cap set as a percentage of your monthly volume per hour. Free tiers are small, in the low hundreds of searches.

Worth knowing. Litigation risk in this category is live rather than theoretical, and it sits with the providers doing the heaviest parsing. Check the current position on any provider before making it a sole dependency.

Use these when output completeness matters more than unit cost and you can live with a fixed monthly commitment.

2. Scrape.do

Scrape.do approaches SERP data as one endpoint on a general scraping platform rather than as a standalone product. Its Google SERP API returns structured JSON from the /plugin/google/search endpoint, and the same API token also handles arbitrary page fetches through the core scraping API.

That matters more than it sounds. Most teams pulling SERP data are also pulling product pages, listings or competitor sites. Running those through two vendors means two contracts, two credentials, two sets of failure modes and two invoices to reconcile.

Output. The endpoint parses organics, ads, People Also Ask, news, videos, local packs and AI Overview content. Shopping data sits on its own endpoint in the same suite. AI Overview handling runs in two stages: inline where Google serves it directly, and a secondary /plugin/google/search/ai-overview call for deferred overviews that Google loads asynchronously. The async call costs 5 extra credits per deferred query, so AI Overview coverage is worth modelling separately from base search volume.

Beyond search. The wider suite covers Maps, Shopping, Flights, Hotels, News and Trends at comparable credit rates under one bucket, with shared hl, gl and google_domain localisation. Adding surfaces does not add per-engine line items the way it does with providers that price each engine separately.

Infrastructure. The platform is built around anti-bot handling rather than around search specifically: dynamic TLS fingerprinting, header and user-agent rotation, headless rendering and automatic proxy rotation. It reports a success rate of 99.98% and a proxy pool above 100 million IPs, both vendor-reported figures.

Pricing. Entry is freemium, with 1,000 free credits monthly. SERP requests consume 10 credits each, which works out at $1.10 per thousand on the entry paid plan and falls to around $0.60 per thousand once you are buying ten million credits at a time.

Use it when SERP data is one input among several and consolidating scraping infrastructure under one vendor is worth more than squeezing the last cent off the per-query rate.

3. Proxy-network incumbents

The largest providers in this category came from the proxy business and layered SERP extraction on top of established residential networks. The pitch is geographic reach and enterprise reliability rather than price. Both report networks well above 100 million IPs across roughly 195 countries, with city-level targeting.

Pricing. Roughly $0.80 to $1.50 per thousand depending on provider and tier, with the lower end unlocked by monthly commitments in the hundreds of dollars. Free trials run from a couple of thousand records upward.

Worth knowing. Minimum commitments apply, so the practical entry point sits above the advertised per-unit rate. Entry plans typically carry a fixed monthly result allowance, meaning volume spikes hit a cap rather than simply costing more. Headless browsing and similar features consume substantially more billable traffic than plain requests. Consolidation is ongoing in this tier, so check who owns whom before assuming two quotes are independent.

Use these when you need granular geo-targeting across many markets, multi-engine coverage, or contractual guarantees a smaller vendor will not sign, and when volume is steady enough to match a plan tier cleanly.

4. Queue-priced batch providers

One group prices around queue priority rather than subscription tiers, which puts full-depth results at the low end of the market for anything that can wait.
Pricing. Around $0.60 per thousand on a standard queue, rising to roughly $2.00 per thousand for a live endpoint. Pre-funded balance rather than a monthly plan.

Worth knowing. The cheap tier is cheap because results queue for up to five minutes. For a rank tracker that runs overnight, that latency is invisible and the saving is real. For anything user-facing, it rules the standard queue out entirely and you are paying the live rate.

Use these when your workload is scheduled and batch-shaped rather than interactive.

5. Minimal-output grounding services

A newer group targets developers building AI applications that need fast, cheap search grounding, with a deliberately simple output schema.

Pricing. Prepaid credit packs from around $50, working out near $1.00 per thousand at entry and falling to roughly $0.30 per thousand on the largest bundles.
Worth knowing. Two details change the effective rate. Credits expire six months after purchase, and requesting more than ten results per query consumes two credits rather than one, which doubles the cost for deep result sets.

Use these when you are grounding an LLM or agent, need speed, and ten results per query is genuinely enough.

6. Mid-tier scrapers with a search endpoint

Some general-purpose scraping services bolt a Google Search endpoint onto an existing platform, and the better ones are unusual for how much detail they return inside each organic result rather than across SERP feature types. Sitelinks and publication dates come parsed per result, which several providers at this price point skip.

Pricing. Plans typically start around $49/month. The search endpoint is usually available at every tier but consumes more credits than a basic request, so the effective per-query cost sits above the headline credit rate. Expect two request modes, a default light request and a heavier one that returns more results.

Worth knowing. Credit multipliers escalate sharply on JavaScript-heavy targets, where premium proxies with rendering can cost many times a basic call. That is a general-scraping consideration rather than a SERP one, but it matters if you use the same account for both.

Use these when organic result metadata such as publication dates drives your analysis, for example freshness tracking or content decay work.

How to choose without regretting it in six months

Model your real annual cost, not the per-request rate. Take your expected monthly volume, apply any Google-specific credit multiplier, add the cost of result depth beyond ten, and account for whether unused allowance rolls over. The ranking of providers by sticker price and by annual cost is rarely the same ranking.

Decide on AI Overviews now. Retrofitting AI Overview capture means a parser change plus a history gap you cannot fill retroactively. If generative answers are relevant to what you are measuring, treat coverage as a hard requirement rather than a nice-to-have, and line it up with however you are already measuring content performance.

Test failure behaviour, not success behaviour. Every provider looks fine on twenty-five clean queries. Send them difficult ones: heavily localised searches, queries that trigger unusual SERP layouts, sustained bursts above your normal rate. What you want to know is what a failure looks like in the response body and whether retries are handled for you or billed to you.

Check whether you are buying one vendor or two. If your pipeline also pulls non-search pages, a platform that covers both keeps the operational surface smaller. If SERP is genuinely all you need, a dedicated provider will usually be cheaper per query.

Conclusion

The Custom Search JSON API shutdown in January 2027 turns this from a procurement exercise into a deadline. Teams still on it should be testing replacements now rather than in the fourth quarter.

For output depth, the full-parse specialists return the most parsed elements. For scheduled batch work, queue-priced providers are the cheapest route to full-depth results. For enterprise geo-coverage, the proxy-network incumbents are the established options.

For teams whose SERP requirement sits inside a broader extraction pipeline, consolidating on infrastructure that handles both search endpoints and arbitrary page fetches under one token removes a category of operational overhead that per-query pricing comparisons tend to ignore.

Whichever way you go, run a real pilot against your own query mix before you migrate. Benchmark tables, including this one, are a starting point rather than an answer.

FAQ

Is Google’s Custom Search JSON API really shutting down?

Yes. Google closed it to new customers in 2025 and announced in January 2026 that it will be discontinued on 1 January 2027. Existing integrations continue until that date.

Google’s guidance points to Vertex AI Search, or to a contact form for its own full web search solution if you need the open index.

Why do SERP API prices vary so much?

Three reasons. Parsing depth costs money, so providers returning more structured elements charge more. Google-specific credit multipliers mean the effective rate can be several times the headline rate. And billing model differences, including expiring credits and non-rolling allowances, change annual cost independently of the per-request price.

Do I need AI Overview support?

If you are measuring visibility, yes. AI Overviews appear on a significant share of queries and change how organic results perform. If you only need organic positions and URLs for internal rank tracking, a cheaper organics-only provider may be sufficient.

Can I just build my own scraper?

Technically yes. The ongoing cost is CAPTCHA handling, proxy rotation, TLS fingerprinting and keeping parsers current as Google changes its layout. For most teams that maintenance load exceeds API pricing quickly, which is why the category exists.

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