ScraperAPI vs AnswerLine

Coverage

ScraperAPI's plans

As published on scraperapi.com/pricing (monthly billing), checked 2026-09-17. Enterprise is custom.

Price per request

ScraperAPI figures are its credits per request, in dollars on the Hobby plan and, in brackets, the Business plan. This API's dollar figure is its credits per request at the credit price of the lowest paid plan. Reference plan: Starter.

How requests, geo, billing and delivery work

Where ScraperAPI fits

• One plan covers any URL plus structured endpoints for Amazon, eBay, Walmart, Redfin and Google Jobs, Shopping and Maps.
• DataPipeline runs recurring jobs of up to 100,000 inputs without code and delivers to a webhook.
• Self-serve plans go up to 500 concurrent threads.

This API fits when you want engine-specific fields, async tasks, and signed webhooks with idempotency keys. The guide below compares the two requests.

Which fits your data

ScraperAPI is the right call if you already use it to scrape e-commerce, real estate or arbitrary pages and its four AI endpoints return the fields you store: an answer as markdown and a source list. Its DataPipeline also schedules recurring jobs without code.

This API is the right call if you need citations and inline citation pills as fields, ChatGPT’s shopping cards, the Google AI Overview, Copilot answers, and signed webhooks with idempotency keys. Its Perplexity and Grok endpoints are paused for now and coming back soon.

Normalized vs engine-specific schemas

ScraperAPI’s AI Results endpoints return one normalized shape for every engine: query, url, model, answer (markdown), sources[] with title, URL, domain and snippet, and related_queries[] (checked 2026-09-17, docs.scraperapi.com). The same docs offer raw HTML with include_html for anything outside those fields.

This API returns one schema per engine. The shared core (text, markdown, sources) has the same names, and each engine’s schema adds its own fields, such as shoppingCards on ChatGPT.

Migration: a ChatGPT answer with sources

On ScraperAPI

curl "https://api.scraperapi.com/structured/chatgpt/search/v1?api_key=$SCRAPERAPI_KEY&query=best+CRM+for+real+estate+agents&sources=true"

Per its docs, sources=true makes citations a condition of a successful response and raises the cost from 25 to 75 credits; without it, sources are often empty for ChatGPT.

On this API

curl -X POST https://api.answerline.dev/v1/monitor/chatgpt \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "best CRM for real estate agents",
    "country": "US",
    "include": { "markdown": true }
  }'

Web search is forced by default on this API’s ChatGPT requests, and there is no separate flag or price for asking for sources. Set disableWebSearch: true only when you want to measure what ChatGPT answers without being pushed to search.

Where each field goes

Google Search: adding the AI Overview

On ScraperAPI

curl "https://api.scraperapi.com/structured/google/search?api_key=$SCRAPERAPI_KEY&query=crm+for+realtors&country_code=us&tld=com"

The documented keys are search_information, shopping_items, organic_results, related_questions, related_searches and pagination.

On this API

import os, requests

r = requests.post(
    "https://api.answerline.dev/v1/monitor/google",
    headers={"Authorization": f"Bearer {os.environ['API_KEY']}"},
    json={
        "query": "crm for realtors",
        "country": "US",
        "include": {"aioverview": {"markdown": True}},
    },
    timeout=330,
)
result = r.json()["result"]
for s in (result.get("aioverview") or {}).get("sources", []):
    print(s["position"], s["url"])

Beyond the AI Overview, the response adds ads, localResults, knowledgeGraph, peopleAreSaying and shoppingCards next to organicResults, peopleAlsoAsk and relatedSearches.

Async jobs and callbacks

ScraperAPI’s async structured endpoints take a JSON body with apiKey, the query and a callback of type webhook; the reply includes a statusUrl, and its docs say a webhook is tried three times before the job is canceled.

This API’s equivalent:

import { Client } from "@answerline/sdk";

const client = new Client({ apiKey: process.env.API_KEY!, baseUrl: "https://api.answerline.dev" });

const prompts = ["best CRM for real estate agents", "Follow Up Boss vs kvCORE"];
const batch = await client.createBatch(
  prompts.flatMap((prompt, i) =>
    (["CHATGPT", "GEMINI"] as const).map((taskType) => ({
      taskType,
      payload: { prompt, country: "US" },
      idempotencyKey: `crm-${i}-${taskType}-US-2026-09-17`,
      webhook: { url: "https://your-app.com/hooks/answers" },
    })),
  ),
);
console.log(batch.summary);

Differences to plan for:

• Delivery retries. Here a delivery is retried up to 10 attempts with exponential backoff, and owners can redeliver a dead delivery from the dashboard after fixing an endpoint.
• Signatures. Every delivery is signed with your account’s secret. Reject unsigned or stale deliveries.
• Keys. The idempotency key makes resubmission safe; ScraperAPI’s async docs list no equivalent (checked 2026-09-17).
• Queue visibility. GET /v1/async/status shows queued and running counts; DELETE /v1/async/queue clears tasks that haven’t started, and those are not charged.

What each side costs

ScraperAPI’s credit value depends on the plan: the same 25-credit request costs roughly five times more per request on Hobby than on Business, as the table above shows. Its sources=true flag triples the ChatGPT cost. This API’s credits per request are 7 for a ChatGPT and 90 for a Copilot task, 5.6 for Gemini, 70 for Google AI Mode, 35 for a one-page Google Search request (plus 35 for the AI Overview) and 35 for a one-page Google News request; synchronous calls add 6.7, and 35 more per results page on Google Search and Google News. Credits per request are the same on every plan; the dollar value of a credit depends on the plan, as listed on pricing.

1. Decide whether you need citations on every ChatGPT answer. If yes, price ScraperAPI at 75 credits.
2. Check the geotargeting limit on the ScraperAPI plan you’d buy: Hobby and Startup are US and EU only.
3. Convert both to dollars per answer per engine, at the plan your total volume needs.
4. Price engines one side lacks separately instead of dropping them.

Testing both before you move the schedule

Collect from both for a week or two, into one table with a provider column.

1. Choose prompts for engines both sides cover.
2. Decide once whether your ScraperAPI ChatGPT baseline uses sources=true; the answer changes both cost and what counts as success.
3. Submit the same prompts here as tasks with webhooks, in the markets your ScraperAPI plan allows, deriving each key from prompt, engine, market and date.
4. Store both in one table with provider, engine, market, answer text, cited domains and status.

Three comparisons come out of that table:

• Answers with sources: the share of answers with at least one source on each side, with the sources setting noted.
• Cited domains overlap per prompt, next to the same prompt’s overlap between two days on one side.
• Cost per usable answer on the plan each side needs for your volume and markets.

Move the engines whose fields you already store, and leave Google on ScraperAPI until you have decided what an aioverview column does to your reports. ScraperAPI’s SERP docs list no counterpart, so it is a new metric to define rather than a migrated one, and mixing those two changes in the same week makes both hard to read.

Where retries live now

ScraperAPI charges for 200 and 404 responses, retries internally for up to 70 seconds, and does not charge a request that still fails after that. The retrying is invisible to your client, which sees one slow call. Here it happens inside a task: you get a task id immediately, transient failures are retried within the task’s own window, and only a COMPLETED task is charged (async tasks).

The timeout you tune therefore moves from the HTTP client to the schedule. Synchronous calls still fail fast with a code you can branch on; the codes are on authentication and errors, and rate limits covers the concurrency limit a synchronous call runs into first.

Deciding factors

1. Citations and pills as fields? This API.
2. AI Overview from Google? Not in ScraperAPI’s SERP endpoint docs (checked 2026-09-17); returned by our Google Search endpoint.
3. Markets beyond US and EU on an entry plan? This API offers the same markets on every plan: 213 countries on ChatGPT, Gemini, Google Search and Google AI Mode, any country on Copilot, and the 71 countries with a Google News edition on Google News.
4. Other scraping needs? Keep ScraperAPI for them.

What to watch for

• Treating an empty sources as zero visibility. ScraperAPI’s own docs say sources are often empty without sources=true. Whichever API you use, store empty source lists together with the request settings, such as whether web search was disabled, so a zero can be interpreted later.
• Mixing related queries and search queries. ScraperAPI’s related_queries are follow-up suggestions; searchQueries here is the field for searches the engine ran, and it comes back empty on the ChatGPT answers served today. They measure different things.
• Carrying API keys in URLs. Header auth here; rotate keys that were logged in query strings.
• Unbounded retries. Retry a synchronous call only when it never reached the server; a 500 or 502 from it is final. See authentication and errors.

The ChatGPT engine page documents the answer and citation fields; the quickstart gets a key working.

ScraperAPI is a trademark of its owner. AnswerLine is not affiliated with or endorsed by ScraperAPI.

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