Similarweb Pro Scraper

Export Similarweb website traffic, SEO, audience, advertising and backlink data for competitor research and agency reporting. Choose from 27 report pages and get one website result with period-labelled records, item counts and JSON files for large reports.

Open input | Pricing

Why Choose Similarweb Pro Scraper

• Research a domain in one place. Combine selected traffic, SEO, audience and advertising reports under one website identity.
• Choose the reports for your job. Start with traffic engagement and social sources, then add keywords, landing pages or backlinks for deeper research.
• Keep reporting periods attached. Section records carry period_start and period_end for comparable reporting.
• Use the data in your workflow. Export nested JSON and retrieve large-report files through report_context[report_key].file_url.

Quick Start Guide

Use the prefilled website and report selection for a first run.

1. Configure

Enter apify.com in Website and select traffic_engagement, social, and display_campaigns in Reports. A website URL is normalized to its domain with a leading www. removed, so https://www.apify.com/store requests apify.com. The result's website field uses that normalized domain.

Use these two inputs for your first run:

{"website":"apify.com","reports":["traffic_engagement","social","display_campaigns"]}

2. Run

Start the Actor and wait for the run to finish. Collection time depends on the selected reports, available history and volume of source data. For a broader analysis, add further report pages in a subsequent run after reviewing the first result.

3. Collect

Open the Dataset and export the website result as JSON. Inspect the selected top-level report fields and their entries in report_context. Retrieve each non-null report_context[report_key].file_url and save it with the Dataset export.

Input Configuration

The input parameters are website and reports, both required and shown in that order. The form prefills the example below; supply both values in automated runs.

Parameter	Type	Required	Description	Example
website	string	Yes	One public domain or website URL; a leading www. is removed from the normalized domain.	apify.com
reports	array of strings	Yes	One or more of the 27 report-page selections. Duplicate selections are combined.	["traffic_engagement", "social", "display_campaigns"]

{
  "website": "apify.com",
  "reports": ["traffic_engagement", "social", "display_campaigns"]
}

Report pages

The report keys match the Reports selector exactly. Available items vary by website, source coverage and reporting period.

Report key	Content
website_performance	Profile, engagement, devices, rankings, traffic trend, visits, geography and channels.
similar_sites	Similar-site candidates.
traffic_engagement	Engagement, device metrics, rankings, traffic trends, new and returning users, and visit totals.
marketing_channels	Marketing sources, channel shares, trends and changes.
audience	Geography, demographics, interests and age/gender audience sections.
search_overview	Search traffic, volume, brand split and keyword distribution.
referral	Referring and outgoing websites, plus referral trends.
advertiser_overview	Advertising metrics, counts and graph observations.
publisher_overview	Publisher metrics, advertisers and totals.
social	Social sources and trends.
seo_overview	Search summaries, trends, SERP features and ranking trends.
keywords	Organic keywords and keyword summary selections.
keyword_clusters	Keyword topic clusters.
landing_pages	Organic landing-page snapshots by available month.
search_competitors	Search competitors and overlap measures.
ranking_distribution	Ranking trends and US keyword/position tables.
ai_traffic	AI assistant contributions and AI landing pages.
paid_keywords	Paid keywords and paid-search summary selections.
paid_landing_pages	Paid landing-page snapshots and summary measures.
search_ads	Text search ads and search campaigns.
display_campaigns	Display campaign records.
display_ads	Display creative records.
display_publishers	Display publishers and reach.
advertiser_activity	Advertising channels, trends and geography.
backlinks_overview	Backlink summary, trend and changes.
referring_domains	Referring-domain records.
backlinks	Individual backlink records.

Reporting periods and coverage

Reporting windows are selected from the source's available history. Similar-site and search-competitor sections use up to the latest three available months. Organic and paid landing pages, US ranking keywords and position tables are collected as individual available monthly snapshots. Backlink trends use their own source reporting window.

Available history can move between runs. Compare the saved period labels as well as item counts when reviewing a website over time.

Marketing comparison sections use the complete month before the available reporting window's end month. A comparison outside that calendar is reported unavailable.

Each paginated list returns at most the first 1,000 distinct source entries per section and reporting period, in source order. This applies to keywords, landing pages, referring domains, backlinks, paid lists, marketing sources and the other paginated sections. The limit applies to each underlying section, so a report with several sections or monthly snapshots can contain more than 1,000 items in total. Reaching this limit completes the selected list scope; billing follows the items actually delivered.

General traffic analysis uses worldwide coverage; the US keyword and position sections use US data. Read each section and period in its own context when comparing measures. An undated section carries null period boundaries.

Output Data Schema

One Dataset row represents one website and its selected report pages. Selected report keys appear directly on the row; unselected report fields are omitted.

Root field	Type	Description
website	string	Website identified by the source, or the requested domain for a definitive not_found result.
Selected report keys, such as traffic_engagement, social and display_campaigns	object	Each inline object maps section names to record arrays. A null report may be file-backed or unavailable; inspect its context.
report_context	object	Per-report storage, file link, item count, and section statuses, counts and periods.
item_count	integer	Distinct delivered source-section items, counted once when reports overlap; used for report-item billing. It can differ from the number of displayed records.
status	string, when present	not_found identifies definitive source absence; this row has no Website Result or Report Items charge.
processor	string	Apify actor URL that processed this record.
processed_at	string	UTC timestamp when this record was processed.

An identified website whose selected reports are conclusively empty also returns one free not_found row, with no report data. If the requested website data cannot be obtained, no answer row is returned. File-backed profile records retain the same title, description, category, employees, founding year and tags as inline records.

An empty response alone does not confirm absence. When the source's empty or zero-data answer cannot be confirmed, no answer row is saved.

Each inline report section is a record array, with period_start and period_end on each record. An empty array means no mapped records for that section; a null section means its data is unavailable. For a file-backed report, the top-level report value is null, report_context[report_key].storage is file, and file_url links to the report's full section object. A null report without a file link is unavailable.

report_context[report_key].sections lists each section's period, item count and collection status: complete, empty, unavailable, not_started, or a partial outcome such as source_window, rate_limited or partial. complete means collection finished for that section within its declared selection limit; empty means no items were returned for that section, although source summary metrics can remain. Partial outcomes retain the records read before collection stopped. These statuses do not establish exhaustive source coverage. Context counts describe displayed records; the root item_count counts distinct source items and can differ. Check the saved data and run status message together, including when the platform run succeeds.

Unfinished sections retain partial status and the records collected. Check the saved website row and report_context before using a report in downstream analysis. An unidentified website with only zero, missing or provider-placeholder data has no paid row or report-item charge.

Business fields

Report records contain the business fields relevant to their section: keywords include search measures; campaign records include advertising measures; numeric observations use metric, dimensions and value or series_values. Missing fields may be absent or null; genuine zero and false values remain intact.

Example item field	Description
monthly_visits	Source estimated monthly website visits; profile and engagement may use different source models.
visit_duration	Average visit duration in seconds.
visit_pages	Average pages per visit.
spend	Source estimated advertising spend; interpret the source unit without assuming a currency.
cpc	Source estimated cost per click; interpret the source unit without assuming a currency.
parent_entity	Source parent domain or advertising entity of a group member.
site_metrics	Source per-website keyword clicks, shares, SERP features and top destinations.

The Dataset schema declares 33 top-level fields and 28 views; individual report objects have section-specific business fields. Shares retain their source scale. Evaluate a measure together with its section, dimensions and period; group aggregates and group members describe different levels of the same population.

Complete record field reference

Fields apply to the sections that supply them; a report does not populate every field. Missing facts remain null or absent. Counts and measures are source estimates where applicable. Shares and changes retain the source scale: their names alone do not establish a denominator or comparison period.

In a profile, country_id identifies the traffic-ranking scope, rather than the company's location. top_country is the source identifier of the highest-traffic country.

Record field	Type	Meaning
active_days	number	Active day count.
active_months	array	Active months.
ad_count	number	Advertisement count.
ad_id	number / string	Source record identifier.
ad_type	string	Advertisement type.
affinity	JSON value / number	Website affinity score.
anchor_text	string	Source backlink anchor text.
assistant_shares	array / boolean / number / object / string	Source traffic shares by AI assistant.
assistant_split	array / boolean / number / object / string	AI-assistant split in the source representation.
assistant_visits	object	Source visit counts by AI assistant.
average_volume	number	Average search volume.
backlink_count	number	Backlink count.
bounce_rate	number	Bounce rate.
campaign_id	number / string	Source record identifier.
category	JSON value / string	Category.
category_rank	integer / number / string	Category rank.
change	JSON value / number	Monthly click change; traffic change; visit change. Retains the source scale and period.
change_state	string	Source click-change label, such as New, Lost, Positive, Negative, NoChange or NoData.
channel	JSON value	Marketing channel.
clicks	number	Click count.
clicks_change	number	Click change. Retains the source scale and period.
clicks_trend	array / boolean / number / object / string	Source click observations indexed by date or source label.
competition	number	Keyword competition.
country_id	number / string	Source country identifier; not necessarily an ISO code.
country_rank	integer / number / string	Country rank.
cpc	number	Estimated cost per click; currency is not inferred.
cpc_high	number	High-bid cost-per-click estimate; currency is not inferred.
cpc_low	number	Low-bid cost-per-click estimate; currency is not inferred.
creative_count	number	Creative count.
creative_id	number / string	Source record identifier.
creative_type	string	Creative type.
date	string	Source observation date or date label; no timezone is inferred.
dedup_users	number	Average monthly deduplicated user count.
description	JSON value / string	Description.
desktop_clicks	number	Desktop click count.
destination_url	string	Source advertisement destination.
difficulty	number	Keyword difficulty.
domain	JSON value / string	Source domain.
domain_authority	number	Domain authority score.
domain_score	number	Domain score.
employees	JSON value	Source employee-count range as text.
engagement_score	number	Engagement score.
filtered_share	number	Filtered traffic share. Retains the source scale and period.
first_seen	string	Source first-seen date or date/time label; no timezone is inferred.
follow_pages	number	Follow referring page count.
founded	string	Source founding year, represented as text.
global_rank	JSON value / integer / number / string	Global rank.
has_adsense	JSON value / boolean	Has ad sense.
image_size	string	Source creative image dimensions as text.
image_url	string	Source image link; no separate image download is promised.
impressions	number	Impression count.
impressions_change	number	Impression change. Retains the source scale and period.
impressions_new	boolean	Has new impressions.
impressions_share	number	Impression share. Retains the source scale and period.
industry	JSON value	Source industry taxonomy, with identifiers and category paths.
is_broken	boolean	Is broken.
is_image	boolean	Is image.
is_lost	boolean	Is lost.
is_new	JSON value / boolean	Is new.
is_subdomain	boolean	Is subdomain.
keyword	string	Keyword.
keyword_count	number	Keyword count.
keyword_overlap	array / boolean / number / object / string	Keyword overlap.
large_image_url	string	Larger source image link, when supplied.
last_seen	string	Source last-seen date or date/time label; no timezone is inferred.
lost_backlinks	number	Lost backlink count.
lost_domains	number	Lost referring domain count.
monthly_visits	number	Estimated monthly visits. Profile snapshots and engagement averages use separate source models.
name	JSON value / string	Title.
network	string	Social network.
new_backlinks	number	New backlink count.
new_domains	number	New referring domain count.
nofollow_pages	number	No follow referring page count.
organic_clicks	number	Organic click count.
organic_share	number	Organic click share. Retains the source scale and period.
overlap	JSON value	Same day cross visitation rate.
overlap_change	JSON value	Cross visitation change. Retains the source scale and period.
page_score	number	Page score.
page_url	string	Source landing-page URL.
page_views	number	Average monthly page view count.
parent_domain	string	Parent domain.
position	number	Search position.
previous_clicks	number	Previous click count.
previous_position	number	Previous search position.
previous_share	number	Previous click share. Retains the source scale and period.
primary_intent	string	Primary search intent.
publisher_count	number	Publisher count.
rank	number	Backlink rank.
referring_domains	number	Referring domain count.
referring_pages	number	Referring page count.
referring_url	string	Source page containing the backlink.
related_apps	JSON value / object	Applications grouped by store; groups contain app records or source store values.
relevancy_rank	JSON value	Audience relevance rank.
relevancy_score	JSON value	Audience relevance score.
search_volume	number	Search volume.
secondary_intent	string	Secondary search intent.
serp_date	string	Source search-results observation date or label.
serp_features	array	Search features.
serp_type	string	Search feature.
share_split	array / boolean / number / object / string	Share split in the source representation.
share_trend	array / boolean / number / object / string	Source share observations indexed by date or source label.
site_metrics	array / object	Per-website keyword observations, including clicks, shares, search features and destination pages.
site_shares	JSON value / array / boolean / number / object / string	Source per-website shares, keyed by website.
spend	number	Estimated advertising spend; currency is not inferred.
spend_change	number	Advertising spend change. Retains the source scale and period.
spend_new	boolean	Has new spend.
spend_share	number	Advertising spend share. Retains the source scale and period.
tags	JSON value	Tags.
title	JSON value / string	Title.
top_country	JSON value / number / string	Source identifier of the highest-traffic country.
top_keyword	string	Top keyword.
top_url	string	Top page URL.
topic_id	number / string	Source record identifier.
total_share	JSON value / number	Total traffic share. Retains the source scale and period.
total_traffic	array / boolean / number / object / string	Total traffic.
traffic	array / boolean / number / object / string	Traffic.
traffic_share	JSON value / number	Advertising visit share; click share; traffic share; traffic source visit share; visit share. Retains the source scale and period.
unique_users	number	Average monthly unique user count.
url_count	number	Url count.
users_share	number	User share. Retains the source scale and period.
video_url	string	Source video link, when supplied; no video download is promised.
visit_duration	number	Average visit duration, in seconds.
visit_frequency	number	Visits per user.
visit_pages	number	Average pages per visit.
visits	JSON value / number / string	Visit count.
visits_change	number	Advertising visit change. Retains the source scale and period.
visits_new	boolean	Has new visits.
visits_trend	array / boolean / number / object / string	Source visit observations indexed by date or source label.
volume_state	string	Source search-volume change label.
zero_share	number	Zero click rate. Retains the source scale and period.
metric	string	Source numeric-measure name; interpret with its section and dimensions.
dimensions	array	Labels aligned to the numeric observation or series.
value	number	Source numeric observation; the unit follows its metric.
series_values	array / object	Source numeric series; preserve its labels and scale.
total_count	number	Source aggregate count for this section, separate from delivered website rows.
source_facets	object / array	Source facet labels, identifiers and counts.
top_source_facets	object / array	Source leading facet labels, identifiers and counts.
source_segments	object / array	Source segment definitions or counts.
categories	array	Category counts; nested entries may contain category, count, id and categories.
entity_scope	string	Whether the record is a source group or a member.
parent_entity	string	Parent website or advertising entity for a member record.
page_group	JSON value	Source AI landing-page group.
landing_id	string / number	Source landing-page identifier.
display_path	string	Source ad display path when no destination URL is available.
period_start	string	Start of this record's source reporting period.
period_end	string	End of this record's source reporting period.

Nested site_metrics records use site (website), value (click count), share, previous_share, serp_features and top_url. A website or date can also be an object key. industry records use id and path. Application records in related_apps use store, id, title, author, icon, category, price, rating and ratecount; prices remain source text and store-specific values can vary. Additional source business fields can appear under normalized field names, retaining their value types. Do not infer a new meaning or unit for such a field.

Each report context has storage (inline, file or unavailable), file_url (string or null), item_count (integer displayed-record count) and sections (object keyed by section). With unavailable storage, the report and file_url are null. Section period records contain status (complete, empty, partial, not_started or a specific unavailable/error state such as schema_changed or rate_limited), item_count (integer), period_start and period_end (string or null). A section can retain valid records while its status reports incomplete collection. A report file contains the same section arrays as inline delivery.

Nested record field	Type	Meaning
site_metrics.*.site	string	Website associated with a keyword observation.
site_metrics.*.value	number	Source click count for that website.
site_metrics.*.share, previous_share	number	Current and comparison traffic shares at the source scale.
site_metrics.*.serp_features	array	Source search-result feature labels.
site_metrics.*.top_url	string	Source leading destination page.
industry.id	string, number	Source taxonomy identifier.
industry.path	array	Source category hierarchy.
related_apps.<store>.*.store	string or number	Source application-store identifier.
related_apps.<store>.*.id	string or number	Source application identifier.
related_apps.<store>.*.title, author	string	Application title and source publisher name.
related_apps.<store>.*.icon	string	Source application image link.
related_apps.<store>.*.category	string	Source application category.
related_apps.<store>.*.price	string, number	Source price text or value; currency is not inferred.
related_apps.<store>.*.rating, ratecount	number	Source rating and review count.
categories.*.category	string	Source category label.
categories.*.count	number	Source count for that category.
categories.*.id	string, number	Source category identifier.
categories.*.categories	array	Child categories with the same structure.

Store-specific native application values and additional source business fields can have other JSON types. They remain source-defined rather than being converted into a fixed business fact.

Illustrative, abbreviated output for the apify.com input with all three prefilled reports. Example values and counts demonstrate the shape; actual periods and values vary by run. Additional sections and fields are omitted.

{
  "website": "apify.com",
  "traffic_engagement": {
    "engagement": [
      {
        "monthly_visits": 100000,
        "visit_duration": 120,
        "visit_pages": 3,
        "period_start": "2026-03-01",
        "period_end": "2026-08-31"
      }
    ]
  },
  "social": {
    "social": [
      {
        "network": "Youtube",
        "traffic_share": 0.5,
        "period_start": "2026-03-01",
        "period_end": "2026-08-31"
      }
    ]
  },
  "display_campaigns": {
    "campaigns": [
      {
        "campaign_id": "apify.com",
        "creative_count": 2,
        "period_start": "2026-03-01",
        "period_end": "2026-08-31"
      }
    ]
  },
  "report_context": {
    "traffic_engagement": {
      "item_count": 1,
      "storage": "inline",
      "file_url": null,
      "sections": {
        "engagement": [
          {
            "status": "complete",
            "item_count": 1,
            "period_start": "2026-03-01",
            "period_end": "2026-08-31"
          }
        ]
      }
    },
    "social": {
      "item_count": 1,
      "storage": "inline",
      "file_url": null,
      "sections": {
        "social": [
          {
            "status": "complete",
            "item_count": 1,
            "period_start": "2026-03-01",
            "period_end": "2026-08-31"
          }
        ]
      }
    },
    "display_campaigns": {
      "item_count": 1,
      "storage": "inline",
      "file_url": null,
      "sections": {
        "campaigns": [
          {
            "status": "complete",
            "item_count": 1,
            "period_start": "2026-03-01",
            "period_end": "2026-08-31"
          }
        ]
      }
    }
  },
  "item_count": 3,
  "processor": "https://apify.com/agentx/similarweb-pro-scraper",
  "processed_at": "2026-11-04T12:00:00Z"
}

JSON preserves the report structure and is the recommended export for further processing. For CSV or spreadsheet analysis, flatten a selected report's section arrays and retain website, section and period columns. Shared sections can appear under multiple selected report pages, so deduplicate by analytical meaning before combining them.

Integration Examples

Run Actor ID E4aGcMycvf3cTbkgm (agentx/similarweb-pro-scraper) asynchronously, wait for completion, and retrieve its Dataset and referenced report files.

Actor ID

Use this Actor ID in API calls, SDKs, Make.com and n8n:

E4aGcMycvf3cTbkgm

In REST API paths, the name form agentx~similarweb-pro-scraper is an equivalent alternative to the Actor ID.

cURL

Requires Bash, cURL and jq. Keep the returned run ID: a client wait ending can leave the run active. Each new start creates another billed run. These examples use the Quick Start input and read every Dataset page, including any saved output from an unsuccessful run.

set -euo pipefail
export APIFY_TOKEN="YOUR_APIFY_TOKEN"
API="https://api.apify.com/v2"
RUN=$(curl --fail --silent --show-error -X POST \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  --data '{"website":"apify.com","reports":["traffic_engagement","social","display_campaigns"]}' \
  "$API/acts/E4aGcMycvf3cTbkgm/runs")
RUN_ID=$(printf '%s' "$RUN" | jq -er '.data.id')
DATASET_ID=$(printf '%s' "$RUN" | jq -er '.data.defaultDatasetId')
printf 'Run ID: %s\n' "$RUN_ID" >&2
while true; do
  STATE=$(curl --fail --silent --show-error \
    -H "Authorization: Bearer $APIFY_TOKEN" "$API/actor-runs/$RUN_ID")
  STATUS=$(printf '%s' "$STATE" | jq -er '.data.status')
  case "$STATUS" in
    SUCCEEDED|FAILED|TIMED-OUT|ABORTED) break ;;
  esac
  sleep 2
done
printf 'Run status: %s\n' "$STATUS" >&2
OFFSET=0
while true; do
  PAGE=$(curl --fail --silent --show-error \
    -H "Authorization: Bearer $APIFY_TOKEN" \
    "$API/datasets/$DATASET_ID/items?format=json&clean=true&offset=$OFFSET&limit=1000")
  printf '%s' "$PAGE" | jq -c '.[]'
  COUNT=$(printf '%s' "$PAGE" | jq 'length')
  [ "$COUNT" -lt 1000 ] && break
  OFFSET=$((OFFSET + COUNT))
done

Python

Uses Python's standard library. Save the run ID if the client stops waiting, then resume polling that run.

import json
import os
import time
from urllib.request import Request, urlopen

API = "https://api.apify.com/v2"
HEADERS = {"Authorization": "Bearer " + os.environ["APIFY_TOKEN"],
           "Content-Type": "application/json"}

def request(path, payload=None):
    body = None if payload is None else json.dumps(payload).encode()
    with urlopen(Request(API + path, data=body, headers=HEADERS), timeout=60) as response:
        return json.load(response)

run = request("/acts/E4aGcMycvf3cTbkgm/runs", {
    "website": "apify.com",
    "reports": ["traffic_engagement", "social", "display_campaigns"],
})["data"]
print("Run ID:", run["id"])
while run["status"] not in {"SUCCEEDED", "FAILED", "TIMED-OUT", "ABORTED"}:
    time.sleep(2)
    run = request("/actor-runs/" + run["id"])["data"]
print("Run status:", run["status"])
offset = 0
while True:
    page = request(f'/datasets/{run["defaultDatasetId"]}/items'
                   f'?format=json&clean=true&offset={offset}&limit=1000')
    for website in page:
        print(json.dumps(website))
    if len(page) < 1000:
        break
    offset += len(page)

JavaScript

Uses Node.js 18 or later with built-in fetch. Save the run ID if the client stops waiting.

const API = "https://api.apify.com/v2";
const headers = {
  Authorization: `Bearer ${process.env.APIFY_TOKEN}`,
  "Content-Type": "application/json",
};
async function request(path, payload) {
  const response = await fetch(API + path, {
    method: payload === undefined ? "GET" : "POST",
    headers,
    body: payload === undefined ? undefined : JSON.stringify(payload),
  });
  if (!response.ok) throw new Error(`Apify returned ${response.status}`);
  return response.json();
}
let { data: run } = await request("/acts/E4aGcMycvf3cTbkgm/runs", {
  website: "apify.com",
  reports: ["traffic_engagement", "social", "display_campaigns"],
});
console.log("Run ID:", run.id);
while (!["SUCCEEDED", "FAILED", "TIMED-OUT", "ABORTED"].includes(run.status)) {
  await new Promise(resolve => setTimeout(resolve, 2000));
  ({ data: run } = await request(`/actor-runs/${run.id}`));
}
console.log("Run status:", run.status);
for (let offset = 0; ; ) {
  const page = await request(`/datasets/${run.defaultDatasetId}/items`
    + `?format=json&clean=true&offset=${offset}&limit=1000`);
  for (const website of page) console.log(website);
  if (page.length < 1000) break;
  offset += page.length;
}

Make.com

Use the Apify integration to start Actor ID E4aGcMycvf3cTbkgm with the apify.com example input. Save the run ID and Dataset ID, then use a run-completion notification or status polling before retrieving Dataset items. Read each selected top-level report or download its report_context[report_key].file_url when file-backed.

n8n

Start Actor ID E4aGcMycvf3cTbkgm with an HTTP Request node posting the apify.com JSON input to https://api.apify.com/v2/acts/E4aGcMycvf3cTbkgm/runs. Keep the returned run ID through a Wait/status-check loop. After completion, retrieve the Dataset, inspect report_context, and expand the selected section arrays into the rows your destination expects.

MCP

Use Apify's MCP integration to select agentx/similarweb-pro-scraper and submit the same website and reports values. Ask the client to wait for the run, inspect report_context and the saved data, and retrieve the website result and any referenced JSON files. See Apify integrations for connection options.

Pricing

A website result costs $0.02 on the FREE tier, report items cost $0.004 per started 1,000 delivered source items, and the Actor Start costs $0.01. One saved website result with 1–1,000 billable items therefore has a $0.034 event subtotal; the report selection alone does not guarantee that count. Each run has one $0.01 Actor Start charge.

Event	FREE	BRONZE	SILVER	GOLD / PLATINUM / DIAMOND
Website Result	$0.02000	$0.01800	$0.01600	$0.01500
Report Items (per started 1,000)	$0.00400	$0.00360	$0.00320	$0.00300
Actor Start	$0.01	$0.01	$0.01	$0.01

The bill follows the delivered source-item count, not the number of visible records after formatting. Items in shared sections are counted once, even when a section appears under two selected pages. Detailed keyword, landing-page and backlink reports can increase the count; for 1,001–2,000 billable items, the FREE-tier event subtotal is $0.038 ($0.01 + $0.02 + 2 × $0.004). These calculations cover the listed events; check Apify for any additional platform or storage charges applicable to your account.

Whole Actor bill examples on the FREE pricing tier, using all three registered events:

Delivered outcome	Actor Start	Website Result	Report Items units	Actor bill
Quick Start: 1 website, 217 source items	1	1	1	$0.034
1 website, 6,025 source items	1	1	7	$0.058
Partial website result, 500 source items retained	1	1	1	$0.034
1 confirmed not_found row	1	0	0	$0.01
0 saved rows	1	0	0	$0.01

The source counts illustrate the arithmetic and can vary on a new run. A partial result is billed only for its saved website result and delivered source items. These are this Actor's charges at the stated tier; separately selected Apify services are outside these examples.

If a spending limit interrupts delivery or billing, inspect the saved Dataset and charged units. Any confirmed Report Items charge remains on the bill for the saved data; inspect that run before retrying. A definitive not_found row has no Website Result or Report Items charge; the Actor Start still applies. Source-access errors or interrupted collection can leave no website result. The data comes from the selected Similarweb Pro report pages.

Prices can change — the current published figures are on the Actor's pricing tab, and Apify explains the pay-per-event model in its Store pricing documentation.

Use Cases

Agency reporting. Compare traffic engagement and social sources for a client website, carrying each section's reporting period into the presentation. Keep source-estimated visits distinct from the client's own analytics.

SEO opportunity research. Analyze keywords, keyword_clusters and landing_pages together. Retain each keyword's source measures and each landing-page snapshot's month when prioritizing content work.

Advertising research. Combine paid_keywords, search_ads, display_campaigns and display_ads to review the source's observed search and display activity for a domain.

Prospect qualification. Use traffic, audience and geographic data to prepare domain-level research before outreach. Read the relevant profile and reporting window so each observation has a clear basis.

Backlink review. Analyze referring domains and individual backlinks alongside the backlink overview. Separate aggregate counts from individual records when preparing summaries.

Alternatives

Choose the research workflow whose data, delivery and account controls fit your task.

Option	Useful fit
Similarweb website interface	Interactive exploration, chart review and source-provided analysis tools.
Similarweb's official API	Direct source integration with documented endpoint contracts and account credit controls.
SEO research suites	Combined research, project management and analyst workflows within one product.
Similarweb Pro Scraper	Selected report pages packaged into a nested website result for Apify workflows.

Similarweb's official API uses data credits, with consumption depending on the endpoint and requested data. Compare the required report coverage and complete task cost when choosing an integration.

Limits and Troubleshooting

Report availability depends on the website, source coverage and reporting window.

• An empty report: an empty section array has no mapped records for that website and period. Check its period and report_context; null or unavailable data is a different outcome.
• Partial collection: inspect the saved sections and final run status; retain delivered data separately from complete results.
• Different totals across sections: source models and aggregation levels can differ. Compare the same metric, section, geography and period.
• An AI landing-page source window: source coverage can limit the available landing pages. A nonempty section is not proof of exhaustive coverage.
• A large report uses a file: download report_context[report_key].file_url and process the same section arrays and record-level periods as inline data.
• A run ends before final delivery: inspect the Dataset and final run status; delivery is finalized as one website result after collection. Plan dependent workflows around the terminal run and its actual saved outputs.
• A row has status: "not_found": the source confirmed absence for that domain; the row is saved without Website Result or Report Items charges. Check the domain spelling. An unrecognized-site or access error is not confirmation of absence.
• Large report selections: group detailed pages by task, such as traffic or SEO, and review each saved website result before expanding the analysis.
• Unavailable sections: source access or report availability can prevent data retrieval. Inspect report_context and the run status message; use the sections actually saved without assuming every selected report completed.
• Reports could not be saved: the final status identifies a saving failure. Keep any confirmed results; the unsaved reports are unavailable in that run.
• A cost-limit message: inspect saved results and charges; if needed, select fewer reports for a later run. A new start has its own Actor Start charge.
• A temporary access message: send support the run ID and selected reports for help with the unavailable data.

For a reproducible problem, open an Issue with the run ID, exact input, affected report and expected output.

Trust and Reliability

The Dataset schema has 33 top-level fields and 28 views. Selected report objects contain section-specific records; report_context supplies storage, counts, statuses and periods. These fields help you interpret what was saved.

Similarweb metrics include modeled estimates. See Similarweb's data methodology for the source's explanation of its data inputs and modeling. Treat these metrics as source-estimated research data, and use first-party analytics for direct measurement of a website you operate.

Keep run status, report status and item counts together. A website row can contain complete, partial, empty or unavailable sections. Nonempty data and a successful platform run do not prove complete source coverage.

Legal and Compliance

Data scope. The Actor returns website-level research reports and the source-provided entities and measures within the selected pages.

Responsible use. Use the reports for purposes consistent with applicable obligations and the rights attached to the data. Apply suitable access controls when combining research data with your own customer records.

Platform terms. Review the terms governing your source-data use and Apify account before integrating exports into a downstream product or distributing them to others.

Frequently Asked Questions

How can I export Similarweb data as JSON?

Start the Actor with one website and your chosen reports, wait for completion, and export the Dataset as JSON. Download report files referenced by file_url to collect the full delivered output.

Which Similarweb traffic reports can I select?

Choose website_performance, traffic_engagement, marketing_channels, audience, referral or social according to your research question. Each page groups related sections in the website result.

What does one result contain?

One result contains website, the selected report keys, report_context, item_count, processor and processed_at. Inline reports contain section arrays; file-backed reports are linked in report_context. Definitive absence adds status: "not_found".

How are dates selected?

The Actor uses the reporting history available from the source. Competitor sections use up to three available months, while monthly landing-page and ranking tables retain separate monthly periods.

Can I schedule runs to monitor website traffic over time?

Use an Apify schedule with the same website and report selections, then save each completed output with processed_at. Compare like-for-like periods and metrics, since source estimates and available reporting history can change.

How much does a website report cost?

On the FREE tier, one website result with 1-1,000 delivered source items has a $0.034 event subtotal: $0.01 Actor Start + $0.02 Website Result + $0.004 Report Items. See Pricing for larger counts and paid-plan tiers.

Which inputs do I supply for access?

Supply website and reports. Service access is handled by the Actor; an access-related run message can be investigated through support using the run ID.

How should I interpret missing values and partial reports?

Preserve null and absent fields as missing data, preserve genuine zero values, and inspect report_context alongside the saved sections and run status message. complete indicates finished section collection, not exhaustive source coverage; keep observations with different periods and availability separate in analysis.

Why can a successful run save no website row?

Apify's SUCCEEDED state means execution finished. An unknown website, unavailable report or access failure can still leave the Dataset empty. Read the final status message and actual Dataset. A confirmed no-data answer instead saves a not_found row. Both zero-row and not_found runs retain the fixed $0.01 Actor Start charge; they have no Website Result or Report Items charge.

What should I do when billing confirmation is pending?

Keep the existing run ID and inspect its Dataset and charged events before starting another run. A website row may already be saved while billing confirmation is pending. Send the run ID to support; restarting can incur another Actor Start charge.

Related AgentX Actors

• Domain Intelligence Lookup — use the returned website for domain registration and infrastructure research.
• Google Keyword Trends — compare search-interest patterns for topics identified in website research.
• All Web Search Scraper — find public pages for deeper website and company research.
• LinkedIn Company Lookup — add a public company profile when you have its LinkedIn company URL.

Support and Community

Ask about website reports, reporting periods and JSON delivery in the AgentX community on Telegram; for a reproducible bug, open an Issue with the run ID and the exact input.

AgentX is an Arcyton brand — arcyton.com.

Last Updated: November 7, 2026