ACTION_ID: website_traffic_using_semrush
NAME: Business Website Traffic
CATEGORY: scrape
CREDITS: 1

Pull a company's monthly website-traffic profile from Semrush
(via Floqer's Semrush connection). Returns top-level traffic
metrics — total visits, unique users, bounced visits, bounce
rate, pages per visit, time on site — plus the channel breakdown
(direct, search, organic search, referral, paid, display ads,
mail, social paid, unknown), the device split (desktop / mobile
share, mobile visits / users / hits / pages per visit / bounce
rate), and a global rank.

Useful for sizing accounts on traffic, qualifying e-commerce or
content businesses by channel mix, and personalising outreach
around traffic momentum (e.g. "noticed you've crossed N visits
from organic search this month").

INDEX:
  1. Inputs
  2. Outputs
  3. How to configure
  4. Key notes
  5. Where it fits in a workflow
  6. When to use
  7. When not to use

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1. INPUTS
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company_name (type: string, optional) — Company Name
  Name of the company to enrich.

company_domain (type: url, optional) — Company Domain
  Company domain or website (e.g. "acme.com").

company_linkedin_url (type: url, optional) — Company LinkedIn URL
  Company LinkedIn page URL (e.g.
  "https://www.linkedin.com/company/acme").

company_crunchbase_url (type: url, optional) — Company Crunchbase URL
  Crunchbase profile URL for the company.

country_code (type: string, optional) — Country Code
  Two-letter ISO country code (e.g. "US", "GB", "DE").

month_period (type: string, optional) — Month Period
  Month to pull traffic data for, in YYYY-MM format. Generally
  not required — leave it unset to get the most recent available
  month (defaults to month before last; see KEY NOTES on the
  trailing-data window). Only set this when you need a specific
  historical month, e.g. for backfill or for a year-over-year
  comparison.

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2. OUTPUTS
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domain (type: string) — Domain
  Resolved target domain the traffic numbers correspond to.

rank (type: number) — Rank
  Global Semrush rank for the domain.

month (type: string) — Month
  Month period the data covers, in YYYY-MM format.

accuracy (type: string) — Accuracy
  Semrush's accuracy / confidence label for the data.

total_visits (type: number) — Total Visits
  Total visits to the domain in the month.

total_unique_users (type: number) — Total unique users
  Total unique users in the month.

bounced_visits (type: number) — Bounced Visits
  Number of bounced visits.

bounce_rate (type: number) — Bounce Rate %
  Bounce-rate percentage.

pages_per_visit (type: number) — Pages Per Visit
  Average pages viewed per visit.

time_on_site (type: number) — Time On Site
  Average time on site, in seconds.

direct (type: number) — Direct
  Direct-traffic share / percentage.

search (type: number) — Search
  Total search-traffic share / percentage.

search_organic (type: number) — Search Organic
  Organic-search-traffic share / percentage.

referral (type: number) — Referral
  Referral-traffic share / percentage.

paid (type: number) — Paid
  Paid-search-traffic share / percentage.

display_ad (type: number) — Display Ad
  Display-ad-traffic share / percentage.

mail (type: number) — Mail
  Email-traffic share / percentage.

social_paid (type: number) — Social Paid
  Paid-social-traffic share / percentage.

unknown_channel (type: number) — Unknown Channel
  Share / percentage of traffic Semrush couldn't attribute.

desktop_share (type: number) — Desktop Share
  Desktop-traffic share.

mobile_share (type: number) — Mobile Share
  Mobile-traffic share.

mobile_visits (type: number) — Mobile Visits
  Total mobile visits.

mobile_users (type: number) — Mobile Users
  Total unique mobile users.

mobile_hits (type: number) — Mobile Hits
  Mobile page hits.

mobile_pages_per_visit (type: number) — Mobile Pages Per Visit
  Mobile pages-per-visit average.

mobile_bounce_rate (type: number) — Mobile Bounce Rate
  Mobile bounce rate.

device_type (type: string) — Device Type
  Device-type breakdown summary.

channel (type: string) — Channel
  Channel-breakdown summary.

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3. HOW TO CONFIGURE
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Configure Action body:

{
  "inputs": {
    "company_domain": "{{input.company_domain}}",
    "company_linkedin_url": "{{input.company_linkedin_url}}",
    "country_code": "US"
  }
}

Pass at least one company identifier (`company_domain`,
`company_linkedin_url`, `company_crunchbase_url`, or
`company_name`). All inputs are optional individually but the
action needs at least one to identify the company.

Identifier preference: prefer `company_domain` or
`company_linkedin_url` when available. `company_name` works but is
more likely to resolve to the wrong record for common / generic /
similarly-named companies.

Leave `month_period` unset for the most recent available month —
only set it when you need a specific historical month. See KEY
NOTES on the trailing-data window.

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4. KEY NOTES
================================================================================

- Trailing data — Semrush data lags by at least one month. You
  cannot get the current month's traffic numbers from this
  action. The default `month_period` is "month before last" (e.g.
  if it's currently April, the default returns February data;
  the most recent month available is typically March, but March
  may not be fully published yet). Set expectations accordingly:
  this is good for quarter-on-quarter or month-on-month
  comparisons, NOT for live / real-time traffic monitoring.

- `month_period` is optional and generally should be left unset.
  Only set it when you specifically need a historical month
  (e.g. backfill, year-over-year comparison). Format is YYYY-MM.

- Preferred identifier: pass `company_domain` when available —
  it's the most reliable match. `company_linkedin_url` and
  `company_crunchbase_url` are fine fallbacks. `company_name` works
  but is more likely to mis-resolve for common / generic names.

- Channel and device fields are percentages / shares (numbers)
  that should sum to roughly 100% across each grouping. Use
  format_data_using_js_expression to compute composite scores
  (e.g. "organic-share-of-paid-traffic", "mobile-engagement
  index") if you want a single ranking signal per row.

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5. WHERE IT FITS IN A WORKFLOW
================================================================================

Pattern (size / qualify by traffic): score or filter accounts on
total visits before spending downstream enrichment / outreach
credits — useful when traffic scale is part of your ICP.

  input (company domain or LinkedIn URL)
    -> website_traffic_using_semrush (returns visits, users,
       channel breakdown, etc.)
    -> filter or rank rows on visits / users / rank
    -> contact discovery + outreach on the qualified subset.

Pattern (channel-mix ICP filter): use the channel breakdown to
target accounts with the right traffic shape — e.g.
"organic-search-heavy" prospects for an SEO product, or
"paid-search-heavy" prospects for a paid-media tool.

  input (company domain)
    -> website_traffic_using_semrush
    -> filter / score on search_organic, paid, social_paid,
       referral, etc.
    -> outreach.

Pattern (per-prospect insight via LLM): feed the traffic profile
into a downstream LLM step to write per-account talking points
(e.g. "your organic share has grown X% in [month]" — keeping in
mind the trailing-month caveat).

  input (company domain)
    -> website_traffic_using_semrush
    -> llm_models (prompt: extract per-account traffic-trend
       talking points)
    -> outreach.

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6. WHEN TO USE
================================================================================

Use website_traffic_using_semrush when:

  - You want to size or qualify accounts on total visits / unique
    users — e.g. "only target sites with > 100k monthly visits".
  - You want to filter on channel mix — e.g. organic-search-heavy
    accounts for an SEO product, paid-search-heavy accounts for
    a paid-media tool, mobile-heavy accounts for a mobile-app
    product.
  - You want device-mix signals (desktop vs mobile share, mobile
    bounce rate) for accounts whose UX matters for your pitch.
  - You want a global rank for prioritisation across a long
    target list.

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7. WHEN NOT TO USE
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Need general firmographics (industry, headcount, HQ, description,
funding, etc.) — not just web traffic
  -> company_enrich_using_people_data_labs
     (https://floqer.com/docs/action-detail/company_enrich_using_people_data_labs.txt)
  -> enrich_company_linkedin_profile
     (https://floqer.com/docs/action-detail/enrich_company_linkedin_profile.txt)

Need workforce trends (growth / churn / tenure / headcount over
time / monthly hires and departures)
  -> company_enrich_using_people_data_labs
     (https://floqer.com/docs/action-detail/company_enrich_using_people_data_labs.txt)
  PDL is the broader provider for workforce-trend signals.

Need real-time / current-month traffic data
  -> not available via this action — Semrush data lags by at
     least one month (see KEY NOTES). For live signals, use a
     web agent against a real-time analytics source, or skip
     traffic enrichment entirely.

Need an e-commerce-specific traffic / sales estimate
  -> store_leads_enrich_company
     (https://floqer.com/docs/action-detail/store_leads_enrich_company.txt)
  StoreLeads returns estimated_visits and estimated_sales tuned
  for e-commerce stores.

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This file is maintained manually. Last updated: 2026-04-30.
Full interactive reference: https://floqer.com/docs/reference
Action catalog: https://floqer.com/docs/action-catalog.txt