Semrush API Explained: Supercharge Your SEO Data Workflow

Last Updated: February 12, 2026

• Semrush API lets you pull keyword, backlink, traffic, and project data straight into your own tools, reports, and workflows without touching the Semrush interface.
• It is best for teams that repeat the same data pulls at scale and want automation, not one‑off manual exports.
• You pay with API units, so planning what you pull and how often matters if you want to avoid surprise costs.
• When you connect Semrush API with Sheets, BI tools, and AI workflows, you can turn raw SEO data into real decisions and, honestly, more revenue.

What the Semrush API Actually Does For You

The Semrush API gives you structured access to the same data you see in the interface, but in a way your scripts, dashboards, and apps can work with directly.

You send a request with some parameters, Semrush sends back rows of data, usually as CSV or JSON, and you can then shape that data any way you want.

If you are tired of clicking around, exporting CSVs, cleaning them, and copy pasting into decks, the API just removes that cycle.

It is not magic, but once you set things up, it feels very close.

When the API Makes Sense, And When It Does Not

If you run one site, check rankings once a week, and rarely touch competitor data, you probably do not need the API yet.

The minute you manage dozens of sites, hundreds or thousands of keywords, or you are reporting to lots of people, that changes fast.

Agencies, in‑house growth teams, and SaaS products that embed SEO metrics are the ones that get the most from Semrush API.

I have also seen solo consultants get value, but only when they commit to real automation, not just replacing one export with another.

Semrush API At A Glance

The details and names may shift over time, but these are the three pillars you will keep seeing: analytics data, project data, and traffic or market insight data.

Before you pay for anything, always double‑check Semrush’s current API docs and pricing pages, because they tweak limits and packaging more often than you would think.

Who Actually Benefits From Semrush API

Not every SEO or marketer needs an API, and I think a lot of people jump too early just because it sounds advanced.

The real question is whether your current workflow hits a wall with manual work, scale, or data access.

Good Fits For Semrush API

• Agencies with many clients: recurring monthly or weekly reports, dashboards, and audits.
• In‑house teams managing multiple brands, regions, or language versions and needing a single source of truth.
• SaaS products that show SEO metrics to users, like rank tracking inside a marketing tool.
• Market research and investment teams who compare many sites and markets on a schedule.
• Programmatic SEO builders that rely on keyword and traffic data at serious scale.

In all of those cases, doing everything by hand either breaks or forces you to hire people just to babysit reports, which does not make sense.

When You Can Skip The API For Now

• You only manage one small site.
• You do not report on fixed dates or heavy dashboards.
• Your team is allergic to code and also not open to no‑code automation tools.

You are better off squeezing more value out of the Semrush interface, GA4, and Search Console APIs for the time being.

I know API talk feels cool, but if you are not going to automate aggressively, the return is weak.

If you mostly enjoy hands‑on research, stay with the interface until copy‑pasting reports feels painful and repetitive, that is usually the real signal you are ready for an API setup.

What You Can Actually Do With Semrush API

The generic answer is: you can recreate almost any Semrush report in your own system.

The better answer is: you use that power to build repeatable, boring, money‑making workflows.

Classic, Still Useful Workflows

• Auto‑build competitor research packs for every new lead, with domain overview, top keywords, and traffic trends.
• Refresh rank tracking dashboards daily across many domains without touching Semrush manually.
• Pull Site Audit issues into your task system so dev teams see them directly, not in PDFs nobody opens.
• Get daily backlink data and flag new or lost referring domains in a central sheet or BI tool.

These are not very glamorous, but this is where the time savings stack up week after week.

Modern AI And LLM Use Cases

This is the big gap in many older guides, and where the API has become far more useful.

You can feed Semrush data into LLM workflows to move from just “data reporting” to actual “what do we do next” suggestions.

• Automated content briefs: pull top ranking pages, SERP features, related keywords, and questions, then send that pack to an LLM to produce a structured content brief.
• Topic and cluster discovery: fetch large keyword sets, then use AI to group them into clusters and prioritize them based on volume, difficulty, and business fit.
• Technical issue triage: combine Site Audit issues with traffic estimates and rankings; ask an LLM to rank issues by impact, not just count.
• Next‑step recommendations: feed in monthly rankings + traffic changes and ask the model to suggest the top 5 actions for the SEO team.

You still need human review here, but it makes your team faster and less stuck in spreadsheet hell.

The strongest AI setups I see do not ask the model to “do SEO,” they just use it to summarize, cluster, and prioritize Semrush data so humans can make better calls.

Programmatic SEO At Scale

Programmatic SEO needs consistent, structured inputs, and this is where APIs shine.

You can use Semrush to fill your database with keyword sets, search intent hints, and traffic potential before you generate pages.

• Pull long‑tail keywords across locations or product dimensions.
• Store search volume, difficulty, and SERP features in your content database.
• Feed that into your pSEO generator or CMS to decide which combinations get pages.
• Use Trends traffic numbers to decide which markets and categories actually deserve templates.

Will every programmatic experiment hit? No, many will be mediocre, but the ones that work build on good data, not guesses.

Revenue And Risk Focused Workflows

This is where many teams leave money on the table by staring only at rankings.

If you join Semrush data with GA4, Search Console, and your CRM, you can track real business impact, not vanity metrics.

• Score pages by revenue or leads, then pull Semrush rankings and traffic estimates to flag critical pages that slipped from top 3 to positions 5 to 10.
• Merge backlink growth with deal flow to see which links and pages correlate with pipeline jumps.
• Use Traffic Analytics data to spot markets or segments where a competitor is growing fast, then prioritize those in your content roadmap.

This is a bit more work to set up because you join multiple datasets, but this is where leadership starts to care.

Semrush API Packages And What They Actually Cover

The naming and packaging can change slightly over time, but in practice you will be dealing with three buckets: Analytics, Projects, and Trends / Traffic Analytics and Market Explorer.

Each one has its own endpoints, limits, and billing quirks, so treating them as “one big API” is where confusion usually starts.

Analytics API

This is the workhorse that powers most keyword, domain, URL, and backlink data.

If you use tools like Domain Overview, Organic Research, Keyword Magic, or Backlink Analytics, you are touching Analytics data.

Main Endpoint Families

• Domain reports: organic keywords, paid keywords, traffic, SERP features for a domain.
• URL and subfolder reports: similar stats, but at more granular levels.
• Keyword reports: related keywords, variations, questions, SERP features, and difficulty scores.
• Backlink reports: backlinks, referring domains, anchors, new and lost links.
• Ads / PLA reports: paid search keywords, positions, ad copies, product listing ads.

Historical depth and row limits vary by endpoint, so always check the current docs for max rows and how far back you can go.

Most of the time you paginate with parameters like a limit and an offset, especially when you want more than a few hundred rows.

Projects API

Projects API talks to your actual Semrush projects, not just public domain data.

That makes it ideal for monitoring your own sites and scaling your day‑to‑day SEO tasks.

Popular Project Endpoints

• Site Audit: issues, crawled pages, checks over time.
• Position Tracking: daily rankings for tracked keywords, visibility scores, device and location data.
• On Page SEO Checker: ideas and content suggestions for specific URLs and keywords, where available.
• Project management: list, create, or update projects, domains, and some tracking settings.

You can usually manage pieces of a project, like adding keywords or changing tags, but you might not be able to configure every single UI option through the API.

Semrush sometimes opens more controls over time, so again, keep an eye on the latest docs for what you can and cannot automate.

Trends, Traffic Analytics, And Market Explorer API

This branch focuses on web traffic estimates, audience behavior, and market comparison.

Semrush has used names like .Trends, Traffic Analytics, and Market Explorer, often as part of the same family.

Typical Data You Get

• Total and unique visits, session duration, bounce rate, and pages per visit.
• Traffic sources: direct, referral, search, paid, social, and so on.
• Geo breakdowns by country or region.
• Top pages, entry pages, and sometimes exit pages.
• Audience interests and sites your audience also visits, at higher tiers.

This is perfect for competitor benchmarking, market sizing, or building little “market share” widgets into investor decks or even into your own product.

When teams start mixing Traffic Analytics with CRM or revenue data, they often spot markets where they are strong in traffic but weak in revenue, or the other way around, which turns into very clear actions.

Getting Access And Setting Things Up Properly

Access depends on your current Semrush plan plus any extra API packs, and this does change over time, so never rely on an old screenshot.

You need to verify in your account which APIs are included, then request or generate keys from the right section.

Typical Steps To Get Your API Key

1. Log into Semrush and go to your profile or subscription settings.
2. Look for an “API” or “API units” section in the account menu.
3. Generate an API key, name it so you remember what uses it, and copy it to a safe place.
4. Confirm how many units you get per month and when they reset.
5. Review live docs for Analytics, Projects, and Trends APIs from Semrush’s help center.

The exact menu names may shift, but there is always some central spot where units and keys live.

Storing Keys Safely

Hardcoding your API key into random scripts or Google Sheets is a good way to leak it when someone shares a file or a GitHub repo.

Instead, keep keys in environment variables or a secrets manager and read them in at runtime.

Simple Environment Variable Example (Python)

# .env file
Semrush_API_KEY=your_real_key_here

# Python example
import os
from dotenv import load_dotenv

load_dotenv()
API_KEY = os.getenv("Semrush_API_KEY")

For Node, you can use a similar pattern with the dotenv package or built‑in environment variable support.

The main idea is that keys stay out of source control and shared documents.

Non‑Developer Options

If your team does not code, you still have options.

• Make, Zapier, n8n: connect Semrush API via HTTP modules, then push data to Sheets, Slack, Notion, or your database.
• Official connectors: use any official Google Sheets, Looker Studio, or Power BI connectors Semrush provides instead of hand‑rolling every call.
• Custom internal tools: ask a developer to build a simple backend endpoint that your non‑technical team can trigger with a form or button.

I think many marketers underestimate how far you can go with Make or n8n before you actually need a developer.

How Semrush API Calls Work In Practice

Every API call is just an HTTP request with parameters that tell Semrush what data you want and how you want it formatted.

You can test calls in your browser, Postman, or from code, then wire them into scheduled tasks once you trust them.

Anatomy Of A Basic Analytics API Call

Here is a simple example that asks for a domain’s organic keywords.

https://api.Semrush.com/?type=domain_organic&key=YOUR_API_KEY&domain=example.com&database=us&display_limit=100&export_columns=Dn,Ur,Po,Tr,Dt

• type=domain_organic: which report you want.
• key: your API key.
• domain: the domain you are analyzing.
• database: the regional database, like us, uk, de.
• display_limit: how many rows you want to return.
• export_columns: which columns to include in your CSV.

Some endpoints support a display_date parameter, but not all, and Semrush can limit how far back snapshots go, so do not assume you can pull any random date.

When you send that URL, Semrush returns CSV data that Sheets or Excel can parse.

Pagination And Filters

For larger datasets, you usually combine a limit with an offset to paginate through results.

Something like this pattern is common.

https://api.Semrush.com/?type=domain_organic&key=YOUR_API_KEY&domain=example.com&database=us&display_limit=100&offset=0
https://api.Semrush.com/?type=domain_organic&key=YOUR_API_KEY&domain=example.com&database=us&display_limit=100&offset=100

Filters help you cut noise and avoid wasting units on rows you do not care about.

Semrush uses a filter syntax where you combine columns and conditions, such as position or volume, into a filter parameter.

&filter=Po_lt_11%7C%7CNq_gt_100

That rough example aims for keywords in positions under 11 and search volume above 100; always check the official filter syntax, because the operators and column names are strict.

Python Example: Fetching Keywords For Multiple Competitors

Here is a small, more realistic script that loops through a list of domains and fetches their top organic keywords.

import os
import csv
import requests

API_KEY = os.getenv("Semrush_API_KEY")
BASE_URL = "https://api.Semrush.com/"

competitors = [
    "example1.com",
    "example2.com",
    "example3.com"
]

params_template = {
    "type": "domain_organic",
    "key": API_KEY,
    "database": "us",
    "display_limit": 100,
    "export_columns": "Dn,Ur,Po,Tr,Dt"
}

with open("competitor_keywords.csv", "w", newline="") as f:
    writer = csv.writer(f)
    writer.writerow(["domain", "keyword", "url", "position", "traffic", "date"])

    for domain in competitors:
        params = params_template.copy()
        params["domain"] = domain

        response = requests.get(BASE_URL, params=params, timeout=30)

        if response.status_code != 200:
            print(f"Error for {domain}: {response.status_code}")
            continue

        lines = response.text.strip().split("n")
        # skip header row from Semrush output
        for row in lines[1:]:
            cols = row.split(";")
            if len(cols) < 5:
                continue
            keyword, url, position, traffic, date = cols
            writer.writerow([domain, keyword, url, position, traffic, date])

This is not production‑grade, but it shows the basic flow: build parameters, send request, parse CSV, and write to your own file.

In a real setup you would add pagination, better error handling, and logging, but this gets you moving.

JSON With Projects API

Projects API often sends back JSON instead of CSV, which is nicer for structured app work.

Here is a sketch of pulling Position Tracking data.

import os
import requests

API_KEY = os.getenv("Semrush_API_KEY")
BASE_URL = "https://api.Semrush.com/management/v1/projects/"  # example, check current docs
PROJECT_ID = "your_project_id"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

response = requests.get(
    f"{BASE_URL}{PROJECT_ID}/position-tracking/keywords",
    headers=headers,
    timeout=30
)

if response.status_code == 200:
    data = response.json()
    for item in data.get("keywords", []):
        print(item.get("keyword"), item.get("position"))
else:
    print("Error", response.status_code, response.text)

The URL structure and fields will vary, but most flows follow the same pattern: authenticated request, JSON parsing, then looping through objects.

Before you build big workflows, spend time in Postman or a similar tool just exploring responses, fields, and filters, because it saves a lot of guesswork once you start coding.

How Semrush API Units And Billing Really Work

API units are your currency, and the fastest way to hate the API is to ignore how those units are burned.

Semrush can change exact pricing and rules, so always cross‑check with the live unit cost tables, but there are stable patterns you can work with.

Unit Basics

• Analytics and Projects APIs usually draw from a pool of API units tied to your subscription or extra packs.
• Each call costs units, often based on rows returned, and some "heavier" endpoints cost more per row.
• Trends / Traffic Analytics and Market Explorer may have their own billing model or packs, sometimes separate from the main unit bucket.

The units reset on a schedule, often monthly, and when you hit your cap, calls start failing or are blocked until the next reset or until you upgrade.

Sample Unit Cost Table

This is a simplified version, so treat it as directional, not exact pricing.

Semrush has detailed tables for this; I do not recommend guessing, especially if finance will ask about API costs later.

Rough Budgeting Example

Imagine you track 500 keywords across 10 domains with Position Tracking and pull daily data, and you run a Site Audit once per week per site.

• Position Tracking: 500 keywords x 10 domains = 5,000 keyword records per day.
• Over a 30‑day month, that is 150,000 keyword rows.
• Site Audit: say each audit returns 5,000 crawled pages per site, once per week.
• 5,000 x 10 domains x 4 weeks = 200,000 pages of audit data.

Depending on unit cost per row, you are now into hundreds of thousands of units just on these two flows, not even counting keyword research or backlinks.

So you need to sense check your plan against your monthly unit pool, otherwise scripts that seem harmless will drain everything in days.

Performance, Rate Limits, And Caching

Semrush will limit how many calls you can send in a short window, both to protect their systems and to keep you from accidentally hurting yourself.

You need to assume limits exist, even if you do not see them spelled out, and code defensively around them.

• Watch for status codes like 4xx or 5xx, or headers that signal throttling.
• Add short delays between batches of calls, especially in loops.
• Implement exponential backoff when you see too many errors, so you back off instead of hammering the API.

Caching is your friend here.

If you pull historical keyword or backlink data, that history rarely changes, so store it in your own database and only refresh new or recently updated parts, not the whole thing every day.

Automation, Dashboards, And Alerts

Pulling data is step one; the fun starts when you wire it into tools your team already uses.

Think about three buckets: dashboards, monitoring, and deeper integrations.

Dashboard Pipelines

For real dashboards you want a stable pipeline, not random CSV imports.

A common stack looks like this.

1. Schedule scripts or no‑code scenarios that call Semrush APIs daily or weekly.
2. Store results in a database, BigQuery, a data warehouse, or at least a stable Google Sheet.
3. Point your BI tool (Looker Studio, Power BI, Tableau) at that storage, not at the API directly.

This decouples your reports from Semrush response times or hiccups, and you can clean and join data before charts see it.

Monitoring And Alerting Logic

Alerts are where the API starts to feel like an extra teammate watching your sites.

You can design simple rules that run every morning and send you messages when something crosses a threshold.

• Ranking drop alerts: pull rankings for key pages, compare with last week, and if a top keyword falls more than 3 positions, ping Slack or email.
• Traffic dips: use Traffic Analytics or organic estimates to spot sudden percentage drops week over week.
• Toxic backlink alerts: pull new backlinks and run them through your own scoring or a spam score, then flag bad ones fast.

The logic does not need to be complex.

Something like this already catches a lot.

if old_position <= 3 and new_position >= 6:
    alert("High value keyword dropped from top 3 to 6+", url, keyword)

You can then decide manually what to do next, but at least you hear about problems before clients do.

Joining Semrush With GA4, Search Console, And CRM

Semrush shines for competitive and market data, while GA4 and Search Console shine for your own site reality.

If you keep them separate, you usually miss chances to connect rankings with revenue.

• Join GA4 revenue and sessions per landing page with Semrush ranking and keyword data to see which revenue pages are underperforming in search.
• Use CRM opportunity or closed‑won data to backtrack which pages and topics drive sales, then pull Semrush keyword clusters around those for expansion.
• Compare Semrush traffic estimates with your real traffic to calibrate expectations about market share and growth potential.

This takes more database work, but it is where SEO starts to feel aligned with pipeline, not vanity charts.

When you can say "this specific ranking drop cost us roughly this much revenue," you stop arguing about whether SEO matters and start arguing about which fixes to ship first, which is a better problem.

Google Sheets, Apps Script, And No‑Code Connectors

Google Sheets is still where many teams live day to day, so it makes sense to connect Semrush there, but basic IMPORTDATA approaches have limits.

They can break on URL length, give you little control over refresh timing, and do not handle errors in a friendly way.

Basic IMPORTDATA Example

You can still do something like this for quick tests.

=IMPORTDATA("https://api.Semrush.com/?type=domain_overview&key=YOUR_KEY&domain=example.com&database=us")

This works as long as the URL is not too long and the API returns CSV, but I would not rely on it for main reporting.

Apps Script Pattern

A small Apps Script gives you more control and lets you hide your API key away from random sheet viewers.

function fetchSemrushDomainOrganic() {
  var apiKey = PropertiesService.getScriptProperties().getProperty('Semrush_API_KEY');
  var url = 'https://api.Semrush.com/?type=domain_organic' +
            '&key=' + apiKey +
            '&domain=example.com&database=us&display_limit=50';

  var response = UrlFetchApp.fetch(url, { 'muteHttpExceptions': true });
  if (response.getResponseCode() !== 200) {
    Logger.log('Error: ' + response.getContentText());
    return;
  }

  var csv = Utilities.parseCsv(response.getContentText(), ';');
  var sheet = SpreadsheetApp.getActiveSpreadsheet().getSheetByName('SemrushData');
  if (!sheet) {
    sheet = SpreadsheetApp.getActiveSpreadsheet().insertSheet('SemrushData');
  }

  sheet.clearContents();
  sheet.getRange(1, 1, csv.length, csv[0].length).setValues(csv);
}

You set the Semrush_API_KEY property in Script Properties, then run or schedule the function.

No‑Code Connectors

Where possible, use official Semrush connectors for Google Sheets or Looker Studio instead of rebuilding their logic in every sheet.

For more complex workflows, tools like Make or n8n can fetch Semrush data and push it into Sheets, Airtable, Notion, or your database on a schedule, no custom code required.

Security, Compliance, And When Not To Use Semrush API

API keys give full access to your Semrush data pool, so you need to treat them like passwords, not casual tokens to drop into chat or shared docs.

And beyond keys, you should think about how you store and expose Semrush data, especially if you work with clients or build public tools.

Security Hygiene For API Keys

• Never hardcode keys in public repos or shared presentations.
• Use environment variables, script properties, or a secret manager in your cloud platform.
• Rotate keys if you suspect they leaked or when team members leave.
• Use different keys for different apps or projects, so one compromise does not affect everything.

If Semrush allows IP whitelisting or similar controls, use them to limit where calls can originate from.

This might feel overkill at first, but it looks very smart the first time a script behaves badly.

Terms, Data Use, And Public Tools

Semrush has rules about how you can store, resell, or publicly display their data, and ignoring them can get your access cut.

• Do not build a public "free Semrush clone" that just exposes raw rows; that usually breaks their terms.
• Check how long you are allowed to cache data and under what conditions.
• Use clear attribution if you show Semrush‑based stats in public dashboards or widgets.

The safe path is to read the latest API terms and, if you are doing anything unusual like a SaaS powered by Semrush data, talk to their team first.

Common Pitfalls To Avoid

• Infinite loops or bad pagination that keep requesting the same data, burning units without adding value.
• Pulling everything, always instead of narrowing down by filters, last changed dates, or key segments.
• Ignoring API change logs and suddenly waking up to broken scripts because an endpoint changed or got deprecated.
• Mixing test and production keys and losing track of which scripts hit which accounts.

Put a log around your calls and unit use, even if it is simple; it will save you when something goes weird.

Semrush API Vs Alternatives And Getting Your First Stack Ready

Semrush API is strong for competitive intelligence, keyword data, and cross‑domain insight, but it is not always the best or cheapest data source for every job.

For your own sites, GA4 and Search Console APIs are more direct, free, and sometimes more accurate, so they should usually sit next to Semrush, not under it.

When Semrush API Is The Right Tool

• You need competitor data at scale that GA4 and GSC cannot give you.
• You are already paying for Semrush and want to stop wasting time on manual exports.
• Your monthly SEO work involves repeated patterns that can be scripted.

Usually the cost starts to feel justified somewhere past a handful of clients or brands, especially once you show leadership a few hours per week saved per person.

When Other APIs Might Be Better

• Tracking exact traffic or conversions for your own site: GA4 and GSC first.
• Custom event or funnel analysis: analytics platforms, not Semrush.
• Ads management: native Google Ads or Meta APIs, then join them with Semrush data after.

The best setups pull from both worlds and join the datasets where it makes sense, instead of trying to make one tool do everything.

Sample "Getting Started" Stacks

If you are unsure how to start, pick a stack that matches your skills and use case.

Non‑Developer Stack

• Semrush Analytics + Projects APIs with enough units for a few key sites.
• Make, Zapier, or n8n to call the API and push data into Google Sheets or Airtable.
• Looker Studio dashboards on top of those sheets for simple reporting.

Technical SEO Stack

• Python scripts running on a scheduler like cron, Cloud Functions, or a small VM.
• PostgreSQL, BigQuery, or another warehouse as the long‑term storage layer.
• Semrush Analytics and Projects APIs feeding into rank, audit, and backlink tables.
• BI tool for reporting plus Slack alerts for key changes.

SaaS / Product Team Stack

• Backend service with a Semrush API client and its own caching layer.
• Background jobs that fetch and refresh data on a schedule, not on every user request.
• Role‑based use of keys so different environments do not clash.
• Product features that show high‑value snapshots, not raw tables that drown users.

Your first project does not have to be huge; one useful report or alert that saves an hour every week is enough proof that the API is worth expanding.

Once you see where the friction drops in your current workflow, you will know which endpoint to wire up next.

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