Ahrefs API Deep Dive: Matching Terms vs. Related Terms vs. Search Suggestions

Summary

• Key Stat: The Ahrefs API v3, which automates keyword research, is exclusive to Enterprise plan subscribers and costs a minimum of 50 units per request.
• Key Learnings: The API offers three distinct endpoints: Matching Terms for on-page depth, Related Terms for topical breadth, and Search Suggestions for finding specific user queries.
• Action Item: Create a comprehensive content ecosystem by using Related Terms for content pillars, Matching Terms for page optimization, and Search Suggestions for FAQs and long-tail content.
• The Synscribe Approach: Synscribe builds on these principles with proprietary tools to develop data-driven SEO & Content Strategies that move beyond manual research to capture high-intent customers.

You've spent hours in the Ahrefs Keywords Explorer, manually sifting through endless keyword lists and feeling frustrated that "most of the keywords that have high volume have a high keyword difficulty score." You're not alone. Many SEO professionals struggle with finding that sweet spot of high-volume, low-competition keywords while trying to understand where and how to use them effectively.

What if there was a more programmatic, scalable way to conduct keyword research that could help you bypass these common roadblocks?

Enter the Ahrefs API v3—a powerful tool that allows you to access Ahrefs' vast database programmatically, giving you unprecedented flexibility for advanced SEO work. But with this power comes the challenge of understanding the subtle yet crucial differences between three core keyword discovery features: Matching Terms, Related Terms, and Search Suggestions.

This article will demystify these three API endpoints, explain when and how to use each one, and demonstrate how they can be combined into a cohesive keyword research strategy that addresses the common pain points of finding rankable keywords and understanding user intent.

Note: The Ahrefs API is exclusively available to Enterprise plan subscribers. If you're on a lower-tier plan, you'll need to use the Ahrefs web interface instead, though the concepts we'll discuss still apply to your manual keyword research.

Understanding the Ahrefs Keywords Explorer API

Before diving into the specific endpoints, it's important to understand the basic structure of the Ahrefs API v3.

The API v3 provides programmatic access to Ahrefs' vast dataset, allowing you to pull data from Site Explorer, Keywords Explorer, SERP Overview, and more. This replaced the now-deprecated API v2, offering more comprehensive data and improved functionality.

A critical technical consideration when working with the API is the consumption of API units:

• Every API request consumes units from your monthly allocation
• The minimum cost for any request is 50 units
• The total cost varies based on the number of rows returned and the specific fields requested

This unit-based model is crucial to understand when planning large-scale data extraction or building automated tools. For more details on consumption rates, check the official documentation on limits and consumption.

Now, let's explore each of the three keyword-related endpoints in detail.

Deep Dive 1: Matching Terms for Laser-Focused Targeting

What It Is

The Matching Terms endpoint is the most straightforward of the three. It retrieves keywords that literally contain your seed keyword or have extremely similar search behavior. As one SEO professional explained it: "Matching Terms finds keywords containing your exact seed keyword."

These are keywords that typically include your original phrase, often with modifiers before or after it. They generally share significant SERP overlap, meaning they tend to rank the same pages.

When to Use It

Matching Terms is ideal for:

• On-page optimization: When you need to identify all the possible variations of your target keyword to include in a single service page, product page, or cornerstone article
• Tight topic clustering: When you want to dominate a specific niche by covering every possible permutation of your head term
• Keyword placement decisions: When you're struggling with "how to decide where these keywords are mentioned, homepage or about or contact?" (a common pain point from our user research)

This endpoint helps you identify terms that belong together on the same page, solving the placement question by grouping closely related variations.

Practical Example

Let's say your target keyword is software company:

Potential Matching Terms results might include:

• custom software company
• enterprise software company
• software company near me
• best software company for startups

All these variations would likely work well on the same service page or homepage, as they represent essentially the same search intent with slight modifications. This addresses the common question of "Should it be in the same order like software company or could it also be software another word company?" - both patterns will be captured.

Deep Dive 2: Related Terms for Building Topical Authority

What It Is

The Related Terms endpoint is more sophisticated, finding keywords that are contextually or thematically related to your seed keyword, even if they don't contain the same words.

As described by Ahrefs, these are "keywords related to the topic of your seed keyword, often found on pages ranking for your term, but not always containing it." They represent the semantic context around your main topic.

When to Use It

Related Terms is perfect for:

• Content strategy & ideation: When you need ideas for blog posts, guides, and supporting content around your main service
• Building topical authority: When you want to demonstrate expertise in a broader subject area, signaling to search engines that you're an authority in the space
• Addressing different stages of the buyer's journey: When you need to find keywords that map to different levels of awareness

This directly addresses the advanced SEO strategy of focusing on topical authority rather than just keyword difficulty, which was highlighted in our user research as a key success factor: "I've had cases where I ranked within a week for KD50+ keywords based on topical authority."

Practical Example

Again, using software company as our target keyword:

Potential Related Terms results might include:

• how to choose a development partner
• custom vs off-the-shelf software
• software development lifecycle
• technology stack comparison
• cloud vs on-premise solutions

Notice that these don't necessarily contain the words "software" and "company," but they're highly relevant to the topic and would make excellent blog content or supporting pages for a software company website.

Deep Dive 3: Search Suggestions for Uncovering User Intent

What It Is

The Search Suggestions endpoint provides autocomplete suggestions pulled directly from Google's search interface. These represent the actual phrases that users are typing into search engines.

As one expert puts it: "Search Suggestions pulls Google's autocomplete suggestions (phrases users type into search) to give you ideas for long-tail and popular queries."

Unlike the other two endpoints, which are based on Ahrefs' own keyword database, this feature taps into real-time user behavior data from Google itself.

When to Use It

Search Suggestions is invaluable for:

• Finding long-tail keywords: When you need highly specific, often lower-competition queries that are easier to rank for
• Answering user questions directly: When you want to create FAQ sections or "how-to" content that addresses specific user needs
• Identifying trending topics: When you want to capture current interests and timely queries

This directly addresses the pain point of finding keywords with decent traffic that aren't "impossible to rank for," as many long-tail queries from Search Suggestions will have lower keyword difficulty scores.

Actionable Implementation

Here's how to leverage the Search Suggestions data effectively, based on best practices from Ahrefs Academy:

1. To find high-volume, low-competition keywords:

   • Filter the API response for keywords where volume is at least 500 (or your desired threshold) and keyword_difficulty is at most 10

2. To find informational keywords:

   • Look for keywords containing modifiers like "how," "what," "why," "guide," or "tutorial"

3. To find transactional keywords:

   • Search for keywords with commercial intent modifiers such as "buy," "price," "cost," "service," or "hire"

Practical Example

For our software company example:

Potential Search Suggestions results might include:

• how to start a software company
• software company business plan template
• what services do software companies offer
• software company pricing models
• best software companies for small business

At a Glance: Matching vs. Related vs. Search Suggestions

Feature	Matching Terms	Related Terms	Search Suggestions
Core Concept	Literal variations containing your seed keyword	Contextually related topics	Real user autocomplete queries
Best For	On-page optimization, targeting a core topic	Content strategy, building topical authority	Finding long-tail keywords, answering user questions
Keyword Type	Close variations, synonyms, modifiers	Thematic, tangential, problem/solution-based	Question-based, specific phrases, trending queries
Example for "SEO Tool"	best seo tools, free seo tool, enterprise seo tool	keyword research, backlink analysis, technical seo audit	how to use seo tools, are free seo tools worth it, seo tool vs agency
Technical Source	Ahrefs keyword database	Pages ranking for similar terms	Google autocomplete API

A Strategic Workflow: Combining All Three for SEO Success

The real power comes when you use these three endpoints together in a cohesive strategy:

1. Start Broad (Related Terms): Begin with your main keyword and use the Related Terms API to map out your entire topical universe. This gives you your main content pillars.

2. Go Deep (Matching Terms): For each content pillar, use the Matching Terms API to find all close variations. These become your target keywords for optimizing that specific page or article.

3. Get Specific (Search Suggestions): For each pillar, use the Search Suggestions API to find all the specific questions users are asking. These become subsections, FAQ items, or separate blog posts that link back to your pillar content.

This three-step process directly addresses the frustration that "Everything with decent traffic felt impossible to rank for" by creating a comprehensive content ecosystem that targets keywords at various competition levels while maintaining topical relevance.

Conclusion: From Keyword Data to Content Strategy

We've seen that Matching Terms is for depth, Related Terms is for breadth, and Search Suggestions is for specificity. Understanding when and how to use each endpoint transforms keyword research from a frustrating exercise into a strategic advantage.

By leveraging the Ahrefs API programmatically with this framework, you create a clear, scalable system to:

• Identify high-value, low-competition keywords
• Understand user intent at different stages
• Build topical authority in your niche
• Optimize content placement across your site

The ultimate goal isn't just to find keywords; it's to understand the landscape of user problems and questions. The Ahrefs API gives you the raw data to do just that, turning what many feel is an overwhelming process into a systematic approach to content development that drives organic traffic and establishes your expertise.

Frequently Asked Questions

What is the main difference between Matching Terms, Related Terms, and Search Suggestions in Ahrefs?

The main difference lies in their scope and data source. Matching Terms finds keywords that literally contain your seed term, Related Terms identifies contextually similar topics, and Search Suggestions pulls real user queries directly from Google's autocomplete feature. In short, use Matching Terms for on-page depth, Related Terms for topical breadth, and Search Suggestions for uncovering specific user intent.

When should I use Matching Terms instead of Related Terms?

You should use Matching Terms when optimizing a single page for its core topic. It helps you find all the close variations of your primary keyword to include in your content. In contrast, use Related Terms when planning a broader content strategy to discover new article ideas and supporting topics that build your site's overall topical authority.

How can I find high-volume, low-competition keywords with the Ahrefs API?

The Search Suggestions endpoint is often your best starting point for finding high-volume, low-competition keywords. Because these are long-tail queries that users are actively searching for, they are often more specific and have a lower Keyword Difficulty (KD) score. You can programmatically filter the API response to show keywords with a minimum search volume and a maximum KD score, quickly identifying rankable opportunities.

Can I apply these keyword research concepts without using the Ahrefs API?

Yes, absolutely. The strategic concepts behind Matching Terms, Related Terms, and Search Suggestions are fundamental to the Ahrefs Keywords Explorer tool in the web interface. The API simply provides a programmatic and scalable way to access this data. Any Ahrefs user can manually follow the same workflow: use "Related terms" for content ideas, "Matching terms" to optimize a page, and "Search suggestions" for long-tail queries.

What is topical authority and how does the Related Terms endpoint help build it?

Topical authority is a site's perceived expertise on a specific subject in the eyes of search engines. The Related Terms endpoint is crucial for building it because it helps you map out all the relevant subtopics and questions you need to cover. By creating a comprehensive cluster of content around these related terms, you signal to Google that you are a definitive resource, which can help all pages within that topic rank higher.

How do Ahrefs API units work for these keyword endpoints?

Every request to the Ahrefs API consumes a minimum of 50 units. The total cost then increases based on the number of rows (keywords) you retrieve and the specific data fields you request. To manage your monthly unit allocation effectively, you should only request the fields you need (e.g., keyword, volume, keyword_difficulty) and be mindful of the number of rows in your query. Always check the official Ahrefs documentation for the most current consumption rates.