7 Tools to Find New Keywords [Free + Paid Options]

You have likely stared at a keyword spreadsheet, sorted by “Volume,” and wondered why the resulting traffic didn’t turn into revenue. It is a common frustration. In 2026, finding the right keywords requires more than just looking for the biggest numbers; it requires understanding exactly how a user is searching. 

As Ben Salomon, an e-commerce expert, notes, “In a fractured search landscape, efficient, data-driven discovery is the only way to compete.” This guide moves beyond a simple list of tools to analyze the methodology of keyword discovery, helping you target terms that drive sales, not just empty clicks.

Key Takeaways: 7 Tools to Find New Keywords [Free + Paid Options]

• The “Citation Moat”: SEO goals are evolving from simply ranking #1 to securing citations within AI Overviews (AIOs), which increasingly serve as the top result.
• Telegraphic Search: Despite the rise of conversational AI, users still often default to “keyword-ese” (e.g., “dentist 11214”) inside LLMs, making specific string matching vital.
• The “Dangerous Middle”: A strong ROI opportunity lies in complex commercial queries where AI summarizes the options, but human verification is still required for the click.
• Tool Synergy: No single tool reveals the full picture; success often requires combining free proprietary data (Google) with paid competitive intelligence (Semrush/seoClarity).

The Macro-Analytical Framework: Search in 2026

Before opening a single tool, it is helpful to understand the environment it operates in. In 2026, selecting a keyword based solely on “high volume” can be challenging. The correlation between a #1 ranking and high traffic has weakened for a segment of queries, specifically those that trigger AI Overviews (AIOs).

To build a resilient strategy, consider these three specific shifts in user behavior and engine architecture.

Understanding Click-Through Rate Volatility

A critical metric in modern keyword research is click probability. Extensive data shows that organic click-through rates (CTR) for informational queries that trigger an AI Overview have decreased by 61% compared to standard SERPs.

This creates a “Zero-Click” environment for simple questions like “what is a loyalty program?” Even if you rank #1 organically, the AI often answers the user’s query directly on the results page, satisfying their intent without a site visit.

This volatility extends to paid search as well, where paid CTR has declined by 68% for terms impacted by AI Overviews. Paying for visibility doesn’t always guarantee traffic if the engine resolves the query at the surface level.

The “Citation Moat” Opportunity

While traffic from traditional rankings has shifted, a new target has emerged: the Citation. The goal of keyword research is increasingly about “being cited as the source of truth.”

This appears to be a competitive edge. Brands that are cited within an AI Overview receive 35% more organic clicks and 91% more paid clicks than those that merely appear on the traditional results page. The strategy, therefore, is to identify keywords where you can provide the specific, structured data—stats, definitions, or distinct viewpoints—that Large Language Models (LLMs) prioritize for their summaries.

The Stability of AI Overview Prevalence

Despite initial fluctuations, the presence of AI in search has stabilized. AI Overviews now appear for approximately 16-30% of queries, but the distribution is uneven.

• Informational Intent: 84% of AI Overviews are triggered by informational queries (e.g., “benefits of retention marketing”).
• Transactional Intent: Only roughly 12% of AIOs appear for transactional queries.

This data highlights the “Dangerous Middle” strategy. Consider targeting complex commercial queries—where an AI might summarize options (e.g., “best enterprise loyalty software for Shopify”), but the user still requires human verification and deep-dive comparisons before making a decision. This “middle” ground often offers a balance of volume and click-through intent.

User Behavior in LLMs: The “Conversational” Myth

A common misconception is that users now search exclusively with long, conversational sentences. However, 75% of ChatGPT sessions still utilize “keyword-ese”—the traditional, telegraphic search language used for decades (e.g., “dentist 11214”). Users often prioritize efficiency over syntax. This validates that traditional volume data from tools like Google Keyword Planner remains a useful proxy for demand, even in the age of LLMs.

1. Google Keyword Planner (Free)

Category: Foundational Data Source Best For: Raw, proprietary search data and competitor URL analysis.

While third-party tools offer excellent filters, Google Keyword Planner (GKP) remains a primary source of direct, proprietary search data. It is often the bedrock of a keyword strategy.

Feature Update: Adaptive Weekly Forecasting

In the past, marketers relied on monthly or quarterly search volume averages, which could mask short-term spikes. Google has updated its forecasting models to support adaptive weekly trends.

This feature is helpful for spotting breakout trends before they appear in third-party tools. For example, a sudden rise in “sustainable packaging for returns” might show up in GKP weeks before competitors notice it. You can access this by selecting “Custom” date ranges in the forecast tool to see week-over-week changes.

Strategy: The “Start with a Website” Feature

One of the most useful features in GKP is the ability to generate keywords from a URL rather than a seed term. This allows you to see the “semantic core” Google associates with a specific page.

• The Workflow: Instead of typing “skin care,” paste the URL of a competitor’s best-selling product page or a high-ranking industry article.
• The Output: Google will list every keyword it believes is relevant to that page. This often reveals “lateral” keywords—terms you wouldn’t have thought to search for but which Google’s algorithm sees as synonymous with your topic.
• Gap Analysis: Use this on non-competitor URLs, such as Wikipedia pages related to your industry. This helps you find neutral, academic terms that are useful for building the authoritative content needed to earn AIO citations.

Cross-Platform Synergy (App + Web)

For SaaS companies or retailers with mobile apps, GKP offers unified discovery for mobile app and web queries. This is essential for capturing distinct mobile-first intent, such as in-store inventory checks or barcode scanning features.

2. Semrush (Paid)

Category: Competitive Intelligence Suite Best For: AI Overview (AIO) Detection and Commercial Intent Mapping.

While Google Keyword Planner provides raw data, Semrush provides context. In 2026, its value is often found in its ability to detect where AI has infiltrated the SERP and where opportunities still exist. As Ben Salomon advises, “The future of search suggests we look beyond the ‘what’ of a keyword to the ‘where’—specifically, where is the click actually going?”

The AIO Sensor and Intent Filtering

A common challenge in modern SEO is prioritizing a high-volume keyword without realizing an AI Overview dominates the top of the page. The presence of AIOs has stabilized at 15.69% of all queries.

However, the distribution is shifting. Commercial queries triggering AIOs have nearly doubled, rising to 18.57%. This means product-focused keywords are also seeing increased AI presence.

The Strategy: Consider using the Semrush “SERP Features” filter to create two distinct keyword lists:

1. The “Citation” List: Keywords with an AI Overview. The goal here is to structure content to be cited.
2. The “Traffic” List: Keywords without an AI Overview. These are traditional SEO targets where a #1 ranking is more likely to result in a direct click.

The Keyword Magic Tool & “Navigational Risk”

With a vast database of keywords, the Keyword Magic Tool is useful for identifying “Navigational Risk.”

Navigational AI Overviews have risen from 0.74% to 10.33% in under a year. This means users searching for specific brand names or websites are increasingly seeing AI summaries.

• Actionable Insight: Run your own brand name and top product names through the tool. If you see high “Competitive Density” and an active AIO feature, prioritize “Brand Defense” content—clear, authoritative definitions of your own products—to help the AI summarize you correctly.

3. seoClarity (Paid / Enterprise)

Category: Enterprise Real-Time Intelligence Best For: “Pixel Depth” Analysis and Citation Mining.

For enterprise brands managing thousands of SKUs, standard rank tracking can sometimes be limited. seoClarity distinguishes itself by moving away from “Rank Position” to “Pixel Depth.”

Beyond Rank: Pixel Depth Analysis

In a mobile-first environment, ranking #1 may be less effective if that result sits 1,200 pixels down the page, beneath an AI Overview or ads.

seoClarity’s “Visibility Share” metric calculates the visual real estate you occupy.

• The Workflow: Filter your keyword report for terms where you rank in the Top 3 but have a “Pixel Depth” greater than 800px.
• The Pivot: For these terms, traditional organic optimization might have reached a limit. Consider pivoting to Paid Search to regain top-of-page visibility or restructuring the content to target the Featured Snippet.

The “Top 20” Citation Strategy

A compelling reason to use seoClarity is their data on AI Citations. Research confirms that 94% of AI Overviews cite a URL from the top 20 organic results.

This reveals a “Striking Distance” opportunity. You do not necessarily need to be #1 to be cited.

• The Data: While #1 rankings are cited 43% of the time, URLs ranking as low as position 20 still have a 7% chance of being cited if they contain the structured data the AI needs.

4. Answer Socrates (Free)

Category: Question-Based Research Best For: Mining the “Natural Language” Long Tail.

In the era of AI Overviews, the format of your content is important. Since AI engines often function as answering machines, a good way to be cited is to provide the direct answer to a specific question. Answer Socrates is a helpful tool for uncovering these questions.

Optimizing for the Informational 84%

As noted earlier, 84% of AI Overviews are triggered by informational queries. To capture this interest, it helps to know the exact interrogatives users are typing.

Answer Socrates aggregates data from “People Also Ask” (PAA), Google Trends, and Autocomplete to visualize search behavior by specific modifiers.

• The Workflow: Enter a seed topic like “loyalty programs.” The tool will generate natural language questions, such as “How to calculate redemption rates for loyalty programs?”
• The Application: Use these specific questions as H2 headers. This structural alignment signals to Google’s AI that your section is the answer to that specific user query.

Strategic Application for SaaS

For B2B and SaaS brands, Answer Socrates helps bridge the gap between “feature” and “pain point.”

• Example: A user might not search for “SMS marketing integration,” but they will search for “How to send review requests via text?”
• Expert Insight: As e-commerce expert Mira Talisman suggests, “In a trust-based economy, the brand that answers the customer’s specific anxiety first tends to win the relationship.” Answering these specific long-tail questions builds the relational trust required for long-term loyalty.

5. Keyword Tool.io (Free/Paid)

Category: Autocomplete Scraper Best For: Capturing “Telegraphic” Queries and Platform Specificity.

While Answer Socrates handles questions, Keyword Tool.io focuses on the other end of the spectrum: the specific, often ungrammatical strings that users type when they are in a rush.

Validating “Keyword-ese”

We often assume that as search engines get smarter, users will type more naturally. Data suggests otherwise. A 2026 observational study found that 75% of ChatGPT sessions still utilize “keyword-ese”—short queries like “best crm for saas.”

Keyword Tool.io excels here because it scrapes Google Autocomplete to find long-tail variations that Google Keyword Planner often groups together.

• The Hidden Long Tail: It will reveal the difference between “best saas crm” (Volume: 1,200) and “best crm for saas startups” (Volume: 400).
• Granularity: specific string matching is vital. Matching your Title Tag to the exact string the user types is a strong relevancy signal.

Platform Specificity (YouTube & Amazon)

One of the tool’s strongest features is its dedicated tabs for YouTube, Amazon, and Instagram.

• The Opportunity: Search behavior differs by platform. A user on Google might search “e-commerce trends,” while on YouTube they search “Shopify store setup tutorial 2026.”

6. Seer Interactive’s Data (Methodology as Tool)

Category: Strategic Benchmark Best For: Risk Assessment and CTR Modeling.

While Seer Interactive is a strategic agency, their publicly available data sets and methodology function as a critical “tool” for the modern researcher. In 2026, it is wise to audit your keyword list for “CTR Risk” rather than assuming traffic based on volume alone.

The “Safe Harbor” Audit

Consider using this data as a pre-production filter. Before finalizing a content calendar, compare your target keywords against Seer’s CTR benchmarks.

• The Calculation: If a keyword cluster is purely informational and likely triggers an AI Overview, consider applying a 61% traffic discount to your projections.
• The Decision Matrix: Ask yourself, “Is the remaining 39% of traffic valuable enough to justify the content investment?”
• The Pivot: If the answer is no, you might shift focus to “Safe Harbor” keywords—terms with commercial intent where Seer’s data shows the “human verification” factor keeps CTRs stable.

Risk Assessment & Efficiency

This methodology acts as a gauge. By identifying high-volume but low-click keywords early in the process, you can allocate resources to terms that drive revenue. As the data confirms, efficiency is key to growth. Focusing on verified click-through probability is a sustainable strategy.

7. ChatGPT (Paid – Plus/Team)

Category: Generative Analysis Best For: Persona Simulation and Semantic Clustering.

Finally, ChatGPT (specifically models like GPT-4o) serves not as a database of search volume, but as a “behavior simulator.” It allows you to qualitatively analyze how your audience searches.

Reverse-Engineering the Prompt

Using the insights from the Sagapixel study regarding “keyword-ese,” you can use ChatGPT to model telegraphic search behavior.

• The Strategy: Do not ask ChatGPT for “keywords.” Ask it to simulate a user.
• Prompt Example: “Act as an Operations Manager for a mid-sized fashion retailer. You are frustrated with your current returns management software. List 20 ‘telegraphic’ or short-hand keywords you would type into Google to find a replacement. Focus on efficiency over grammar.”
• The Output: This often generates terms like “returns software shopify” or “automated returns api”—high-intent strings that standard brainstorming might miss.

Semantic Clustering & Gap Analysis

Grouping thousands of rows of data is often tedious. ChatGPT can assist here.

• Workflow: Paste a CSV export from Semrush into ChatGPT and ask it to “Cluster these keywords by User Journey Stage (Awareness, Consideration, Decision) and identify the primary intent for each cluster.”

Synthesis: A Workflow for 2026

Effective SEO strategists often build a “stack” that balances raw data with competitive intelligence. To navigate the 2026 landscape, consider adopting this three-phase workflow.

Phase 1: Discovery & Volume (The Raw List)

Start with Google Keyword Planner. Use the “Start with a Website” feature on competitor product pages to build a list of semantically related terms. At this stage, aim for maximum breadth to capture ideas you might have missed.

Phase 2: Risk Assessment (The Filter)

Import your raw list into Semrush. Apply the “SERP Features” filter to identify which terms trigger an AI Overview.

• For AIO Terms: Cross-reference with Seer Interactive’s benchmarks. If the term is purely informational, apply a traffic discount to your projections to see if it’s still worth targeting.
• For Non-AIO Terms: These are your “Safe Harbor” keywords.

Phase 3: The Citation Layer (The Optimization)

For the keywords where you compete with an AI, use Answer Socrates to find the specific questions users are asking. Use these questions as H2s in your outline. Finally, run your title tags through Keyword Tool.io to ensure you are matching the string users are typing.

How Yotpo Reviews & Loyalty Uncover Hidden Keywords

Yotpo Reviews

While external tools estimate demand, your own customer data is a highly accurate source of intent. Yotpo Reviews functions as a real-time keyword mine, as customers often describe products using “problem/solution” language that differs from marketing copy. By analyzing this User-Generated Content (UGC), you can discover untapped long-tail queries. 

For example, AI-powered Smart Prompts are 4x more likely to capture mentions of specific high-value topics (like “sizing” or “durability”), revealing exactly what features future buyers are searching for. Furthermore, syndicating this fresh content to Google via Seller Ratings is proven to drive a 17% increase in CTR on ads. Combining this with Yotpo Loyalty data allows you to identify “Retention Keywords”—the terms your VIPs search for—enabling you to optimize for Lifetime Value (LTV).

Conclusion

SEO hasn’t ended; it has evolved into “Entity Optimization.” As the data confirms, efficiency is critical. Rather than targeting broad, high-volume terms that might be summarized by AI, successful discovery in 2026 involves finding the “Dangerous Middle”—complex commercial queries where human verification is still required. By using these 7 tools to identify “telegraphic” intent and optimize for AI citations, you build a strategy that drives revenue, not just traffic.

FAQs: 7 Tools to Find New Keywords Free + Paid Options

What is the best free keyword research tool for 2026?

While Google Keyword Planner remains the foundational “source of truth” for raw volume data, Answer Socrates is a top free tool for specifically targeting AI Overviews. It is excellent for mining “People Also Ask” data to find the natural language questions that trigger AI citations.

How do AI Overviews impact keyword research strategy?

AI Overviews (AIOs) have shifted the goal from “ranking” to “citation.” Data shows that organic CTRs for AIO-impacted queries have dropped by 61%. However, brands that are cited within the AI summary see a 35% increase in organic clicks, making “Citation Optimization” a key priority.

Can I use ChatGPT for keyword research?

Yes, but it is best for qualitative analysis, not volume data. A Sagapixel study reveals that 75% of users still use “keyword-ese” even in LLMs. Therefore, ChatGPT is best used for persona simulation—asking it to act as a customer and generate keywords—rather than asking it for volume metrics.

What is the difference between informational and transactional intent in 2026?

The difference is often defined by AI saturation. 84% of AI Overviews are triggered by informational queries, making them lower-click targets. Transactional queries see only ~12% AIO prevalence. The “Dangerous Middle” (complex commercial queries) offers a balance of traffic and click potential.

Why is “pixel depth” important for keyword selection?

“Rank #1” can be a misleading metric if that result is pushed 1,200 pixels down the page by an AI Overview and ads. seoClarity’s data emphasizes “Visibility Share” over rank position, as being “above the fold” is key to guaranteeing a click on mobile devices.

How does “telegraphic” search behavior affect my keyword list?

Despite the rise of conversational AI, users prefer efficiency. The fact that nearly half of ChatGPT prompts are “one-shot” queries suggests you should still optimize for exact-match strings like “best shopify loyalty app” rather than just long, conversational sentences. Tools like Keyword Tool.io are helpful for capturing these variations.

Is Google Keyword Planner enough for SEO research?

It is a great foundation, but often insufficient on its own. While GKP provides proprietary volume data, it cannot detect AI Overviews. Without a third-party tool like Semrush to filter out AIO-triggering keywords, you risk optimizing for terms where the CTR is low, regardless of your ranking.

How often should I update my keyword research?

With Google’s introduction of weekly forecasting in Keyword Planner, quarterly updates may be too slow. Markets shift quickly. Consider checking for “breakout” trends (e.g., “sustainable packaging”) on a monthly basis to capture demand before third-party tools aggregate the data.

What is “Generative Engine Optimization” (GEO)?

GEO is the practice of optimizing content to be recognized and cited by Large Language Models (LLMs) and AI engines. Unlike traditional SEO, which focuses on links and keywords, GEO focuses on Structured Data, Authoritativeness, and Direct Answers to ensure your brand is included in the AI-generated summary.

How do I find “low competition” keywords that are still valuable?

Look for “Striking Distance” keywords using the “Top 20” strategy. 94% of AI Overviews cite a URL from the top 20 results. If you rank on Page 2 (Positions 11-20), optimizing that specific content for an AIO citation is often a lower-competition path to visibility than fighting for the traditional #1 spot.