On March 13, 2025, we hosted a live session where we explored 50 ways to use Large Language Models (LLMs) to enhance your SEO strategy in just 50 minutes. If you missed the session or want to revisit the insights, check out the recording and download the slides, where you’ll find detailed prompts and examples.
Better Prompt Engineering
The quality of any AI output hinges on the quality of the prompt. Whether you’re working on content briefs or dev tickets, take the time to refine your prompts. Tools like Anthropic’s Console help identify vague instructions, making your AI-generated results more consistent and reliable.
Research
LLMs are excellent for quickly gathering information on a new client’s industry or tackling complex SEO queries. While AI is great for deep research, always verify any facts before relying on them.
Summarize Videos
Want to save time deciding whether a webinar is worth your attention? Tools like Raycast’s “Summarize YouTube” provide bullet-point overviews of videos, so you can get the key takeaways without watching the entire thing.
Creating Word Lists
Whether it’s city names, car models, or niche terminology, a well-structured prompt can generate large, de-duplicated lists. Our Keyword Vault in SEOmonitor is ideal for storing these lists—where they can even be rank-tracked automatically.
Categorization
Group keywords or URLs by topics, intent, personas, or user needs. SEOmonitor does much of this automatically, but you can also pair it with an LLM for custom classification. Third-party tools like Refined Query Classifier add another layer of insight into how Google interprets queries.
Translation
Modern machine translation is good enough for quick proof-of-concept pages in new languages, letting you confirm search demand before you invest in professional localization.
Trend Forecasting
LLMs can provide code (e.g., Python scripts) for advanced traffic or ranking forecasts, while SEOmonitor’s own forecasting is available at the keyword, category, or site level.
What-If Scenarios
Once forecasting is in place, you can ask “What if we delay a big content push?” or “What if we acquire a competitor?”—as long as you guide the AI with realistic assumptions.
Content Gap Analysis
Compare your page titles to a competitor’s to see topics you’re missing. For very large datasets, look for an LLM that supports big context windows (like Google’s upcoming Gemini). SEOmonitor also offers a Missing Pages report to highlight uncovered areas.
Sentiment Analysis of User Reviews
LLMs can produce scripts (e.g., Python + SpaCy) to parse your reviews, rather than letting the AI guess sentiment. This method is more reliable for finding recurring likes/dislikes.
SERP Quality Checking
An LLM can compare top-ranking pages to Google’s Quality Rater Guidelines. If the SERP is overall weak, that’s a prime opportunity for better content.
Synthetic Users
For immediate user feedback, specialized platforms blend real data with an LLM-based “virtual panel.” Pricier than a simple AI prompt, but it offers rapid insight into brand perceptions or test copy.
Content Briefs
Simple prompts like “Write an article on X” won’t cut it. Incorporate audience insights, brand guidelines, and competitor data. SEOmonitor brings these signals together automatically in its brief-creation process.
Writing Blog Posts
General LLMs alone may overlook brand nuances or E-E-A-T requirements. For high-priority pages, pair an advanced prompt with thorough fact-checking, or turn to a specialized SEO content solution.
Page Relevancy Checker
Use embeddings or cosine similarity to confirm how closely a page’s text matches a target keyword, especially if brand edits have changed its focus.
Factual Accuracy Checker
Accurate content is vital for industries like finance or health. A site-wide “accuracy audit” can spot outdated or incorrect info. Tools like Loki (or AI-generated scripts) handle this at scale.
Transcreation
Adapt an existing post for Twitter, Facebook, Instagram, or other channels by prompting the AI for style and formatting changes. One prompt can yield multiple platform-ready versions.
Newsjacking
Set up a daily AI “agent” to monitor relevant headlines. It summarizes each article and suggests potential angles for your brand or client.
Persona Generation
Pair your analytics data with an LLM prompt to create personas. This approach yields structured outputs—name, demographics, motivations, frustrations—that can be shared across your team.
Splitting Pages into Buckets
For SEO A/B tests, feed an LLM your Google Analytics data and have it split the pages into two groups that behave similarly—giving you a fair comparison for any on-page experiments.
Producing “Good Enough” Content
If you only need quick copy to test a hypothesis (e.g., adding 200 words to a product page), an LLM can generate a workable draft in minutes. If it performs well, invest in a professional rewrite.
Generating Variations of Content
Test different tones to see if user engagement changes. For instance, rewrite a formal landing page in a more casual style and compare the metrics.
Benchmark Pages Against QRG
In-depth version of a SERP check. Give an LLM a single page to match up with Google’s Quality Rater Guidelines, revealing trust or expertise gaps.
Better Tickets to Devs
Miscommunication with developers slows projects. An AI-driven “ticket generator” can clarify acceptance criteria, dependencies, and timelines—reducing time lost to back-and-forth.
Complex Page Matches
By combining Screaming Frog with an LLM, you can classify thousands of pages at scale (e.g., finding negative brand sentiment or missing legal disclaimers).
Redirect Maps
During a migration, let embeddings or fuzzy matching handle large-scale URL mapping. Dentsu’s AI Redirect Mapper is a no-code solution; otherwise, you can run BERT-based scripts locally.
Alt Text for Images
Automate the tedious task of writing image alt text with a CSV of image URLs plus an AI workflow (like one built in Make.com or via Screaming Frog).
Better Change Alerts
SEOmonitor flags page changes out of the box. If you need additional detail, set up a workflow that sends old vs. new page copy to the AI for a concise summary of what changed.
Run a Local LLM
If corporate data policies forbid cloud-based AI, run an LLM offline using LM Studio or similar tools. This keeps your confidential data in-house.
Proof-of-Concept Interactive Elements
Some LLMs, like Claude, can code entire JavaScript widgets from a single prompt. This lets you quickly embed interactive elements on your site without waiting for developers.
Questions for Clients
An LLM can analyze a vague brief and produce a list of clarifying questions—helpful when projects are complex or scope is unclear.
Rewriting Emails for Different Audiences
Generate distinct email versions for a client, a developer, and an account manager. Each version matches their level of technical detail and communication style.
Predictive Churn Analysis
Combine past client churn data with SEOmonitor’s account health signals. The AI may pinpoint which clients are at risk—letting you intervene proactively.
AI Time Tracking
Hate manual timesheets? Snap screenshots whenever you switch tasks, then feed them to an LLM that logs your hours and descriptions automatically.
Newsletter Summaries
If you’re swamped with unread newsletters, forward them as attachments and let an LLM build a “super newsletter.” It identifies overlapping topics and important trends.
Internal Knowledge Base Creation
Turn Slack or email explanations into structured articles in Notion (or your chosen wiki). An LLM can rewrite them for clarity. Over time, you build a robust internal KB with minimal effort.
Maintaining Knowledge
When a key employee goes on leave (or leaves permanently), ingest their emails into a local LLM solution (like AnythingLLM). You can then query “What happened last time the client asked for a site migration?” without losing historical context.
By combining LLM-driven processes with SEOmonitor’s specialized features, you’ll cut down on the repetitive aspects of SEO and free up more time for creative, strategy-focused work.
