Generative AI Revolutionizes Marketing: 37 Real-World Applications Revealed

Generative AI tools such as ChatGPT, Claude, and Letaido have seen significant advancements over the past year, transforming previously unautomatable aspects of marketing. This report details 37 practical AI applications in marketing, categorized by discipline, all derived from actual marketer experiences. These workflows can be implemented using Letaido, an AI marketing agent from Ahrefs. Ahrefs customers can try Letaido for free for one month.

SEO

SEO tasks, often tedious and complex, are prime candidates for AI assistance. However, it’s crucial to note that AI is not a substitute for expertise; it augments human judgment.

1. Google Quality Rater Page Grading: Dan Hinckley of Go Fish Digital has developed an AI agent that evaluates web pages against Google’s quality rater guidelines. By inputting a keyword and a page URL, the AI analyzes Google’s handbook, searches for the keyword, assesses search intent, reviews the target page, and provides a report on compliance, even recording a video of the process. This offers a quick assessment compared to manually reading and applying the 168-page handbook.

2. Accelerated Keyword Research: Ahrefs’ VP Marketing, Sam, utilized Letaido to automate keyword research. By providing a niche like "coffee," the AI generates a comprehensive plan, including seed keywords, search volume data, SERP analysis for intent and difficulty, and page type identification within top rankings. Keywords are then graded (Go, Maybe, Skip), clustered into topics, and accompanied by competitor gap analysis and a hub-and-spoke map.

3. Developer-Actionable Site Audits: Ahrefs has integrated its Site Audit tool with GitHub using generative AI. A weekly automated job pulls the latest audit data, prioritizes high-severity issues (like indexability problems and broken links), and creates pull requests for developers. These requests include a checklist and audit data, streamlining the fixing process.

4. AI-Generated FAQs Boost Traffic: Steven Macdonald’s controlled experiment showed a 32% average traffic increase on 21 existing posts after using ChatGPT to identify and answer reader questions, appending them as an FAQ section. Updated posts saw an average of 16,000 extra visits and 3,500 additional keyword rankings, while a control group declined.

   

5. Internal Linking Engine Development: An AI tool has been developed to suggest internal links for blog articles. It converts blog content into numerical representations (vector embeddings) to understand article topics. By comparing a given URL to all others, it identifies the closest thematic matches, aiding in the crucial SEO practice of internal linking to improve page discoverability, authority distribution, and contextual relevance. Ahrefs’ Site Audit also offers an "Internal link opportunities" report, identifying specific text passages for link insertion.

6. Automated Internal Link Insertion: John Iwuozor created a Python script that identifies relevant internal links and automatically inserts them into web pages. The script analyzes content to find the closest subject match and suggests sensible anchor text within the article’s paragraphs, automating the often time-consuming task of editing and linking.

7. Search Console Data to Prioritized Plan: Rudiger Dalchow developed a tool that analyzes Search Console exports to create actionable plans. By processing query and page data, it groups pages by topic, identifies search intent, flags competing internal pages, and generates briefs for writers. This process addresses structural SEO issues that are not apparent in standard traffic-sorted lists. Ahrefs’ Site Explorer’s "Opportunities" report offers similar functionality.

AI Search Optimization

Optimizing for AI search, such as with ChatGPT, presents a unique challenge. The following methods focus on understanding how AI models process content.

8. LLM Page Perception Analysis: Aimee Jurenka built a tool that captures raw HTML and rendered screenshots of a URL, then uses GPT to analyze how a language model perceives the page. It provides scores and feedback on content clarity, citation worthiness, and issues trapped by JavaScript.

9. Mapping Fan-Out Queries: Chris Long’s script assesses a website’s ability to answer the nuanced questions AI assistants pose. It breaks down user queries into narrower sub-questions, scores them against existing pages, and identifies content gaps.

10. Rewriting Pages Based on AI Queries: Wil Reynolds uses Bing’s free webmaster tools to identify which of his pages are cited in AI answers and the exact questions that led to those citations. He then rewrites the pages to directly address these queries, turning content optimization into a data-driven comparison rather than guesswork.

    

11. AI-Informed Page Template Design: Adina Timar rebuilt her listicle and comparison page templates based on AI citation data from various models. By analyzing which pages are quoted, how assistants structure answers, and which page sections are utilized, she creates templates informed by actual AI behavior, emphasizing the value of pages with genuine insights and competitive comparisons.

12. Content Prioritization from AI Citations: Ross Hudgens’ team identifies AI-driven content opportunities by tracking prompts leading to sales and analyzing which pages are most frequently cited. They prioritize topics that are both heavily cited by AI and have significant ordinary Google search volume, focusing on what is likely to be profitable.

Content Marketing

While AI-generated blog posts can be generic, AI excels at various individual steps in the content marketing process.

13. Accelerated Draft to Publishable Stage: An AI content process has been developed to bring an article to publication standard in approximately two hours, down from several days. This is achieved by breaking down the editorial process into small, manageable steps (topic selection, briefing, outlining, editing, drafting, product integration, line editing, internal linking, metadata, formatting) and guiding the AI through each stage with expert oversight.

14. AI-Assisted Web Page Development: Kelsey Libert learned to build landing pages using Cursor, a code editor with integrated AI. By describing page requirements in plain language, the AI generates code, enabling marketers without a development background to create and launch pages efficiently, bypassing traditional bottlenecks.

15. AI-Powered Data Study Creation: Mateusz from Ahrefs’ content team used AI to write code for pulling data from Ahrefs and Polygon APIs, combining datasets, running correlations, and generating charts for a study on organic traffic and stock prices. While AI handled the initial data processing, a human data scientist refined the analysis.

16. Eliminating AI’s Generic Tone: Myriam Jessier utilizes a "system prompt" called Absolute Mode to remove filler, hype, and conversational elements from ChatGPT’s output, resulting in more direct and concise responses. This streamlines editing by addressing stylistic issues at the instruction level.

    

17. Idea to Presentation Deck Generation: Wil Reynolds explains a concept, transcribes the explanation, and uses an LLM to create a story arc. Tools like NotebookLM and Gamma then generate deck variations from this structure, providing a rough framework for a presentation that can be further edited.

18. Managing a Large Content Refresh Backlog: An "Update Pipeline" tool has been developed to manage the refresh of approximately a thousand blog articles. It identifies stale statistics, outdated product descriptions, and missing content compared to current rankings. The tool presents changes side-by-side for review and approval, making content updates more manageable and aligning with AI assistants’ preference for fresher content.

19. Discovering Undiscovered Statistics: An AI tool searches PDFs, Word documents, and PowerPoint decks for statistics, providing approximately 30 results with publication year, source link, and file origin. This method uncovers statistics not readily available on web pages, offering unique data points for articles.

20. Querying Expert Quotes: Mateusz Makosiewicz uses NotebookLM to query a collection of expert quotes submitted for articles. By uploading PDFs of email notifications, he can ask questions of the entire set and receive answers with source references, avoiding the need to open each document individually.

    

21. Repurposing Webinars into Multiple Content Pieces: An AI workflow transforms webinar recordings into three blog outlines, a guide to key clips, and social media briefs, all filed in Notion. A subsequent step expands outlines into drafts, and another analyzes sales calls to extract customer pain points and objections into a tagged database, providing valuable content from existing resources.

Marketing Analytics

Reporting, a time-consuming task, is highly automatable with AI, though interpretation remains a human responsibility.

22. Automated Monthly Reporting: Letaido generates a monthly blog performance report on the 2nd of each month, pulling data from Google Search Console and Ahrefs Web Analytics. The report includes KPI tiles, trend charts, subfolder splits, winner/loser tables, anomaly callouts, and paginated post lists, along with draft analysis bullets for commentary.

    

23. Content On-Topic Verification: A semantic audit of the Ahrefs blog uses AI to convert articles into vector embeddings, creating a central "topic" representation for the entire blog. By measuring the distance of each article from this center, pages are categorized by their relevance, revealing that core-topic pages receive significantly more organic traffic.

24. Integrated Data Audits: An AI content audit assistant, documented by Chris Long, integrates crawl data, analytics, and Search Console numbers. This allows for the identification of pages losing traffic, those with drifted search intent, and pages that no longer align with the site’s overall theme. Letaido offers a streamlined version of this, with built-in connectors for Google Analytics and Search Console.

Social Media and Community

AI can assist with monitoring mentions and drafting social media content, but human judgment is essential for engagement.

25. Identifying Relevant Reddit Conversations: The team at lemlist used AI to sift through Reddit discussions, identifying relevant threads for engagement. This led to a 22% increase in traffic from Reddit, with higher sign-up rates and Google ranking for their threads. Human oversight was crucial in crafting genuine replies.

26. Extracting Customer Language: Britney Muller outlines a method to extract audience insights from community platforms using APIs and AI. This process identifies recurring complaints, questions, and comparisons, providing the authentic language customers use, which is invaluable for creating resonant marketing materials.

27. Generating Personalized Social Media Drafts: An AI social post generator creates five distinct drafts for each published article, tailored to the author’s voice. These drafts offer different angles (e.g., surprising fact, story, question, takeaways, counter-argument) to facilitate choice and editing before scheduling via Ahrefs’ Social Media Manager.

PR and Outreach

AI can monitor news and draft outreach messages, but timing and personalization remain critical human elements.

28. Real-Time PR Opportunity Monitoring: Mark Williams-Cook developed a Python script that uses a local LLM to scan thousands of daily news stories from RSS feeds, matching headlines and descriptions against client interest profiles. Qualified leads are sent to Slack for the digital PR team.

29. Five-Minute Follow-Up Emails: Andy Chadwick uses a ChatGPT workflow, trained on his tone and product details, to draft follow-up emails from sales call transcripts. This reduced composition time from 45 minutes to five minutes, resulting in a reported 90% close rate on high-ticket services.

30. AI-Powered Cold Outreach Campaigns: Sam Oh built an outreach campaign managed by AI agents that research prospects, analyze Ahrefs data, verify traffic growth, and draft emails. This process, controlled via Slack, resulted in seven booked meetings from 54 sent emails, demonstrating AI’s ability to handle the research-intensive aspect of outreach. Letaido offers similar functionality.

    

31. Automated Press Release Generation: An AI Press Release Generator creates formatted press releases from blog post URLs or product feature notes. This tool aims to consistently produce press releases for data studies, streamlining promotion and increasing media pick-up.

Product Marketing

AI can generate entire launch packages and reverse-engineer competitor campaigns, but human oversight is vital for consistency and accuracy.

32. Comprehensive Launch Package Generation: Andrei, head of product marketing at Ahrefs, created a GTM Generator that produces a launch package from a single product brief, including a refined brief, landing page, video script, promotional email, flyer, and a crucial final check. This final stage identifies discrepancies across all documents.

    

33. Competitor Paid Campaign Analysis for Ad Copy: Ahrefs’ Paid Ads Campaign Builder analyzes a competitor’s paid keywords and landing pages to generate relevant ad copy for similar campaigns. It identifies keyword themes and bidding gaps, providing three headlines and two descriptions per ad variation within character limits.

34. Webinar Setup Automation: Constance, who manages Ahrefs’ webinars, uses an AI automation app that sets up entire webinars based on a title, date, and speaker. It creates tasks in Linear for Zoom event setup, landing pages, promotional copy, slide creation, and post-webinar reporting, ensuring all necessary steps are completed in the correct order.

International Marketing

AI can translate content and localize visuals, but cultural nuance and accuracy require human review.

35. Link-Preserving Blog Post Translation: A translation pipeline handles seven languages, incorporating tone guides, glossaries, and translation rules. Crucially, it checks and swaps internal links to point to the correct localized versions of other articles, and performs keyword research specific to each target country.

36. Localized Chart and Diagram Translation: A dedicated translator for visuals processes images (PNG, JPG, PDF) and localizes them based on language and region, adjusting prices, web addresses, and names. Users can correct translated terms, with the AI redrawing the image accordingly.

37. Live Subtitle Generation for Conferences: A "Live Interpreter" tool runs on a laptop, generating live English and Japanese subtitles from microphone feeds at conferences. It waits for complete sentences and utilizes a glossary of product names for accurate translation, using Gemini 3 Flash for speed.

Final Thoughts

Generative AI is a powerful tool that augments, rather than replaces, marketing expertise. The effectiveness of these AI applications relies heavily on the marketer’s existing knowledge, judgment, and taste. By leveraging AI for efficiency and scale, marketers can enhance their work, making it faster, better, and more enjoyable. Skepticism is advised, as AI is not a standalone solution but a multiplier of human capability.