SEO and content tactics

1) Map the customer's awareness ladder (skip 'not aware'; cover aware of need -> aware of some solutions -> aware of specific solutions -> aware of benefits -> ready to buy). Use ChatGPT to list the questions a buyer asks at each step and how they phrase them. 2) Check monthly YouTube search volume per phrase with Keywords Everywhere (or VidIQ). 3) Prioritize by buying intent and search volume; start with 10-20 keywords. 4) Look at what ranks now: if nothing relevant, publish ASAP (even a bad video can rank #1); if there is a long rambling video, make a shorter, more useful one so YouTube gets better watch data. 5) Make a video for each step so every viewer can be led to the next one until they buy. Claims correct SEO gets a top 3-5 spot almost every time, even on a new channel. Same search approach is used on TikTok and Instagram.

Title: front-load the primary keyword, make it obvious the viewer is in the right place, but write it for a human (add words that raise relevance for the person). Description: the first two sentences show in search, so don't lead with just the app link; write a compelling description with several relevant keywords, then the app link. Tags: every way people phrase the target (e.g. 'unfollower app Instagram', 'Instagram unfollow app', 'Instagram unfollow app comparison'). Example title 'Best Instagram Unfollower Tracker Apps' with description 'Looking to find who unfollowed you on Instagram? These are the best apps to find unfollowers on Instagram in 2026.'

Uses Ahrefs to find very high-intent, low-competition keywords with ~300-800 monthly searches, close to the product (e.g. 'social media API', 'scheduling API for Twitter'). Writes in-depth guides that answer the searcher's intent (e.g. 'how to schedule Instagram posts automatically'). Keeps clean site structure, fast load, mobile optimization and proper metadata. Builds backlinks with tools and by manually reaching out to site owners and paying them. Tracks rankings in Ahrefs and Google Search Console and keeps optimizing click-through rate. Playbook version: list core keywords in a spreadsheet with volume and difficulty, aim to rank within 3-6 months; publish 10-15 high-quality pieces (blog posts, landing pages or free tools) in the first week, each with a big CTA to the signup page and internal links; don't publish too much low-quality content.

After a customer signs up, an onboarding email asks: 'Do you want any custom tutorial just meant for you?' Replies surface the exact long-tail problems and confusion customers have, which become tutorials.

Treats support as an education channel. When a customer asks for help, they reply 'Send us your file. We will record a custom tutorial or custom Loom video for you.' Sometimes they get on a call, walk through the customer's workflow and solve it live. All of it is recorded; the 1,500+ recordings from 3 years surface real problems and edge cases that never show up in keyword research, and they turn them into content.

Before publishing, runs a checklist to give each video an SEO angle so it ranks on Google, not just YouTube. A YouTube video targeting the same search intent can rank on Google without the authority and backlinks a blog post needs. Optimization: keyword in the title, in the description, and spoken in the first 30 seconds of the transcript.

Launched livebustimes.org (Sept 2025) giving away live bus/train times and route maps from the app's data. Hand-built plain HTML/CSS/JS (no frameworks) for speed and reliability, with invisible structured data on each page for search engines and chatbots. Submitted to Google Search Console and Bing (which ChatGPT search uses); a daily job regenerates the sitemap for millions of pages. Pages show ads for the app (seeing your bus on a map). Measured ChatGPT-User visits in Cloudflare's free analytics.

Posts are first-person stories from daily life as a SaaS marketer, with screenshots as proof, e.g. 'I paid 5 influencers on LinkedIn to promote my SaaS, here's what $1,250 got me' and a post about being rejected at the Y Combinator interview. Never put the SaaS directly in the post; trigger curiosity by highlighting it and let readers find it (SaaS linked in the profile bio). Change the angle every post; can redirect to a YouTube video or X post. Drafting: tells the story to ChatGPT by voice, then has it translate and correct it (non-native English), which captures more detail. Pre-launch founders can post about the problem they're solving and how it's going.

Buy Ahrefs ($129) for one month and use its 500 credits for a quarter's keyword research: filter keyword difficulty < 20 and search volume > 500, check what competitors rank for, and list keywords across 30-50 topics. Start with 2-3 posts a week, scaling to 6-7. Use AI as a research assistant to outline what already ranks, then add your own insights, user data and tone ('net-new information'). Run NeuronWriter pre-publish checks; track in Google Search Console.

Built almost 50 free tools, each related to the main product so its users are likely SiteGPT customers (e.g. PDF-to-markdown converter, chatbot name generator). Each tool has a CTA below it pitching the main product in context, e.g. for a chat-with-PDF tool: 'You have tried chatting with one PDF. What if you can create a chatbot with all of your business content? Try SiteGPT.' New tools are built in under five minutes by telling Cursor to look at the existing free tools and create a similar one for a given keyword.

1) In Ahrefs Keywords Explorer, search with the box left blank to get all keywords. 2) Add 'include' filters for your space and tool type (e.g. 'AI' + 'generator'; also try 'builder', 'creator'). 3) Keyword difficulty filter under 10 (e.g. 'AI image generator' is KD 87, too hard). 4) Volume filter of at least 1,000 monthly searches. Keep ones relevant to the product (e.g. 'AI reply generator'). 5) List keywords with global volume and KD in Notion. 6) Write the CTA each tool would carry to the main product. 7) Build a table: keyword, volume, KD, build effort, relevance to product; prioritize high volume, low KD, easy to build, highly relevant.

People google unknown numbers while the phone rings. Built a honeypot of 300,000+ company-owned phone lines (old 'dirty' numbers bought from Twilio and carriers) that record and transcribe robocalls, never recording consumer calls. Generated a landing page per phone number showing it is a scam, with the recording and transcription and a CTA ('block this and 7 million other robocallers') into a frictionless trial. The acquirer later planned to point paid traffic at the same pages.