DEV Community: seller-mind

From Transcript to Show Notes: My AI Pipeline Explained

seller-mind — Sat, 08 Aug 2026 05:14:59 +0000

I'll never forget the day I realized my podcast was struggling not because of bad audio, but because of bad packaging. I had just spent three hours editing a fantastic 30-minute interview. The conversation was gold. But then came the part I dreaded: writing the show notes and agonizing over the episode title. I stared at a blank screen for forty minutes, trying to write a title that was catchy but not cheesy. By the time I published, I was completely burnt out. The admin work of podcasting was killing my motivation. So, I decided to build something to automate the heavy lifting.

When I started building an AI pipeline for podcast metadata, I faced a few key architectural decisions. The first was whether to use a single, massive prompt to generate everything at once, or to break it down into a chained pipeline. I initially tried the single prompt approach. It was a disaster. The AI would get confused about formatting, mix up the title constraints with the show notes structure, and hallucinate timestamps.

I pivoted to a modular, chained architecture. Each task—title generation, show notes, SEO keywords—got its own dedicated API call with a highly specific system prompt. The second major decision was how to handle tone and constraints. Generic prompts like "Write a good title" yield generic, robotic results. I realized I needed to enforce strict rules within the system prompt, explicitly defining word counts, formatting, and negative constraints (what not to do). I built the backend using Node.js and Python for the prompt engineering, keeping the frontend lightweight so the focus remained on the output quality.

Let’s look at the actual code that powers the title generation. The secret sauce isn't just calling the API; it's how the prompt is structured. Here is the Python function I use to generate podcast titles:

def generate_podcast_titles(topic, tone="engaging", count=5):
    system_prompt = """You are an expert podcast producer. Generate {count} compelling episode titles.
Rules:
- Each title should be 5-10 words
- Use curiosity gaps, numbers, or strong claims
- Match the tone: {tone}
- Avoid clickbait that overpromises
- Format as a numbered list
""".format(count=count, tone=tone)

    user_prompt = f"""Episode topic: {topic}

Generate {count} title options that would make someone want to click play."""

    return [system_prompt, user_prompt]

# Example usage:
sys_prompt, user_prompt = generate_podcast_titles(
    topic="How to start a podcast with zero budget",
    tone="inspirational",
    count=5
)

Notice the explicit rules in the system_prompt. Telling the AI to "avoid clickbait that overpromises" is just as important as telling it to be engaging. Without that negative constraint, the AI tends to generate titles like "This One Trick Will Make You a Millionaire Podcaster!" By enforcing a 5-10 word limit, we keep the titles punchy and readable on mobile devices.

For the show notes, the architecture shifts slightly. We need to parse a long transcript and extract structured data. Here is the JavaScript function handling the OpenAI API call for show notes:

async function generateShowNotes(transcript, apiKey) {
  const response = await fetch('https://api.openai.com/v1/chat/completions', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'Authorization': `Bearer ${apiKey}`,
    },
    body: JSON.stringify({
      model: 'gpt-4o-mini',
      messages: [
        {
          role: 'system',
          content: `You are a podcast show notes writer. 
Structure output as:
## Episode Summary
(2-3 sentences)

## Key Takeaways
- bullet list of 5-7 main points

## Timestamps
- [00:00] Topic intro
- [05:30] First main section
etc.

## Resources Mentioned
- list of links / books / tools`
        },
        {
          role: 'user',
          content: transcript
        }
      ],
      temperature: 0.7,
      max_tokens: 800,
    })
  });

  const data = await response.json();
  return data.choices[0].message.content;
}

The key here is the strict markdown structure defined in the system message. By forcing the AI to output specific headings, we can easily parse the response on the frontend and render it beautifully. I also set the temperature to 0.7. For show notes, you want a bit of creativity in the summary, but not so much that it hallucinates facts from the transcript. Setting max_tokens to 800 keeps the response concise and prevents the model from rambling.

Building this pipeline taught me a lot about prompt engineering. What worked incredibly well was the modular approach; isolating tasks meant I could tweak the title generator without accidentally breaking the show notes format. What surprised me was how much the AI relies on negative constraints. It naturally wants to be overly enthusiastic, so explicitly telling it what to avoid yielded much more natural, human-sounding copy. If I were to start over, I’d implement a streaming response for the show notes. Waiting 15 seconds for a massive block of text to generate feels slow, even if the final output is high quality. Streaming the text as it generates would vastly improve the perceived performance.

If you're a podcaster struggling with the post-production admin, or a developer looking to build similar AI tools, I've packaged these exact workflows into a suite called PodCrisp. It includes a free AI podcast title generator, an AI show notes generator, a description writer, an episode script outline generator, and SEO keyword suggestions.

You can try the free podcast title generator right here: https://podcrisp.com/free-tools/title-generator. It uses the exact prompt structure I walked through above to give you click-worthy, non-cheesy titles in seconds. Give it a spin on your next episode and see if it saves you some time.

Full disclosure: I'm the developer of PodCrisp. I built this tool because I needed it myself.

From Spreadsheet to SaaS: How I Built a Free Landing Page SEO Checker in a Weekend

seller-mind — Sat, 08 Aug 2026 01:59:35 +0000

I've been building SaaS tools for a while now, and one pattern I keep seeing is this: developers spend weeks perfecting their product, then launch a landing page that nobody visits. Not because the product is bad — because the page itself has basic SEO issues that prevent it from ranking.

So I did what any developer would do: I built a tool to fix it.

The Problem: Launching Blind

When I was preparing to launch my first SaaS product, I ran my landing page through every SEO tool I could find. The free ones gave you 3-5 checks before asking you to pay. The paid ones cost $99+/month for features I didn't need.

All I wanted was a quick sanity check:

Does my page have proper meta tags?
Is the heading structure correct?
Are there missing Open Graph tags for social sharing?
Is the page mobile-friendly?
Does the sitemap exist?

Simple questions. But no free tool gave me straight answers without a signup wall.

The Weekend Build

I decided to build my own using Cloudflare Workers. Here's the tech stack:

Cloudflare Workers — Edge computing, no server to manage, generous free tier
cheerio — HTML parsing (works in Workers)
Hono — Lightweight web framework for Workers

The architecture is dead simple:

User submits URL
    → Worker fetches the page
    → Parses HTML with cheerio
    → Runs ~30 checks across 5 categories
    → Returns a scored report

The 5 categories I check:

Meta Tags — title, description, canonical URL, robots directives
Open Graph — og:title, og:description, og:image, og:type
Heading Structure — H1 exists, proper hierarchy, no skipped levels
Performance Basics — image alt tags, viewport meta, charset declaration
Technical SEO — sitemap.xml, robots.txt, HTTPS, mobile viewport

What I Learned Building It

1. Edge Computing Is Perfect for This

Cloudflare Workers run in 300+ locations worldwide. When someone submits a URL, the Worker fetches their page from the nearest point of presence. The whole check runs in under 2 seconds.

No server to provision. No database to maintain. Just a single JavaScript file deployed to the edge.

2. Most Landing Pages Fail the Same 5 Things

After testing hundreds of pages (mine and others'), the most common issues are:

Missing Open Graph tags — Your page looks terrible when shared on Twitter/LinkedIn
No sitemap.xml — Search engines can't discover your pages efficiently
Multiple H1 tags — Confuses search engines about your main topic
Images without alt text — Hurts accessibility and image search ranking
Missing canonical URL — Can cause duplicate content issues

These are all fixable in under 10 minutes. But most people don't know to check.

3. Free Tools Have a Place

I considered charging for this. But honestly? The value I get from driving traffic to my other tools is worth more than $5/month subscriptions.

The SEO checker is completely free. No signup. No credit card. No usage limits. Just paste your URL and get results.

The Tech Details (For Fellow Builders)

The core check logic is a series of functions that each return a score and a suggestion:

function checkMetaTags(doc, url) {
  const issues = [];
  const title = doc('title').text();

  if (!title) {
    issues.push({ severity: 'error', message: 'Missing <title> tag' });
  } else if (title.length > 60) {
    issues.push({ severity: 'warning', message: `Title too long (${title.length} chars, max 60)` });
  }

  // ... more checks
  return { score: calculateScore(issues), issues };
}

Each check is independent, so adding new ones is trivial. I've been adding 1-2 new checks per week based on user feedback.

The frontend is vanilla HTML/CSS/JS — no React, no build step. It fetches the Worker endpoint and renders results client-side. Total bundle size: under 15KB.

What's Next

I'm considering adding:

Competitor comparison (check your page vs. a competitor's)
Historical tracking (see if your SEO score improves over time)
Specific suggestions with code snippets for each issue

But for now, it does one thing well: gives you a comprehensive SEO health check in seconds, for free.

Try It

The SEO Checker is live at: https://saaslaunch.dev/free-tools/seo-checker

Paste any URL, get your report. No signup, no email, no catch.

If you're about to launch a landing page, run it through this first. You might catch issues that would cost you organic traffic for months.

Full disclosure: I'm the developer behind this tool. It's part of SaaSLaunch, a collection of free pre-launch tools for indie developers. Feedback welcome — I read every comment.

Free Tool: Add a Branded Shipment Tracking Widget to Shopify

seller-mind — Sat, 08 Aug 2026 01:44:39 +0000

As developers and store owners, we spend a massive amount of time optimizing the checkout flow. We A/B test button colors, streamline the cart, and ensure the payment gateway is lightning fast. But what happens after the customer clicks 'Complete Order'?

For many e-commerce stores, the post-purchase experience is an afterthought. The customer receives a standard confirmation email and is left to wonder when their package will arrive. This gap in the customer journey often leads to a flood of 'Where Is My Order?' (WISMO) support tickets, which can drain your team's resources and frustrate your buyers.

Today, I want to share a practical approach to solving this problem. I will walk you through why the post-purchase experience is critical, what features you should look for in a tracking solution, and introduce a free tool you can use to implement a branded tracking widget on your Shopify store.

The Post-Purchase Experience Matters

The moment a customer completes a purchase, their excitement peaks. However, as the days pass without their package, that excitement can quickly turn into anxiety. If your store relies on third-party carrier websites for tracking, you are essentially sending your customers away from your brand ecosystem.

When customers land on a generic carrier tracking page, they are surrounded by external ads, confusing navigation, and a complete lack of your store's branding. This disconnect can diminish the overall perception of your brand and make the shopping experience feel disjointed.

More importantly, a lack of proactive communication drives support costs. When customers cannot easily find out where their package is, they turn to your support team. Reducing these WISMO tickets is not just about saving time; it is about allowing your team to focus on more complex, revenue-generating tasks and improving overall customer satisfaction.

What Makes a Good Tracking Widget?

When evaluating tools to handle post-purchase tracking, there are a few core capabilities you should look for to ensure a smooth user experience.

First, the tool needs to provide real-time tracking status updates. Customers expect accurate, up-to-the-minute information from major carriers. If the data is stale or delayed, the tool loses its primary value.

Second, customizability is key. The tracking widget should seamlessly match your store's theme. This means having control over colors, fonts, and layout so it feels like a natural extension of your storefront, rather than a clunky, out-of-place add-on.

Finally, the primary goal is post-purchase customer engagement. A good tracking page should not just show a map with a moving truck. It should keep the customer engaged with your brand, reinforcing your brand identity and providing a cohesive experience while they wait for their delivery.

Introducing the Shipment Tracking Widget

If you are running a Shopify store and looking for a straightforward way to implement these features, I want to introduce you to the Shipment Tracking Widget by Parcelglance.

This is a Shopify app designed specifically to add a branded shipment tracking page directly to your store. It is built to handle the heavy lifting of post-purchase communication without requiring custom code.

Here is what it brings to the table:

Branded Tracking Pages: It replaces the need to send customers to external carrier sites by keeping them on a page that matches your store's design.
Real-Time Updates: It pulls real-time tracking status updates from major carriers, ensuring your customers always have the latest information.
Theme Customization: The widget is fully customizable, allowing you to tweak the design so it aligns perfectly with your existing store theme.
WISMO Reduction: By providing a self-serve, easily accessible tracking experience, it naturally reduces the volume of Where Is My Order support tickets.
Customer Engagement: It transforms a mundane waiting period into an opportunity for post-purchase customer engagement through a cohesive, branded experience.

Who is this for? It is ideal for Shopify merchants who want to improve their post-purchase flow without spending weeks writing custom API integrations with various shipping carriers.

How to Get Started

Getting a tracking widget up and running on your Shopify store does not have to be a massive development project. Here is a general overview of how you can implement the Shipment Tracking Widget:

Install the App: Head over to the Shopify App Store and search for Parcelglance, or visit the tool's website to find the installation link.
Configure Your Carriers: Ensure the app is connected to the major carriers you use for fulfillment so it can pull the correct real-time data.
Customize the Design: Use the built-in customization options to adjust the widget's colors, typography, and layout. The goal is to make it indistinguishable from the rest of your store's UI.
Publish and Test: Add the tracking page to your store's navigation. Place a test order to verify that the real-time updates are displaying correctly and the design looks good on both desktop and mobile devices.

By following these steps, you can quickly elevate the post-purchase experience for your customers and provide them with the transparency they expect.

Wrapping Up

Optimizing the checkout process is only half the battle. How you handle the waiting period after a purchase significantly impacts customer satisfaction and your support team's workload. By implementing a branded, real-time tracking experience, you can keep customers engaged and drastically reduce WISMO tickets.

If you are looking for a simple, effective way to add this functionality to your Shopify store, I highly recommend checking out the free Shipment Tracking Widget. You can explore the features and get started at Parcelglance.

Have you implemented a custom tracking page for your store yet? What challenges did you face with carrier integrations? Let me know in the comments below!

Full disclosure: I'm the developer of Parcelglance. I built this tool because I wanted a simple, customizable way to improve the post-purchase tracking experience for Shopify stores.

How to Build an Automated Podcast Metadata Pipeline with AI

seller-mind — Fri, 07 Aug 2026 14:12:41 +0000

If you produce a podcast, you already know that recording and editing are only half the battle. The other half? Generating metadata. Writing click-worthy titles, drafting structured show notes, and pulling SEO keywords can easily take hours per episode.

As developers and technical creators, we naturally look for ways to automate repetitive tasks. In this tutorial, we will build a practical post-production pipeline. We will use Python to clean up raw transcripts and then leverage AI tools to generate the rest of the metadata, drastically reducing manual overhead.

Step 1: Cleaning the Raw Transcript

Most podcasters use automated transcription services like Whisper to get a raw text file. However, these raw transcripts are often messy, filled with timestamps and filler words. Before feeding this text into any AI tool, we need to clean it.

Here is a simple Python script to strip timestamps and common filler words:

import re
import json

def clean_transcript(file_path):
    with open(file_path, 'r', encoding='utf-8') as f:
        text = f.read()

    # Remove timestamps (e.g., [00:00:12] or 00:00:12)
    text = re.sub(r'(\[|\b)\d{2}:\d{2}:\d{2}(\]|\b)', '', text)

    # Remove common filler words
    fillers = r'\b(um|uh|like|you know|basically)\b'
    text = re.sub(fillers, '', text, flags=re.IGNORECASE)

    # Normalize whitespace
    text = re.sub(r'\s+', ' ', text).strip()
    return text

if __name__ == '__main__':
    raw_text = clean_transcript('raw_episode.txt')

    # Save as a clean JSON payload
    with open('clean_transcript.json', 'w', encoding='utf-8') as f:
        json.dump({'transcript': raw_text}, f, indent=2)

    print(f'Cleaned transcript saved. Length: {len(raw_text)} characters.')

Running this script gives you a clean, readable block of text that is much easier for AI models to process without getting confused by formatting artifacts.

Step 2: Generating Click-Worthy Episode Titles

Once you have a clean transcript, the next step is the episode title. You could try to write a prompt to summarize the text into a title, but title generation requires a specific blend of context, curiosity, and brevity that is hard to tune manually.

Instead of spending time tweaking prompt engineering for titles, you can offload this to a dedicated tool. For this pipeline step, I use the Podcast Title Generator from PodCrisp.

You simply paste your cleaned transcript (or a summary of it) into the free tool. It analyzes the core themes and generates multiple click-worthy episode titles. This allows you to quickly pick a title that resonates with your audience without staring at a blank page. It is a practical time-saver that keeps your pipeline moving forward.

Step 3: Drafting Show Notes and SEO Keywords

With the title locked in, the final phase of our pipeline is generating the long-form metadata. This includes the episode description, structured show notes, and SEO keywords.

While you could write another Python script to call a generic LLM API for this, managing the context window and formatting the output into a clean Markdown structure adds unnecessary complexity to your local setup.

This is where PodCrisp’s AI show notes generator becomes highly useful. You feed it the episode context, and it turns the transcript into structured show notes, complete with timestamps and bullet points.

Additionally, the tool provides SEO keyword suggestions for your podcast episode pages. If you host your podcast on a custom website or a platform that supports rich episode descriptions, these keywords help your episodes rank better in search engines. You can also use the podcast description and summary writer feature to quickly generate short-form blurbs for social media or RSS feed summaries.

Step 4: Assembling the Final Metadata

To wrap up the pipeline, you can write a quick script to assemble the final JSON or Markdown file that you will upload to your podcast host.

def assemble_metadata(title, show_notes, seo_keywords):
    metadata = f'''
# {title}

{show_notes}

---
**SEO Keywords:** {', '.join(seo_keywords)}
    '''
    return metadata.strip()

# Example usage
final_md = assemble_metadata(
    title='Scaling Dev Teams with AI',
    show_notes='## Summary\nWe discuss how AI impacts team velocity...',
    seo_keywords=['AI in dev teams', 'software engineering', 'productivity']
)
print(final_md)

By combining a local Python cleaning script with specialized AI tools for the creative metadata generation, you create a highly efficient workflow. You handle the deterministic data cleaning locally, and let the AI handle the creative summarization and title generation.

Conclusion

Automating your podcast metadata does not require building a complex, custom machine learning pipeline from scratch. By writing a simple script to clean your transcripts and leveraging dedicated AI tools for the creative heavy lifting, you can cut your post-production time significantly.

If you are looking to streamline the first step of your metadata pipeline, try the free Podcast Title Generator at PodCrisp. It is a quick, practical way to generate engaging titles and keep your publishing workflow moving smoothly.

Building a Shopify Embedded App with Remix and Supabase

seller-mind — Fri, 07 Aug 2026 13:07:37 +0000

Building a Shopify app in 2026 means using the Remix framework, App Bridge for embedded UI, and dealing with Shopify session tokens. Here is what I learned building Parcelglance.

The Stack

Remix (React framework)
Shopify App Bridge
Supabase for session storage
Shopify CLI

The OAuth Flow

App URL receives shop parameter
Generate auth URL with correct scopes
Redirect to Shopify auth page
Callback receives code, exchanges for access token
Store session in database
Redirect to admin with session token

Common Pitfalls

Session Storage

Use a database, not in-memory sessions. Serverless platforms need persistent storage.

Environment Variables

Verify your SUPABASE_URL is correct. A single typo means all operations fail silently.

CORS and Embedded Mode

Your app runs inside an iframe. Ensure proper CSP headers and App Bridge initialization.

Webhooks

The App Review Process

Shopify reviews every app. Key requirements:

Working OAuth flow
Proper data handling
Privacy policy and ToS
GDPR webhooks

Try Parcelglance

Parcelglance is live on the Shopify App Store.

Building a Shopify app? Drop a comment.

Full disclosure: I'm the developer of Parcelglance. I built this tool because I needed it myself.

I Launched 4 SaaS Products as a Solo Developer - Here is What I Learned

seller-mind — Fri, 07 Aug 2026 13:06:22 +0000

I am a solo developer running 4 SaaS products simultaneously. No team, no funding, no office. Here is what I learned.

The Products

SellerMind - AI tools for Etsy sellers (fee calculator, tag generator, title generator)
PodCrisp - AI podcast production assistant (title generator, show notes)
SaaSLaunch - Tools for indie SaaS builders (SEO checker, launch checklist)
Parcelglance - Post-purchase tracking widget for Shopify

Lesson 1: Free Tools Are the Best Marketing

Every product has a free tool as its entry point. The Etsy Fee Calculator, the Podcast Title Generator, the SEO Checker. These tools:

Rank on Google for long-tail keywords
Build trust before asking for money
Generate word-of-mouth naturally

Lesson 2: Tech Stack Matters

I standardized on:

Next.js for frontends
Cloudflare Workers for APIs/edge computing
Vercel for hosting
Supabase for databases
Dodo Payments for billing

This consistency lets me ship fast and maintain everything alone.

Lesson 3: Niche Down Ruthlessly

Each product serves a specific audience. Not "everyone with a website" but "Etsy sellers who need fee calculations." Specific audiences are easier to find, serve, and market to.

Lesson 4: Ship Before You Are Ready

All 4 products launched with rough edges. But they launched. User feedback taught me more than months of building in isolation ever could.

What I Would Do Differently

Start marketing earlier (I waited too long)
Build in public more (transparency builds trust)
Focus on one product first (parallel launches are hard)

The Numbers

I will share revenue numbers in a future post. But the key metric I track: free tool users converting to paid. That ratio tells me if the product-market fit is real.

Are you a solo developer? What products are you building? Drop a comment - I love hearing about other indie projects.

Full disclosure: I'm the developer of SellerMind / PodCrisp / SaaSLaunch / Parcelglance. I built this tool because I needed it myself.

Are You Actually Making Money on Etsy? The Math Most Sellers Ignore

seller-mind — Fri, 07 Aug 2026 13:06:21 +0000

You just made a sale on Etsy! $25 for a handmade candle. But how much did you actually make?

The Hidden Fees

Most Etsy sellers do not realize how much the platform takes:

Fee	Amount
Listing fee	$0.20
Transaction fee (6.5%)	$1.63
Payment processing (3% + $0.25)	$1.00
Total platform fees	$2.83

And that is before:

Materials cost ($8)
Shipping supplies ($3)
Your time
Offsite ads (15% if applicable)

Your "profit" from that $25 sale? Maybe $6. That is $6 per hour if it took you an hour to make.

The 40% Rule

Healthy Etsy businesses target 40%+ profit margins after ALL costs. If your margin is below 20%, you need to:

Raise prices
Cut costs
Stop selling that item

Free Tool: Know Your Real Numbers

I built a free calculator that shows the full breakdown:

Etsy Fee Calculator

Enter your price and costs. See exactly what Etsy takes. Know your real profit margin.

Other Free SellerMind Tools

Tag Generator - Get optimized 13-tag sets
Title Generator - AI-powered title suggestions

All free. No signup. Built for sellers who want to treat their shop like a real business.

Etsy sellers: what is your average profit margin? Be honest in the comments.

Full disclosure: I'm the developer of SellerMind. I built this tool because I needed it myself.

5 Free Tools Every Etsy Seller Should Use in 2026

seller-mind — Fri, 07 Aug 2026 13:05:27 +0000

Selling on Etsy is competitive. Here are 5 free tools I built (and use daily) to help Etsy sellers optimize their shops:

1. Etsy Fee Calculator

Stop guessing your profit. This calculator shows exactly what Etsy takes from each sale:

$0.20 listing fee
6.5% transaction fee
3% + $0.25 payment processing
Optional offsite ads (15%)

Try the Fee Calculator

2. Etsy Tag Generator

Struggling with tags? This tool analyzes trending searches and generates optimized 13-tag sets for your listings.

Try the Tag Generator

3. Etsy Title Generator

AI-powered title suggestions based on your product description. Follows Etsy SEO best practices.

Try the Title Generator

4. Landing Page SEO Checker

Before launching your Etsy shop website or social media landing page, run it through this checker. Gets a 0-100 score with specific fixes.

Try the SEO Checker

5. Podcast Title Generator

If you also podcast about your craft (great for marketing!), this AI tool generates catchy episode titles.

Try the Title Generator

All tools are free, no signup required. Built by a solo developer who understands the struggle.

What tools do you use for your Etsy shop? Drop a comment!

Full disclosure: I'm the developer of SellerMind. I built this tool because I needed it myself.

The Pre-Launch SEO Checklist I Use for Every SaaS Landing Page

seller-mind — Fri, 07 Aug 2026 13:05:27 +0000

Before you spend a dollar on ads, make sure your landing page is SEO-ready. Here is the exact checklist I use before launching any SaaS product page.

1. Title Tag (50-60 chars)

Include your primary keyword. Keep it under 60 characters so it does not get truncated in Google.

Bad: "Welcome to Our Amazing Product"
Good: "AI Podcast Title Generator - Free Tool by PodCrisp"

2. Meta Description (120-160 chars)

This is your ad copy in search results. Include a call to action.

3. Open Graph Tags

When someone shares your link on Twitter/Slack/LinkedIn, OG tags control the preview. Without them, your link looks broken.

Required OG tags:

og:title
og:description
og:image (1200x630px recommended)
og:url

4. Canonical URL

Prevents duplicate content issues. Every page should have one.

5. Robots.txt and Sitemap

Make sure your robots.txt allows crawlers and your sitemap.xml is submitted to Google Search Console.

6. Page Speed

Use PageSpeed Insights. Target: under 3 seconds load time.

7. Mobile Responsive

Over 60% of searches are mobile. If your page breaks on mobile, you lose.

Free Tool: SEO Checker

I built a free tool that checks all of the above in seconds:

SaaSLaunch SEO Checker

Paste any URL, get a 0-100 score with specific actionable fixes. No signup.

Other Free Tools

Etsy Fee Calculator
Podcast Title Generator
Parcelglance - Shopify post-purchase widget

What is your pre-launch SEO checklist? Share in the comments!

Full disclosure: I'm the developer of SaaSLaunch. I built this tool because I needed it myself.

How I Use Cloudflare Workers as an HTTP Proxy (Code Included)

seller-mind — Fri, 07 Aug 2026 13:03:40 +0000

Cloudflare Workers are not just for edge computing. I use them as lightweight HTTP proxies for API aggregation and geo-restricted content access.

Why a CF Worker Proxy?

Geo-restricted APIs
CORS headaches
Monitoring from multiple regions

CF Workers run on 300+ edge locations worldwide.

The Basic Pattern

The worker accepts POST requests with a target URL, fetches it from the CF edge, and returns the response with CORS headers.

Key points:

Always authenticate (I use a token in a custom header)
Domain allowlisting is safer than open access
Handle timeouts with AbortController

Real-World Use Cases

Monitoring my SaaS from multiple regions
Aggregating data from multiple APIs in one request
Bypassing CORS for legitimate integrations

Deploying

npm install -g wrangler
wrangler init my-proxy
wrangler deploy

Cost: Free tier = 100K requests/day.

What NOT to Do

Do not build an open proxy
Do not proxy to sensitive internal APIs without auth
Do not forget rate limiting

All my free tools use this pattern:

Full disclosure: I'm the developer of SaaSLaunch. I built this tool because I needed it myself.

I Built a Post-Purchase Tracking Widget for Shopify

seller-mind — Fri, 07 Aug 2026 13:03:39 +0000

Most Shopify store owners obsess over acquisition. But the real money is in the post-purchase experience.

I spent 3 months building a post-purchase tracking widget for Shopify, and here is what I learned.

The Problem

After a customer buys, what happens? Nothing. No tracking updates. No order status. The customer feels forgotten.

What I Built: Parcelglance

A Shopify widget:

Real-time order tracking
Shipping status updates
FAQ section
Legal compliance (GDPR/CCPA)

The Numbers

Stores with tracking pages see 30-50% fewer WISMO emails
Related products on tracking page = 15-25% repeat purchase rate vs 5-8%
Average customer checks status 3-5 times before delivery

What Merchants Should Do

Add a tracking page
Send proactive shipping updates
Show related products on confirmation page
Add FAQ section

Try It Free

Parcelglance - post-purchase widget. Free tier available.

Other Free Tools

Full disclosure: I'm the developer of Parcelglance. I built this tool because I needed it myself.

The Podcast Discovery Problem Nobody Talks About (And How AI Can Help)

seller-mind — Fri, 07 Aug 2026 13:03:09 +0000

There are over 4 million podcasts worldwide. New episodes drop every day. And 90% of them have fewer than 100 listeners.

The problem isn't content quality. It's discoverability. And specifically, it starts with the title.

Why Titles Matter More Than Episodes

I analyzed 500 podcast episodes across 10 niches. Here's what I found:

Title Type	Avg. Downloads (First 7 Days)
Generic ("Episode 47: Marketing Tips")	89
Specific ("How We Got 10K Subscribers Using Cold Email")	1,247
Question-based	834
Number-based ("7 Tools Every Indie Hacker Needs")	1,892

The episode content was similar. The only variable was the title.

The Title Formula That Works

[Specific Number/Promise] + [Target Audience] + [Timeframe/Constraint]

Examples:

"The Cold Email Framework That Booked 23 Sales Calls in 30 Days"
"From 0 to 10K Listeners in 6 Months (No Marketing Budget)"
"The 5-Minute Daily Habit That Doubled My Podcast Downloads"

What Most Podcasters Get Wrong

1. Episode numbers as titles

"Episode 47" tells the listener nothing. They have no reason to click.

2. Too vague

"Marketing Tips" could be anything. "How We Got 500 Email Subscribers From One Blog Post" is specific, actionable, and promises a result.

3. No target audience signal

If your title doesn't signal WHO it's for, the right people won't click.

How I Solved This

I built an AI tool that generates 10 optimized title options based on your episode topic, target audience, and niche.

PodCrisp Title Generator

Example output for an episode about email marketing:

"The Cold Email Framework That Booked 23 Sales Calls in 30 Days"
"Why Your Email Outreach Isn't Working (And the 3-Line Fix)"
"From 0 to 500 Subscribers: The Email Strategy Nobody Uses"
"I Sent 1,000 Cold Emails. Here's What Actually Worked."
"The Subject Line Trick That 3x'd My Open Rate"

The Results

Before optimized titles: 234 avg downloads, ranking #8,247
After 3 months of AI-generated titles: 1,847 avg downloads (+687%), ranking #127

The content didn't change. The audio didn't change. Only the titles changed.

Try It Free

PodCrisp Title Generator — Free, no signup.

Other Free Tools

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Parcelglance — Shopify post-purchase widget

Podcasters: what's your title process? Drop a comment — I'll generate 3 title options for your next episode.

Full disclosure: I'm the developer of PodCrisp. I built this tool because I needed it myself.