<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Jay Park Lead Notes]]></title><description><![CDATA[Jay Park Lead Notes]]></description><link>https://jaypark-leads.hashnode.dev</link><generator>RSS for Node</generator><lastBuildDate>Wed, 04 Nov 2026 04:56:30 GMT</lastBuildDate><atom:link href="https://jaypark-leads.hashnode.dev/rss.xml" rel="self" type="application/rss+xml"/><language><![CDATA[en]]></language><ttl>60</ttl><item><title><![CDATA[A five-column lead sheet for local outreach]]></title><description><![CDATA[Most local outreach sheets have too many columns. I keep five: business name, website, email, category and review count. I fill them by running a Google…]]></description><link>https://jaypark-leads.hashnode.dev/a-five-column-lead-sheet-for-local-outreach</link><guid isPermaLink="true">https://jaypark-leads.hashnode.dev/a-five-column-lead-sheet-for-local-outreach</guid><category><![CDATA[sales]]></category><category><![CDATA[Productivity]]></category><dc:creator><![CDATA[Jay Park]]></dc:creator><pubDate>Sun, 25 Oct 2026 05:13:44 GMT</pubDate><content:encoded><![CDATA[<p>Most local outreach sheets have too many columns. I keep five: business name, website, email, category and review count. I fill them by running a Google Maps search for a niche plus a city and exporting with <a href="https://www.gmapsemailextractor.com/">gmapsemailextractor.com</a>, which de-duplicates results and exports CSV or Excel. Review count is my priority signal; category lets me write one relevant opening line per segment. Everything else can wait until someone replies.</p>
]]></content:encoded></item><item><title><![CDATA[A practical filter stack before you bulk-download from Chrome tabs]]></title><description><![CDATA[When I need images, PDFs, and other files off a pile of research tabs, clicking each link is slow. Opening every tab, choosing Save as, and renaming files…]]></description><link>https://jaypark-leads.hashnode.dev/a-practical-filter-stack-before-you-bulk-download-from-chrome-tabs</link><guid isPermaLink="true">https://jaypark-leads.hashnode.dev/a-practical-filter-stack-before-you-bulk-download-from-chrome-tabs</guid><category><![CDATA[Productivity]]></category><category><![CDATA[extensions]]></category><category><![CDATA[Downloading]]></category><category><![CDATA[chrome extension]]></category><dc:creator><![CDATA[Jay Park]]></dc:creator><pubDate>Sun, 25 Oct 2026 03:32:36 GMT</pubDate><content:encoded><![CDATA[<p>When I need images, PDFs, and other files off a pile of research tabs, clicking each link is slow. Opening every tab, choosing Save as, and renaming files by hand eats the time I wanted for the actual reading. I use a short filter stack first: file type, extension, URL pattern, then link text. That order keeps the candidate list small before anything is downloaded.</p>
<p><a href="https://www.simplemassdownloader.com/pricing">Simple Mass Downloader</a> is a Chrome extension that scans the current page, open tabs, or a pasted URL list, applies those filters, lets me preview images, and then saves separate files, one ZIP, or a chosen folder. I start with the file type so PDFs and images do not mix, then tighten the list with an extension or a URL pattern when a site uses predictable paths. Link text is the last pass, useful when the same page mixes real downloads with ordinary navigation.</p>
<p>Failed downloads retry up to three times with completion checks, so a dropped connection does not leave a half-saved file I have to hunt for later. The free plan gives 300 download credits with no account, which is enough to test the stack on a real research session. It does not bypass DRM, logins, or paywalls. If a file sits behind a login, I still open that page myself and only queue what the browser can already see.</p>
]]></content:encoded></item><item><title><![CDATA[Notes from turning a driveway photo into a stunt frame]]></title><description><![CDATA[A friend sent me a still photo of a hatchback in a driveway and asked whether it could look like a short action shot. I did not have a ramp, a drone, or a…]]></description><link>https://jaypark-leads.hashnode.dev/notes-from-turning-a-driveway-photo-into-a-stunt-frame</link><guid isPermaLink="true">https://jaypark-leads.hashnode.dev/notes-from-turning-a-driveway-photo-into-a-stunt-frame</guid><dc:creator><![CDATA[Jay Park]]></dc:creator><pubDate>Sat, 24 Oct 2026 07:46:16 GMT</pubDate><content:encoded><![CDATA[<p>A friend sent me a still photo of a hatchback in a driveway and asked whether it could look like a short action shot. I did not have a ramp, a drone, or a closed street, so I tried a small creative tool instead of a shoot.</p>
<p>The workflow was simple. I used a clear side photo, picked one move, and waited for a short clip. Three lengths showed up in the tool:</p>
<ul>
<li>ramp flight, roughly 15 seconds</li>
<li>side-view kickflip, roughly 6 seconds</li>
<li>head-on kickflip, roughly 8 seconds</li>
</ul>
<p>The result is a stylized video, not a real driving test. I would not treat it as footage of a brand or of a car I do not own. The project I used is called Flying Car AI, and the page that explains the three moves is here: <a href="https://www.flyingcar.art/en">https://www.flyingcar.art/en</a></p>
<p>What I would do differently next time is start with a higher-resolution side photo and keep the background uncluttered. The clip is only useful as a creative preview.</p>
]]></content:encoded></item><item><title><![CDATA[A simple workflow for building a local SEO audit list from Google Maps]]></title><description><![CDATA[Building a local SEO audit list starts with a clear target: one niche, one area. Here is a simple workflow that keeps the data usable. Pick a category and…]]></description><link>https://jaypark-leads.hashnode.dev/a-simple-workflow-for-building-a-local-seo-audit-list-from-google-maps</link><guid isPermaLink="true">https://jaypark-leads.hashnode.dev/a-simple-workflow-for-building-a-local-seo-audit-list-from-google-maps</guid><dc:creator><![CDATA[Jay Park]]></dc:creator><pubDate>Fri, 23 Oct 2026 19:18:51 GMT</pubDate><content:encoded><![CDATA[<p>Building a local SEO audit list starts with a clear target: one niche, one area. Here is a simple workflow that keeps the data usable.</p>
<h2>1. Define the search</h2>
<p>Pick a category and location in Google Maps, for example "dentists in Austin". Narrow searches give cleaner results than broad ones.</p>
<h2>2. Collect the listings</h2>
<p>Use <a href="https://www.gmapsscraper.net/">GMaps Scraper</a>, a Chrome extension, to pull the visible listings into a table: name, category, address, phone, website, ratings and Place ID. Auto-pagination loads more results, and duplicates are removed for you. Export to CSV or XLSX.</p>
<h2>3. Clean the sheet</h2>
<ul>
<li>Deduplicate by Place ID or website domain.</li>
<li>Remove closed businesses and rows without a website.</li>
<li>Keep the rating and review count; they are useful signals.</li>
</ul>
<h2>4. Add audit columns</h2>
<p>Add columns for the checks you care about: does the site load over HTTPS, is it mobile friendly, is the phone number on the page, is the Google profile complete, how many reviews and how recent.</p>
<h2>5. Prioritize</h2>
<p>Sort by low ratings, few reviews or missing websites. These businesses usually have the clearest local SEO gaps, so they make the most relevant prospects.</p>
<h2>6. Review before outreach</h2>
<p>Spot-check a sample by hand and follow the anti-spam rules where you operate.</p>
<p>A short, focused list with a few useful audit columns beats a huge unfiltered export every time.</p>
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