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I made a Google Sheets add-on that adds 28 new SEO custom functions

Hacker News

I made a Google Sheets add-on that adds 28 new SEO custom functions

Hey Hacker news! This is my first launch here and I’m glad to present you: Unlimited Sheets. Let me show you why Unlimited Sheets was created ^^ Problem Google Sheets is a great tool. Actually, if you work from the Internet, it is one of the most used ones or at least in my field: SEO. The problem with Google Sheets is that it is very limited when we are talking about functionalities related to the web (or even SEO). There are a lot of good templates trying to solve specific problems. Do you need to scrape something? Here’s one template. Do you need to extract the search volume data from a set of keywords? Another template… and the list goes and goes. I’ve started creating some custom functions that helped me in my day to day needs in order to avoid the template madness but when I’ve built more than 15 new custom functions it was not optimal to copy/paste every single one that I needed in a specific spreadsheet in order to use it. Imagine if someone on my team needed a function too in another spreadsheet, yeah, it was a mess. What I wanted was to have all of these new features in different spreadsheets for all the users of that spreadsheet without the hassle of creating different templates or doing copy/paste of every function I needed. Solution I’ve discovered that Google Sheets allows you to improve its functionality with add-ons. The good thing about the add-ons is that they can work in several spreadsheets with just one click. So I’ve created Unlimited Sheets, an add-on that adds advanced custom functions for your day to day needs. It has some free functions and other paid ones: Free SEO functions getStatusCode getSearchVolume getUrlsFromSitemap removeHtml scrapeByRegex slugify suggestQueries getAvgDailyTrafficFromWeek getLocaleBySubdomain getRunRateCurrentMonth getRunRateNextMonth Free utilities existsInColumn groupByCell myReplace returnCellInversed returnLastCell unlimitedVlookup (beta) v2lookup combineAll (columns) Premium functions The premium functions are a bit different from the rest. Every premium function consumes API credits as they are connected to 3rd party paid services. Depending on the functions that you want to use you'll need more or less API credits. No API credits required All free functions selectRandomCell 1 API credit per execution indexNow scrapeByXPath scrapeByCssPath 10 API credits per execution getAllPagesFromSERP getPaidPagesFromSERP getOrganicPagesFromSERP getKeywordPosition 200 API Credits per execution getSearchVolumeFromGoogle (up to 1000 keywords per execution) I hope it helps you in your day to day needs ^^ Thanks,

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting
95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, new · Missing: mac, agents, macos
66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, hacker news, 000 · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month, google, users · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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