Se

Searcherries – SEO Opportunities from GSC

Hacker News

Searcherries – SEO Opportunities from GSC

Hey HN, I’m Edward, an indie maker and SEO specialist. I built Searcherries – a tool that pulls raw data from Google Search Console (via API) to help you find pages and queries with a lot of impressions… but not many clicks. Here’s the link: https://searcherries.com This started as a side tool for myself. I manage sites with hundreds of pages and wanted a faster way to spot content that’s almost working — those pages sitting on page 1 or 2, getting tons of views, but just not converting into clicks. But with a 1,000-row limit and no real tooling around it, it’s painful. So I built Searcherries. You’ll get: - Low-click pages and queries detection - Keyword performance by click trends (not just rank) - Comparison reports - Monthly SEO summaries It works best if your site has lots of pages, but it’s still useful even for smaller sites. One caveat: the site needs to be verified in your GSC account. I’d love for folks here to try it out. The Standard and Advanced plans are fully unlocked and free for the first 14 days — no feature limits. Also: I’ve got a ton of features on the roadmap (and would love to hear your ideas!). Appreciate any feedback — ideas, critiques, bugs, all welcome!

Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
96%96% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, google, monthly · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released
47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: google · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, 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 · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Creworth
Creworth50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Get opportunities by showing your entourage.

Indie Hackerscommitment-full-time
Zag.ai
Zag.ai47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find huge SEO and traffic opportunities hiding right within your data

AppSumo38
Jarbug
Jarbug84%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Uncover Hidden SEO Opportunities

Indie Hackerscommitment-full-time
Fi
Find local volunteering opportunities during the Coronavirus outbreak39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find local volunteering opportunities during the Coronavirus outbreak

Hacker News1
De
DevSwag – swag opportunities for developers #Hacktoberfest59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

DevSwag – swag opportunities for developers #Hacktoberfest

Hacker News1
devSwag
devSwag19%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

😎 swag opportunities for developers

Indie Hackers3$1/mocommunity
UN
UN Volunteers Opportunities Dashboard56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

UN Volunteers Opportunities Dashboard

Hacker News3
AIAuthoritySEO
AIAuthoritySEO55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

SEO

Indie Hackers1advertising
Mex SEO
Mex SEO51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mex SEO

Indie Hackers1$1,000/moanalytics
Positional
Positional72%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An all-in-one SEO toolset

Product Hunt+546Marketing