GA

GA Insights – Never Log into Google Analytics Again

Hacker News

GA Insights – Never Log into Google Analytics Again

Hey HN! We are Patrick & Chris, bootstrapped co-founders of GA Insights ( https://www.ga-insights.com ) - a simple way of getting reports and alerts for your tools inside Slack and Teams. We started as a technical tool to monitor client accounts in Slack, interfacing with Microsoft Azure insights, and then pivoted to supporting business intelligence tools like Google Analytics and Google Search Console. The idea was born out of the angst that we had experienced using disparate tools to monitor our metrics, client & to share information. Google Analytics has an ever-evolving interface that most developers would rather not spend a day getting lost in. We decided to take the primary use cases we had for Google Analytics and provide an engine to process, visualize, and ship to Slack or Teams. This gets us daily or weekly reports on metrics such as page speed, bounce rates, page engagement, and when the cart checkout breaks. Once we started to gain some traction with clients, we extended the capacity to include other data sources like Google Search Console and Google Ads, making it simple for indie businesses and large corporations to extract the value from these reporting surfaces and send them to a channel that we use every day, like Slack or Teams. We use ML to analyze 100s of metric streams to detect anomalies in your data, and are soon expanding into providing root-cause analysis when anomalies occur. Currently, we send 2.6k alerts per week and 3.2K scheduled reports into Slack, Teams & Email. Slack has seen the biggest uptake followed by Teams. We run on Azure, combines NoSQL, Serverless, Redis, Warehousing, and scalable architecture to deal with bursty loads (common in report scheduling). We're launching new data sources and integrations rapidly, with Facebook, Stripe, and Zapier next on our docket. Happy to answer any questions you might have.

Share card

Actual performance

42points
28comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: slack, google, stripe · Missing: mac, agents, macos
95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: started, para · Missing: supports, reddit linkedin, podcasting
91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: google, visualize, way · Missing: mobile apps, ios, personal
52%52% 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, io · Missing: https docs, excited, just released
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface, soon · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: bootstrapped · Missing: arr, mrr, revenue
14%14% 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.

Incorrect prediction on native model

Similar products

I
I replaced Google Analytics with simple log-based analytics58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I replaced Google Analytics with simple log-based analytics

Hacker News475
Go
Google analytics for Confluence60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Google analytics for Confluence

Hacker News1
G.
G.A. Joe – Get More Out of Google Analytics60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

G.A. Joe – Get More Out of Google Analytics

Hacker News2
Go
Google Analytics for where you have been60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Google Analytics for where you have been

Hacker News8
Re
Replacements for Google Analytics (Borrowed from Rapnie)72%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Replacements for Google Analytics (Borrowed from Rapnie)

Hacker News3
Ho
Hover-Over Google Analytics62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hover-Over Google Analytics

Hacker News4
Au
Automated insights from your Google Analytics48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Automated insights from your Google Analytics

Hacker News10
Au
Automated Insights from Your Google Analytics48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Automated Insights from Your Google Analytics

Hacker News25
Veonr Analytics
Veonr Analytics59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Get precise insights on your website. Google Analytics sucks

Indie Hackers2advertising
Google Analytics Course 2.0
Google Analytics Course 2.021%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Last chance to learn Google Analytics from a seasoned vet

AppSumo11