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The demand for Eppo expertise is on the rise across various data roles. As more companies prioritize A/B experimentation, proficiency in Eppo can give you a competitive edge in the job market.
Run reliably informative A/B experiments. Built for today's product teams and the modern data stack. There have been recent reports of fraudulent emails from people impersonating the Eppo talent team. All legitimate correspondence from Eppo will come only from geteppo.com. Anything else should be reported to LinkedIn as a scam. For more information on these fake job scams, you can see this resource from the FTC: https://consumer.ftc.gov/consumer-alerts/2023/08/scammers-impersonate-well-known-companies-recruit-fake-jobs-linkedin-and-other-job-platforms
External link for Eppo
Eppo helps companies unlock growth and encourages an entrepreneurial culture with a trusted platform for randomized experiments. It talks directly to your data warehouse (Snowflake, BigQuery, or Redshift) and lets your analysts define metrics in familiar SQL. With our advanced statistics features, experiments analyzed on the Eppo platform lead to decisions more quickly than traditional A/B tests.
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🚀 Major announcement for experimentation and data teams Eppo just unveiled Outperform, the new go-to resource for all things experimentation. Get access to ideas, playbooks, and frameworks for ambitious experimentation pros. Subscribe via this link: https://lnkd.in/ereSDP34 --- Some of my favorite content by theme: 👉 [A/B testing] Four Customer Characteristics That Should Change Your Experiment Runtime by Simon Jackson https://lnkd.in/edn2EbGM 👉 [Growth] How Startups Like Figma, Facebook, and Airbnb Found Sudden Growth Inflections by Lenny Rachitsky https://lnkd.in/esxmY8_r 👉 [Engineering] Building a Custom DAG Orchestration System for Experimentation by Eric Petzel https://lnkd.in/eDbnQDZs 👉 [Statistics] Bayesian Angels and Frequentist Demons by Sven Schmit https://lnkd.in/e3vYqE-8 👉 [Culture] From 10s to 1000s: How to Scale Experimentation Velocity by Lukas Goetz-Weiss https://lnkd.in/eThJ8SJY
Eppo reposted this
Introducing: Outperform Winning insights from the world's best businesses on driving innovation and better decision making with experimentation. For the teams ready to rise above the status quo and transform their companies and careers. https://lnkd.in/eyW9bDNU
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🎉 🚀 Eppo is now available on both AWS and GCP Marketplaces! Enjoy an enhanced and simplified subscription experience while making experimentation and feature flagging accessible to everyone in your organization. → AWS Marketplace Listing: https://lnkd.in/eMbqdqeV → GCP Marketplace Listing: https://lnkd.in/eN8PJcDt cc: Youssef Francis
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🗽 NYC data leaders: we just added a few more slots for our Data Leader Happy Hour happening tomorrow, July 10th, at a charming new venue in NYC. This is a fantastic opportunity to connect, share insights, and enjoy a great evening with fellow data leaders. Interested in joining? Comment below or DM me at sid@geteppo.com to secure your invite.
Eppo reposted this
🗽 If you're a data leader in NYC who is passionate about experimentation, join fellow leaders for an evening of wings, pizza, beer, and wine at a charming ~new~ venue on July 10th. Comment below or DM me (sid@geteppo.com) to get the invite. 7 slots remaining.
Don't just rely on sample size calculations when planning your A/B tests. Consider these 4 "Runtime Modifiers" to tailor your experiment runtimes to your customers and get high-quality results faster: 1: HOW MANY RELEVANT PARTICIPANTS DO YOU HAVE? The more relevant customers you have, the less time you'll need to run your experiment. 2: HOW YOUR PARTICIPANTS ENROLL Participants enrolling regularly over time vs. skewed enrolment over time can drastically affect your experiment runtime. 3: PARTICIPANTS’ FREQUENCY OF USE High-frequency-of-use customers are more susceptible to novelty effects, requiring longer experiment runtimes. Low-frequency-of-use customers tend to be more oblivious to changes, allowing for shorter experiments. 4: TIME FOR PARTICIPANTS TO TRIGGER VALUE Fast time-to-value customers allow for shorter experiments, while slow time-to-value customers typically require longer experiment runtimes. Former Canva, Meta, and Booking.com experimentation leader Simon Jackson walks you through it all on the Eppo blog: https://lnkd.in/eJpiPNqM
We’re all set up at #ExElite24 and ready to help teams level up their experimentation on Eppo! Drop by for swag (like our insanely popular US-import Control/Variation socks) and putt-putt to win bigger prizes😎
🌟 Another week, another amazing new hire to introduce!! Please join us in welcoming Christine B. to the Eppo team as our Engagement Manager! 🚀 At Eppo, we emphasize the importance of an entrepreneurial mindset in everything that we do. We believe that Christine embodies this philosophy, sharing our enthusiasm for innovation and willingness to explore new ideas! Let's give a warm welcome to Christine! We're thrilled to have her with us and look forward to seeing all of her contributions to Eppo! 📈 #NewHires #WelcomeToTheTeam #JoiningEppo #Eppo