Привет, Хабр! 7-го мая в Wrike TechClub мы собрали экспертов из XSolla, Pandora и Wrike и поговорили о подходах и решениях в продуктовой аналитике, инсайтах, экспериментах и взаимодействии аналитика с другими отделами. Доклады и обсуждение проводили на английском, так что если хотите потренировать язык на удаленке, делимся с вами видеозаписями докладов и слайдами (в описании к видео).
Если вам близка тема продакт-менеджмента,
Kirill Shmidt, Product Analyst at Wrike — Reproducible research in data analytics
‘You decided to double-check your report or research which was done a couple of months ago. You discover that you’ve lost your data and forgot a precise method of transformation. So, you try to replicate the same result — you get different data and different conclusions. How can you trust your research if you can’t repeat it with the same result?
To handle this problem in Wrike we use a special approach in our research and analytics procedure which ensures that everything will be reproducible and accessible no matter who performed research and how long ago.’
Alexander Tolmachev, Head of Data Science at XSolla — Auto insights from data to make next best actions to up your business
‘In XSolla we’ve built a system that helps to find insights in data. It automatically finds strategies and recommends where you will have the largest impact to achieve your goals. Simply input your data and ask what business problems you would like to solve. I will talk about how we built this system from scratch.’
Tanya Tandon, Product Analyst, Pandora — Best practices to partner across different stakeholders for better visibility and higher impact
‘As a product analyst, you solve multiple problems. These problems could be anything — from collecting and analyzing the effect of an event such as coronavirus or mapping how a user discovers a feature. And solving these problems is important and most of us know how to handle it. But what do you do after you solve that particular problem? Report to your manager and people who asked those questions. Right?
That may seem enough, it really is not. We are product analysts loaded with such rich knowledge of data that many business folks are starving for without even knowing. You are way more valuable than you give yourself credit for.’