Growth Experiments is a complete platform to track ideas, hypotheses and results.
You may be wondering 🤔 why your ITOps transformation projects are slowing down or becoming resource intensive❓ ➜ More than likely it is due to data – which is inherently complex and raw - and the amount of work your team has to put together (over and over) to make data work for you – it simply adds up, to the man-hrs🛠️ and cost 💲 You have seen 👓 all those ELT/ETL and data pipeline tools, but hey, why do they only end up in the enterprise data architecture teams, working on business data, like sales, marketing, insurance, healthcare, etc. What about IT data, which is predominantly machine-generated, and more tools, data formats, delivery modes, and APIs than you can imagine‼️ 💡You may be thinking of the RPA route, but, RPA is generally good at business processes and user task automation. 🤔 At this point, you may be getting frustrated, what are my options? How do I tackle this IT data problem? You are not alone – we are seeing this time and again, in IT organizations - and that’s why we have introduced Robotic Data Automation (RDA).
Are you familiar with the statistical love story of diapers and beer? It's actually a story of market basket analysis. Maybe the name of this analysis sounds intimidating, and maybe you don't really know what it does or how and where to find it. So we decided to make your life easier. From the "explain it to 8th-grade child" definition: "The market basket analysis technique helps find items that people buy together. This is a way to figure out which items are related, or which items customers buy the most. This type of data analysis is based on Association Rule Mining, a subset of machine learning which learns “rules” that account for items purchased together." to a detailed tutorial on: Where to perform it How to perform it How to interpret the findings to set up the experiment that will help you skyrocket your revenue. Make sure to read the article to learn exactly how to use this type of data mining technique.
Data science is the field of applying advanced mathematical and statistical techniques to large sets of data to uncover insights that can improve the performance of different parts of a business. Data science is used in growth to uncover commonalities between types of users that are either successful or unsuccessful with a product. Marketers and growth teams use data science findings to improve the performance of their product, user acquisition funnel, user retention and more. These are the best articles on how to use data science to grow your business. From how to analyze data using R, pandas for Python, regression, model building, SQL and more, you'll learn how to apply data science concepts to growth.