What's new in Mixpanel?
We’ve been hard at work. Check in every week to see our latest product updates for March.
March 25 – 29, 2019
Group Analytics (open beta)
Toggle between analyzing data by individual user, company, device – or any other way you define or group your customers. With Group Analytics, B2B companies can tell which accounts are healthy, which are at-risk, and see how product usage impacts account health. Hardware companies can better understand how devices or assets are used over their lifetime, to more accurately forecast and allocate resources. This gives you the flexibility to analyze and define your customers in a way that makes the most sense for your business.
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Draft saving
Now you can save a draft at any point of time in your message creation flow. You will also see a new tab next to your inactive messages, called “drafts”. Use these drafts to store templates and easily duplicate them to create new messages.
Learn more about messagingMarch 18 – 22, 2019
Statistical significance in Funnels
Statistical significance allows you to have certainty that the trends you see – mobile users converting better than those on the web, for example – are worth acting on. This will allow you to clearly see the most statistically significant – or definitive – insights and prioritize action or inaction accordingly. Use this feature to figure out which cohort has a statistically significant variation in behavior or to measure the significance of A/B test results right from funnels.
Learn moreMarch 11 – 15, 2019
Send messages to cohorts
Create a cohort of users who opened your last three email campaigns, or added something to their cart, but didn’t complete a purchase, all in the last four months. Open the cohort in Explore, and then send them a targeted email, push notification, SMS or webhook, nudging them towards completing a purchase. Afterwards, you’ll be able to clearly track the impact in of your efforts, all in Mixpanel.
Learn moreMarch 4 – 8, 2019
Advanced cohort creation
Save time by combining or creating new versions of existing cohorts. Say your data science team built a complex cohort to identify churn-risk users, and you’re only interested in a particular portion of that cohort. Simply use the existing “churn-risk users” cohort, add your additional criteria, and save it as a new cohort.
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