Modeling Revenue and Transaction Data for Mixpanel Insights
What is the best way to model revenue/transaction data for use in Mixpanel?
What is the best way to model revenue/transaction data for use in Mixpanel?
Hi Dwi A., Please stand by as I search the Mixpanel knowledge base for an AI-powered answer. I normally take about 15 seconds or so. In case AI cannot answer your question, feel free to reach out to Mixpanel support at mixpanel.com/get-support. If you have follow-up questions for this thread, please tag me again with your question: @kapa.ai <follow-up question> 👋
Feel free to ask a follow-up question once I've answered by mentioning me with @kapa.ai
To model revenue/transaction data for use in Mixpanel, there are two main approaches depending on your business model: 1. For transaction-based businesses (e.g. ecommerce): Send purchase value as an event property on every purchase event. For example: LBKSEvent: Purchase completed Properties: {item: clothing, price: $100}LBKS2. For subscription-based businesses: Send a monthly snapshot of revenue per user/account as a historical profile property. For both models, it's recommended to use Mixpanel's Warehouse Connectors with Mirror mode enabled. This ensures your data in Mixpanel stays 100% in sync with your data warehouse, even if the warehouse data is updated.Mirror mode is especially important for transaction data, as it allows Mixpanel to reflect changes like refunds, cancellations, or credit card failures that may occur after the initial purchase.As stated in the Mixpanel documentation: "Mirror mode allows customers to do that because the data you use in Mixpanel stays in perfect sync and is as reliable as your warehouse data."Revenue Analytics Q&A with Mixpanel Product Manager Neha NathanBy modeling your data this way and using Warehouse Connectors with Mirror mode, you can ensure accurate revenue analytics in Mixpanel and take full advantage of its revenue analysis capabilities.
kapa.ai is still learning and improving, please let me know how I did by reacting below.
ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.
Let me check the knowledge base for you again. One moment! 📚
Based on the information provided in the knowledge sources, Mixpanel offers capabilities to track and analyze subscription-based revenue metrics directly within the platform. Here's how you can approach tracking MRR movements, MRR churn rate, and MRR churn: 1. Data Preparation: First, ensure you're sending monthly snapshots of revenue per user/account as historical profile properties to Mixpanel. This is crucial for subscription-based models. As mentioned in the documentation: "For Subscription based models - Please send a monthly snapshot of the revenue per user/ account as a historical profile property." [Guides > Launch > Building Revenue Metrics > Frequent Asked Questions](https://docs.mixpanel.com/guides/launch/revenue-analytics#frequent-asked-questions) 2. Tracking MRR Metrics: Mixpanel has built-in functionality to calculate these metrics: • MRR movements: Mixpanel can track changes in MRR, including new, upsell, and downgrade revenue. • MRR churn rate: This is calculated automatically. • MRR churn: Mixpanel can compute this metric for existing customers. As stated in the Mixpanel blog: "Subscription businesses have ARR growth rate, ARR churn rate, ARR (by new, upsell, and downgrade), average deal size (ADS), net revenue retention (NRR), and expansion rate." [Revenue Analytics Q&A with Mixpanel Product Manager Neha Nathan](https://mixpanel.com/blog/revenue-analytics-qa-with-mixpanel-product-manager-neha-nathan/) 3. Composing Calculations: You can compose these calculations directly in Mixpanel. The platform offers computed properties specifically for subscription revenue metrics. As mentioned in the documentation: "We've got 2 new computed properties to help you with subscription revenue metrics. The model is built by comparing 2 data points - 1. recurring revenue change: looks at 'numerical difference' between the 2 values 2. recurring revenue change type: tells you 'type of change'" [Guides > Launch > Building Revenue Metrics > Subscriptions Business Models](https://docs.mixpanel.com/guides/launch/revenue-analytics#subscriptions-business-models) 4. Using Warehouse Connectors: While you can prepare calculations in your warehouse first, it's not necessary. Mixpanel's Warehouse Connectors allow you to bring your data directly from your warehouse and perform the calculations within Mixpanel. This approach ensures data accuracy and real-time updates. "If there's one universal truth about revenue data most people would agree on, it's that it needs to be 100% correct for users to trust it. So, it's imperative that Mixpanel get the data directly from the source of truth." [Revenue Analytics Q&A with Mixpanel Product Manager Neha Nathan](https://mixpanel.com/blog/revenue-analytics-qa-with-mixpanel-product-manager-neha-nathan/)
In conclusion, you can compose and track these MRR metrics directly in Mixpanel without needing to prepare the calculations in your warehouse first. However, ensure that your data is properly structured and synced using Warehouse Connectors for the most accurate and up-to-date analysis.
kapa.ai is still learning and improving, please let me know how I did by reacting below.
ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.
Novindra P. check this please