1. Identify all data sources. Your RevOps team will need data that likely sits in disparate systems – CRMs, ERPs and EPMs, data warehouses, and customer service applications. Find all data elements related to revenue and the customer journey. For example, you’d want data for marketing campaigns, products, leads, accounts, quotes, orders, contracts, payments, and renewals.
2. Consolidate data in a repository. Extract, transform, and combine all of these different types of data into a repository–typically a cloud data warehouse. This will give you a comprehensive view of your customer journey. Be sure to use a CDC tool to capture and track changes in our data over time.
3. Build a stream processor. If your organization produces a steady flow of real-time data, a streaming data process will allow you to respond to situations faster. Using a tool such as Apache Kafka or Amazon Kinesis, your data will be processed sequentially and incrementally on a record-by-record basis. This will allow your data to be immediately passed to downstream applications for analysis, presentation, or triggered actions.
4. Implement a RevOps Analytics Platform. This platform allows you to perform many types of analysis on your stored and/or real-time data–such as the following examples:
- Create real-time dashboards and interactive visualizations which help you identify patterns and develop insights faster
- Use predictive insights to spot revenue risks before they progress
- Combine your CRM data with other sources to improve your decision making
- Identify customer preferences and purchasing patterns to create better aligned sales strategies
- Use real-time sales data to improve your forecasting and revenue pipeline
- Maximize sales opportunities by using alerts and automation to drive timely actions.