If your business is like most, you have a rich set of data on your customers, and the likelihood that individual customers have more than one profile is high: in fact, more than 60% of enterprises have serious challenges treating customers as unique individuals. The Accelerator for Unified Customer Spend Analysis, powered by Data Cloud, seeks to help you solve the problem of identifying individual customers and their value to your business: this Accelerator, from Egen, provides a unified view of customers and their transaction history across various contact points with your organization.
This Accelerator connects to standard Data Cloud objects to show you the Art of the Possible with customer data, displaying important metrics like customer lifetime value and allowing you to drill into individual customer details to view contact point unification and make actionable decisions in near-real time. This dashboard was initially created for an academic University aiming to consolidate and link different areas within their organization but can be used across a variety of different industries and use cases.
You can engage with the customer data experts who built this Accelerator at DreamForce in September of 2023, and it's easy to self-serve their insights from their video content and blog post.
Answer Key Business Questions
- Which geographies have the most customers?
- Which customers have the highest lifetime value and how has spending changed YoY?
- Which demographic groups have the most customers and how has that changed YoY?
- What is the current total yearly spend and current average yearly spend for company?
- What are key details on the unified customers?
- What is the total spend by the individual customer?
Monitor and Improve KPIs
- Customer lifetime value
- Average order quantity
- Spending over time
- Total revenue by individual customer
- Number of contact points for each customer
- Customer demographics
Required Data Attributes
This Accelerator connects to standard objects in Data Cloud. You can connect to your own instance of Data Cloud by right-clicking the data connection and selecting [Edit], then entering your own Data Cloud credentials.