The need for Customer and Member Insight
Understanding customer or member behavior is a most important business priority. All functions in a business, especially marketing, need customer insight to professionally manage the business and to set and reach organizational goals.
Information in multiple data sources
Much of the data for analysis will reside in one or more data systems that are part of running the business. These systems may include internal data systems such as Billing, Customer Relationship Management (CRM), Customer Service, Registration, Online Ordering, and Marketing Leads (inquiries, web site visitors, white paper downloads, webinar attendees, and conference attendees). Also important data often resides in external data sources, such as purchased marketing data, social media data, and marketing partner lists.
Data Framework for business analysis and actions
Building and maintaining an analysis Data Framework based on all pertinent data sources can provide profound value for business analysis and action steps. Transaction and purchase history is an essential part of the Data Framework.
With properly developed and configured data, powerful insights can be derived. The Data Framework can be queried to answer a myriad of questions as to who, what, where, when, and how much. The Data Framework can also be used with predictive analysis tools to understand the why of things.
Coordinate data sources, link key reported & derived data facts
The Data Framework should be built around customer or member contact and organizational data correlated from all data sources. The data should include reported data facts, along with derived data and indicators.
Reported data facts are details about individual customers, members and prospects, including the organizations with whom they are affiliated. This includes names, addresses, geographic codes, customer/member type, industry codes, job function and organizational relationships.
Derived data comprises calculated data based on “rolled up” transaction activity, including transaction activity over time. This includes activity indicators for example such as Customer/Member 2016, 2015, 2014 (and so on) indicators or Annual Conference participation 2016, 2015, 2014, (and so on) indicators. Tracking a customer’s activity over time is helpful in determining “loyalty”. Also volume indicators over time, such as the number (and $ amount) of purchases 2016, 2015, 2014 (and so on) are essential in quantifying the analysis.
Start simple, plan for growth
The initial Data Framework may start out simple. That is fine, because it is important to start building it and using it. The framework should be frequently updated. Also, the Data Framework should be built with the understanding that it will be expanded over time.
Empower Your Organization
From the Data Framework, meaningful standard and ad hoc reports and analyses can be produced. All on your business team, with the need to know, can be working with the same consistent data. Also, helpful extracts from the Data Framework can provide highly useful outreach lists for customer research and customer contact.
The analysis Data Framework is fundamental to understanding the business, knowing the customer, and taking important actions to reach goals.