First Steps Toward Customer Data Integration
Keep in mind that this single view is often a moving target, and the key is to build an understanding of what is actually required by your company, what is doable and at what price.
No. 5: Collect transaction history data. Hold and provide appropriate access to a minimum of three years of transaction history in a form that enables detailed analysis. Three years typically represents two or more sales cycles (except for some industries, such as automotive, where six years of data may be required).
Data should be held at the transaction level and should include a unique customer ID along with the date, product, volume, value and channel/outlet for each transaction. For analysis purposes, ZIP codes and customer segmentation-related fields also should be accessible.
No. 6: Use customer data to understand customer worth, lifetime value, preference and retention. An organization should be able to determine the worth of individual customers by combining sales margin, sales and marketing costs, and logistics and services. Armed with this information, an organization is able to make clear decisions about marketing activity.
Your company should also recognize the potential length of lifetime for new and existing customers, which ideally should be translated into an allowable cost-per-sale. Customer preference data is compiled by inviting customers to advise your company on their preferences around communications frequency, channel and time, as well as information sharing. This can be a powerful retention tool and a significant contributor to reduced operating cost.
And speaking of retention, a reason for every customer loss should be sought and stored in the customer database. Given the bottom-line benefits of retention over ongoing acquisition, any supporting information for retention is valid. Similarly, data events such as price inquiries, changing order patterns and lapsed accounts can be used as possible predictors of defection.