In this blog we provide a brief introduction to the subject of customer data management, as well as a guide on how to get started with your lifecycle management.
Customer data management explained
Customer data management (CDM) is the process of structuring and managing data related to your customers. It can include several sub-processes such as data collection, structuring and storage and internal sharing. The customer data itself can include contact information and addresses, purchase history, company signatories and representatives, legal data and so on.
According to several studies, customer data quality has a big impact on the performance of a bunch of different processes, for example:
- Customer onboarding, experience, loyalty and retention;
- Communication and marketing strategies;
- Regulatory compliance
Guide: Customer Data Lifecycle Management
How to get started!
1. Collecting customer data
Start by performing an audit of what customer data you require, for example from the following perspectives:
- What data do we need to collect to ensure regulatory compliance?
- What data do we need to collect from a risk- and analysis perspective?
- What data do we want to have from a sales and marketing perspective?
- What data is not business critical? In other words, what data can we do without?
Make sure you document your audit as well as a plan for how the process of gathering data should work. I.e. What data will be collected, when and how will it be collected?
Information today is usually collected digitally when a customer makes a purchase or registers for your service or product. A convenient way to collect the data you need is through APIs, where information can be retrieved in the background while the customer registers. This can apply, for example, to an address that is retrieved from a social security number that the customer enters or company information that is retrieved from the customer's specified company id.
Read more about API solutions here!
2. Ensure data quality over time
Many companies use regular updates or "data cleansing", often with a 6 or 12 month gap between updates. A lot can happen in that time and the cleansing is often related to a lot of manual work, making it a suboptimal way of working to ensure data quality over time. Instead, there are more modern and secure ways to keep your customer data up to date!
Roaring, for example, offers a monitoring service through a technical solution called webhooks. Meaning, if changes occur in your data, you'll receive a notification of it and a request to retrieve the changes. Your system can then incorporate it into your system/s and automatically update it, for example your CRM.
Read more about monitoring customer data via webhooks.
3. A structure and framework for offboarding
First, make sure you structure and build a framework for compliance (GDPR, Money Laundering Act etc.). The framework should be available internally as well as externally, and provide details on what customer data you collect, how its stored and used and how and when you delete it. If there are time stamps on all your data, it is easy to assess how long you've had it in your possession, and therefore create rules on when to automatically delete it.
The legal grounds for collection of data should also rule on how long the information. When it is no longer possible to claim a purpose for the data to be stored, it must be discarded and deleted.