Customer Data Management (CDM)

Definition of Customer Data Management (CDM)

Customer Data Management (CDM) is a solution mechanism in which an organization's customer data is collected, managed and analyzed. CDM is geared toward resolving customer requirements and issues while enhancing customer retention and satisfaction, allowing an organization to convert customer data into Customer Intelligence (CI). With CDM, one or more software applications are integrated to facilitate access to reliable and efficient customer data. Attracting and retaining customers requires a clear understanding of customer requirements. CDM streamlines customer relationship management (CRM), marketing and customer feedback management (CFM).

Customer data management is defined as the people, processes, technologies, and systems that collect, analyze, and organize customer data.

source: MarTech Advisor

Centralizing the management of customer information is critical for a business’s continued longevity. According to DZone, 92 percent of organizations have 16 to 20 data sources, with that data spread across multiple locations in multiple formats. With so many data sources spread throughout the organization, and locked into functional and channel-specific silos, there is no way to build a single view of the customer without implementing CDM processes and technologies. Strong customer data management practices empower companies to build better products, orchestrate contextually relevant marketing campaigns, and provide a personalized customer experience. Customer retention dramatically improves in organizations with strong CDM practices, with Forbes Insights finding that data-driven marketing organizations are five times more likely to achieve a competitive advantage (74 percent vs. 13 percent). Higher customer retention is a tangible benefit to the organization. We all know that it’s cheaper to retain existing customers than acquire new ones, so the ability of CDM processes to improve that capability can provide substantial support to revenue. With customers increasingly demanding personalized experiences across channels, the benefits of robust CDM processes are hard to deny.

Background of Customer Data Management (CDM)

Customer data management, as a term, was coined in the 1990s, pre-dating the alternative term enterprise feedback management (EFM). CDM was introduced as a software solution that would replace earlier disc-based or paper-based surveys and spreadsheet data. Initially, CDM solutions were marketed to businesses as software, specific to one company, and often to one department within that company. This was superseded by application service providers (ASPs) where software was hosted for end user organizations, thus avoiding the necessity for IT professionals to deploy and support software. However, ASPs with their single-tenancy architecture were, in turn, superseded by software as a service (SaaS), engineered for multi-tenancy. By 2007 SaaS applications, giving businesses on-demand access to their customer information, were rapidly gaining popularity compared with ASPs. Cloud computing now includes SaaS and many prominent CDM providers offer cloud-based applications to their clients.

In recent years, there has been a push away from the term EFM, with many of those working in this area advocating the slightly updated use of CDM. The return to the term CDM is largely based on the greater need for clarity around the solutions offered by companies, and on the desire to retire terminology veering on techno-jargon that customers may have a hard time understanding.

Components of Customer Data Management (CDM)

CDM must be tightly integrated across the departments of an organization, including IT, sales and HR. CDM components include:

• Categorization: Customer data is classified and subclassified.
• Correction: Collected data is verified for accuracy and consistency. When necessary, contact details are updated, and duplicate records are removed.
• Enrichment: Incomplete data is collected and completed.
• Collection: Customer data and insight activity is collected via a customer feedback system or sources, like sales, customer support, surveys, reports, newsletters and other customer interactions.

Customer data is organized and shared throughout an organization.

source: Techtarget

Organizations can implement CDM with in-house software tools or cloud computing services that collect, analyze and organize customer information in a single, consistent platform. Once in place, the data can be accessed in real time by all relevant departments across the entire organization, including sales, marketing and customer support. CDM software products can be used in a variety of ways, such as:

• Allow stakeholders to initiate an instant response to customer feedback or issues.
• Allow stakeholders to identify and contact a target audience segment
• Allow stakeholders to identify and contact specific marketing qualified leads (MQLs) and sales qualified leads (SQLs).

Customer Data Management Strategy

Customer data is the most valuable resource of a business. Customer data management includes collecting, cleaning, managing, tracking, analyzing, and combining customer data to glean insights for predicting customer preferences, sales trends, etc. Below are five basic steps to help you plan an effective customer data strategy:

• Identify Critical Data: According to a Forrester blog post, “On average, between 60% and 73% of all data within an enterprise goes unused for analytics.” What effects can unused data have on your systems?
  • Too much data can become unwieldy.
  • It can hinder the decision-making process, as it responds much slower to manipulation and retrieval.
  • Unused data becomes an unnecessary burden on your system.

Identifying critical data, thus becomes a pivotal step in customer data management. You need to strategize what and how much data to collect.

• Decide on Data Collection Methods: After identifying what critical data you need, decide where and how to collect it. Some important considerations while collecting data are:
  • Identifying direct sources — surveys, web forms, contests, purchase history and customer records in your CRM system
  • Including indirect methods — customer activity on your web portal and social media pages or building personalized profiles based on a person’s location and behavior patterns.
  • Being ethical and upfront while collecting data. Trust is crucial for building relationships with your customers. Be clear about what data you are collecting, how you will use it and request customer consent.
• Maintain Data Well: Data becomes unusable if it is not sorted and verified. Opportunities are lost and resources are wasted if it is not updated regularly. Data maintenance involves setting up a data management team who will:
  • Integrate data from marketing, sales, and service teams
  • Validate whether the customer information is correct
  • Verify if the information is consistent
  • Clean the database by eliminating redundancies, duplicates, incomplete or erroneous records
  • Update the database regularly to record customer dynamics
  • Maintain overall data quality
• Invest in the Right Technology: Spreadsheets are no longer enough to manage, analyze, and efficiently retrieve data. You need to invest in the right technology to better manage and access data, eliminate silos, and provide real-time insights. Marketers’ favorite solutions include:
  • Customer Data Platforms (CDPs): CDPs can ingest any form of data from disparate sources, handle varying volumes of customer information, and unify customer records to make them readily accessible.
  • Customer Relationship Management (CRM): CRM systems can help integrate customer data and interactions across touchpoints at one place. They can segment customer data to glean insights, and track the customer journey to identify opportunities.
• Focus on Customer Data Security: Maintaining customer privacy and ensuring that customer data is secure is paramount. It helps build customer trust, saves your business from losses, and prevents litigation. The security measures you can undertake are:
  • Invest in backup systems
  • Devise robust security policies that include password policy, encryption, biometric authentication, etc.
  • Invest in security training for your employees

An effective customer data management strategy includes responsible data collection and management, securing better quality data and focusing on data security.

See Also

Customer
Customer Acquisition Cost (CAC)
Customer Centricity
Customer Demographics
Customer Due Diligence (CDD)
Customer Dynamics
Customer Effort Score (CES)
Customer Engagement
Customer Engagement Hub (CEH)
Customer Experience Management (CEM)
Customer Lifecycle
Customer Lifetime Value
Customer Loyalty
Customer Needs
Customer Retention
Customer Service
Customer Service Management
Customer Relationship Management (CRM)<ref> Customer Data Integration (CDI)
Enterprise Data Integration (EDI)<ref> Data Management