Poorly managed and unclean customer master data can give rise to numerous issues and hurdles for businesses. At its core, these challenges often manifest as inaccuracies in data, encompassing incorrect contact details, addresses, and other vital information. Such inaccuracies can lead to misunderstandings, miscommunications, and failed business transactions, alongside the accumulation of duplicate records in the system. The presence of duplicate customer entries can sow confusion, waste resources, and introduce errors in analysis and reporting processes.
Additionally, the absence of crucial details may impede effective customer communication, hinder marketing efforts, and adversely affect overall customer relationship management. This, in turn, can impact decision-making processes, resulting in faulty strategic decisions, ineffective targeted marketing campaigns, and misallocation of resources. The repercussions extend to reduced productivity, with employees expending more effort and time in managing data.
Furthermore, the ramifications of poorly maintained customer data extend to a subpar customer experience marked by irrelevant communications or difficulties in accessing services. This dissatisfaction can potentially lead to the loss of business. Finally, inaccurate or outdated customer data poses the risk of non-compliance with data protection regulations, legal issues, fines, and damage to the organization’s reputation.
Outdated and irrelevant customer data creates a messy and purposeless digital landscape. This demands immediate attention. Far from being acceptable, this situation necessitates a decisive move toward comprehensive bulk data cleaning; because nearly all aspects of an organization’s information are intricately linked through the customer master and this may reside in CRM, a CDP, or some other customer data management platform but likely is not in a CMDM (Customer Master Data Management) system.
The imperative here is clear then – preserve this invaluable data asset not by choice, but by necessity. Unkempt customer data not only raises questions about your organization’s credibility but also poses a tangible risk to operational efficiency and compliance.
The rate at which customer data becomes obsolete can vary greatly depending on the industry, the type of data, and how often it’s updated. However, it’s important to note that data can become outdated quite quickly. The Data Genomics Index found that over 40% of stored data has not been touched in over three years, and is considered ‘stale’.
A significant portion of stored data is considered redundant, obsolete, or trivial (ROT). A 2016 Veritas Global Databerg Report found that 33% of data is considered ROT and provides little or no business value at all.
All this serves to underscore the importance of regular data cleansing and updating to maintain the accuracy and relevance of customer data. It’s also crucial to have a robust data governance framework in place to manage the lifecycle of data and ensure its quality and compliance.
Establishing a Single Source of Truth (SSoT) is considered the “brass ring” of data capability in that it refers to a definitive and centralized repository for customer information that acts as the authoritative source for all customer-related data across the organization.
Having regularized standard Data Governance Processes provides some assurances around data accuracy and completeness, and integrating Customer Data with Other Systems and Data Sources allows for a more comprehensive view of the customer. The presence of Data Lineage and Auditing in all your data management activities helps you to track the origin of data and changes made to it over time.
Providing Self-Service Capabilities for customers to manage their data empowers the customer. It can lead to more accurate zero and first-party data which is preferred over second and third-party data.
Regularly Evaluating and Improving Processes for Customer Data Management is part of continuous improvement and is key to maintaining high-quality data. Taking Security seriously and ensuring data privacy should be integral to all your organization does with customer data to build and maintain customer trust.
Customer data master Data Cleansing isn’t just a clean-up; it’s a strategic process meticulously executed to purge irrelevant and corrupted records, creating a pristine canvas for accurate data entries. The significance of doing this extends beyond driving operational efficiency – it is a cornerstone for optimizing data management operations, with the further promise of access to invaluable customer insights.
The clutter within customer data masters, if left unchecked, becomes a bottleneck in customer data management. The domino effect is felt most acutely through the inefficiency of incomplete and duplicated records that may be present in the data landscape.
A daily ritual of data cleansing should be not just a routine; but a habit that holds all data-using teams together. Any deviation, be it due to data inaccuracies or outdated information, sends compounding waves of chaos through normally streamlined processes, derailing promises to upsell, marketing, service, and support.
Data Cleansing Action
Data cleansing shouldn’t be viewed as a pointless chore; it’s a catalyst for unlocking the new, freeing teams from broken, outdated, and duplicated data. Success in outreach and communications campaigns hinges on a hygienic robust database of customer data. Cleaning the customer data master allows teams to channel focus toward accurate accounts, bypassing the wasteful exercise of re-verifying incorrect information through emails or calls.
Cleaning the customer data master is not to be trivialized, at scale, in particular, it can be a challenge. Fortunately, systematic automated data cleansing is possible, liberating companies from a historically time-consuming activity.
Understanding the nuances of data cleaning is paramount, irrespective of the chosen method.
Clear out Duplicates: Duplicates are stealthy infiltrators, entering customer data masters through various channels. Identifying and eliminating them is not just a best practice; it’s a necessity to prevent potential customer loss. Automation takes centre stage to proactively block duplicates and fortify data integrity.
Archive the Old Data: Archiving old data in the customer data master recognizes its latent value. Though seemingly dormant, certain data holds perpetual importance, adapting to the context of the moment.
Data Cleansing Tools: Choosing the right data cleansing tools is a strategic decision. Opt for tools equipped with smart duplicate data detectors, data formatting capabilities, and automation functionalities. The aim is not just to prevent bad data but to fortify customer data masters against inaccuracies.
Customer data master data cleansing transcends the realm of a mere cleanup tool; it emerges as the catalyst propelling your company toward sustained growth. The strategic elimination of obstacles – duplication, data overload, or inaccuracies – accelerates overall growth and amplifies your company’s performance. The focus should not merely be on eliminating unwanted data; it should encompass the optimization of data quality, ensuring the CMDM system operates as a beacon of efficiency within your organizational framework.
The key lies in eliminating the unwanted and embracing the ethos of better quality and efficient data management – the essence of customer master data cleansing.