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Backend Pain – We All Have It, So Let’s Fix It

Understanding the Importance of a Structured Data Management System

Data management is complex, messy, and outright confusing, which is why most enterprise CX teams choose to lower it on their list of priorities. This mentality and lack of understanding has led to a serious industry problem—hundreds of millions of records from various data sources with no definitive structure. To run a large CX program, it requires more than linking your survey responses to a CX platform—it requires a structured data management system that helps your business understand market performance, compensation programs, customer experience, brand loyalty, and other operational metrics through its consumption of raw data, which then transforms that into usable insight for reporting.

Don’t Let Your DIY Data Management Process Leave You Vulnerable

When you have data sources ranging from call center transcriptions, unstructured text analytic data, and operational data, you need a system that will consume that information as is and establish consistency. In the case of enterprise customer experience programs, data is not found within a single system, rather a patchwork of systems like CRMs for sales channels or spreadsheets for business units. With so many moving parts, using a DIY approach to manage data can leave a company vulnerable to system inefficiencies and reporting inaccuracies.

Why You Should Demand “Data Integrity” from Your CX Provider?

Maintaining data integrity is the single most important thing a practitioner can demand from its CX provider. The more steps that exist between a data source (CATI/IVR, social, external third-party) and the CX platform, the more opportunity there is for data integrity issues. This potential problem is exacerbated when one or more of those steps are manually managed. For a system to operate smoothly and without error, it must be data agnostic, neutralize formatting for platform consumption, and link to the actual applications that produce dashboards and reports.

Focus on Your Customers, While Your CX Provider Focuses on Your Backend Data

At MaritzCX we’ve found the answer to an ongoing industry problem. It allows our customers to take raw data from any source and transform it into a usable format. CXWorkflow is an automated data workflow engine that prepares data from its point of origin, cleanses and enriches that data within the platform, and then sends that data in real-time to its proper location via data transfer protocols, so CX leaders and their internal IT teams can focus on fewer backend items and more customer-facing initiatives.

If you haven’t discussed data management with your CX provider, do it now! As AI and machine learning continue to become a larger part of the CX conversation, practitioners need to consider the backend mechanisms running their programs. Look for a tool that will empower you to address your most demanding data needs and has a simple user interface to eliminate the need for internal IT resources. Data management should be at the top of any CX practitioners list.