Data Quality Scorecard Infographic

Data Quality Scorecard Infographic – Facts about Data Quality

You are a marketing manager and want to plan your campaigns cost-effective and efficient? Surely the following three challenges are well known to you. 

Three challenges of campaign management

  1. Target group not reached
    Do you sometimes feel that reaching your target audience is a matter of luck? In order to make every shot a hit the target audience must be precisely defined, selected and analysed. For that a consistent and quality-assured data base is needed.

  2. CRM has white spots
    For a successful customer segmentation and definition only a look at the own CRM helps. But the next challenge is already waiting here: Quickly it gets clear that it has major gaps. False, outdated, incomplete and inconsistent data is widely spread and reduces its quality - and therefore, of course, the success of your marketing campaigns.

  3. Processes are running anything but smooth
    Professional campaign management consists of a variety of processes that must be perfectly coordinated with each other in order to achieve both long-term strategic objectives as well as short-term tactical objectives. But campaign-specific business processes can only be as good as the customer data master data that support this.

Data Quality as Success Factor

These three challenges make it clear: The success of your marketing activities depends significantly on the quality of customer master data. But this knowledge alone can not solve the challenges of master data management. Often it is questionable, where exactly the shoe pinches. Are the data problems business- or process-driven or does the technology not match to the needs of your business? Often there are only vague assumptions - it lacks clearly established facts and figures. 

But how can these challenges of master data management be countered? How do you get transparent and reliable reports on your data quality? And how can you gain insights for the campaign management?

Data Quality Score – the basis for successful data quality processes

Our solution: the Data Quality Scorecard. It provides you measurable KPIs that allow you to measure the quality of your data over a certain period of time on a regular basis with individually defined business rules. So is visible and measurable, such as your customer data, the actual support data-driven processes. So it gets visible and measurable, how your customer data actually supports your data-driven processes. 

With the Uniserv DQ Scorecard you receive an early warning system that can identify negative trends in data quality at an early stage. With this you are able to introduce specific countermeasures - even before any damage occurs. It also becomes visible whether initiated data quality activities were successful and desired changes have occurred. Thus you transform your reactive data quality management to a proactive data quality management.

Targeted Campaigns – Every Shot a Hit

The result:

  • reliable reports that show which entities or rules have led to a weaker Data Quality Score 
  • clean customer data through a targeted control of data quality measures
  • smooth processes by focusing on business cases
  • successful campaigns through quality-assured customer master data