High data quality is the foundation for effective processes, well-informed decisions and sustainable customer relationships. Yet many companies are unaware of the true state of their data quality. Our data quality check sheds light on the situation – systematically, transparently and with a clear outcome. We analyse your customer data against key criteria such as completeness, consistency, plausibility, redundancy and timeliness. In doing so, we identify weaknesses and draw up specific recommendations for action. This provides you with the basis for targeted optimisation measures – regardless of whether you use a CRM, ERP or bespoke systems.
Requirements for a sustainable data quality check
Completeness
All mandatory fields (e.g. name, address, contact details) must be completed. Missing values are detected and flagged as incomplete records.
Accuracy
Data must be factually correct and plausible (e.g. valid email addresses, existing postcodes, syntactically correct telephone numbers).
Absence of redundancy
Duplicate detection ensures that each customer is recorded only once in the system. Similar entries (e.g. those with slightly different spellings) are merged or flagged for review.
Timeliness
Data must be checked regularly to ensure it is up to date (e.g. to identify out-of-date addresses, inactive email addresses or expired contracts).
Consistency
Data must not contradict each other within the system (e.g. country and dialling code must match, and title and gender must correspond).
Integrity
Links to other data objects (e.g. assignment to a sales region, customer category or contact person) must be valid and exist.
Logging
To ensure a sustainable process, all vulnerabilities identified and the actions taken to address them must be documented.
Prioritisation
Quality defects must be assessed according to their business relevance and prioritised for subsequent processing.
Action-oriented approach
Action-oriented: The results must identify specific, actionable measures for checking and correcting data.
Our structured audit process
Your benefits at a glance
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Objective quality status of your dataTransparent assessment rather than subjective judgement.
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Rapid identification of vulnerabilitiesA clear overview of critical data fields and areas requiring action.
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Audit-proof documentationA clear and comprehensible analysis with a robust presentation of results.
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Cross-system analysisA comprehensive overview of your data landscape.
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Clear recommendations for actionConcrete, prioritised measures rather than theoretical concepts.
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Can be expanded in a modular fashion to include data cleansing and monitoringA direct transition to operational optimisation is possible.
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Minimal effort for your IT and business departmentsEfficient analysis using a clearly structured approach.
Find out what your data has to offer.
The data quality check is the first step towards becoming a data-driven organisation. It highlights where action is needed – and how you can prepare your data for CRM, BI, automation and digital customer processes. We would be happy to support you in the next step, whether that involves operational data cleansing or setting up a continuous quality monitoring system.
Contact
Let’s work together to measurably improve your data quality – please get in touch.
FAQ
A data quality check systematically analyses the quality of your data and highlights any weaknesses. It lays the foundation for reliable, efficient and future-proof customer processes by identifying issues such as incomplete, out-of-date or inconsistent data.
As part of the check, key quality dimensions such as completeness, consistency, timeliness, plausibility and the absence of redundancy are examined. In addition, the structural quality, transparency and business relevance of data deficiencies are assessed. For customer data, we take all important aspects into account, e.g. name structure, title, salutation, academic titles, company name, address, telephone number and email address. We check whether any changes of address are known, whether individuals have passed away, or whether there have been any changes affecting corporate clients.
You send us your data via a secure transmission channel. We convert the incoming data into a standard format. Our data quality tools check the data and generate both a summary report and a list of anomalies and potential errors for each customer record. The check is then repeated at regular intervals – for example, monthly.
You will gain an objective overview of the data quality of your customer data. You will quickly identify weaknesses and receive specific, prioritised recommendations for improvement. This lays the foundation for sustainable optimisations such as data cleansing and monitoring. As a result, you will ensure smooth processes, reach your customers and gain a holistic view of your customers.