Vendor comparison address and data quality

Vendor comparison of address and data quality tools

   At this point we compare Data Quality Tools providers for you. We orientate ourselves and here strongly on the German Address and Data Quality Landscape which we published in July 2020. This will give you a good first overview of the diverse current German-speaking landscape.

To see the address and data quality landscape in full size, click here Data Quality Tool Landscape

You can sort according to your requirements using a few selected criteria. The selection of criteria varies from time to time.

All information in the table has been verified by the suppliers. For more information about the providers, read on below.

Anbieter Data Quality ToolDublettenerkennungFlexible Justierung der Match- bzw. Abgleichsregeln möglichVorschlag zur Fusionierung durch das SystemRegeln zur Zusammenführung der DublettenFüllgrad-AnalysenQualitäts-AnalysenAnreicherung durch externe DatenReporting zu den AnalysenIntegration in eine CRM-Systemlandschaft möglichIntegration in eine E-Commerce-Landschaft möglich
Deutsche Post Adress
Deutsche Post Direkt

Additional information on the individual providers:


  • Filling level analyses: checking and enrichment of the salutation, recognition and structuring of the name and address components and date of birth, checking and correction of postal addresses, telephone numbers and e-mail addresses
  • Quality analyses: name analyses (correctness of first and last names, static age, company name recognition), analysis of postal addresses, telephone numbers, e-mails, deliverability and confirmation of postal addresses
  • enrichment through external data: Telephone numbers (public sources), deliverability of postal address, information on relocation and deceased persons (internal: Deutsche Post Adress GmbH & Co. KG, ABIS GmbH, external: SAZ, eXotarget, Gemini, Axiom), telephone number and email address validation
  • Reporting: In the form of a standard report (ABIS audit) or individually according to requirements
  • Integration into an e-commerce or CRM software landscape: As an interface or software, currently as a customer-specific solution

Deutsche Post Address

  • 100% identical to the subsidiary ABIS
    1. Additionally: “topicality” and “internationality
    2. A core competence of Deutsche Post Adress is address updating. The relocation database POSTADRESS MOVE, based on redirection orders to Deutsche Post, is the database with the most new relocation notifications per year in Germany. Other reference data sources enable users to identify undeliverable addresses and addresses of deceased customers.
      Deutsche Post Adress also offers many services for master data maintenance and data quality optimization for international address data through its sales unit POSTADRESS GLOBAL. A global network of service providers enables companies to maintain addresses from almost every country in the world.

Deutsche Post Direkt

  • Option for application programming interface (API) for customer-specific on-premise setup
  • various enrichment of various additional information
  • Comprehensive reporting thanks to visualized address audit and/or customer profile analyses
  • Various integration paths for vendor-independent CRM system landscapes via API (REST, SOAP), web service or asynchronously for bulk files via SFTP
  • Established integrations for eCommerce applications via plugin for the following providers: Magento, Shopware, Plentymarkets or even GitHub for individually desired integration


  • Fill level analyses: postcode, town and address
  • All firmographic features can be enriched by external data
  • Reporting can be called up via online analysis


  • Fill level analyses; data set oriented and attribute oriented
  • Quality analyses: duplicate recognition, completeness check, consistency check, plausibility check, syntax check, semantic check
  • Enrichment: Address data/vendor data: Deutsche Post Direkt, Melissa Data, Bisnode, Creditreform, Jaroso
  • Reporting: External and regular temporal triggering, ad-hoc reporting, standard data quality key figures as well as individual data quality key figures, recording and presentation of the temporal development of data quality key figures, aggregation
  • Customized interfaces to e-commerce and CRM software landscapes: Salesforce, SugarCRM, SAP ERP (IDOC), MS Dynamics, Oracle, Pepolesoft, PSIpenta, Sage ERP, Comarch ERP

Kroll software

  • Enrichment by external data possible via ODBC/OLEDB or CV
  • Reporting on the analyses: duplicates found are clearly displayed with the degree of agreement.
  • Kroll software is a standalone and can access any tables, therefore it can be connected to e-commerce or CRM software landscapes


  • Filling level analyses: absolute and percentage possible
  • enrichment through external data: Any data sources, e.g. insolvencies, relocation information, deliverability, phone numbers, deceased verification, commercial register information, company information (employees, industry, etc.) and geo coordinates.
  • Reporting: Capture performance data and KPIs for processes or as evaluation of the complete data stock. Support of third-party applications, e.g. Grafana or Power BI
  • Integration is possible: in Microsoft CRM, C4/HANA, Salesforce, Microsoft Business Central, SAP and many other systems via REST/SOAP Services, the frontend is simply possible



  • Duplicate detection: Any number of data sources, all common data formats and databases. Furthermore: postal address check, name check, check of further data (including UST-ID, IBAN, e-mail, domain, etc.), data formatting (telephone numbers, data, etc.)
  • search rules: Automatically generated rules for standard tasks, individual definition of rules: Individually configurable down to field level. Several rules can be applied in parallel (e.g. name / address, first name / mobile number, VAT ID). Hierarchical data structures (e.g. company/contact person), reference data and dictionaries (individual additions/adaptations), result postprocessing incl. team processing.
  • Interface for the user: Windows (Ribbon-based GUI) or command-line variant for integration into processing procedures.
  • Proposal for fusion: q.address supported:
  1. Selection: Selection of a data set (required, for example, if the data of several
    address suppliers to be merged)
  2. Merge: Merging at field level (“merging without data loss”)
  3. In-place-Cleansing: Inventory Cleansing in Dynamics 365 CE (CRM), Salesforce, SAP CRM
  4. Rules: a) Priority at the level of the data source (file), record and data field, b) Priority according to record/data field quality, age etc.
  • Fill level analyses as counts
  • Quality analyses: Countings (incl. consideration of data quality, e.g. number and type of duplicates, correct postal codes, spelling etc.)
  • Enrichment through external data: beDirect, BDS Online, Creditreform. Furthermore: any other data provided
  • Reporting: Prepared analyses
  • Integration in CRM system landscapes: Ready integrations in Dynamics 365 Customer Engagement (CE/CRM), Dynamics 365 Business Central (BC/NAV), Salesforce, SAP CRM. Furthermore: For own integrations we offer: q.address Quality Server, q.address Cloud Services
  • Integration into an e-commerce system landscape possible via q.address Quality Server and q.address Cloud Services


  • The fill level analyses work on each original field, as well as all validation results or enrichment potentials
  • Quality analyses: In addition to the validation, assurance and production of good data quality, there are additional solutions for the analysis of complete data sets and the presentation of the respective results in dedicated data quality dashboards and reports. Furthermore, any results can be imported into existing BI systems via interfaces.
  • Integration in e-commerce and CRM system environments is possible: All solutions from Uniserv can integrate a wide range of APIs in any system (CRM, ERP, e-commerce, MDM, etc.). Dedicated and certified plug&play connectors are available for the entire SAP platform. For Microsoft Dynamics, Salesforce, Aurea and many others, there is a partner network, as well as corresponding project experience.
  • central post-processing console or the datasteward console


  • Fill level analyses: breaking down and sorting the components of names and addresses and checking and correcting personal data such as address, e-mail and telephone number and adding missing components (e.g. postcode)
  • Quality analyses: address validation, address auto-completion, e-mail validation, telephone number verification, name analysis, identity check, duplicate check and geocoding
  • Enrichment through external data: Melissa offers a wide range of data quality solutions in the field of address management. There are various partnerships and data sources for this purpose – in each case for the appropriate solutions.
  • Reporting on the analyses: On request, a Data Quality Report can be created to give you an insight into your data with the statistics. In addition, result codes are issued for the individual solutions, which show you the errors (e.g. errors in the postal code) and the changes (e.g. postal code changed).
  • Integration in a CRM landscape: As a Web Service, Microsoft Dynamics CRM, Oracle (including PepoleSoft)
  • Integration into an e-commerce system landscape: As REST interface. PlugIns, e.g. for Magento and Shopware


  • Fill level analysis for master data (name, address, dates of birth)
  • Quality analyses for master data (name, address, dates of birth)
    • Listing of the characteristics mentioned
    • Minimum and maximum values
    • Correctness check
    • Check for completeness
  • Enrichment through external data:
    • Geocoordinates for addresses
    • statistical districts automotive industry
  • Integration in CRM landscape possible in:
    • MS Dynamics 360
    • Salesforce



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