Advantage
Significant Improvement for All Customer-Facing Processes
Data
Historical Data including Necessary Entities like Activities and Documents
Methods
Optimizing Data Quality
Challenge
An international hotel chain, after acquiring another hotel chain, faced the task of merging CRM data while avoiding duplicates and other errors. The customer data of both companies was available in identical versions of Salesforce.com® CRM systems.
Goal
Fast Cleanup and Consolidation of CRM Data to Optimally Support Processes Between Company and Customers Even After the Merger.
Solution
Even during the creation of the requirements profile, it became clear that the existing data, primarily due to contained duplicates, was not as good as initially assumed. Therefore, the comparison-relevant entries were first cleaned. A Machine Learning model was used to clean the addresses, for example, removing incorrect addresses or email addresses from the dataset. This also allowed for uniformity between the two CRM systems to be linked and differing designations to be standardized.
eoda performed duplicate detection during the merging of the two CRM systems using its own application. eoda not only identified clear duplicates but also similar entries in leads, companies, or contacts. The final step is the import into the target system, in this case, the Salesforce.com® CRM, with the cleaned customer data from both companies.
Result
The consolidation of data is crucial in a merger because data represents a vital asset. Fully merging historical data, including necessary entities like activities and documents, combined with optimizing data quality, provides a significant improvement for all customer-facing processes.
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We look forward to exchanging ideas with you.
Your expert on Data-Science-Projects:
Lutz Mastmayer
projects@eoda.de
Tel. +49 561 87948-370
