Data quality products from TOLERANT Software tap the full potential of CRM systems, making AI and business intelligence applications possible in the first place.
CRM systems are wonderful tools for managing and maintaining customer relationships. They make it possible to invite relevant customers to the trade fair, to offer special offers to certain customers or to accompany them on the customer journey in a targeted manner. But all these measures come to nothing if the customer data is not properly maintained. An incorrect salutation in the customer address is one of the more minor errors. A lack of data quality has more serious consequences if customers are incorrectly segmented as a result of an input error. Duplicates in the customer base can lead to the history of a customer being incorrectly evaluated. A regular customer of many years’ standing is then treated as a supposed new customer because his or her double has only recently been created. The sales or marketing measures offered by the CRM system are useless if the customer data is not properly maintained. Without high data quality, sales and marketing managers cannot fully exploit the potential of CRM systems.
But what characterises good data quality and how can it be achieved? Good data quality requires that the data is captured correctly on the one hand and maintained continuously on the other. For consistent and complete recording, the data must be entered uniformly and according to the same pattern, so that they are coherent and fit together. All data fields must be filled in without gaps. Inconsistent postcodes that do not match the city or female first names that are combined with the male form of address are trivial input errors that can lead to returns or loss of image. With a structured master data management and a regular comparison with relocation and deceased data, the quality of the data can be sustainably ensured. But only a few companies employ a person responsible for data quality who takes care of this.
A remedy is provided by data quality programmes that identify discrepancies and help to rectify them. The data quality products from TOLERANT Software support CRM users right from the input stage and ensure that data is recorded homogeneously and consistently. With the help of reference data, the TOLERANT Post and TOLERANT Bank programmes validate postcodes and SEPA bank data, for example, and complete them automatically. The TOLERANT Name software analyses names and automatically structures them with a syntax check into the components salutation, title, first name and surname, so that the user only has to fill in a single name field. The assignment takes place automatically. The tool also checks whether the gender is entered correctly and whether the first name matches the salutation. At the core of all products, TOLERANT Software uses error-tolerant search functions, whereby the entire database is fuzzily searched so that duplicates are avoided from the outset. For example, if a user enters the name “Alex Schepanski” in the search field, the programme will find similar spellings such as “Alexander Sczepansky” within seconds if they already exist in the database. The same function also detects duplicates when merging different databases with TOLERANT Match. Move data can be checked and cleansed using reference data with the TOLERANT Move tool.
“Well-maintained data is a basic requirement for working with customer relationship systems,” confirms Stefan Sedlacek, one of the three managing directors of TOLERANT Software. “Our products create order in the databases and thus extract the full potential from CRM systems.”
Open interfaces connect TOLERANT Software’s data quality products directly to popular CRM systems such as Siebel, Oracle or Salesforce. This eliminates the need for data cleansing at intervals. The TOLERANT products integrated into the CRM system ensure consistently good data quality and thus strengthen the relationship with the customer.
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