Customer service: 3 DataQuality use cases for responding quickly and well
According to Customer Experience Trends 2022 (Zendesk report), 70% of customers worldwide make their purchasing decisions based on the quality of service they receive. It is therefore strategic that your customer service provides them with quick and relevant answers. Data Quality facilitates the task of representatives, as illustrated by three common use cases in customer service and call centers.
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Your customer service department needs well-honed productivity tools, good customer knowledge, and a view of each customer’s history in order to respond quickly and effectively to their requests. The common denominator: reliable and unified customer data. This is why Data Quality Management is essential to strengthen operational processes. The proof is in 3 use cases that customer services and call centers know well.
1 - Create error-free customer records and avoid slow customer service
A customer has received their product but does not know how to operate it. Their reflex: call your customer service to get help. Talking directly with a representative is still a popular way for customers to explain their problem and receive tailored assistance.
This type of exchange is often an opportunity for the representative to create a customer file. However, collecting information can quickly become tedious when a name or address has to be spelled or repeated, not to mention that manual entry of customer data is one of the largest sources of error. All this affects the exchange, because the representative spends too much time on it to the detriment of listening to the customer’s problem. In addition, the customer file will be of little use in the future if it contains incomplete or invalid contact information.
In this scenario, Data Quality is a necessity in order to create customer records without guesswork and without wasting time. Functionalities such as data entry assistance and real-time control of information reduce the creation of a file to a simple and fast formality. The representative is assisted with input suggestions at the right time – street name, first elements before the “@” of an email address, among other elements. A dynamic check immediately identifies any input errors and validates the contactability of email addresses and phone numbers.
The representative can then move on to the creation of a support ticket without delay and listen to the customer’s problem.
2 - Immediately locate an existing customer who is already present in the database
Another classic case in a customer service department: a customer calls with a complaint, such as receiving the wrong product, after having created an account on the brand’s web portal. Without the implementation of Data Quality, the customer service representative cannot see, from their CRM tool, that a previous customer record exists in the web portal information system. This risks creating a new duplicate customer record and thus affecting the quality of the database.
With a DQM solution, it is possible to carry out a pre-existence search and thus avoid unnecessary re-entry, and of course generating duplicates. In this case, the file created by the customer in selfcare will appear on the representative’s screen thanks to a link between the DQM solution and the CRM tool. The representative can retrieve the customer profile directly from the support ticket tracking tool, without re-entering it, open the file and deal with the customer without any preliminary steps. Both the representative and the customer benefit from this, with time savings, accuracy, and a remedy that prevents duplication and guarantees the relevance of answers.
3 - Avoid customer service from the hindrance of duplicate data
It is not uncommon to have several customer records associated with the same person appear on the screen of a representative who takes a call. This is one of the most critical situations: which record should be used? Which one can you trust? These duplicates are a classic case, when the customer has used multiple points of contact with your company – email, previous call, online registration… Without identifying the duplicates or being able to merge them all, multiple customer records are entered. In fact, they inevitably contain differences that make them appear as separate records in the CRM tool – for example, a first name as an initial, then entered as a full name. They are also usually incomplete.
The solution consists in identifying that these records concern the same customer by dynamic deduplication, then reconciling the data they contain.
DQM’s state-of-the-art tools identify the master data to be retained, control the contact information, and then merge them into a single parent record that inherits all the validated elements.
These 3 use cases are part of daily life for your customer service department, in particular its call center, which is under pressure to provide relevant answers immediately. Offering an intelligent Data Quality Management system to your teams is not just a useful option, but a real imperative for efficiency and job satisfaction. It goes without saying that the customer relationship also benefits directly!
About DQE
Because data quality is essential to customer knowledge and the construction of a lasting relationship, since 2008, DQE has provided its clients with innovative and comprehensive solutions that facilitate the collection of reliable data.
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