Reduce effort in customer experience: customer data has a hand to play
Organizations need to watch out for an imbalance in effort in their relationship with customers. When customer experience becomes an obstacle course in resolving certain situations, the brand risks losing everything: loyalty, repeat purchase, notoriety and ultimately, revenue. To ensure that customers feel that they are in a fair relationship with your company, you need to concentrate on the quality of your contact information data and focus on automation that removes incidents that irritate customers.
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In its recent white paper “Customer Experience: Why treating customers fairly is the key to success”, Ipsos reminds us how much customer relations and ultimately revenues are impacted when a customer feels that he or she had to put more effort than the company to resolve a situation. In such a case, the probability that the customer will no longer use the company’s services or buy its products is multiplied by more than 4, while he will be 3 times more likely to share his negative experience and 2 times more likely to talk about it to his entourage. In other words, balancing the customer’s efforts along the customer journey is strategic in terms of encouraging buying behavior and sales performance.
In numerous situations clients are forced to make tremendous efforts when performing a task: entering data into a form numerous times before being able to validate it, re-explaining a problem to an umpteenth customer service representative, trying to understand why their loyalty points do not match what the brand has counted, receiving emails in duplicate or triplicate… Patience, like customer loyalty, is put to the test.
In most cases, intelligent Data Quality Management can lessen these efforts and restore the balance of energy deployed by both the customer and the brand.
Cleanse client data for a better experience
An essential part of the customer relationship is to talk to the right person, with the right contact information, using the right name. A correctly spelled first and last name, with the customer’s orders arriving at the correct address obviously contribute to a seamless customer experience. But above all, receiving a correctly labeled order saves the customer the effort of trying to understand why a particular package has not arrived, or whom they need to contact to confirm the default email address.
The quality of contact and identity data is, therefore, crucial in facilitating exchanges and even avoiding contentious situations. No company can really afford not to cleanse its customer database, update it, and maintain its quality on an ongoing basis. The relational quality that is played in the quality of customer data directly lightens the efforts of consumers committed to the brand. They also feel known and recognized and therefore, are more inclined to renew their purchase.
Simplify and make the opening of an account more reliable
Filling in a data form to open an account, be it to access online services or to make a purchase on an e-commerce platform, can quickly become an ordeal if the form is poorly designed and difficult to validate without input assistance. Who has never had to redo a form two or three times before being able to validate it, sometimes by having to scan the entire screen to understand “what’s blocking?” In this case, the effort requested from the client is too high, which creates a risk of abandonment.
To make the process easier for new registrants, Data Quality Management tools offer intelligent autocompletion solutions that also check the accuracy of an entry in real time. Some input fields such as addresses are completed automatically according to the national postal standards in force. If there is a problem with an entry, for example, a typo in the domain name of the email, the user is clearly warned of this and can immediately correct the mistake without having to look for it. This input help saves users valuable time, giving them every chance to fill out and validate the form quickly, in one go. With minimal effort, the account is opened without difficulty.
Unify customer data for the benefit of customer knowledge
When the quality of the client database is not optimal, knowledge of the client suffers. For customer service, it is difficult, if not impossible, to respond appropriately to a customer when their information is broken down into different customer files in different systems. So how can we have an overview and be able to consider everything that has forged the customer’s experience with the brand? This is the case, for example, with recording points in the context of a loyalty program. If the customer has earned loyalty points at different points of contact, all the points must be combined in the base used by the CRM tool for the correct count to appear.
In this case, as in others that require the customer to listen to endless explanations before having the final word, the solution lies in the ability to identify duplicates for the same customer and to unify them. Customer service can then work on a complete and reliable view, and respond intelligently to customers, thereby avoiding unnecessary entanglements.
Provide supportive customer service with no irritating experiences
When they approach an organization’s customer service department, customers expect to be recognized. When they ask questions or bring up a problem, they don’t want to have to reexplain the situation every time they use the service, which already requires an effort.
Businesses cannot afford this kind of weighty customer relationship. Here again, an overall view of the customer, knowledge of who they are and their contact habits with the company and working with reliable and accurate data are all imperative for the quality of the relationship and the relevance of the answers. Data Quality Management of customer data makes it possible to cut short many irritants. And even better than reducing the customer’s effort in the relationship, it enables the company to prove that it does the most to earn their satisfaction and loyalty.
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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