Defining qualified contact information for your organisation: where should you start?
Your company has taken the plunge and equipped itself with a Data Quality solution? This is an excellent decision for enhancing your customer data and improving customer knowledge and relationships! However, you need to go one step futher and define what is considered a ‘qualified’ contact within your company. And there may be differing definitions, depending on function or use case. Several considerations need to be considered by the four main business lines that use customer data in a company.
Verified customer data, existing and reachable contacts, all unified customer by customer, without information loss: Data Quality generates multiple benefits for many of your internal departments.
But from one service to another, the use of data and the expected quality criteria are not necessarily the same. Standardized postal addresses, reachable and active emails and names entered without syntax errors are all aspects of Data Quality. How can you define the priorities that your data quality solution must meet according to the customer data use cases? The first constructive reflex: get your business lines involved!
Defining quality, dealing with non-quality: arbitrate!
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.
Business by business, to each their own Data Quality
For the marketing department, ensuring the profitability of marketing campaigns is a major challenge. However, when an email campaign is based on a database containing too many invalid or inactive emails, or when a text message campaign comes up against non-existent numbers, profitability is impacted. Therefore, one of the first requirements of marketing departments is to work with existing and reachable contact data.
> Email, and/or phone numbers, and/or postal addresses? Depending on the marketing department’s preferred contact data, the quality criteria must be chosen to avoid phenomena such as email or text messages that are “lost” or sent several times to the same customer, or undelivered mail. Some marketing departments will focus on emails first, others on all contact data – it’s up to your marketing department to decide.
At points of sale, salespeople give priority to advising customers, accompanying the purchase, recommending other products, and encouraging re-purchase. At this point of contact the problems associated with customer data must be discreet and “not disturbing”. The expectations here are more for assistance with data entry on loyalty program forms and real-time control of the accuracy of records. This will speed up interventions on customer files on the one hand, and on the other hand, will allow for referring to reliable customer data in order to answer customers’ questions.
> Input help is one of the Data Quality functions that is particularly relevant at the point of sale. Reflection in this area must also take into account the information that is really necessary for the sales staff – in other words, is it really useful to display all the customer data held in the database on their screens? Sorting out and making accessible only the data that is useful in store can thus be part of the arbitration.
In customer and CRM services, the need is above all for quick access to reliable data to establish a quality customer relationship, in which the customer is known and recognized, without any gaps in information. These services must be ceratin that all the information held on a customer is complete, up-to-date and accurate. They must also be able to respond quickly and without hesitation to questions asked by customers.
> The contact channels of your customer service orient the choice of Data Quality functionalities to be activated: telephone, email, web portal with forms to be filled in, or even all of them? The arbitration of the criteria activated to validate a record of verified and exploitable data must come from a reliable and complete view of the customer, but also from efficient operations, notably in the assistance and hotline services. Self-completion must also be studied, both for employees and for customers in self-care, for example on online support ticket requests.
The Digital and Data departments give priority to a coherent and easy-to-follow customer journey. The customer experience must not be too rough or too prone to abandonment, for example because of tedious forms, or initial text message or email exchanges that do not reach their recipient due to a lack of reliable contact data. However, it is important to find the balance between a smooth customer journey and reliable data recording.
> On the digital journey, the variations of Data Quality offer different levels and make it possible to go beyond the simple validation of the existence and syntax of contact information. In particular, the email addresses call for an alert to the user for immediate correction in case of error, since they can only be corrected by the customer for regulatory compliance reasons. Finally, autocompletion remains a relevant function to activate to accelerate data entry and make real-time records more reliable.
These points of attention allow you to start thinking about the appropriate Data Quality criteria for your company. To complete the process and to define exhaustive rules, you should be accompanied by an expert: your Data Quality vendor is there to help you avoid omitting anything and to anticipate the pitfalls. Ask them!
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.
+15
Year of
expertise
+400
Clients in all
sectors
3Md
Queries per
year
