Customers, teams, decision-makers: what are the benefits of data quality?
Thanks to Data Quality, the value of customer data soars. When it is qualified and unified, data becomes a reliable asset with multiple benefits for business lines, decision-makersand customers.
For more data quality info: Subscribe to our newsletter on Linkedin
Data quality management is an integral part of data governance. Data quality management, combining data cleansing, real-time validation of data entry, deduplication and unification, makes this crucial asset more reliable and enables companies to make the most of it.
Quality data at the heart of a premium customer experience
You want to avoid rough spots on the customer journey! Filling in a data form to open an account, whether to access online services or to buy on an e-commerce platform, can quickly become a chore if the form is poorly designed and difficult to validate. That is why a fluid input experience has a positive impact on the conversion rate, starting at the contact form.
To make things easier for customers and prospects on the form, data quality management tools offer intelligent solutions to autocomplete fields and to check input accuracy in real time. This input help saves the user precious time, and gives them a greater chance of completing and validating the form quickly, in one go, without typing errors.
Optimizing both operational efficiency and marketing ROI
Currently, 73% of employees feel that their CRM does not provide verified data*. But many of our missions -welcoming and registering customers, serving and advising them, contacting them and communicating with them, for example – cannot be carried out perfectly without contacts that can be reached and contact details that can actually be used, a correctly spelled name, a known and recognized first name, and unified customer information.
In relational campaigns, being able to reach your customers, to get to know them, and to recognize them is essential. However, unreachable contacts impact the ROI of marketing and CRM campaigns. In email marketing, for example, distribution of emails to invalid or inactive addresses is a pure loss, and poses the risk of blacklisting by ISPs. Communicating using data that is verified, and having a contact that can be reached is a prerequisite. By processing contact databases that contain email addresses, telephone numbers, and postal addresses, campaign deliverability reaches new heights. A well-distributed campaign means a higher ROI!
A lever for strengthening internal data quality management
Data quality helps to nurture an in-house data culture – an asset for Chief Data Officers, of whom 69% spend the majority of their time on data acculturation initiatives**.
In the field, when faced with gaps in the quality of customer data, operational staff often try to adapt, without always being able to follow best practices. For example, when faced with duplicates: a customer service department gets into the habit of juggling several records when calling the same customer. This symptom of duplication in the database considerably slows down operations, hence the implementation of a makeshift solution to get around the obstacle. It is not uncommon to see departments writing micro-procedures, sometimes on a case-by-case basis, to explain where to find the right information for a customer among their various records.
Deploying a data quality solution helps to eliminate bad practices, for example by blocking form validation when there is data entered that is inaccurate, invalid, or already in the database. It contributes to employee satisfaction, who achieve better results when they work with reliable customer data. As such, data quality presents a convincing argument for acculturating teams to customer data: the results it brings in terms of operational efficiency.
Decision-making informed by quality data
As long as operations are running and reporting metrics are not showing suspicious numbers or variations, it is difficult to pinpoint data quality issues. However, reports can be distorted if the customer database is full of duplicates, because the number of customers recorded in the database is artificially inflated. This is enough to have a negative effect on several elements. Customer data deduplication and unification are essential in order to remedy this situation. this situation.
And that is not all: the unification of correctly deduplicated data helps to give better knowledge of the customer, and eliminates the confusion and approximations caused by duplication. This is an essential factor in understanding each customer’s journey with the company and serving them better. Data quality thus makes arbitration more reliable in terms of segmentation, customer relations, and adaptation of the service offering.
Data quality provides benefits in terms of costs and compliance
High-quality data is easy to locate and consult. Data quality avoids tedious tasks such as recreating or searching for data sets. A major benefit, given that 28%*** of salespeople spend only 28% of their weekly time on selling, as they are occupied with manual tasks such as data entry.
With qualified data, this working time can be allocated to far more profitable tasks. It is also easier to store quality data in the right environment, and collect and compile it into the various reports required, especially for regulatory purposes. Consequently, the company is in a better position to ensure compliance and avoid penalties.
*Forrester, 2022
**AWS & MIT CDOIQ, 2023
***Salesforce, 2023
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.
17
Year of
expertise
800
Clients in all
sectors
3Md
Queries per
year
