The importance of data in business is now unanimously recognized. Data is the engine of customer relations, business strategy and any marketing project. Investing in data management solutions is a no-brainer for many businesses. However, the quality of the data they include is still lagging behind in becoming a priority. How to effectively capitalize on incomplete, imprecise or even inaccessible information? The value of a piece of data depends above all on its quality. Data quality is thus at the heart of business issues. The qualification process must start as soon as the data is integratedwithin the organization. A major challenge when you know that once stored, cross-referenced and analyzed, qualified data brings high added value at all levels of the company.
Data quality: definition
Before getting to the heart of the matter, it seems necessary to define what quality data really is. According to Axysweb, data quality covers several dimensions : completeness, consistency, validity, updating, availability and traceability.
Data completeness and accuracy
Do we have all the necessary information about a prospect, a customer, a supplier to be able to interact effectively with him?
Validity is the second characteristic of qualified data. Quality data is error-free information, free of typos or syntax errors in names, numbers, stored addresses, etc.
Standardization allows the unification of data and plays in favor of their validity. The organization must set itself a standard to follow , for example it only uses full addresses and not abbreviations: “Avenue” instead of “Av.”.
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To create value, data must absolutely be recent . Updating is an important issue because the value of the information that a company holds decreases over time. The data held by companies is changing very quickly: turnover, workforce, product prices, etc.
Data quality involves cleaning and regular updating , at the risk of becoming obsolete and having a negative impact on the company’s strategy.
Availability is another key point. Is the data accessible in the company’s analytics applications ? Are they usable quickly by business users? Are they stored in the right place, in the right format ? How long does an employee take to find the information necessary for his activity?
Establishing data traceability in the company promotes qualification. Users must be able to be sure of the origin of the data they use on a daily basis in their daily activities, at the risk of ending up with unusable information later on.
Data quality thus corresponds to the ability of companies to maintain the durability of their data by keeping them complete, consistent, up-to-date and available in the context of sales, marketing, HR and other operations, etc.
Data quality: what benefits for the company?
Data is the fuel for analytics applications and business operations. Ensuring the quality of data means guaranteeing effective sales and loyalty actions . Data quality also makes it possible to optimize the impact of marketing and HR campaigns . This practice represents several advantages for the company.
The data collected, qualified, stored and then analyzed by a company allows it to generate more business opportunities and to distinguish itself from the competition .
The better the company knows its prospects, the better the sales teams will be able to adapt their speeches and sell effectively . The quality of the information is decisive for guaranteeing precise targeting , segmenting prospects and relying on real and relevant indicators .
Among other things, an in-depth knowledge of the customer will make it possible to set up personalized exchanges with him , and therefore to create stronger links .
The qualification of the data also makes it possible to avoid harmful errors : non-receipt of a letter because of bad coordinates, reiteration of the requests for information to the customer, etc… These errors are a source of frustration and degrade the customer relationship.
Benefiting from qualified data makes it possible to individualize the customer experience as much as possible by personalizing messages, offers and providing different responses.
The better you know your customer, the better you will be able to satisfy him by getting closer to his expectations. This is where you will enrich the customer experience .
At the same time, relevant data on your customer will allow you to arouse their trust and create a feeling of closeness with them.