The steps of global data management.

How to globally manage data after implementing Data Quality solutions?

How to globally manage data after implementing Data Quality solutions?

The challenges of data quality:
  • Ensuring the validity of a data during collection before it enters the database.
  • Avoiding incorrect data returns during marketing and sales campaigns: targeting the best audience with reliable data.

Data is not static; it changes and evolves over time. For example, an email address may be valid today but become a hard bounce in a few months. The same applies to postal addresses, as there can be relocations or changes in street names.

With preventive solutions, we ensure that the data is valid before it enters the database. Additionally, we continue to process the data regularly with corrective solutions.

How to manage this data in the RCU?With the integration of Data Quality solutions to enhance data quality:1st option: Simple integration by plugging in preventive solutions on e-commerce websites or in-store.2nd option: Integration of both preventive and corrective solutions, ensuring communication between the two through different systems.

Quality code:

To enable communication between preventive and corrective solutions, it is necessary to implement a quality code. These codes will be stored in your databases to identify the quality of the entered data and ensure its validity. Once the quality code is assigned to each field, it provides a snapshot of the database at a given moment and allows you to determine the quantity of valid data (e.g., “At a certain date, I had 95% of my data valid, and after implementing the quality codes, I have 99%”).

Once the data is stored and the quality codes are in place, you can begin the global data management project.

1: Storing high-quality data with the implementation of preventive solutions across various touchpoints:

On the web: If an address is incorrect due to an incorrect street number, the preventive solutions and quality code flag this issue, and it can be corrected. The same applies when someone enters their email address as “gmal” instead of “gmail.”

In-store: If an email address is incorrect but the salesperson enters it forcefully, the preventive solutions can help identify such issues.

Preventive solutions eliminate the majority of incorrect data, resulting in a database with 98% or 99% of correct data. The remaining data is either incorrect or questionable. Therefore, it is crucial to store in the database only the data that is qualified and, consequently, correct.

Process: We integrate the solution across various touchpoints. During the validation process, if an email address is found to be incorrect and forced, a quality code is assigned.

During email campaigns, we only select valid email addresses to preserve the reputation of IP addresses, increase deliverability rates, and ensure the success of marketing campaigns.

2: Implementation of corrective treatmentsOnce preventive solutions are in place, we revisit the database and reassign quality codes to establish an overall status of the database. Data is dynamic, so it is essential to regularly perform these treatments to maintain the desired level of quality using Data Quality solutions and routing.

For example, in the case of a hard bounce email, if the Laposte email server closes email addresses that have been inactive for the past 6 months, the quality code needs to be modified in your database. Through email, postal, SMS, or other actions, you can identify incorrect data and take appropriate actions to update the database with this information.

3: Management of incorrect dataTo address the remaining incorrect data, it is necessary to take action in order to recover reliable data:

1st possibility: Requalifying the data during customer contactExample: The customer returns to the store, and it is identified that one of their pieces of information is incorrect. The store interacts with the customer and asks them to correct the data and/or verify its accuracy. Once the correction is made, the quality code is updated. The same approach can be used when the customer logs into their online account, where an alert message can be sent to prompt them to update any incorrect details in their profile.This process can take longer as it relies on customers returning to the store or logging into their accounts online. However, it is highly effective because the store operator or salesperson can guide the customer through the necessary updates.

2nd possibility: Mass communicationsExample: If a postal address is identified as incorrect, an email can be sent to the customer inviting them to update the data. They would then be directed to a dedicated interface with the retailer’s logo where they can reenter the correct address. The same process can be applied to other data elements, such as sending an SMS campaign to prompt customers to update their email addresses.Mass communications can be done with or without Capency, where we provide advisory services and offer a dedicated interface for data updates. Once the data is updated, the information is reflected in the database. However, since there is no direct contact with the customer, this option may be less effective than the first possibility.

In summary ?

The quality code is the most important aspect in a comprehensive data management project. It is also crucial to implement preventive solutions to stop data leakage and then work on correcting the stored data to achieve a database with 100% accurate and usable data.Our objective is to provide guidance on implementing these solutions, as it is not always straightforward to create these fields.


How to proceed if it’s not possible to add quality code fields to the database?

The data needs to be regularly processed through Data Quality solution:
– By using a buffer database with quality codes assigned in case the system doesn’t allow adding fields. 
Through regular corrective processes before each marketing campaign.

And if I cannot install preventive solutions across all the front-ends?

With the establishment of a post-processing flow using CAPENCY web services to qualify the data without necessarily undergoing a complicated integration. Entries in degraded mode (for example, when an agency has lost connection with the web service) require different management: a quality code is assigned to indicate that the entry was made differently without verification. In the evening, we can revisit this entry and modify it if it is incorrect.

Should we perform corrective treatments if we are not processing postal addresses?

It depends on whether you have a possible link between your routings and your database. Through the routings, you can identify invalid emails and set the quality code in the database. Once the hard bounces are identified, you can reactivate them through our hard bounce reactivation service (refer to our webinar on this topic).

Data Quality
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