The initial step in creating a database is to manually gather contact information of healthcare professionals from reliable online and offline sources such as web journals, e-book subscription forms, visitor information collected from tradeshows, and news agencies to name a few.
Patent machine learning tools verify the contact information collected, and missing fields are appended in this stage, making it easier to compile and segment the contact list.
The data in the contact lists are put through an intense scanning process for validation, after which manual verification is done.
The data is then cross verified using social media platforms to authenticate the quality of the database.
Advanced algorithms are employed statistical and analytical techniques to check and correct anomalies.
The data cleansing process is then implemented to identify the presence of stale data, followed by manual inspection to ensure sublime data quality.
In this step, the data is carefully examined to enhance accuracy.
If any record requires manual fixing, our data experts step in to make relevant changes, after which the cycle of validation, verification, and cleaning is repeated.
To ensure compliance with global data policies such as CAN-SPAM, GDPR and CASL, consent-based information is legalized and legitimized through AB-tested opt-in email campaigns.
Tele-verification campaigns and opt-out mailers are sent to individuals included in our final list to confirm their consent to have their information displayed in our database.
Compliant
Compliant
Compliant
Compliant
Compliant
Compliant
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