This easy-to-install component allows you to simply select a table or range of records in Excel and have a Melissa Data server correct, verify, and append missing data. Personator goes beyond simple contact data validation and performs cutting-edge data quality uplift, which cross-references the validity of data by verifying the customer record is deliverable, and that names correspond to address, email, and telephone data. It can also ensure that the record is complete with all contact points appended. Achieving data quality uplift is considered to be the highest level of data accuracy.
Flexible payment model for different size business needs
In addition to the traditional Automatic Recurring Billing payment model for high volume customers, Listware provides a flexible pay-as-you-use option - giving purchase-as-needed access for businesses where demand fluctuates. This is achieved by a new credit purchase system. A shopping cart checkout links the user to a menu of services and required credits per record enabling one to purchase the right number of credits for the required service.
In the above example, the customer has selected to purchase enough credits to Check, Verify and Geocode 50,000 records. In addition to those services performed on each record, he is purchasing enough credits to Append Phone Numbers and Move Updates to records where that data is available. The Melissa Data Shopping cart will calculate the total cost for billing and dispense the credits into the customer's account for usage.
Unique billing for appended data
After selecting the input range of data, and choosing the data quality operations to be performed and output options, Listware for Excel will estimate the amount of credits required.
Why approximate credit consumption? For Move Update and Append services, your credits will only be consumed upon success - you pay only if this data is appended, making this a uniquely priced solution.
Your data will be verified and updated via a Web service call underneath the component to Melissa Data's servers, making the data quality process seamless.
Concise record summary counts and color coordinated output cell options make viewing and analyzing the output results easy, while the Review option gives the user a visual interface to step through records where errors were found. In cases where obvious data format errors caused the error, the user can edit, re-scan and save the new results - resolving records in an interactive fashion.
For larger data sets where interactive analyzing isn't practical, Listware returns a series of status and error codes which can be queried to filter records of the desired criteria.
There's no coding, data importing, or output-export conversions necessary. Reading, processing and saving the output results are all done directly in Excel!
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