Recognize over 6,000,000 last names and 4,000,000 first names across different countries and languages.
Split dual names (ex. Mr and Mrs John and Mary Jones)
Assign gender based on known first names and prefixes.
Output preferred output Salutation name parts.
Basic Order of Operations
Create an instance of the request object
Populate the request element CustomerID with your product license key
Add input Names to the “Records” array with anywhere from 1 to 100 records
Call the method and pass in the request to the service using the WEB endpoint for JSON requests
Examine and parse the response from the reply object back from the service
Interpret the result codes
NOTE: It expects UTF-8 character encoding. Be on the lookout for question marks (?), squares (▖) or other weird characters like �. They may be an indication of encoding issues and may result in data loss. Bad encoding or character loss is not something our service can correct for you.
With a REST request, you can include all the input along with the URL for an easy and quick way of sending a single record.
curl –X GET https://globalName.melissadata.net/V3/WEB/GlobalName/doGlobalName?id=LICENSE_KEY &full=Doktor Enna Schäfer&ctry=DE&t=Global Name CurlExample
You can also put the URL without the "curl -X GET" command directly into your browser. You can also toggle between getting XML or JSON back using the format input parameter. As you can see, in this example, we are asking for JSON back.
You can send batch requests of up to 100 records per batch that are sent using HTTPS POST. This means you cannot send it in a browser like with HTTPS GET.
This is a string value that serves as a unique identifier for this set of records. It is returned as sent.
The License Key issued by Melissa.
Default. Preserve first name spellings; no correction allowed.
Allows first name misspelling corrections.
Name will always be treated as normal name order regardless of formatting or punctuation.
Default. If necessary, statistical logic will be employed to determine name order, with no bias toward either name order.
Name will always be treated as inverse name order, regardless of formatting or punctuation.
Bias toward male.
Default. No bias toward either gender.
Bias toward female.
Aggressive name genderizing.
Default. Neutral name genderizing.
Conservative name genderizing.
Default. Contains the name prefix, last name, and suffix. Ex: Mr. Smith MD
Contains the first name. Ex: John
Contains the fist name and last name. Ex: John Smith
Returns <blank>. Ex: <blank>
Company name to be standardized (Optional; Required if FullName is not inputted)
Full name to be genderized, standardized, and parsed (Optional; Required if Company is not inputted)
The Country ISO2, ISO3, or spelled out name. (Optional; default is US)
Input Best Practices
Single Record vs Batch Processing
Melissa Data cloud services are capable of both single record real-time processing and batch processing. The difference is simply in the number of records sent in each request. Melissa Data cloud services take an array of records. This array can contain a single record or 100 records. For a real time process like a web form entry or a call center application, send in a request with one record. For batch processing scenario like a database, send requests of up to 100 records until all the records are processed.
Since Melissa Data uses multiple clustered servers, in the unlikely event that one server is temporarily overloaded or down, it is very likely that another server is up and running. For this reason, it is best to catch any errors returned by the service and retry. We recommend retrying up to 5 times.
int Retry = 0;
Boolean ReqRet = false;
// Perform Phone Lookup and store results to the Response
ResPhone = PhoneClient.doPhoneCheck(ReqPhone);
ReqRet = true;
catch (Exception ex)
} while ((ReqRet == false) && (Retry < 5));2
Here is a sample response of the real-time request from above.
A unique identifier for the current record if one was sent in the request. Use this element to match a request record and the corresponding response record.
Comma delimited status, error codes, and change codes for the record.
The standardized company name.
The first identified prefix from the input full name.
The first identified first name from the input full name.
The first identified middle name from the input full name.
The first identified last from the input full name.
The first identified suffix from the input full name.
The first identified nickname from the input full name.
The first professional title from the input full name.
A one-character string value indicating the gender of the first name from the input.
The second identified prefix from the input full name.
The second identified first name from the input full name
The second identified middle name from the input full name.
The second identified last from the input full name.
The second identified suffix from the input full name.
The second identified nickname from the input full name.
The second professional title from the input full name.
A one-character string value indicating the gender of the second name from the input.
The first identified name properties which you can use to create the desired salutation format.
Melissa products use a result code system to indicate data quality; the status and any errors. These result codes are four-character codes (two letters followed by two numbers), delimited by commas. Result code definitions are shared among Melissa products. Instead of looking at multiple properties and methods to determine status, you can look at the output of the results parameter.
This example input: ‘Mr John and Mrs Mary Jones’ will return the result code string:
NS01, NS05, NS06, NS07, NS08
From these Result codes you can determine that the disposition of the Name is: