Nationalize

App · Contact Management · 4 actions

Predict which country a name most likely comes from. Send a surname like Nguyen or a full name like Sarah Johnson and Nationalize answers with up to five countries, each with a probability and the number of records behind it, so a workflow can route a lead to the right regional team, pick a language to write in, or fill in a likely country on a contact record. Names can be checked one at a time or a hundred at once.

Actions

ActionWhat it does
Check a name against a countryCheck whether a name is likely to come from one particular country: for routing a lead to a regional team or picking a language to write in.
Check your remaining namesCheck how many names your Nationalize plan has left this billing period, so a workflow can hold off on a large batch rather than run out halfway.
Predict nationalityPredict which country a name is most likely to come from.
Predict nationality for several namesPredict where each name in a list is from, in a single request: for enriching a list of contacts or a spreadsheet column.

Check a name against a country

Check whether a name is likely to come from one particular country: for routing a lead to a regional team or picking a language to write in. Answers yes or no with a probability rather than failing, and says which country the name really points to when the answer is no.

Inputs

NamenametextRequired
The name to place. A surname on its own works, and a full name works better -- 'Sarah Johnson' is a stronger prediction than 'Johnson'. Titles, initials and nicknames are fine, the order of the parts does not matter, and accents are optional.
CountrycountrytextRequired
The country to check the name against.One of: AF (Afghanistan), AX (Åland Islands), AL (Albania), DZ (Algeria), AS (American Samoa), AD (Andorra), AO (Angola), AI (Anguilla), AQ (Antarctica), AG (Antigua & Barbuda), and 239 more.

Outputs

countrytext
The country it was checked against.
country_codetext
That country's two-letter code.
is_likelytrue/false
True when Nationalize lists this country among the name's likely origins.
nametext
The name checked.
probabilitynumber
How likely this country is, between 0 and 1. Zero when Nationalize does not list it at all.
ranknumber
Where this country places among the name's countries, 1 being the most likely. Empty when it is not among them.
recordsnumber
How many records the prediction is based on.
top_countrytext
The country the name most likely comes from.
top_country_codetext
That country's two-letter code.
top_probabilitynumber
How likely that country is, between 0 and 1.
urltext
Nationalize's website.
Example output
{
  "country": "Japan",
  "country_code": "JP",
  "is_likely": true,
  "name": "Hiroshi Tanaka",
  "probability": 0.9312,
  "rank": 1,
  "records": 41208,
  "top_country": "Japan",
  "top_country_code": "JP",
  "top_probability": 0.9312,
  "url": "https://nationalize.io/"
}

Check your remaining names

Check how many names your Nationalize plan has left this billing period, so a workflow can hold off on a large batch rather than run out halfway. Nationalize reports this only alongside a lookup, so the check itself uses one name.

Inputs

None.

Outputs

names_allowednumber
How many names the plan allows per period.
names_remainingnumber
How many are left in the current period.
names_usednumber
How many have been used in this period.
resets_attext
When the period resets, in UTC.
resets_in_daysnumber
How many days until it resets.
urltext
Nationalize's website.
Example output
{
  "names_allowed": 2500,
  "names_remaining": 2371,
  "names_used": 129,
  "resets_at": "2026-10-01T00:00:00Z",
  "resets_in_days": 28,
  "url": "https://nationalize.io/"
}

Predict nationality

Predict which country a name is most likely to come from. Returns the most likely country on its own, so a step can use it straight away, with up to four runners-up behind it and the number of records the prediction rests on.

Inputs

NamenametextRequired
The name to place. A surname on its own works, and a full name works better -- 'Sarah Johnson' is a stronger prediction than 'Johnson'. Titles, initials and nicknames are fine, the order of the parts does not matter, and accents are optional.

Outputs

candidateslist
Up to five countries, most likely first.
countrytext
The most likely country's English name. Empty when not found.
country_codetext
The most likely country's two-letter code.
foundtrue/false
False when Nationalize has no records for this name.
nametext
The name that was looked up.
probabilitynumber
How likely the most likely country is, between 0 and 1.
recordsnumber
How many records the prediction is based on.
urltext
Nationalize's website.
Example output
{
  "candidates": [
    {
      "country": "United States",
      "country_code": "US",
      "probability": 0.4104,
      "rank": 1
    },
    {
      "country": "United Kingdom",
      "country_code": "GB",
      "probability": 0.1386,
      "rank": 2
    },
    {
      "country": "Canada",
      "country_code": "CA",
      "probability": 0.0494,
      "rank": 3
    },
    {
      "country": "Australia",
      "country_code": "AU",
      "probability": 0.0377,
      "rank": 4
    },
    {
      "country": "Nigeria",
      "country_code": "NG",
      "probability": 0.0295,
      "rank": 5
    }
  ],
  "country": "United States",
  "country_code": "US",
  "found": true,
  "name": "Sarah Johnson",
  "probability": 0.4104,
  "records": 2147809,
  "url": "https://nationalize.io/"
}

Predict nationality for several names

Predict where each name in a list is from, in a single request: for enriching a list of contacts or a spreadsheet column. Takes up to 100 names at a time. Each name counts against your monthly quota, so repeated names are looked up only once.

Inputs

NamesnameslistRequired
The names to place, one per entry. A surname works, a full name works better. Up to 100 at a time; repeated names are looked up once.

Outputs

found_countnumber
How many of them Nationalize could place.
name_countnumber
How many names were looked up.
resultslist
One answer per name, in the order given.
urltext
Nationalize's website.
Example output
{
  "found_count": 2,
  "name_count": 2,
  "results": [
    {
      "candidates": [
        {
          "country": "Vietnam",
          "country_code": "VN",
          "probability": 0.5612,
          "rank": 1
        },
        {
          "country": "United States",
          "country_code": "US",
          "probability": 0.0353,
          "rank": 2
        }
      ],
      "country": "Vietnam",
      "country_code": "VN",
      "found": true,
      "name": "Nguyen",
      "probability": 0.5612,
      "records": 360408
    },
    {
      "candidates": [
        {
          "country": "Germany",
          "country_code": "DE",
          "probability": 0.2245,
          "rank": 1
        },
        {
          "country": "Denmark",
          "country_code": "DK",
          "probability": 0.1201,
          "rank": 2
        }
      ],
      "country": "Germany",
      "country_code": "DE",
      "found": true,
      "name": "Schmidt",
      "probability": 0.2245,
      "records": 187032
    }
  ],
  "url": "https://nationalize.io/"
}

On this page