Predictive Scores API

REACH Predictive Scores API returns data built from Versium’s predictive analytics engine. These scores help businesses understand specific consumer behavior characteristics that improve marketing efficiencies.

Predictive Scores utilize machine learning and complex algorithms to produce predictive models that score likelihood to take a specific action. Predictive Scores available include:

Auto Finance Score – predicts and ranks the value of auto buyer prospects
Donor Score – predicts likelihood to donate to a cause – charitable or political
Green Score – predicts environmentally consciousness, and likelihood to purchase green products or services
Wealth Score – predicts discretionary buying power
DIY Score - predicts DIY interest
New Tech Adopter Score - predicts New Tech interest
Online Shopper Score - predicts Online Shopper buying propensity
Travel Score - predicts Travel buying propensity

Predictive scores can be appended to customer lists, prospect lists or existing enterprise applications via APIs so that businesses can easily act on a single piece of information.

Scores range from 0 to 99 - the higher the score the higher the predictive propensity.

Format

Here's the format to call the Predictive Scores API:

Example

Example:

https://api.versium.com/v2/predictiveScores?output[]=auto_finance_score&first=joe&last=smith&[email protected]

Output Type - what data will be returned by the API

Output type is what the user would like to obtain from the Predictive Scores API. There are eight different types of output type as described in the below table.

Output Type
auto_finance_score
donor_score
green_score
wealth_score
diy_score
new_tech_adopter_score
online_shopper_score
travel_score

Note: multiple output type can be used at the same time, for example:

https://api.versium.com/v2/predictiveScores?output[]=auto_finance_score&output[]=donor_score&output[]=green_score&first=joe&last=smith&[email protected]

Inputs - what the API uses to search

This API accepts a consumer first and last name, and any other known consumer contact information listed in Common Inputs and API Parameters.

For hashed input details, please visit Hashed Input Support

The below table provides a quick reference on the inputs that can be used.

Value	Description	Example
first	A person’s first name	Joe
last	A person’s last name	Smith
address	A house/building number and street	123 Main St.
city	A city name	Redmond
state	A US state two letter abbreviation	WA
zip	A 5 digit US ZIP code	98052
phone	A valid 10 digit North American phone number	2031235555
email	A valid email address	[email protected]

The API will then match your inputs with consumers in the Versium Data store, and returns business information, as available.

Optional Parameters

At present, the Predictive Scores API does not have optional parameters.

Output Sample

Predictive Scores

{
  "versium": {
    "version": "2.0",
    "match_counts": {
      "auto_finance_score": 1,
      "donor_score": 1,
      "green_score": 1,
      "wealth_score": 1,
      "diy_score": 1,
      "new_tech_adopter_score": 1,
      "online_shopper_score": 1,
      "travel_score": 1
    },
    "num_matches": 8,
    "num_results": 1,
    "query_id": "feac636723969c5cad81040496030a54",
    "query_time": 1.0294029712677002,
    "results": [
      {
        "AutoFinanceScoreNorm": "41",
        "DonorScoreNorm": "87",
        "GreenScoreNorm": "32",
        "WealthScoreNorm": "88",
        "DIYScoreNorm": "46",
        "NewTechAdopterScoreNorm": "46",
        "OnlineShopperScoreNorm": "79",
        "TravelScoreNorm": "66"
      }
    ],
    "input_query": {
      "first": "john",
      "last": "smith",
      "city": "redmond",
      "state": "wa"
    }
  }
}