One of the key features of Service Objects’ Lead Validation products is customizable scoring criteria for scoring a lead. These criteria, in turn, help you make better decisions about leads by letting YOU choose which data are more important or less important in their contact data. These criteria are collectively known as a test type.
In this article, we will discuss how having different test types for business versus residential data can give you more flexibility in scoring and processing your leads. Understanding these differences helps in tailoring validation processes to ensure accurate and relevant lead data for marketing and sales efforts.
Generally, a test type involves instructions for the API to tell it which data points to score, and how. Each test type is designed to check various elements such as address accuracy, phone number legitimacy, email validity, and whether a lead is classified as business or residential.
When discussing test types for Lead Validation International, particularly for distinguishing business from residential leads, it is essential to understand their distinct characteristics and implications. Business leads often require verification of company data, such as corporate addresses and phone numbers, ensuring that the lead is connected to a legitimate business entity. Residential leads, on the other hand, focus on verifying personal contact information, like home addresses and personal phone numbers.
This means that using the correct test type can be extremely important for whether a lead is scored correctly. To see an example of the distinction between business and residential test types, let’s take a look at an example of a business lead and a residential lead, and see how each kind of test type scores each lead.
Example 1: Business Lead
Name: Alexandra Stuart
Address: 136 West Canon Perdido St STE D, Santa Barbara, CA 93101-8207
Email: astuart@serviceobjects.com
Phone 805-963-1700 ext.744
IP: 98.185.249.94
Company name (considered in business test type only): Service Objects
For this lead, we will use test types normal1p and business to score the data points for name, address, email, phone, and IP address. The following table shows the results for each test type. (Note: Some empty output fields have been removed for brevity.)
business
{
"OverallCertainty": "100",
"OverallQuality": "Accept",
"LeadType": "BUSINESS",
"LeadCountry": "US",
"NoteCodes": "101,102,103,106,107,108,109,110,111,120",
"NoteDesc": "IsNamePhoneMatch,IsPhoneAddressMatch,IsNamePhoneAddressMatch,IsNameEmailMatch,IsPhoneEmailMatch,IsBusinessEmailMatch,IsBusinessGoodEmailMatch,IsNameGoodEmailMatch,IsPhoneContactGoodEmailMatch,IsIPAddressLocationMatchHIGH",
"NameCertainty": "100",
"NameQuality": "Accept",
"FirstName": "Alexandra",
"LastName": "Stuart",
"NameNoteCodes": "102,103,105,110,111",
"NameNoteDesc": "IsFirstNameKnown,IsLastNameKnown,IsFemaleGender,IsCommonFirstName,IsCommonLastName",
"AddressCertainty": "80",
"AddressQuality": "Accept",
"AddressResolutionLevel": "DPV",
"AddressLine1": "136 W Canon Perdido St STE D",
"AddressLine2": "Santa Barbara, CA 93101-8207",
"AddressLocality": "Santa Barbara",
"AddressAdminArea": "CA",
"AddressPostalCode": "93101-8207",
"AddressNoteCodes": "102,107",
"AddressNoteDesc": "IsDeliverable,IsBusinessAddress",
"EmailCertainty": "100",
"EmailQuality": "Accept",
"EmailCorrected": "astuart@serviceobjects.com",
"EmailNoteCodes": "101,107",
"EmailNoteDesc": "IsGoodMailBox,IsBusinessEmail",
"IPCertainty": "100",
"IPQuality": "Accept",
"IPLocality": "Santa Barbara",
"IPAdminArea": "CA",
"IPCountry": "US",
"Phone1Certainty": "100",
"Phone1Quality": "Accept",
"Phone1Locality": "Cambria",
"Phone1AdminArea": "Ca",
"Phone1NoteCodes": "106,111,112",
"Phone1NoteDesc": "IsVOIP,IsBusiness,IsPorted",
"PhoneContact": {
"Name": "SERVICE OBJECTS",
"Address": "27 E COTA ST STE 500",
"City": "SANTA BARBARA",
"State": "CA",
"Zip": "93101-7602",
"Type": "BUSINESS"
},
"BusinessCertainty": "100",
"BusinessQuality": "Accept"
}
normal1p
{
"OverallCertainty": "64",
"OverallQuality": "Review",
"LeadType": "BUSINESS",
"LeadCountry": "US",
"NoteCodes": "106,110,120",
"NoteDesc": "IsNameEmailMatch,IsNameGoodEmailMatch,IsIPAddressLocationMatchHIGH",
"NameCertainty": "80",
"NameQuality": "Accept",
"FirstName": "Alexandra",
"LastName": "Stuart",
"NameNoteCodes": "102,103,105,110,111",
"NameNoteDesc": "IsFirstNameKnown,IsLastNameKnown,IsFemaleGender,IsCommonFirstName,IsCommonLastName",
"AddressCertainty": "40",
"AddressQuality": "Reject",
"AddressResolutionLevel": "DPV",
"AddressLine1": "136 W Canon Perdido St STE D",
"AddressLine2": "Santa Barbara, CA 93101-8207",
"AddressLocality": "Santa Barbara",
"AddressAdminArea": "CA",
"AddressPostalCode": "93101-8207",
"AddressNoteCodes": "102,107",
"AddressNoteDesc": "IsDeliverable,IsBusinessAddress",
"EmailCertainty": "100",
"EmailQuality": "Accept",
"EmailCorrected": "astuart@serviceobjects.com",
"EmailNoteCodes": "101,107",
"EmailNoteDesc": "IsGoodMailBox,IsBusinessEmail",
"IPCertainty": "100",
"IPQuality": "Accept",
"IPLocality": "Santa Barbara",
"IPAdminArea": "CA",
"IPCountry": "US",
"IPNoteCodes": "",
"IPNoteDesc": "",
"Phone1Certainty": "10",
"Phone1Quality": "Reject",
"Phone1Locality": "Cambria",
"Phone1AdminArea": "Ca",
"Phone1NoteCodes": "106,111,112",
"Phone1NoteDesc": "IsVOIP,IsBusiness,IsPorted",
"PhoneContact": {
"Name": "SERVICE OBJECTS",
"Address": "27 E COTA ST STE 500",
"City": "SANTA BARBARA",
"State": "CA",
"Zip": "93101-7602",
"Type": "BUSINESS"
},
"BusinessCertainty": "0",
"BusinessQuality": "Accept"
}
There are some notable differences between these two cases – a powerful testament to how changing one aspect of the API request can drastically impact the results. We can see when the lead is tested with the appropriate test type (business in this case), the lead is correctly scored and indicates a high level of certainty that the lead is valid and contactable. However, when you switch the test type to a residential one (normal1p in this case), the results indicate that the lead should give pause for consideration.
Although all of the data points line up as shown by the business test type, since all of the data points tested correspond to business information, the lead becomes suspicious under a residential test type. If your business deals with residential leads, business data can be an indication of fraud. Not only do you want to make sure that the data points line up with each other and match, but also that they are the correct type of lead that fits your business.
Example 2: Residential Lead
Name: Alexandra Stuart
Address: 2407 W Kiowa St, Colorado Springs, CO 80904
Email: alexandrarstuart@gmail.com
Phone: [blocked out for privacy]
IP: 156.108.217.2
For this lead, we will use test types normal1p and businessonly to score the data points for name, address, email, phone, and IP address. The following table shows the results for each test type. (Note: Once again, some empty output fields have been removed for brevity.)
businessonly
{
"OverallCertainty": "66",
"OverallQuality": "Review",
"LeadType": "RESIDENTIAL",
"LeadCountry": "US",
"NoteCodes": "8,101,102,103,106,110,120,123",
"NoteDesc": "IsNotBusinessEmailMatch, IsNamePhoneMatch, IsPhoneAddressMatch, IsNamePhoneAddressMatch, IsNameEmailMatch, IsNameGoodEmailMatch, IsIPAddressLocationMatchHIGH, IsPhoneAddressLocationMatchHIGH",
"NameCertainty": "100",
"NameQuality": "Accept",
"FirstNameLatin": "",
"LastNameLatin": "",
"FirstName": "Alexandra",
"LastName": "Stuart",
"NameNoteCodes": "102,103,105,110,111",
"NameNoteDesc": "IsFirstNameKnown, IsLastNameKnown, IsFemaleGender, IsCommonFirstName, IsCommonLastName",
"AddressCertainty": "50",
"AddressQuality": "Reject",
"AddressResolutionLevel": "DPV",
"AddressLine1": "2407 W Kiowa St",
"AddressLine2": "Colorado Springs, CO 80904-2644",
"AddressLocality": "Colorado Springs",
"AddressAdminArea": "CO",
"AddressPostalCode": "80904-2644",
"AddressNoteCodes": "102,106",
"AddressNoteDesc": "IsDeliverable,IsResidentialAddress",
"EmailCertainty": "100",
"EmailQuality": "Accept",
"EmailCorrected": "alexandrarstuart@gmail.com",
"EmailNoteCodes": "101,105",
"EmailNoteDesc": "IsGoodMailBox,IsFreeEmail",
"IPCertainty": "100",
"IPQuality": "Accept",
"IPLocality": "Pueblo",
"IPAdminArea": "CO",
"IPCountry": "US",
"Phone1Certainty": "55",
"Phone1Quality": "Review",
"Phone1Locality": "Colorado Springs",
"Phone1AdminArea": "Co",
"Phone1NoteCodes": "102,105,110,113",
"Phone1NoteDesc": "IsActive, IsWireless, IsResidential, IsRecentlyPorted",
"PhoneContact": {
"Name": "ALEXANDR STUART",
"Address": "",
"City": "COLORADO SPRINGS",
"State": "CO",
"Zip": "80903",
"Type": "RESIDENTIAL"
},
"BusinessCertainty": "20",
"BusinessQuality": "Reject",
"BusinessNoteCodes": "1",
"BusinessNoteDesc": "BusinessNameNotGiven"
}
normal1p
{
"OverallCertainty": "100",
"OverallQuality": "Accept",
"LeadType": "RESIDENTIAL",
"LeadCountry": "US",
"NoteCodes": "101,106,107,110,111,120,123",
"NoteDesc": "IsNamePhoneMatch, IsNameEmailMatch, IsPhoneEmailMatch, IsNameGoodEmailMatch, IsPhoneContactGoodEmailMatch, IsIPAddressLocationMatchHIGH, IsPhoneAddressLocationMatchHIGH",
"NameCertainty": "100",
"NameQuality": "Accept",
"FirstNameLatin": "",
"LastNameLatin": "",
"FirstName": "Alexandra",
"LastName": "Stuart",
"NameNoteCodes": "102,103,105,110,111",
"NameNoteDesc": "IsFirstNameKnown, IsLastNameKnown, IsFemaleGender, IsCommonFirstName, IsCommonLastName",
"AddressCertainty": "80",
"AddressQuality": "Accept",
"AddressResolutionLevel": "DPV",
"AddressLine1": "2407 W Kiowa St",
"AddressLine2": "Colorado Springs, CO 80904-2644",
"AddressLocality": "Colorado Springs",
"AddressAdminArea": "CO",
"AddressPostalCode": "80904-2644",
"AddressNoteCodes": "102,106",
"AddressNoteDesc": "IsDeliverable, IsResidentialAddress",
"EmailCertainty": "100",
"EmailQuality": "Accept",
"EmailCorrected": "alexandrarstuart@gmail.com",
"EmailNoteCodes": "101,105",
"EmailNoteDesc": "IsGoodMailBox, IsFreeEmail",
"IPCertainty": "100",
"IPQuality": "Accept",
"IPLocality": "Pueblo",
"IPAdminArea": "CO",
"IPCountry": "US",
"Phone1Certainty": "100",
"Phone1Quality": "Accept",
"Phone1Locality": "Colorado Springs",
"Phone1AdminArea": "Co",
"Phone1NoteCodes": "102,105,110,113",
"Phone1NoteDesc": "IsActive, IsWireless, IsResidential, IsRecentlyPorted",
"PhoneContact": {
"Name": "ALEXANDR STUART",
"Address": "",
"City": "COLORADO SPRINGS",
"State": "CO",
"Zip": "80903",
"Type": "RESIDENTIAL"
},
"BusinessCertainty": "0",
"BusinessQuality": "Accept",
}
Once again, we see that the choice of test type is incredibly important in determining the validity of a lead. The lead data is the same in each case, but the switch of a test type can have serious consequences on the analysis of your results. We can see here that the residential address and phone data can make or break the status of the lead, even though all data points line up.
Choosing the Proper Test Type
In conclusion, distinguishing between residential and business test types is crucial for accurately validating lead data. Residential tests focus on personal contact details, while business tests verify company-related information. Understanding these differences ensures that lead validation processes are tailored to the specific needs of each type of lead, enhancing the effectiveness of marketing and sales efforts. Service Objects offers customizable test types, allowing clients to adapt the validation process to their unique requirements, ensuring the highest quality and relevance of lead data.
