Overview
Welcome to EverString developer docs! This page will guide you on how to use EverString’s Enrichment API. The following section has details on how to generate an access token that you need to access the Enrichment API. The Enrichment section will help you understand the API, the various Request Parameters and the expected Response Formats. You will also find sample requests and responses.
Getting Started
To authorize, use this code:
# With shell, you can just pass the correct header with each request
curl "https://api.everstring.com/v1/companies/data_enrich"
-H "Authorization: Token {Access_Token}"
Replace the {Access_Token} with the token generated from the EAP platform.
Before you can access the Enrichment API, you need to generate an access token, that you will pass with every call. Access token can be generated by logging into EAP as an administrator. Once you log in, click on “Account” in the top right corner, select the REST API tab and click the refresh icon. Remember that generating a new access token will invalidate the existing access token.
Once you have an access token, you can call the enrichment API by passing the access token in the Authorization header in the following format:
Authorization: Token {Access_Token}
A sample call using cURL is in the example section.
Real Time Company Enrichment API
Endpoint URL: https://api.everstring.com/v1/companies/data_enrich
The Company Data Enrichment Real Time REST API provides an interface to access information available for companies in the EverString database. It takes as input a company website, email, name, address, phone, ecid and / or location id and returns enriched information as the output based on fuzzy (or direct) match.
Note: This API return will always include basic firmographics for the company matched even if nothing is passed in select parameters.
Basic firmographics: name, domain, ecid, locationId, street, city, state, zipcode, country, companyPhone, employeeSize, revenue(in thousands), industry, keywords, naics, sic, companyAge, numLocation, companyYearFounded.
Rate limit: 120 calls/minute if you only request basic firmographics for only one record, otherwise, it will be 20 API calls/minute
Request Parameters
Example Enrich single record request (with optional fields specified in select):
curl "https://api.everstring.com/v1/companies/data_enrich" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{
"address": {
"street": "",
"city": "",
"state": "",
"postcode": "",
"country": ""
},
"name": "EverString",
"website": "everstring.com",
"email": "contact@everstring.com",
"phone": {
"country": "United States",
"number": "(650) 425-3937"
},
"match_reasons": [{
"name": "E",
"website": "E",
"match_score": 5
}],
"select": ["businessToBusiness", "businessToConsumer", "marketingSophistication", "facilitiesInMultipleLocations", "employeesInMultipleLocations", "technologySpend", "marketingSpend", "salesSpend", "hrSpend", "financeSpend", "socialSophistication", "technologySophistication", "salesSophistication", "hrSophistication", "financeSophistication", "hrDeptStrength", "financeDeptStrength", "salesDeptStrength", "marketingDeptStrength", "techDeptStrength", "shippingProviders", "discounts", "shippingMethods", "onlineShopping", "numLemmas", "inc5000Bucket", "fortune500Bucket", "fundingLatestRound_age", "numInvestors", "investorNames", "fundingStrengthBucket", "fundTypes", "fundingTotalAmount", "fundingLatestRoundAmount", "numFundTypes", "top3_industries", "top3Websites", "hasMobileApp", "latestFundingDate", "alexaRank", "facebookUrl", "linkedinUrl", "twitterUrl", "description", "companyListNames", "similarCompanies", "intentTopic", "intentTime", "top5Naics", "models"],
"model_ids": [20000183, 20000173, 20000181]
}'
Example Enrich single record response:
{
"data": [
{
"ES_AdvancedInsights": [
{
"description": "Each funding type",
"name": "fund types",
"value": [
"Series B",
"Series A",
"Non Equity Assistance",
"Seed Round"
]
},
{
"description": "The total amount of funding a company has received",
"name": "Total Funding Amount",
"value": 78700000
},
{
"description": "All websites related to a company",
"name": "Multiple Websites",
"value": [
"everstring.com"
]
},
{
"description": "Date when the company last received funding",
"name": "Last Funding Date",
"value": "2015-10-13"
},
{
"description": "Number of investors for a company",
"name": "Number of Investors",
"value": 7
},
{
"description": "A measure of funding strength of a business based on type and who they received funding from (Low, Medium, High)",
"name": "Funding Strength",
"value": "High"
},
{
"description": "The amount of funding in the latest funding round of a company",
"name": "Latest Funding Amount",
"value": 65000000
},
{
"description": "The number of ES_Keywords associated with a company. Larger numbers usually indicate a more sophisticated website and/or many lines of businesses.",
"name": "Number Of Keywords",
"value": 389
},
{
"description": "The number of funding rounds a company has had",
"name": "Number of Funding Rounds",
"value": 4
},
{
"description": "All investor names from publicly available sources",
"name": "Investor Names",
"value": [
"Lakestar",
"IDG Ventures",
"Sequoia Capital",
"Lightspeed Venture Partners",
"DHVC",
"Microsoft Accelerator",
"ZhenFund"
]
},
{
"description": "A measure of technology spend as modeled by the types of technology purchase.",
"name": "Technology Spend",
"value": "High"
},
{
"description": "A measure of the relative strength of marketing department when comparing the number of employees in marketing vs the overall number of employees for a company.",
"name": "Marketing Department Strength",
"value": "Low"
},
{
"description": "A measure of marketing spend as modeled by the types of marketing technology purchase, type of titles, website sophistication by a company.",
"name": "Marketing Spend",
"value": "High"
},
{
"description": "A measure of the relative strength of technology department when comparing the number of employees in technology vs the overall number of employees for a company",
"name": "Technical Department Strength",
"value": "High"
},
{
"description": "A measure of the relative strength of sales department when comparing the number of employees in sales vs the overall number of employees for a company.",
"name": "Sales Department Strength",
"value": "High"
},
{
"description": "Company has offices or other facilities located at more than one address based on web presence.",
"name": "Facilities in Multiple Locations",
"value": "No"
},
{
"description": "Company has employees located in more than one state or country based on contact information.",
"name": "Employees in Multiple Locations",
"value": "Yes"
},
{
"description": "Level of use of marketing technology by company, presence of senior marketing employees at company, and execution of marketing programs across multiple channels by company.",
"name": "Marketing Sophistication",
"value": "High"
},
{
"description": "A measure of Finance sophistication of a business.",
"name": "Finance Sophistication",
"value": "Low"
},
{
"description": "A measure of HR sophistication of a business.",
"name": "HR Sophistication",
"value": "High"
},
{
"description": "A measure of social sophistication of a business.",
"name": "Social Sophistication",
"value": "High"
},
{
"description": "A measure of Finance spend as modeled by the types of Finance technology purchased by a company.",
"name": "Finance Spend",
"value": "High"
},
{
"description": "A measure of the relative strength of HR department when comparing the number of employees in HR vs the overall number of employees for a company.",
"name": "HR Department Strength",
"value": "Low"
},
{
"description": "A measure of social sophistication of a business.",
"name": "Sales Sophistication",
"value": "High"
},
{
"description": "A measure of the relative strength of finance department when comparing the number of employees in finance vs the overall number of employees for a company.",
"name": "Finance Department Strength",
"value": "Low"
},
{
"description": "A measure of technology sophistication of a business.",
"name": "Technology Sophistication",
"value": "High"
},
{
"description": "A measure of sales spend as modeled by the types of sales technology purchased by a company.",
"name": "Sales Spend",
"value": "High"
},
{
"description": "A measure of HR spend as modeled by the types of HR technology purchased by a company.",
"name": "HR Spend",
"value": "High"
},
{
"description": "Company offers services or products for consumer market.",
"name": "Business-to-Consumer (B2C)",
"value": "Yes"
},
{
"description": "Company offers services or products for businesses and is not a government, educational, or non-profit institution.",
"name": "Business-to-Business (B2B)",
"value": "Yes"
}
],
"ES_AlexaRank": 358859,
"ES_City": "San Mateo",
"ES_CompanyListNames": "Companies in CRM|Companies Having Intent",
"ES_CompanyPhone": "+1 6504253937",
"ES_Country": "United States",
"ES_ECID": 152695187,
"ES_Employee": 132,
"ES_EmployeeBand": "101-200",
"ES_EstimatedAge": 7,
"ES_FacebookUrl": "facebook.com/everstringtechnology",
"ES_Industry": "Computer Software",
"ES_Intent": {
"Computer Sciences Corporation (CSC)": {
"score": 73,
"signal": true
},
"General Electric (GE)": {
"score": 72,
"signal": true
},
"Google (GOOG)": {
"score": 67,
"signal": true
},
"Google Nexus": {
"score": 69,
"signal": true
},
"Intel Joule": {
"score": 64,
"signal": true
},
"Samsung Electronics": {
"score": 67,
"signal": true
}
},
"ES_IntentAggregateScore": 98,
"ES_IntentByTier": {
"Tier 1": [
{
"name": "Computer Sciences Corporation (CSC)",
"score": 73,
"signal": true
},
{
"name": "General Electric (GE)",
"score": 72,
"signal": true
}
],
"Tier 2": [
{
"name": "Google (GOOG)",
"score": 67,
"signal": true
},
{
"name": "Google Nexus",
"score": 69,
"signal": true
}
],
"Tier 3": [
{
"name": "Intel Joule",
"score": 64,
"signal": true
},
{
"name": "Samsung Electronics",
"score": 67,
"signal": true
}
]
},
"ES_IntentNumByTier": {
"Tier 1": 2,
"Tier 2": 2,
"Tier 3": 2
},
"ES_IntentStr": "Computer Sciences Corporation (CSC)|General Electric (GE)|Google (GOOG)|Google Nexus|Intel Joule|Samsung Electronics",
"ES_IntentTime": "2019-07-24 22:47:27",
"ES_Keywords": "predictive scoring|sales intelligence|account-based marketing|marketing and sales|predictive analytics|predictive insights|b2b sales and marketing|marketing and sales teams|b2b sales|demand generation|data science|sales and marketing systems|sales and marketing|ideal customer profile|saas platform|predictive marketing|marketing and crm|customer profile|predictive sales|applied data science",
"ES_LinkedInUrl": "linkedin.com/company/everstring-technology",
"ES_LocationID": "152695187WBQRDMZFFR",
"ES_MatchName": "EverString",
"ES_MatchReasonBuildingName": "M",
"ES_MatchReasonBuildingNumber": "M",
"ES_MatchReasonBusinessType": "M",
"ES_MatchReasonCity": "M",
"ES_MatchReasonCompanyPhone": "E",
"ES_MatchReasonCountry": "M",
"ES_MatchReasonDirectional": "M",
"ES_MatchReasonName": "E",
"ES_MatchReasonRoadName": "M",
"ES_MatchReasonRoadType": "M",
"ES_MatchReasonState": "M",
"ES_MatchReasonUnit": "M",
"ES_MatchReasonWebsite": "E",
"ES_MatchReasonZip": "M",
"ES_MatchScore": "5",
"ES_Models": {
"20000173": 74,
"20000181": 100,
"20000183": 100
},
"ES_NAICS2": "51",
"ES_NAICS2Description": "Information",
"ES_NAICS4": "5112",
"ES_NAICS4Description": "Software Publishers",
"ES_NAICS6": "511210",
"ES_NAICS6Description": "Software Publishers",
"ES_Name": "EverString",
"ES_NumLocations": 3,
"ES_NumSignalingTopics": 6,
"ES_PrimaryWebsite": "everstring.com",
"ES_Revenue": 12000,
"ES_RevenueBand": "$10M-$25M",
"ES_SIC2": "73",
"ES_SIC2Description": "Business Services",
"ES_SIC3": "737",
"ES_SIC3Description": "Computer and Data Processing Services",
"ES_SIC4": "7372",
"ES_SIC4Description": "Prepackaged Software",
"ES_SimilarCompanies": [
{
"domain": "6sense.com",
"ecid": 139178931
},
{
"domain": "mintigo.com",
"ecid": 157224278
},
{
"domain": "lattice-engines.com",
"ecid": 112453612
},
{
"domain": "leadspace.com",
"ecid": 138134660
},
{
"domain": "infer.com",
"ecid": 152998799
},
{
"domain": "radius.com",
"ecid": 161566188
},
{
"domain": "rainkingonline.com",
"ecid": 161248452
},
{
"domain": "demandbase.com",
"ecid": 156680511
},
{
"domain": "birst.com",
"ecid": 139726534
},
{
"domain": "leandatainc.com",
"ecid": 121598439
},
{
"domain": "sisense.com",
"ecid": 158213274
},
{
"domain": "corporate360.us",
"ecid": 136232660
},
{
"domain": "quickpivot.com",
"ecid": 114582448
},
{
"domain": "discoverorg.com",
"ecid": 150084738
},
{
"domain": "pyramidanalytics.com",
"ecid": 142085737
},
{
"domain": "pardot.com",
"ecid": 118053833
},
{
"domain": "sigmoid.com",
"ecid": 161850031
},
{
"domain": "insideview.com",
"ecid": 125961580
},
{
"domain": "treasuredata.com",
"ecid": 161334365
},
{
"domain": "market-bridge.com",
"ecid": 108969177
},
{
"domain": "engagio.com",
"ecid": 158339574
},
{
"domain": "seismic.com",
"ecid": 130963214
},
{
"domain": "optimove.com",
"ecid": 114532921
},
{
"domain": "nuevora.com",
"ecid": 115624174
},
{
"domain": "dataxylo.com",
"ecid": 123879105
}
],
"ES_State": "California",
"ES_Street": "1850 Gateway Dr Ste 400",
"ES_Top5NAICS": [
"511210",
"423430",
"525990",
"541613",
"517919"
],
"ES_TwitterUrl": "twitter.com/everstring",
"ES_YearStarted": "2012",
"ES_Zip": "94404",
"ES_LastUpdatedDate": "2020-10-22",
"ES_HQCity": "San Mateo",
"ES_HQCompanyPhone": "+1 6503501330",
"ES_HQCountry": "United States",
"ES_HQECID": 152695187,
"ES_HQEmployee": 61,
"ES_HQEmployeeBand": "51-100",
"ES_HQLocationID": "152695187WBQRDMZFFR",
"ES_HQName": "Everstring",
"ES_HQRevenue": 12000,
"ES_HQRevenueBand": "$10M-$25M",
"ES_HQState": "California",
"ES_HQStreet": "1850 Gateway Dr Ste 400",
"ES_HQWebsite": "everstring.com",
"ES_HQZip": "94404",
"ES_IsHQ": "Y",
"ES_InactiveFlag": false,
"ES_EIN": "",
"ES_ReleaseDate": "20201022",
"ES_Tier": 1,
"ES_AddressConfidenceScore": 1,
"ES_CompanyPhoneConfidenceScore": 0.6,
"ES_EmployeeConfidenceScore": 1,
"ES_IndustryConfidenceScore": 1,
"ES_NAICSConfidenceScore": 1,
"ES_NameConfidenceScore": 1,
"ES_RevenueConfidenceScore": 1,
"ES_SICConfidenceScore": 0.6,
"ES_WebsiteConfidenceScore": 1,
"ES_WebsiteStatus": "VALID",
"error_messages": [],
"inputId": 0
}
],
"time_taken": "0:00:00.278872"
}
Request parameters are POSTed to API in a JSON structure with following attributes:
Note: At least one of website, email, name, address, phone, ecid or location id must be provided.
| Attribute | Is Optional | Description |
|---|---|---|
| website | YES | Website of the company to enrich |
| YES | An email of a lead from the company | |
| name | YES | Name of the company to enrich |
| address | YES | Address of the company to enrich. Address format consists of street, city, state, postcode and / or country. All fields are optional (except “state” which must be passed) |
| phone | YES | Phone of a company, it’s dictionary, for example, {“country”: “United States”, “number”: “xxxxxxx”} |
| ecid | YES | EverString company id (unique) |
| location_id | YES | EverString location id of a company (unique) |
| match_reasons | YES | Optional customized match reasons specified on different attributes and match_score to decide how the match for that particular attribute should be. Acceptable attributes: name, website, bldg_name, bldg_number, road_name, road_type, directional, unit, city, state, zip, country, phone, biz_type and match_score. Acceptable values for attributes: E (exact match), F (fuzzy match), D (different match) and M (missing). Acceptable value for match score: 1, 2, 3, 4, or 5; Example: To get (match score of 3 AND exact match on website AND state AND fuzzy match on name) OR (match score of 3 AND exact match on name AND phone) OR (match score of 1 AND fuzzy match on city AND state) OR (match score of 4 with any combination for other attributes): "match_reasons": [ { "name": "F", "website": "E", "state": "E", "match_score": 3 }, { "name": "E", "phone": "E", "match_score": 3 }, { "city": "F", "state": "F", "match_score": 1 },{ "match_score": 4 }] |
| select | YES | An “optional” array to specify “additional” list of parameters to include in the response. Supported parameters are alexaRank, description, businessToBusiness, businessToConsumer, employeesInMultipleLocations, facilitiesInMultipleLocations, marketingSophistication, discounts, financeDeptStrength, financeSophistication, financeSpend, hrDeptStrength, hrSophistication, hrSpend, marketingDeptStrength, marketingSpend, onlineShopping, salesDeptStrength, salesSophistication, salesSpend, shippingMethods, shippingProviders, socialSophistication, techDeptStrength, technologySophistication, technologySpend, numLemmas, inc5000Bucket, fortune500Bucket, fundingLatestRound_age, numInvestors, investorNames, fundingStrengthBucket, fundTypes, fundingTotalAmount, fundingLatestRoundAmount, numFundTypes, top3Industries, top3Websites, hasMobileApp, latestFundingDate, facebookUrl, linkedinUrl, twitterUrl, companyListNames, similarCompanies, intentTopic, intentTime, top5Naics, models. We will ALWAYS return basic firmographics for the company matched even if nothing is passed in select. To learn more about which Advanced insights you have access to , please reach out to your CS representative. |
| model_ids | YES | An array to specify the list of models to include model score in the response. |
There are different ways these parameters are interpreted:
Direct Look-up If either of website, phone, ecid and / or location_id is passed “alone”, API will do a direct match on those respective fields. Location id and / or ecid have highest precedence in case of any conflict.
Fuzzy Match If any combination of name, address, website, email and / or phone is passed, API will do a fuzzy match (with weightage) on those respective fields depending on the combination of fields being passed in the input.
When the request parameters have a conflict, the following resolutions occur:
- If the website resolves to a company that is different than the provided name and address, we resolve by giving a higher weight to name and address over the website
- If the website resolves to a company that is different than the name (assuming address is not provided), we resolve with 100% match on website and 30% fuzzy match on the name
- If the name resolves to a location that is different than address, we resolve based on our in-house algorithm that considers all of the input fields
Enrich Multiple Records (Beta)
Example Enrich multiple records request (with optional fields specified in select):
curl "https://api.everstring.com/v1/companies/data_enrich" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{
"companies":[
{
"address":{
"street":"",
"city":"",
"state":"",
"postcode":"",
"country":""
},
"name":"EverString",
"website":"everstring.com",
"email": "contact@everstring.com",
"phone":{"country": "United States", "number":"(650) 425-3937"},
"location_id":"",
"ecid":""
},
{
"website":"google.com",
"name":"google",
"ecid":"",
"location_ids":"119408012CUOSVXPEAR"
}
],
"match_reasons": [{ "name": "E", "website": "E", "match_score": 5}],
"select" : ["businessToBusiness", "businessToConsumer", "marketingSophistication", "facilitiesInMultipleLocations", "employeesInMultipleLocations", "technologySpend", "marketingSpend", "salesSpend", "hrSpend", "financeSpend", "socialSophistication", "technologySophistication", "salesSophistication", "hrSophistication", "financeSophistication", "hrDeptStrength", "financeDeptStrength", "salesDeptStrength", "marketingDeptStrength", "techDeptStrength", "shippingProviders", "discounts", "shippingMethods", "onlineShopping", "numLemmas", "inc5000Bucket", "fortune500Bucket", "fundingLatestRound_age", "numInvestors", "investorNames", "fundingStrengthBucket", "fundTypes", "fundingTotalAmount", "fundingLatestRoundAmount", "numFundTypes", "top3_industries", "top3Websites", "hasMobileApp", "latestFundingDate", "alexaRank", "facebookUrl", "linkedinUrl", "twitterUrl", "description", "companyListNames", "similarCompanies", "intentTopic", "intentTime", "top5Naics", "models"],
"model_ids":[20000183, 20000173, 20000181]
}'
Example Enrich multiple records response:
{
"data": [
{
"ES_AdvancedInsights": [
{
"description": "Each funding type",
"name": "fund types",
"value": [
"Series B",
"Series A",
"Non Equity Assistance",
"Seed Round"
]
},
{
"description": "The total amount of funding a company has received",
"name": "Total Funding Amount",
"value": 78700000
},
{
"description": "All websites related to a company",
"name": "Multiple Websites",
"value": [
"everstring.com"
]
},
{
"description": "Date when the company last received funding",
"name": "Last Funding Date",
"value": "2015-10-13"
},
{
"description": "Number of investors for a company",
"name": "Number of Investors",
"value": 7
},
{
"description": "A measure of funding strength of a business based on type and who they received funding from (Low, Medium, High)",
"name": "Funding Strength",
"value": "High"
},
{
"description": "The amount of funding in the latest funding round of a company",
"name": "Latest Funding Amount",
"value": 65000000
},
{
"description": "The number of ES_Keywords associated with a company. Larger numbers usually indicate a more sophisticated website and/or many lines of businesses.",
"name": "Number Of Keywords",
"value": 389
},
{
"description": "The number of funding rounds a company has had",
"name": "Number of Funding Rounds",
"value": 4
},
{
"description": "All investor names from publicly available sources",
"name": "Investor Names",
"value": [
"Lakestar",
"IDG Ventures",
"Sequoia Capital",
"Lightspeed Venture Partners",
"DHVC",
"Microsoft Accelerator",
"ZhenFund"
]
},
{
"description": "A measure of technology spend as modeled by the types of technology purchase.",
"name": "Technology Spend",
"value": "High"
},
{
"description": "A measure of the relative strength of marketing department when comparing the number of employees in marketing vs the overall number of employees for a company.",
"name": "Marketing Department Strength",
"value": "Low"
},
{
"description": "A measure of marketing spend as modeled by the types of marketing technology purchase, type of titles, website sophistication by a company.",
"name": "Marketing Spend",
"value": "High"
},
{
"description": "A measure of the relative strength of technology department when comparing the number of employees in technology vs the overall number of employees for a company",
"name": "Technical Department Strength",
"value": "High"
},
{
"description": "A measure of the relative strength of sales department when comparing the number of employees in sales vs the overall number of employees for a company.",
"name": "Sales Department Strength",
"value": "High"
},
{
"description": "Company has offices or other facilities located at more than one address based on web presence.",
"name": "Facilities in Multiple Locations",
"value": "No"
},
{
"description": "Company has employees located in more than one state or country based on contact information.",
"name": "Employees in Multiple Locations",
"value": "Yes"
},
{
"description": "Level of use of marketing technology by company, presence of senior marketing employees at company, and execution of marketing programs across multiple channels by company.",
"name": "Marketing Sophistication",
"value": "High"
},
{
"description": "A measure of Finance sophistication of a business.",
"name": "Finance Sophistication",
"value": "Low"
},
{
"description": "A measure of HR sophistication of a business.",
"name": "HR Sophistication",
"value": "High"
},
{
"description": "A measure of social sophistication of a business.",
"name": "Social Sophistication",
"value": "High"
},
{
"description": "A measure of Finance spend as modeled by the types of Finance technology purchased by a company.",
"name": "Finance Spend",
"value": "High"
},
{
"description": "A measure of the relative strength of HR department when comparing the number of employees in HR vs the overall number of employees for a company.",
"name": "HR Department Strength",
"value": "Low"
},
{
"description": "A measure of social sophistication of a business.",
"name": "Sales Sophistication",
"value": "High"
},
{
"description": "A measure of the relative strength of finance department when comparing the number of employees in finance vs the overall number of employees for a company.",
"name": "Finance Department Strength",
"value": "Low"
},
{
"description": "A measure of technology sophistication of a business.",
"name": "Technology Sophistication",
"value": "High"
},
{
"description": "A measure of sales spend as modeled by the types of sales technology purchased by a company.",
"name": "Sales Spend",
"value": "High"
},
{
"description": "A measure of HR spend as modeled by the types of HR technology purchased by a company.",
"name": "HR Spend",
"value": "High"
},
{
"description": "Company offers services or products for consumer market.",
"name": "Business-to-Consumer (B2C)",
"value": "Yes"
},
{
"description": "Company offers services or products for businesses and is not a government, educational, or non-profit institution.",
"name": "Business-to-Business (B2B)",
"value": "Yes"
}
],
"ES_AlexaRank": 358859,
"ES_City": "San Mateo",
"ES_CompanyListNames": "Companies in CRM|Companies Having Intent",
"ES_CompanyPhone": "+1 6504253937",
"ES_Country": "United States",
"ES_ECID": 152695187,
"ES_Employee": 132,
"ES_EmployeeBand": "101-200",
"ES_EstimatedAge": 7,
"ES_FacebookUrl": "facebook.com/everstringtechnology",
"ES_Industry": "Computer Software",
"ES_Intent": {
"Computer Sciences Corporation (CSC)": {
"score": 73,
"signal": true
},
"General Electric (GE)": {
"score": 72,
"signal": true
},
"Google (GOOG)": {
"score": 67,
"signal": true
},
"Google Nexus": {
"score": 69,
"signal": true
},
"Intel Joule": {
"score": 64,
"signal": true
},
"Samsung Electronics": {
"score": 67,
"signal": true
}
},
"ES_IntentAggregateScore": 98,
"ES_IntentByTier": {
"Tier 1": [
{
"name": "Computer Sciences Corporation (CSC)",
"score": 73,
"signal": true
},
{
"name": "General Electric (GE)",
"score": 72,
"signal": true
}
],
"Tier 2": [
{
"name": "Google (GOOG)",
"score": 67,
"signal": true
},
{
"name": "Google Nexus",
"score": 69,
"signal": true
}
],
"Tier 3": [
{
"name": "Intel Joule",
"score": 64,
"signal": true
},
{
"name": "Samsung Electronics",
"score": 67,
"signal": true
}
]
},
"ES_IntentNumByTier": {
"Tier 1": 2,
"Tier 2": 2,
"Tier 3": 2
},
"ES_IntentStr": "Computer Sciences Corporation (CSC)|General Electric (GE)|Google (GOOG)|Google Nexus|Intel Joule|Samsung Electronics",
"ES_IntentTime": "2019-07-24 22:47:27",
"ES_Keywords": "predictive scoring|sales intelligence|account-based marketing|marketing and sales|predictive analytics|predictive insights|b2b sales and marketing|marketing and sales teams|b2b sales|demand generation|data science|sales and marketing systems|sales and marketing|ideal customer profile|saas platform|predictive marketing|marketing and crm|customer profile|predictive sales|applied data science",
"ES_LinkedInUrl": "linkedin.com/company/everstring-technology",
"ES_LocationID": "152695187WBQRDMZFFR",
"ES_MatchName": "EverString",
"ES_MatchReasonBuildingName": "M",
"ES_MatchReasonBuildingNumber": "M",
"ES_MatchReasonBusinessType": "M",
"ES_MatchReasonCity": "M",
"ES_MatchReasonCompanyPhone": "E",
"ES_MatchReasonCountry": "M",
"ES_MatchReasonDirectional": "M",
"ES_MatchReasonName": "E",
"ES_MatchReasonRoadName": "M",
"ES_MatchReasonRoadType": "M",
"ES_MatchReasonState": "M",
"ES_MatchReasonUnit": "M",
"ES_MatchReasonWebsite": "E",
"ES_MatchReasonZip": "M",
"ES_MatchScore": "5",
"ES_Models": {
"20000173": 74,
"20000181": 100,
"20000183": 100
},
"ES_NAICS2": "51",
"ES_NAICS2Description": "Information",
"ES_NAICS4": "5112",
"ES_NAICS4Description": "Software Publishers",
"ES_NAICS6": "511210",
"ES_NAICS6Description": "Software Publishers",
"ES_Name": "EverString",
"ES_NumLocations": 3,
"ES_NumSignalingTopics": 6,
"ES_PrimaryWebsite": "everstring.com",
"ES_Revenue": 12000,
"ES_RevenueBand": "$10M-$25M",
"ES_SIC2": "73",
"ES_SIC2Description": "Business Services",
"ES_SIC3": "737",
"ES_SIC3Description": "Computer and Data Processing Services",
"ES_SIC4": "7372",
"ES_SIC4Description": "Prepackaged Software",
"ES_SimilarCompanies": [
{
"domain": "6sense.com",
"ecid": 139178931
},
{
"domain": "mintigo.com",
"ecid": 157224278
},
{
"domain": "lattice-engines.com",
"ecid": 112453612
},
{
"domain": "leadspace.com",
"ecid": 138134660
},
{
"domain": "infer.com",
"ecid": 152998799
},
{
"domain": "radius.com",
"ecid": 161566188
},
{
"domain": "rainkingonline.com",
"ecid": 161248452
},
{
"domain": "demandbase.com",
"ecid": 156680511
},
{
"domain": "birst.com",
"ecid": 139726534
},
{
"domain": "leandatainc.com",
"ecid": 121598439
},
{
"domain": "sisense.com",
"ecid": 158213274
},
{
"domain": "corporate360.us",
"ecid": 136232660
},
{
"domain": "quickpivot.com",
"ecid": 114582448
},
{
"domain": "discoverorg.com",
"ecid": 150084738
},
{
"domain": "pyramidanalytics.com",
"ecid": 142085737
},
{
"domain": "pardot.com",
"ecid": 118053833
},
{
"domain": "sigmoid.com",
"ecid": 161850031
},
{
"domain": "insideview.com",
"ecid": 125961580
},
{
"domain": "treasuredata.com",
"ecid": 161334365
},
{
"domain": "market-bridge.com",
"ecid": 108969177
},
{
"domain": "engagio.com",
"ecid": 158339574
},
{
"domain": "seismic.com",
"ecid": 130963214
},
{
"domain": "optimove.com",
"ecid": 114532921
},
{
"domain": "nuevora.com",
"ecid": 115624174
},
{
"domain": "dataxylo.com",
"ecid": 123879105
}
],
"ES_State": "California",
"ES_Street": "1850 Gateway Dr Ste 400",
"ES_Top5NAICS": [
"511210",
"423430",
"525990",
"541613",
"517919"
],
"ES_TwitterUrl": "twitter.com/everstring",
"ES_YearStarted": "2012",
"ES_Zip": "94404",
"ES_LastUpdatedDate": "2020-10-22",
"ES_HQCity": "San Mateo",
"ES_HQCompanyPhone": "+1 6503501330",
"ES_HQCountry": "United States",
"ES_HQECID": 152695187,
"ES_HQEmployee": 61,
"ES_HQEmployeeBand": "51-100",
"ES_HQLocationID": "152695187WBQRDMZFFR",
"ES_HQName": "Everstring",
"ES_HQRevenue": 12000,
"ES_HQRevenueBand": "$10M-$25M",
"ES_HQState": "California",
"ES_HQStreet": "1850 Gateway Dr Ste 400",
"ES_HQWebsite": "everstring.com",
"ES_HQZip": "94404",
"ES_IsHQ": "Y",
"ES_InactiveFlag": false,
"ES_EIN": "",
"ES_ReleaseDate": "20201022",
"ES_Tier": 1,
"ES_AddressConfidenceScore": 1,
"ES_CompanyPhoneConfidenceScore": 0.6,
"ES_EmployeeConfidenceScore": 1,
"ES_IndustryConfidenceScore": 1,
"ES_NAICSConfidenceScore": 1,
"ES_NameConfidenceScore": 1,
"ES_RevenueConfidenceScore": 1,
"ES_SICConfidenceScore": 0.6,
"ES_WebsiteConfidenceScore": 1,
"ES_WebsiteStatus": "VALID",
"error_messages": [],
"inputId": 0
},
{
"ES_AdvancedInsights": [
{
"description": "The number of ES_Keywords associated with a company. Larger numbers usually indicate a more sophisticated website and/or many lines of businesses.",
"name": "Number Of Keywords",
"value": 8114
},
{
"description": "All websites related to a company",
"name": "Multiple Websites",
"value": [
"google.com",
"google.co.uk",
"google.je"
]
},
{
"description": "Proximity of maturity of a company as compared to Fortune 500 companies (Low, Medium, High)",
"name": "Fortune500 Score",
"value": "Low"
},
{
"description": "Identifies if this company has a mobile app link detected on their website (1 or blank)",
"name": "Has MobileApp",
"value": 1
},
{
"description": "Company offers services or products for businesses and is not a government, educational, or non-profit institution.",
"name": "Business-to-Business (B2B)",
"value": "Yes"
},
{
"description": "Company has offices or other facilities located at more than one address based on web presence.",
"id": 294855851496237,
"name": "Facilities in Multiple Locations",
"value": "Yes"
},
{
"description": "Level of use of marketing technology by company, presence of senior marketing employees at company, and execution of marketing programs across multiple channels by company.",
"name": "Marketing Sophistication",
"value": "High"
},
{
"description": "Company has offices or other facilities located at more than one address based on web presence.",
"name": "Facilities in Multiple Locations",
"value": "Yes"
}
],
"ES_AlexaRank": 1,
"ES_City": "Mountain View",
"ES_CompanyListNames": "Companies in CRM|Companies Having Intent",
"ES_CompanyPhone": "+1 6502530000",
"ES_Country": "United States",
"ES_ECID": 119408012,
"ES_Employee": 66615,
"ES_EmployeeBand": "10,000+",
"ES_EstimatedAge": 69,
"ES_FacebookUrl": "facebook.com/google",
"ES_Industry": "Internet",
"ES_Intent": {
"CA Technologies (CA)": {
"score": 81,
"signal": true
},
"Cisco Systems (CSCO)": {
"score": 80,
"signal": true
},
"Dreamforce": {
"score": 70,
"signal": true
},
"Fujitsu": {
"score": 66,
"signal": true
},
"General Electric (GE)": {
"score": 70,
"signal": true
},
"Perceptive Pixel": {
"score": 62,
"signal": true
},
"Watson IoT Platform": {
"score": 82,
"signal": true
}
},
"ES_IntentAggregateScore": 100,
"ES_IntentByTier": {
"Tier 1": [
{
"name": "CA Technologies (CA)",
"score": 81,
"signal": true
},
{
"name": "Cisco Systems (CSCO)",
"score": 80,
"signal": true
},
{
"name": "Dreamforce",
"score": 70,
"signal": true
},
{
"name": "Fujitsu",
"score": 66,
"signal": true
},
{
"name": "General Electric (GE)",
"score": 70,
"signal": true
},
{
"name": "Perceptive Pixel",
"score": 62,
"signal": true
},
{
"name": "Watson IoT Platform",
"score": 82,
"signal": true
}
]
},
"ES_IntentNumByTier": {
"Tier 1": 7
},
"ES_IntentStr": "CA Technologies (CA)|Cisco Systems (CSCO)|Dreamforce|Fujitsu|General Electric (GE)|Perceptive Pixel|Watson IoT Platform",
"ES_IntentTime": "2019-07-24 22:47:27",
"ES_Keywords": "search advertising|google advertisement|platform as a service|enterprise search|database as a service|google cloud|collaboration and productivity|mobile development platforms|social networks|hosting services|infrastructure as a service|mobile development|mobile app testing|web design|data visualization|application development|digital advertising|business content management|video hosting|office suites|operating system|digital analytics",
"ES_LinkedInUrl": "linkedin.com/company/google",
"ES_LocationID": "119408012CUOSVXPEAR",
"ES_MatchName": "Google Inc",
"ES_MatchReasonBuildingName": "M",
"ES_MatchReasonBuildingNumber": "M",
"ES_MatchReasonBusinessType": "M",
"ES_MatchReasonCity": "M",
"ES_MatchReasonCompanyPhone": "M",
"ES_MatchReasonCountry": "M",
"ES_MatchReasonDirectional": "M",
"ES_MatchReasonName": "E",
"ES_MatchReasonRoadName": "M",
"ES_MatchReasonRoadType": "M",
"ES_MatchReasonState": "M",
"ES_MatchReasonUnit": "M",
"ES_MatchReasonWebsite": "E",
"ES_MatchReasonZip": "M",
"ES_MatchScore": "5",
"ES_Models": {
"20000173": 100,
"20000181": 100,
"20000183": 100
},
"ES_NAICS2": "51",
"ES_NAICS2Description": "Information",
"ES_NAICS4": "5191",
"ES_NAICS4Description": "Other Information Services",
"ES_NAICS6": "519130",
"ES_NAICS6Description": "Internet Publishing and Broadcasting and Web Search Portals",
"ES_Name": "Google Inc",
"ES_NumLocations": 157,
"ES_NumSignalingTopics": 7,
"ES_PrimaryWebsite": "google.com",
"ES_Revenue": 37108853,
"ES_RevenueBand": "$5B+",
"ES_SIC2": "73",
"ES_SIC2Description": "Business Services",
"ES_SIC3": "737",
"ES_SIC3Description": "Computer and Data Processing Services",
"ES_SIC4": "7375",
"ES_SIC4Description": "Information Retrieval Services",
"ES_SimilarCompanies": [
{
"domain": "microsoft.com",
"ecid": 125495516
},
{
"domain": "apple.com",
"ecid": 129735703
},
{
"domain": "salesforce.com",
"ecid": 103162132
},
{
"domain": "oracle.com",
"ecid": 128865529
},
{
"domain": "hpe.com",
"ecid": 125741409
},
{
"domain": "sap.com",
"ecid": 102030786
},
{
"domain": "facebook.com",
"ecid": 136503056
},
{
"domain": "adobe.com",
"ecid": 129635378
},
{
"domain": "amazon.com",
"ecid": 108792606
},
{
"domain": "cisco.com",
"ecid": 142882396
},
{
"domain": "ibm.com",
"ecid": 131519987
},
{
"domain": "redhat.com",
"ecid": 160313984
},
{
"domain": "ca.com",
"ecid": 141650936
},
{
"domain": "yahoo.com",
"ecid": 104921296
},
{
"domain": "samsung.com",
"ecid": 146257381
},
{
"domain": "centurylink.com",
"ecid": 103919194
},
{
"domain": "sas.com",
"ecid": 107452286
},
{
"domain": "blackberry.com",
"ecid": 116406907
},
{
"domain": "linkedin.com",
"ecid": 142002054
},
{
"domain": "citrix.com",
"ecid": 146602580
},
{
"domain": "twitter.com",
"ecid": 115451062
},
{
"domain": "rackspace.com",
"ecid": 163212354
},
{
"domain": "emc.com",
"ecid": 161887538
},
{
"domain": "schneider-electric.com",
"ecid": 155564159
},
{
"domain": "csc.com",
"ecid": 131004253
},
{
"domain": "btplc.com",
"ecid": 157734792
},
{
"domain": "dell.com",
"ecid": 132876084
},
{
"domain": "pearson.com",
"ecid": 146384821
},
{
"domain": "verizon.com",
"ecid": 141150373
},
{
"domain": "fujitsu.com",
"ecid": 140584928
},
{
"domain": "telekom.com",
"ecid": 155826827
}
],
"ES_State": "California",
"ES_Street": "1600 Amphitheatre Pkwy",
"ES_Top5NAICS": [
"519130",
"518210",
"517311",
"519190",
"517919"
],
"ES_TwitterUrl": "twitter.com/google",
"ES_YearStarted": "1950",
"ES_Zip": "94043",
"ES_LastUpdatedDate": "2020-10-13",
"ES_HQCity": "Mountain View",
"ES_HQCompanyPhone": "+1 4044879000",
"ES_HQCountry": "United States",
"ES_HQECID": 119408012,
"ES_HQEmployee": 95019,
"ES_HQEmployeeBand": "10,000+",
"ES_HQLocationID": "119408012CUOSVXPEAR",
"ES_HQName": "Google LLC",
"ES_HQRevenue": 47690210,
"ES_HQRevenueBand": "$5B+",
"ES_HQState": "California",
"ES_HQStreet": "1600 Amphitheatre Pkwy",
"ES_HQWebsite": "google.com",
"ES_HQZip": "94043",
"ES_IsHQ": "Y",
"ES_InactiveFlag": false,
"ES_EIN": "770493581",
"ES_ReleaseDate": "20201022",
"ES_Tier": 1,
"ES_AddressConfidenceScore": 1,
"ES_CompanyPhoneConfidenceScore": 0.4,
"ES_EmployeeConfidenceScore": 1,
"ES_IndustryConfidenceScore": 1,
"ES_NAICSConfidenceScore": 1,
"ES_NameConfidenceScore": 1,
"ES_RevenueConfidenceScore": 1,
"ES_SICConfidenceScore": 0.6,
"ES_WebsiteConfidenceScore": 1,
"ES_WebsiteStatus": "VALID",
"error_messages": [],
"inputId": 1
}
],
"time_taken": "0:00:00.185490"
}
Company Data Enrichment Real Time API supports enrichment of multiple records at the same time. This section documents the request/response format when enriching multiple records.
Rate limit: 20 API calls/minute
Note: The API currently supports enrichment of a max of 25 records at a time. No pagination is supported yet.
When enriching multiple records, a JSON with a single attribute “companies” is POSTed. companies is an array of request objects and has the same parameters as for Enriching a single record.
Also, in the case of multiple companies enrichment, the response order is in same as request inputs order.
Response Parameters
Response for a successful search call is a JSON structure describing the result companies.
Companies
| Attribute | Description | Data Type |
|---|---|---|
| ES_AddressConfidenceScore | Confidence score for the ES_Address field (0.2, 0.4, 0.6, 0.8, 1 - 1 being highest) | DECIMAL |
| ES_AlexaRank | Alexa rank for the company, representing web traffic. Lower number indicates higher rank/traffic. | INT |
| ES_CompanyListNames | This field contains names of saved lists which the company is a part of, this is pipe separated These lists are created/saved in EAP |
VARCHAR |
| ES_City | Company’s physical city | VARCHAR |
| ES_CompanyPhone | Company phone number | VARCHAR |
| ES_CompanyPhoneConfidenceScore | Confidence score for the ES_CompanyPhone field (0.2, 0.4, 0.6, 0.8, 1 - 1 being highest) | DECIMAL |
| ES_Country | Company’s physical country | VARCHAR |
| ES_ECID | EverString Company ID (ECID) is a unique identifier for a company entity | BIGINT |
| ES_EIN | The Employer Identification Number (EIN) of a company. | VARCHAR |
| ES_Employee | Raw employee count for a company | BIGINT |
| ES_EmployeeBand | Employee category band (1-10 11-20 21-50 51-100 101-200 201-500 501-1,000 1,001-2,000 2,001-5,000 5,001-10,000 10,000+) |
VARCHAR |
| ES_EmployeeConfidenceScore | Confidence score for the ES_EmployeeBand field (0.2, 0.4, 0.6, 0.8, 1 - 1 being highest) | DECIMAL |
| ES_HQCity | HQ Company’s physical city | VARCHAR |
| ES_HQCompanyPhone | HQ Company’s phone number | VARCHAR |
| ES_HQCountry | HQ Company’s physical country | VARCHAR |
| ES_HQECID | EverString Company ID (ECID) for the headquarters (HQ) of a company entity | BIGINT |
| ES_HQEmployee | HQ Raw employee number for a company | BIGINT |
| ES_HQEmployeeBand | HQ Employee category band (1-10 11-20 21-50 51-100 101-200 201-500 501-1,000 1,001-2,000 2,001-5,000 5,001-10,000 10,000+) |
VARCHAR |
| ES_HQLocationID | Location ID for the headquarters (HQ) of a company entity | VARCHAR |
| ES_HQName | HQ Company name. May match ES_Name | VARCHAR |
| ES_HQRevenue | HQ Raw revenue number in USD | BIGINT |
| ES_HQRevenueBand | HQ Revenue category band in USD ( $0M-$1M $1M-$5M $5M-$10M $10M-$25M $25M-$50M $50M-$100M $100M-$250M $500M-$1B $1B-$5B $5B+) |
VARCHAR |
| ES_HQState | HQ Company’s physical state | VARCHAR |
| ES_HQStreet | HQ Company’s physical street | VARCHAR |
| ES_HQWebsite | HQ Primary website of the company. May contain yelp.com websites. May match ES_Website | VARCHAR |
| ES_HQZip | HQ Company’s physical zip/postal code | VARCHAR |
| ES_InactiveFlag | Identifies if a company is inactive | BOOLEAN |
| ES_Industry | Primary industry based on EverString’s industry taxonomy | VARCHAR |
| ES_IndustryConfidenceScore | Confidence score for the ES_Industry field (0.2, 0.4, 0.6, 0.8, 1 - 1 being highest) | DECIMAL |
| ES_Intent | Requires EAP and have Intent Topics configured. This field maps intent topic with its score and if the topic is signaling or not. For example: { “Computer Sciences Corporation (CSC)”: { “score”: 73, “signal”: true }, “General Electric (GE)”: { “score”: 72, “signal”: true } } This particular company has an intent score of 73 and is signaling intent on the topic “Computer Sciences Corporation (CSC)”, and an intent score of 72 and is signaling intent on the topic “General Electric (GE)” |
DICT |
| ES_IntentByTier | This field provides intent scores and information based on tiers. This requires intent topics to be set up and split into tiers in EAP For example: { “Tier 1”: [ { “name”: “Computer Sciences Corporation (CSC)”, “score”: 73, “signal”: true }, ], “Tier 2”: [ { “name”: “Google (GOOG)”, “score”: 67, “signal”: true }, ], “Tier 3”: [ { “name”: “Intel Joule”, score": 64, “signal”: true }, ] } This company has a Tier 1 topic called Computer Sciences Corporation (CSC)“ which is signaling intent with a score of 73 This company has a Tier 2 topic called "Google (GOOG) which is signaling intent with a score of 67 |
DICT |
| ES_IntentNumByTier | This field provides number of topics with signals at every Tier. For example: { "Tier 1”: 2, “Tier 2”: 2, “Tier 3”: 2 } This company has 2 Tier 1 topics with signals, 2 Tier 2 topics with signals and 2 Tier 3 topics with signals |
DICT |
| ES_IntentStr | This is list of all intent topics for which the company has signals For example: “Computer Sciences Corporation (CSC)\General Electric (GE)\Google (GOOG)\Google Nexus\Intel Joule\Samsung Electronics” |
VARCHAR |
| ES_IntentTime | Intent time is the time at which the intent data was refreshed. Currently, this refresh occurs on a weekly basis.“ | VARCHAR |
| ES_IsHQ | Indicates if location-level firmographic fields contain HQ-level data. Possible values are "Y” or “N”. | CHAR |
| ES_Keywords | Machine generated tags for the company | VARCHAR |
| ES_LinkedInUrl | Linkedin URL for the company | VARCHAR |
| ES_LocationID | Location ID, which uniquely identifies each separate physical location, office, or branch of a company | VARCHAR |
| ES_MatchName | Based on the customer’s input company name, the best entity match that EverString can make | VARCHAR |
| ES_MatchReasonBuildingName | EverString matching reason codes for interpretation and workflow triggers for building name; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonBuildingNumber | EverString matching reason codes for interpretation and workflow triggers for Business Type; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonBusinessType | EverString matching reason codes for interpretation and workflow triggers for building number; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonCity | EverString matching reason codes for interpretation and workflow triggers for company name; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonCompanyPhone | EverString matching reason codes for interpretation and workflow triggers for company phone; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonCountry | EverString matching reason codes for interpretation and workflow triggers for country; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonDirectional | EverString matching reason codes for interpretation and workflow triggers for road directional; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonName | EverString matching reason codes for interpretation and workflow triggers for company name; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonRoadName | EverString matching reason codes for interpretation and workflow triggers for road name; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonRoadType | EverString matching reason codes for interpretation and workflow triggers for type of road; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonState | EverString matching reason codes for interpretation and workflow triggers for state; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonUnit | EverString matching reason codes for interpretation and workflow triggers for unit designation i.e. suite # or floor #, etc. ; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonWebsite | EverString matching reason codes for interpretation and workflow triggers for company website; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchReasonZip | EverString matching reason codes for interpretation and workflow triggers for zipcode; E is exact match, F is fuzzy match, D is different, and M is missing | CHAR |
| ES_MatchScore | Confidence score for the match based upon the input data and our matching engine (1, 2, 3, 4, 5 - 5 being highest) | DECIMAL |
| ES_Models | This field maps the modelID and the fit score based on the model. This requires the models to be set-up/built in EAP For example { “20000173”: 74, “20000181”: 100, “20000183”: 100 } This company has a fit score of 74 against model ID 20000173, etc. The model ID and model name relationship can be found on EAP |
VARCHAR |
| ES_NAICS2 | Primary 2-digit NAICS code | VARCHAR |
| ES_NAICS2DESCRIPTION | Primary 2-digit NAICS code description | VARCHAR |
| ES_NAICS4 | Primary 4-digit NAICS code | VARCHAR |
| ES_NAICS4DESCRIPTION | Primary 4-digit NAICS code description | VARCHAR |
| ES_NAICS6 | Primary 6-digit NAICS code | VARCHAR |
| ES_NAICS6DESCRIPTION | Primary 6-digit NAICS code description | VARCHAR |
| ES_NAICSConfidenceScore | Confidence score for the ES_NAICS6 field (0.2, 0.4, 0.6, 0.8, 1 - 1 being highest) | DECIMAL |
| ES_Name | Company name for a given ECID | VARCHAR |
| ES_NumLocations | Number of locations | INT |
| ES_NumSignalingTopics | Total number of topics with intent signals across all tiers | INT |
| ES_PrimaryWebsite | Primary website of the company. May contain yelp.com URLs for companies without a top-level domain. | VARCHAR |
| ES_ReleaseDate | Year and Month of this data release in YYYYMM format. i.e., 201902 | VARCHAR |
| ES_Revenue | Raw revenue number in USD (in thousands) | BIGINT |
| ES_RevenueBand | Revenue category band in USD ( $0M-$1M $1M-$5M $5M-$10M $10M-$25M $25M-$50M $50M-$100M $100M-$250M $500M-$1B $1B-$5B $5B+) |
VARCHAR |
| ES_SIC2 | Primary 2-digit SIC code | VARCHAR |
| ES_SIC2Description | Primary 2-digit SIC description | VARCHAR |
| ES_SIC3 | Primary 3-digit SIC code | VARCHAR |
| ES_SIC3Description | Primary 3-digit SIC description | VARCHAR |
| ES_SIC4Description | Primary 4-digit SIC description | VARCHAR |
| ES_SICConfidenceScore | Confidence score for the ES_SIC4 field (0.2, 0.4, 0.6, 0.8, 1 - 1 being highest) | DECIMAL |
| ES_SimilarCompanies | This field provides domains of similar companies to the domain of the input company. For example: [{ “domain”: “6sense.com”, “ecid”: 139178931 }, { “domain”: “mintigo.com”, “ecid”: 157224278 }] |
LIST |
| ES_State | Company’s physical state | VARCHAR |
| ES_Street | Company’s physical street | VARCHAR |
| ES_Tier | Overall data quality tier for a record (3, 2, 1 - 1 being highest) | INT |
| ES_Top5NAICS | Comma separated top 5 NAICS mapped to the company | VARCHAR |
| ES_TwitterUrl | Twitter URL for the company | VARCHAR |
| ES_YearStarted | Founding year of the company | VARCHAR |
| ES_WebsiteConfidenceScore | Confidence score for the ES_PrimaryWebsite field (0.2, 0.4, 0.6, 0.8, 1 - 1 being highest) | DECIMAL |
| ES_WebsiteStatus | Identifies if a company’s website is still active or redirects to another website. VALID, INVALID, PARKED, REDIRECT. | VARCHAR |
| ES_Zip | Company’s physical zip/postal code | VARCHAR |
| ES_LastUpdatedDate | Company’s last updated date | VARCHAR |
| ES_AdvancedInsights | Advanced insights we have for the company, with description, name and value. Currently, we share following advanced insights: Marketing Sophistication Business-to-Business (B2B) Business-to-Consumer (B2C) Facilities in Multiple Locations Employees in Multiple Locations Shipping Methods HR Spend Finance Spend Marketing Spend Social Sophistication Finance Sophistication Sales Department Strength Sales Spend Discounts HR Sophistication Sales Sophistication Shipping Providers HR Department Strength Technical Department Strength Finance Department Strength Online Shopping Technology Sophistication Marketing Department Strength Technology Spend Number Of Keywords Inc5000 Score Fortune500 Score Last Funding Age Number of Investors Investor Names Funding Strength Funding Type Total Funding Amount Latest Funding Amount Number of Funding Rounds Top3 Industries Multiple Websites Has MobileApp Last Funding Date For Example: ES_AdvancedInsights": [ { “description”: “Company offers services or products for businesses and is not a government, educational, or non-profit institution.”, “name”: “Business-to-Business (B2B)”, “value”: “Yes” } ] |
VARCHAR |
| InputId | This is the index of the company we are enriching when we are enriching multiple records | INT |
| time_taken | “0:00:00.278872” | VARCHAR |
Advanced Insight Name to Parameter Map
In our advanced insights, please use the following mapping to identify which input parameter provides which output Advanced insights name. For example, if you pass “businessToBusiness” in input, you will have an advanced insight with name “Business-to-Business (B2B)”.
| Parameter | Advanced Insight Name |
|---|---|
| businessToBusiness | Business-to-Business (B2B) |
| businessToConsumer | Business-to-Consumer (B2C) |
| employeesInMultipleLocations | Employees in Multiple Locations |
| facilitiesInMultipleLocations | Facilities in Multiple Locations |
| marketingSophistication | Marketing Sophistication |
| discounts | Discounts |
| financeDeptStrength | Finance Department Strength |
| financeSophistication | Finance Sophistication |
| financeSpend | Finance Spend |
| hrDeptStrength | HR Department Strength |
| hrSophistication | HR Sophistication |
| hrSpend | HR Spend |
| marketingDeptStrength | Marketing Department Strength |
| marketingSpend | Marketing Spend |
| onlineShopping | Online Shopping |
| salesDeptStrength | Sales Department Strength |
| salesSophistication | Sales Sophistication |
| salesSpend | Sales Spend |
| shippingMethods | Shipping Methods |
| shippingProviders | Shipping Providers |
| socialSophistication | Social Sophistication |
| techDeptStrength | Technical Department Strength |
| technologySophistication | Technology Sophistication |
| technologySpend | Technology Spend |
| numLemmas | Number Of Keywords |
| inc5000Bucket | Inc5000 Score |
| fortune500Bucket | Fortune500 Score |
| fundingLatestRound_age | Last Funding Age |
| numInvestors | Number of Investors |
| investorNames | Investor Names |
| fundingStrengthBucket | Funding Strength |
| fundTypes | Funding Type |
| fundingTotalAmount | Total Funding Amount |
| fundingLatestRoundAmount | Latest Funding Amount |
| numFundTypes | Number of Funding Rounds |
| top3Industries | Top3 Industries |
| top3Websites | Multiple Websites |
| hasMobileApp | Has MobileApp |
| latestFundingDate | Last Funding Date |
Discover API
Endpoint URL: https://api.everstring.com/v1/companies/discover
The Discover REST API provides an interface to search companies in the EverString database.
Request Parameters
Example search request:
curl "https://api.everstring.com/v1/companies/discover" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{"criteria": {"revenue": ["$0M-$1M", "$1M-$5M"],
"similarDomains": ["google.com"],
"department": ["Administrative", "Computing & IT", "Educator"],
"city": ["San Mateo, California"]},
"limit": 10,
"offset": 0,
"orderBy" : "-fitScore",
"modelName": "CRM Fit"}'
Request parameters are POSTed to API in a JSON structure with following attributes:
| Attribute | Description | Data Type |
|---|---|---|
| criteria | Search filter, it’s a map, default value is {}, all the values in the map are list, supported keys and values listed in the table, please refer the following criteria details | JSON |
| limit | Total number of records to return, default value is 50, can be set to 1-1000 | integer |
| offset | Offset, default value is 0, can be set to a number which not less than 0, for example, you can set limit to 1000, offset to 0 to get the first 1000 result, change offset to 1000 to get the second 1000 result | integer |
| orderBy | Supported values are “companyName”, “industry”, “revenue”, “employeeSize”, “alexaRank”, “fitScore”, “relevanceScore”, “relevanceScoreDomain”, default value is “companyName”, you also can add “-” to those values to do the descending order. Only when you have keywords in the criteria, you can order by “relevanceScore”, only when you have similarDomains in the criteria, you can order by “relevanceScoreDomain”, By addtition, we don’t support keywords and similarDomains in the same api call | String |
| modelName | Model Name, not required if you don’t do order by fitScore or filter by fitScore | String |
Criteria Details
| Key | Value Options |
|---|---|
| state | “Alabama”, “Alaska”, “American Samoa”, “Arizona”, “Arkansas”, “California”, “Colorado”, “Connecticut”, “Delaware”, “District of Columbia”, “Florida”, “Georgia”, “Guam”, “Hawaii”, “Idaho”, “Illinois”, “Indiana”, “Iowa”, “Kansas”, “Kentucky”, “Louisiana”, “Maine”, “Maryland”, “Massachusetts”, “Michigan”, “Minnesota”, “Mississippi”, “Missouri”, “Montana”, “Nebraska”, “Nevada”, “New Hampshire”, “New Jersey”, “New Mexico”, “New York”, “North Carolina”, “North Dakota”, “Northern Mariana Islands”, “Ohio”, “Oklahoma”, “Oregon”, “Pennsylvania”, “Puerto Rico”, “Rhode Island”, “South Carolina”, “South Dakota”, “Tennessee”, “Texas”, “Utah”, “Vermont”, “Virgin Islands”, “Virginia”, “Washington”, “West Virginia”, “Wisconsin”, “Wyoming” |
| industry | “Accounting”, “Airlines/Aviation”, “Alternative Medicine”, “Apparel & Fashion”, “Architecture & Planning”, “Arts and Crafts”, “Automotive”, “Biotechnology”, “Building Materials”, “Business Organizations”, “Business Supplies and Equipment”, “Chemicals”, “Civic & Social Organization”, “Civil Engineering”, “Commercial Real Estate”, “Computer Hardware”, “Computer Network & Security”, “Computer Software”, “Construction”, “Consumer Electronics”, “Consumer Goods”, “Consumer Services”, “Cosmetics”, “Defense & Space”, “Design”, “Education”, “Electrical/Electronic Manufacturing”, “Environmental Services”, “Events Services”, “Executive Office”, “Facilities Services”, “Farming”, “Financial Services”, “Food & Beverages”, “Fund-Raising”, “Furniture”, “Gambling & Casinos”, “Glass, Ceramics & Concrete”, “Government”, “Graphic Design”, “Health, Wellness and Fitness”, “Hospital & Health Care”, “Hospitality”, “Human Resources”, “Import and Export”, “Individual & Family Services”, “Industrial Automation”, “Information Technology and Services”, “Insurance”, “International Affairs”, “International Trade and Development”, “Internet”, “Legal Services”, “Leisure, Travel & Tourism”, “Libraries”, “Logistics and Supply Chain”, “Luxury Goods & Jewelry”, “Machinery”, “Management Consulting”, “Maritime”, “Marketing and Advertising”, “Mechanical or Industrial Engineering”, “Media and Entertainment”, “Medical Devices”, “Military”, “Mining & Metals”, “Museums and Institutions”, “Nanotechnology”, “Newspapers”, “Nonprofit Organizations”, “Oil & Energy”, “Online Media”, “Outsourcing/Offshoring”, “Packaging and Containers”, “Paper & Forest Products”, “Performing Arts”, “Pharmaceuticals”, “Photography”, “Plastics”, “Printing”, “Professional Training & Coaching”, “Program Development”, “Public Relations and Communications”, “Public Safety”, “Publishing”, “Real Estate”, “Recreational Facilities and Services”, “Religious Institutions”, “Research”, “Restaurants”, “Retail”, “Security and Investigations”, “Sporting Goods”, “Sports”, “Staffing and Recruiting”, “Telecommunications”, “Textiles”, “Tobacco”, “Translation and Localization”, “Transportation/Trucking/Railroad”, “Utilities”, “Veterinary”, “Warehousing”, “Wholesale”, “Writing and Editing” |
| revenue | “$0M-$1M”, “$1M-$5M”, “$5M-$10M”, “$10M-$25M”, “$25M-$50M”, “$50M-$100M”, “$100M-$250M”, “$250M-$500M”, “$500M-$1B”, “$1B-$5B”, “$5B+” |
| employeeSize | “1-10”, “11-20”, “21-50”, “51-100”, “101-200”, “201-500”, “501-1,000”, “1,001-2,000”, “2,001-5,000”, “5,001-10,000”, “10,000+” |
| department | “Administrative”, “Computing & IT”, “Educator”, “Engineering”, “Finance”, “HR”, “Legal”, “Marketing”, “Medical & Health”, “Operations”, “Other”, “Ownership/Board”, “Research & Development”, “Sales” |
| crmFilter | “In CRM”, “Not In CRM” |
| fitScore | “0-10”, “11-20”, “21-30”, “31-40”, “41-50”, “51-60”, “61-70”, “71-80”, “81-90”, “91-100” |
| city | The value format for one city is “{city}, {state}”, for example: “San Mateo, California” |
| zipcode | The value format for one zipcode is “{state}-{zipcpde}”, for example: “Alabama-01050” |
| intentTopic | List of words |
| keywords | List of words |
| similarDomains | List of domains, now only support one domain in the list |
Response Parameters
Example search response:
{
"companies":[
{
"name":"EverString",
"domain":"everstring.com"
},
{
"name":"Salesforce",
"domain":"salesforce.com"
}
]
}
Response for a successful search call is a JSON structure describing the result company name and domain.
Companies
| Attribute | Description | Data Type |
|---|---|---|
| name | Company Name | String |
| domain | Company Domain | String |
Real Time Contact Enrichment API
Endpoint URL: https://api.everstring.com/v1/contacts/data_enrich
The Contact Data Enrichment Real Time REST API provides an interface to access information available for contacts in the EverString database. It takes as input a contact email and / or linkedin_url and returns enriched information as the output.
Rate limit: 120 calls/minute if you only query for one record, otherwise, it will be 20 API calls/minute
Request Parameters
Example Enrich single record request:
curl "https://api.everstring.com/v1/contacts/data_enrich" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{
"email": "narin@everstring.com"
}'
Example Enrich single record response:
{
"data": [
{
"ES_ContactTier": "Tier2",
"ES_Department1": "Engineering",
"ES_Department2": "",
"ES_Department3": "",
"ES_Department4": "",
"ES_Department5": "",
"ES_DirectPhone": "+1 1234567890",
"ES_CompanyPhone": "+1 6504253937",
"ES_PhoneStatus": "valid_company_phone",
"ES_ECID": 152695187,
"ES_EPID": 1509462529,
"ES_Email": "narin@everstring.com",
"ES_EmailStatus": "Accept-All: Email Address",
"ES_FirstName": "Narin",
"ES_JobLevel": "Non-Manager",
"ES_LastName": "Kittikul",
"ES_ContactLinkedInUrl": "https://www.linkedin.com/in/nkittikul",
"ES_PrimaryWebsite": "everstring.com",
"ES_Title": "Full Stack Engineer",
"ES_ContactLastUpdatedDate": "2020-01-18",
"inputId": 0
}
],
"time_taken": "0:00:00.630029"
}
Example Enrich single record /w fuzzy match request:
curl "https://api.everstring.com/v1/contacts/data_enrich" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{
"email": "bad_email@noteverstring.com",
"first_name": "nari",
"last_name": "kittikul",
"company_name": "evertsring"
}'
Example Enrich single record /w fuzzy match response:
{
"data": [
{
"ES_CompanyPhone": null,
"ES_ContactLastUpdatedDate": "2020-01-01",
"ES_ContactLinkedInUrl": "https://www.linkedin.com/in/nkittikul",
"ES_ContactTier": "Tier2",
"ES_Department1": "Engineering",
"ES_Department2": "",
"ES_Department3": "",
"ES_Department4": "",
"ES_Department5": "",
"ES_DirectPhone": "",
"ES_ECID": 152695187,
"ES_EPID": 1509462529,
"ES_Email": "narin@everstring.com",
"ES_EmailStatus": "Accept-All: Email Address",
"ES_FirstName": "Narin",
"ES_JobLevel": "Non-Manager",
"ES_LastName": "Kittikul",
"ES_PhoneStatus": null,
"ES_PrimaryWebsite": null,
"ES_Title": "Full Stack Engineer",
"inputId": 0
}
],
"time_taken": "0:00:00.131786"
}
Request parameters are POSTed to API in a JSON structure with following attributes:
Note: At least one of email, linkedin_url, or (first_name, last_name, and company_name) must be provided.
| Attribute | Is Optional | Description |
|---|---|---|
| YES | A contact’s email | |
| linkedin_url | YES | A contact’s linkedin url |
| first_name | YES | A contact’s first name |
| last_name | YES | A contact’s last name |
| company_name | YES | Name of company to which contact belongs |
The API will normalize provided email/linkedin_url and then do a direct match on those respective fields.
If no direct match on email/linkedin_url is found (or if those fields were not provided), and first_name/last_name/company_name have all been provided, the API will return the most relevant fuzzy matches (if any) based on first_name/last_name/company_name.
Enrich Multiple Records
Example Enrich multiple records request:
curl "https://api.everstring.com/v1/contacts/data_enrich" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{
"contacts":[
{
"email": "narin@everstring.com"
},
{
"linkedin_url": "https://www.linkedin.com/in/innalevy"
}
]
}'
Example Enrich multiple records response:
{
"data": [
{
"ES_ContactTier": "Tier2",
"ES_Department1": "Engineering",
"ES_Department2": "",
"ES_Department3": "",
"ES_Department4": "",
"ES_Department5": "",
"ES_DirectPhone": "+1 1234567890",
"ES_CompanyPhone": "+1 6504253937",
"ES_PhoneStatus": "valid_company_phone",
"ES_ECID": 152695187,
"ES_EPID": 1509462529,
"ES_Email": "narin@everstring.com",
"ES_EmailStatus": "Accept-All: Email Address",
"ES_FirstName": "Narin",
"ES_JobLevel": "Non-Manager",
"ES_LastName": "Kittikul",
"ES_ContactLinkedInUrl": "https://www.linkedin.com/in/nkittikul",
"ES_PrimaryWebsite": "everstring.com",
"ES_Title": "Full Stack Engineer",
"ES_ContactLastUpdatedDate": "2020-01-18",
"inputId": 0
},
{
"ES_ContactTier": "Tier2",
"ES_Department1": "Engineering",
"ES_Department2": "",
"ES_Department3": "",
"ES_Department4": "",
"ES_Department5": "",
"ES_DirectPhone": "",
"ES_CompanyPhone": "+1 6504253937",
"ES_PhoneStatus": "",
"ES_ECID": 152695187,
"ES_EPID": 1632592971,
"ES_Email": "inna@everstring.com",
"ES_EmailStatus": "Accept-All: Email Address",
"ES_FirstName": "Inna",
"ES_JobLevel": "Manager",
"ES_LastName": "Levy",
"ES_ContactLinkedInUrl": "https://www.linkedin.com/in/innalevy",
"ES_PrimaryWebsite": "everstring.com",
"ES_Title": "Senior Technical Program Manager",
"ES_ContactLastUpdatedDate": "2020-01-18",
"inputId": 1
},
],
"time_taken": "0:00:00.630029"
}
Contact Data Enrichment Real Time API supports enrichment of multiple records at the same time. This section documents the request/response format when enriching multiple records.
Rate limit: 20 API calls/minute
*Note: The API currently supports enrichment of a max of 25 records at a time. *
When enriching multiple records, a JSON with a single attribute “contacts” is POSTed. contacts is an array of request objects and has the same parameters as for Enriching a single record.
Also, in the case of multiple contacts enrichment, the response order is in same as request inputs order.
Response Parameters
Response for a successful search call is a JSON structure describing the result contacts.
Contacts
| Attribute | Description | Data Type |
|---|---|---|
| ES_ECID | EverString Company ID (ECID) is a unique identifier for a company entity to which contact belongs | BIGINT |
| ES_EPID | EverString Person ID (EPID) is a unique identifier for a contact entity | BIGINT |
| ES_PrimaryWebsite | Website of contact’s company | VARCHAR |
| ES_FirstName | First name of contact | VARCHAR |
| ES_LastName | Last name of contact | VARCHAR |
| ES_Title | Title of contact | VARCHAR |
| ES_JobLevel | Seniority level of contact | VARCHAR |
| ES_Department1 | Department 1 of contact | VARCHAR |
| ES_Department2 | Department 2 of contact | VARCHAR |
| ES_Department3 | Department 3 of contact | VARCHAR |
| ES_Department4 | Department 4 of contact | VARCHAR |
| ES_Department5 | Department 5 of contact | VARCHAR |
| ES_Email | Email address of contact | VARCHAR |
| ES_DirectPhone | Contact direct phone number | VARCHAR |
| ES_CompanyPhone | Company phone number | VARCHAR |
| ES_ContactLinkedInUrl | LinkedIn URL of contact | VARCHAR |
| ES_ContactTier | Tier of contact | VARCHAR |
| ES_EmailStatus | Contact email status (Valid, Accept-All, etc.) | VARCHAR |
| ES_PhoneStatus | Contact phone status | VARCHAR |
| ES_ContactLastUpdatedDate | Date when contact was last updated | VARCHAR |
| InputId | This is the index of the contact we are enriching when we are enriching multiple records | INT |
| time_taken | “0:00:00.278872” | VARCHAR |
Contact Search API
Endpoint URL: https://api.everstring.com/v1/contacts/search
The Contact Search REST API provides an interface to search contacts in the EverString database.
Rate limit: 120 calls/minute if you only query with one ecid/website. Multiple ecids/websites will be rate limited to 20 calls/minute.
Request Parameters
Example search request using ecids:
curl "https://api.everstring.com/v1/contacts/search" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{"criteria": {"ecids": [152695187, 132002315],
"departments": ["Engineering", "Computing & IT"],
"job_levels": ["Non-Manager", "Manager", "Director"],
"titles": ["full stack", "quality assurance", "database"],
"exclude_titles": ["ninja"]},
"limit": 10,
"offset": 0,
"order_by" : "-relevance"}'
Example search request using websites:
curl "https://api.everstring.com/v1/contacts/search" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{"criteria": {"websites": ["everstring.com", "box.com"],
"departments": ["Engineering", "Computing & IT"],
"job_levels": ["Non-Manager", "Manager", "Director"],
"titles": ["full stack", "quality assurance", "database"],
"exclude_titles": ["ninja"]},
"limit": 2,
"offset": 0,
"order_by" : "-relevance"}'
Request parameters are POSTed to API in a JSON structure with following attributes:
| Attribute | ________Is_Optional________ | Description |
|---|---|---|
| criteria | No | Object specifying contacts to search for, see “Criteria Details” section below |
| limit | Yes (defaults to 50, max 100) | Total number of contacts per company to return |
| offset | Yes (defaults to 0, max 9900) | Offset of contacts per company to return |
| order_by | Yes (defaults to ’-relevance’) | Supported values are “first_name”, “last_name”, “job_level”, and “relevance”. Add a “-” at the beginning of the value to order by descending order. For example, “-relevance” will return most relevant contacts first, “relevance” will return least relevant contacts first. |
Criteria Details
| Key | Value Options |
|---|---|
| ecids | List of ecids to specify companies in which contacts will be searched. One of “ecids” or “websites” must be included in “criteria”. If “ecids” are provided, “websites” cannot be provided. Maximum length is 25. |
| websites | List of websites to specify companies in which contacts will be searched. One of “ecids” or “websites” must be included in “criteria”. If “websites” are provided, “ecids” cannot be provided. Websites ideally are formatted as “everstring.com”, “google.com”, etc. Maximum length is 25. |
| departments | “Administrative”, “Computing & IT”, “Customer Service / Support”, “Education / Training”, “Engineering”, “Finance / Accounting”, “Human Resources”, “Legal”, “Marketing”, “Medical / Health”, “Operations”, “Other”, “Ownership / Board”, “Product”, “Research & Development”, “Sales” |
| job_levels | “Board / Shareholder”, “C-Level”, “Vice President”, “Director”, “Manager”, “Non-Manager” |
| titles | List of titles to fuzzy match on. A single title cannot exceed 8 words and 50 characters. |
| exclude_titles | List of titles to exclude with fuzzy match. A single title cannot exceed 8 words and 50 characters. |
Note: If the sum of the limit and offset parameters exceeds 100, then you cannot query with more than one ecid/website at a time.
Response Parameters
Example search response:
{
"data": {
"completeTotal": 450,
"results": [
{
"contacts": [
{
"ES_ContactTier": "Tier2",
"ES_Department1": "Engineering",
"ES_Department2": "",
"ES_Department3": "",
"ES_Department4": "",
"ES_Department5": "",
"ES_DirectPhone": "+1 1234567890",
"ES_CompanyPhone": "+1 6504253937",
"ES_PhoneStatus": "valid_company_phone",
"ES_ECID": 152695187,
"ES_EPID": 1738744519,
"ES_Email": "escontact1@everstring.com",
"ES_EmailStatus": "Accept-All: Email Address",
"ES_FirstName": "John1",
"ES_JobLevel": "Non-Manager",
"ES_LastName": "Doe1",
"ES_ContactLinkedInUrl": "https://www.linkedin.com/in/escontact1",
"ES_PrimaryWebsite": "everstring.com",
"ES_Title": "Software Engineer",
"ES_ContactLastUpdatedDate": "2020-01-18"
},
{
"ES_ContactTier": "Tier2",
"ES_Department1": "Engineering",
"ES_Department2": "",
"ES_Department3": "",
"ES_Department4": "",
"ES_Department5": "",
"ES_DirectPhone": "",
"ES_CompanyPhone": "+1 6504253937",
"ES_PhoneStatus": "",
"ES_ECID": 152695187,
"ES_EPID": 1351629023,
"ES_Email": "escontact2@everstring.com",
"ES_EmailStatus": "Accept-All: Email Address",
"ES_FirstName": "John2",
"ES_JobLevel": "Non-Manager",
"ES_LastName": "Doe2",
"ES_ContactLinkedInUrl": "https://www.linkedin.com/in/escontact2",
"ES_PrimaryWebsite": "everstring.com",
"ES_Title": "Data Engineer",
"ES_ContactLastUpdatedDate": "2020-01-18"
}
],
"inputEcid": 152695187,
"total": 8
},
{
"contacts": [
{
"ES_ContactTier": "Tier2",
"ES_Department1": "Computing & IT",
"ES_Department2": "Engineering",
"ES_Department3": "Product",
"ES_Department4": "",
"ES_Department5": "",
"ES_DirectPhone": "",
"ES_CompanyPhone": "+1 8777294269",
"ES_PhoneStatus": "",
"ES_ECID": 132002315,
"ES_EPID": 1730696402,
"ES_Email": "boxcontact1@box.com",
"ES_EmailStatus": "Accept-All: Email Address",
"ES_FirstName": "Jane1",
"ES_JobLevel": "Non-Manager",
"ES_LastName": "Doe1",
"ES_ContactLinkedInUrl": "https://www.linkedin.com/in/boxcontact1",
"ES_PrimaryWebsite": "box.com",
"ES_Title": "Product Security Engineer",
"ES_ContactLastUpdatedDate": "2020-01-18"
},
{
"ES_ContactTier": "Tier2",
"ES_Department1": "Product",
"ES_Department2": "",
"ES_Department3": "",
"ES_Department4": "",
"ES_Department5": "",
"ES_DirectPhone": "",
"ES_CompanyPhone": "+1 8777294269",
"ES_PhoneStatus": "",
"ES_ECID": 132002315,
"ES_EPID": 1532007099,
"ES_Email": "boxcontact2@box.com",
"ES_EmailStatus": "Accept-All: Email Address",
"ES_FirstName": "Jane2",
"ES_JobLevel": "Non-Manager",
"ES_LastName": "Doe2",
"ES_ContactLinkedInUrl": "https://www.linkedin.com/in/boxcontact2",
"ES_PrimaryWebsite": "box.com",
"ES_Title": "Product",
"ES_ContactLastUpdatedDate": "2020-01-18"
}
],
"inputEcid": 132002315,
"total": 442
}
]
},
"time_taken": "0:00:01.349901"
}
Response for a successful search call is a JSON structure describing the result contacts, totals, and original inputs
Contacts
| Attribute | Description | Data Type |
|---|---|---|
| ES_ECID | EverString Company ID (ECID) is a unique identifier for a company entity to which contact belongs | BIGINT |
| ES_EPID | EverString Person ID (EPID) is a unique identifier for a contact entity | BIGINT |
| ES_PrimaryWebsite | Website of contact’s company | VARCHAR |
| ES_FirstName | First name of contact | VARCHAR |
| ES_LastName | Last name of contact | VARCHAR |
| ES_Title | Title of contact | VARCHAR |
| ES_JobLevel | Seniority level of contact | VARCHAR |
| ES_Department1 | Department 1 of contact | VARCHAR |
| ES_Department2 | Department 2 of contact | VARCHAR |
| ES_Department3 | Department 3 of contact | VARCHAR |
| ES_Department4 | Department 4 of contact | VARCHAR |
| ES_Department5 | Department 5 of contact | VARCHAR |
| ES_Email | Email address of contact | VARCHAR |
| ES_DirectPhone | Contact direct phone number | VARCHAR |
| ES_CompanyPhone | Company phone number | VARCHAR |
| ES_ContactLinkedInUrl | LinkedIn URL of contact | VARCHAR |
| ES_ContactTier | Tier of contact | VARCHAR |
| ES_EmailStatus | Contact email status (Valid, Accept-All, etc.) | VARCHAR |
| ES_PhoneStatus | Contact phone status | VARCHAR |
| ES_ContactLastUpdatedDate | Date when contact was last updated | VARCHAR |
| inputEcid | ecid to which contacts in respective JSON object belong | BIGINT |
| inputWebsite | website to which contacts in respective JSON object belong | VARCHAR |
| total | Total filtered contacts found in company specified by “inputEcid” or “inputWebsite” | INT |
| completeTotal | Total filtered contacts found across all companies | INT |
| time_taken | “0:00:00.278872” | VARCHAR |
Location Search API
Endpoint URL: https://api.everstring.com/v1/locations/search
The Location Search REST API provides an interface to search company locations in the EverString database.
Request Parameters
Example search request:
curl "https://api.everstring.com/v1/locations/search" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{"criteria": {"state": ["California", "Washington"],
"city": ["Seattle", "Hercules"],
"zipcode": ["94547", "98101", "98134"],
"employeeSize": ["1-10", "11-20", "21-50", "10,000+"]},
"ecid": 155569976,
"limit": 10,
"offset": 0}'
Request parameters are POSTed to API in a JSON structure with following attributes:
| Attribute | Is Optional | Description |
|---|---|---|
| ecid | NO | ECID specifying the company for which to search locations |
| criteria | YES | Dictionary describing filter conditions for the search. See “Criteria Details” section below. |
| limit | YES | Total number of locationIds to return, default 10 |
| offset | YES | Offset of locationIds to return, default 0 |
Criteria Details
criteria allows filtering on specific locations for the given ECID. Locations must match on one of the provided values of every criteria key.
For example, the example search request specifies “state”, “city”, “zipcode”, and “employeeSize”. This means that every locationId in the response must be in one of the specified states, AND one of the specified cities, AND one of the specified zipcodes, AND have an employee size within one of the specified buckets.
| Key | Description |
|---|---|
| revenue | List of one or more strings specifying revenue buckets: “$0M-$1M”, “$1M-$5M”, “$5M-$10M”, “$10M-$25M”, “$25M-$50M”, “$50M-$100M”, “$100M-$250M”, “$250M-$500M”, “$500M-$1B”, “$1B-$5B”, “$5B+” |
| employeeSize | List of one or more strings specifying employee size buckets: “1-10”, “11-20”, “21-50”, “51-100”, “101-200”, “201-500”, “501-1,000”, “1,001-2,000”, “2,001-5,000”, “5,001-10,000”, “10,000+” |
| state | List of one or more strings specifying states (exact match) |
| city | List of one or more strings specifying cities (exact match) |
| zipcode | List of one or more strings specifying zipcodes (exact match) |
Response Parameters
Example search response:
{
"data": {
"locationIds": [
"155569976BYUYOXPKYA",
"155569976XCVGBQMKXM",
"155569976NWKLKKNDQR",
"155569976OWVPEBVQSF",
"155569976AWRCKLIJUY",
"155569976MPTQLTBXRW",
"155569976QHQMPGUBEQ",
"155569976SKHLDLVNOP",
"155569976OQCKPEVUEV",
"155569976VSXHLJXVBW"
],
"primaryLocationId": "155569976BYUYOXPKYA",
"total": 24
}
}
Response for a successful search call is a JSON structure describing the matching company location IDs, primary location ID, and total matching locations
Company Locations
| Attribute | Description | Data Type |
|---|---|---|
| locationIds | Location IDs within the specified page (based on limit/offset) that match input ecid/criteria | List |
| primaryLocationId | Primary location ID of input ECID. Will be null if not included in page of locationIds. |
String |
| total | Total locations that match input ecid/criteria | Integer |
Intent Recommendation API
Endpoint URL: https://api.uat.everstring.com/v1/recommendations/intent
The Intent Recommendation REST API provides an interface to recommend intent topics, based on an intent topic or domain input.
Request Parameters
Example topic input request:
curl "https://api.uat.everstring.com/v1/recommendations/intent?topic=Everstring" \
-X GET -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}"
Example topic input response:
{
"data": [
"Account-Based Marketing (ABM)",
"Advanced Analytics",
"Channel Marketing",
"Clearbit",
"Data Analytics",
"Data Science",
"DataRobot",
"Demand Generation",
"Demandbase",
"Full Circle Insights",
"Highspot",
"InsideView",
"Lattice Engines",
"LeadIQ",
"Leadspace",
"Looker Data Sciences",
"Master Data Management (MDM)",
"People.ai",
"Predictive Analytics",
"Prescriptive Analytics",
"Sales Intelligence"
]
}
Example domain input request:
curl "https://api.uat.everstring.com/v1/recommendations/intent?domain=everstring.com" \
-X GET -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}"
Example domain input response:
{
"data": {
"1": [
"Everstring",
"Demandbase",
"Leadspace",
"Full Circle Insights",
"Lattice Engines",
"Sales Acceleration",
"Channel Marketing",
"Demand Generation",
"Dun & Bradstreet",
"Data-Driven Marketing",
"Sales Enablement",
"Customer Lifecycle",
"Sales Intelligence",
"Customer Acquisition",
"Marketing ROI",
"Marketing Analytics",
"Teradata (TDC)",
"Clicktale",
"Multichannel Marketing",
"Predictive Lead Scoring",
"Marketing Attribution",
"Marketing Automation",
"Customer Intelligence",
"Account-Based Marketing (ABM)",
"HG Insights",
"Sales Pipeline",
"B2B Marketing",
"InsideView",
"Datanyze",
"Lead Scoring",
"True Influence",
"Marketing Funnel",
"Outbound Marketing",
"Relationship Marketing",
"Lead Generation",
"Televerde",
"Zoominfo",
"Content Personalization",
"TOPO",
"Brightedge",
"Marketing Technology",
"TechTarget",
"Clearbit",
"Shopify",
"Upserve",
"Behavioral Data",
"Sales Funnel",
"Nimble Storage",
"Automated Marketing",
"Salesforce Einstein",
"Triblio",
"Kenshoo",
"ON24",
"Customer Lifetime Value",
"Amplitude",
"Hotjar",
"Mixpanel",
"Customer Behavior",
"IBM Blockchain",
"Highspot",
"Integrated Marketing",
"Intent Data",
"Lead Nurturing",
"ClearSlide",
"Lead411",
"Return on Marketing Investment",
"Invoca",
"Traditional Marketing",
"Tealeaf",
"Experian (EXPN)",
"Lead Management",
"First-Party Data",
"Concentrix",
"Multi-Touch Attribution",
"Azure Data Lake",
"Oracle",
"Microsoft Corporation",
"Interactive Marketing",
"Marketing Dashboards",
"Pricing Analytics"
],
"2": [],
"3": []
}
}
Request parameters are provided to the API via GET/POST with the following attributes:
| Attribute | Optional | Description |
|---|---|---|
| topic | YES | The name of an intent topic. Response is a set of topics; order not indicative of relevance. |
| domain | YES | A company’s domain. Response returns topics organized within tiers, elaboration below. |
A domain input response organizes recommended topics into 3 tiers. Tier 1 contains the most relevant and tier 3 contains the least relevant topics, based on certain relevance score thresholds. Order within a tier is based on the number of input domain keywords that match on a given topic. Topics directly mapped to one of the domain input’s top 50 similar domains are placed at the top of tier 1.
AI Assistants
The AI assistants REST API provides an interface to access the Everstring AI generated data
Similar Companies
Endpoint URL: https://api.everstring.com/v1/companies/similar_companies
Request Parameters
Example enrich similar companies for one single company request:
curl "https://api.everstring.com/v1/companies/similar_companies" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{
"type": "website",
"values": ["everstring.com"],
"limit": 5
}'
Request parameters are POSTed to API in a JSON structure with following attributes:
| Attribute | Description | Data Type |
|---|---|---|
| type | support “website”, “email”, “name”, “ecid” | String |
| values | list of value for one type in website, email, name, ecid, Only support one element in the list for now | List |
| limit | Limit similar companies number to return | integer |
Response Parameters
Example response:
{
"data": [{
"ecid": 152695187,
"input": "everstring.com",
"name": "EverString",
"primaryWebsite": "everstring.com",
"similarCompanies": [{
"ecid": 139178931,
"name": "6sense",
"primaryWebsite": "6sense.com"
},
{
"ecid": 112453612,
"name": "Lattice Engines",
"primaryWebsite": "lattice-engines.com"
},
{
"ecid": 157224278,
"name": "Mintigo",
"primaryWebsite": "mintigo.com"
},
{
"ecid": 152998799,
"name": "Infer, Inc.",
"primaryWebsite": "infer.com"
},
{
"ecid": 138134660,
"name": "Leadspace",
"primaryWebsite": "leadspace.com"
}
]
}]
}
Response for a successful call is a JSON structure. For a sample response check the code section. The following are the higher order sections in the response along with various attributes in them.
data
| Attribute | Description | Data Type |
|---|---|---|
| ecid | EverString company id | integer |
| input | Input from the request for one value | String |
| name | Company Name | String |
| primaryWebsite | Company primary Website | String |
| similarCompanies | Company similar Companies, please refer the sample | List of dictionary |
Industry Classifier
Endpoint URL: https://api.everstring.com/v1/companies/industry_classifier
Request Parameters
Example enrich industry and naics code request:
curl "https://api.everstring.com/v1/companies/industry_classifier" \
-X POST -H "Content-Type: application/json" \
-H "Authorization: Token {Access_Token}" \
-d '{
"type": "website",
"values": ["everstring.com", "salesforce.com"]
}'
Request parameters are POSTed to API in a JSON structure with following attributes:
| Attribute | Description | Data Type |
|---|---|---|
| type | support “website”, “email”, “name”, “ecid” | String |
| values | list of value for one type in website, email, name, ecid, Only support one element in the list for now | List |
Response Parameters
Example response:
{
"data": [{
"ecid": 152695187,
"industry": "Computer Software",
"input": "everstring.com",
"naics2": {
"code": "42",
"id": 42,
"name": "Wholesale Trade"
},
"naics4": {
"code": "4234",
"id": 4234,
"name": "Professional and Commercial Equipment and Supplies Merchant Wholesalers"
},
"naics6": {
"code": "423430",
"id": 423430,
"name": "Computer and Computer Peripheral Equipment and Software Merchant Wholesalers"
},
"name": "EverString",
"primaryWebsite": "everstring.com"
}, {
"ecid": 103162132,
"industry": "Computer Software",
"input": "salesforce.com",
"naics2": {
"code": "51",
"id": 51,
"name": "Information"
},
"naics4": {
"code": "5112",
"id": 5112,
"name": "Software Publishers"
},
"naics6": {
"code": "511210",
"id": 511210,
"name": "Software Publishers"
},
"name": "Salesforce.com Inc",
"primaryWebsite": "salesforce.com"
}]
}
Response for a successful call is a JSON structure. For a sample response check the code section. The following are the higher order sections in the response along with various attributes in them.
data
| Attribute | Description | Data Type |
|---|---|---|
| ecid | EverString company id | integer |
| input | Input from the request for one value | String |
| name | Company Name | String |
| industry | Company industry | String |
| primaryWebsite | Company primary Website | String |
| naics2 | Company naics info with 2 numbers, please refer sample response | Dictonary |
| naics4 | Company naics info with 4 numbers, please refer sample response | Dictonary |
| naics6 | Company naics info with 6 numbers, please refer sample response | Dictonary |
Status Codes
The following status codes are possible for every API call:
| Status Code | Meaning |
|---|---|
| 200 | OK – Successful API call |
| 400 | Bad Request |
| 401 | Unauthorized – The access token is invalid or expired |
| 405 | Method Not Allowed – Enrichment API is available as POST only |
| 406 | Not Acceptable – You requested a format that isn’t JSON |
| 500 | Internal Server Error – We had a problem with our server. Try again later. |
| 503 | Service Unavailable – We’re temporarily offline for maintenance. Please try again later. |