Job Opening
Information on a prospect's hiring trends that are relevant to the seller's selling motion
The Job Opening insight provides information on a prospect's hiring trends that are relevant to the seller's selling motion. This insight requires both the user ID and contact ID, which can be either their LinkedIn URL, email address, company URL, or company LinkedIn URL.
Note: the only current available parameters for
generate-insights
arecontactEmail
andcontactLinkedinUrl
.
- The system will pass back an array of insights, ranked by relevance.
- The below documentation still accurately covers our schema, and demonstrates what might exist in that array.
- Soon, you'll be able to specify certain insight types in your API request. Coming Q3 2024.
Retrieving Job Opening Insight
To retrieve the Job Opening insight using the Autobound Insights API, you need to make a POST request to the /generate-insights endpoint with the appropriate parameters..
import requests
url = 'https://api.autobound.ai/api/external/generate-insights/v1.0.0'
headers = {
'X-API-KEY': 'YOUR-API-KEY-HERE',
'Content-Type': 'application/json'
}
data = {
"userLinkedinUrl": "https://www.linkedin.com/in/johndoe",
"contactLinkedinUrl": "https://www.linkedin.com/in/janesmith",
"insightType": "JOB_OPENING"
}
response = requests.post(url, headers=headers, json=data)
print(response.text)
Replace 'YOUR-API-KEY-HERE' with your actual API key and provide the appropriate user ID and contact ID parameters. The user ID and contact ID can be either their LinkedIn URL, email address, company URL, or company LinkedIn URL.
If the prospect ID is provided on the individual level (not the company level), this unlocks more relevant potential job openings because the API will figure out the pain points on the prospect level, not the general company level, to map to the open positions that are relevant to the seller.
Response Format
The API will respond with the Job Opening insight in JSON format. The response will contain an object with the following fields::
{
"data": {
"name": "Hiring Data Engineers",
"job_title_keywords": [
"data engineer",
"data pipeline",
"ETL",
"data integration",
"data transformation"
],
"specific_business_problem": "ingestion and transformation pipelines, which can be time-consuming and distract data teams from focusing on insights and reporting.",
"quantity": 2,
"positions": [
{
"job_title": "Senior Data Engineer",
"job_description": "We are seeking a Senior Data Engineer to design and implement scalable data pipelines and architectures. The ideal candidate will have experience with big data technologies and a strong understanding of data modeling and ETL processes.",
"url": "https://www.example.com/jobs/senior-data-engineer",
"salary": "150000",
"last_seen": "2023-06-15",
"location": "San Francisco, CA"
},
{
"job_title": "Data Engineer",
"job_description": "We are looking for a Data Engineer to build and maintain our data infrastructure. The successful candidate will collaborate with cross-functional teams to ensure data quality, reliability, and accessibility.",
"url": "https://www.example.com/jobs/data-engineer",
"salary": "120,000",
"last_seen": "2023-06-12",
"location": "New York, NY"
}
]
}
}
Field Descriptions
name
(string): The name or title of the job opening insight, indicating the hiring trend.job_title_keywords
(array of strings): An array of keywords related to the job titles associated with the hiring trend.specific_business_problem
(string): A description of the specific business problem or challenge that the hiring trend aims to address.quantity
(integer): The number of open positions related to the hiring trend.positions
(array of objects): An array of objects representing the individual job openings.job_title
(string): The title of the job opening.job_description
(string): A brief description of the job opening and its responsibilities.url
(string): The URL of the job opening posting.salary
(string): The salary range or compensation for the job opening.last_seen
(string): The date when the job opening was last observed or updated.location
(string): The location of the job opening.
Use Cases
The Job Opening insight is valuable for various use cases, such as:
- Sales Prospecting: Identify potential prospects based on their hiring trends and open positions. Job openings can indicate a company's growth, strategic initiatives, or pain points that align with the seller's offerings.
- Account Mapping: Map out the hiring trends and open positions within a target account to understand their priorities, challenges, and potential needs. This information can help tailor the sales approach and identify relevant stakeholders.
- Personalized Outreach: Leverage the specific business problems and pain points associated with the hiring trends to personalize outreach messages and demonstrate how the seller's products or services can address those challenges.
- Competitive Intelligence: Monitor the hiring trends of competitors to gain insights into their strategic initiatives, expansion plans, or areas of focus. This information can help inform competitive strategies and differentiation.
- Partner Ecosystem: Identify potential partners or complementary solutions based on the hiring trends and open positions of prospects. Job openings can indicate areas where collaboration or integration opportunities exist.
- Talent Acquisition: Utilize the job opening insights to identify companies that are actively hiring for specific roles or skill sets. This information can be valuable for recruiters or talent acquisition teams looking to source candidates or understand market demand.
By leveraging the Job Opening insight, sellers can gain valuable information about a prospect's hiring trends, specific business problems, and open positions. This insight can help inform sales strategies, personalize outreach, identify opportunities, and enhance the overall sales process.
Updated about 2 months ago