Overview

Use this template to track job postings, score them based on relevance, and enrich the data before pushing it to your CRM. Additionally, use the AI integration to extract valuable sales insights for your sales teams to activate these opportunities.

How It Works #

This workflow systematically tracks and qualifies job postings by:

1. Analyzing job descriptions with AI to extract missions and tech stack
2. Scoring relevance to your product offering
3. Filtering high-value opportunities
4. Finding and enriching stakeholder contacts
5. Pushing qualified leads to your CRM and sales sequences

Setup

Required Variables #

Configure the following input variables in the variables node at the beginning of the workflow:

• keywords: Keywords related to the job roles you are targeting (e.g., “engineer”, “sales”, “marketing”)
• yourPersona: Description of the target persona (e.g., “mid-level sales manager, technical people”)
• yourValueProposition: Value proposition of your company (e.g., “We’re working on a new project that helps companies automate their sales processes and boost productivity”)
• linkedinID: LinkedIn ID of the company publishing the job posting
• titleKeywords: Job titles of the target persona to be used for stakeholder enrichment

Workflow Steps

Step 1: Extract Missions and Technographics with AI #

Job postings contain valuable information that is rare to find elsewhere.

Use one or more OpenAI nodes to parse the job posting. This step extracts structured information about the mission of the role being hired for. To ensure high-quality output, strictly define the analysis rules in the system prompt of the OpenAI integration, setting clear guardrails for the instructions.

Example prompt:

Example system prompt:

::: For each mission where you can relate {{your company's name\}\}'s offering, extract the exact sentence and explain why you think this specific mission is a good fit.

At the end, you should also return a relevancy score of the job offer compared to our offering on a scale from 0 to 20.

Return a JSON with:

1. Missions and explanations of the fit.
2. Score of the job’s relevancy to our company’s offering.
3. Tools used by the new hire. :::

Use the response format to structure the schema of an acceptable output, either a string or a JSON object format.

Step 2: Filter and Upsert High-Scoring Accounts #

The filter node filters the job postings based on the score created by the AI analysis in the previous step. In this example, only postings with a score greater than 18 are processed further.

The subsequent CRM write node updates or inserts the hiring company’s account information into the CRM.

Step 3: Find Stakeholders at the Company #

The data input from the Datachimp-based data model will contain a website domain and a LinkedIn company ID of the hiring company. Using this, you can use an enrichment provider’s search action (in this case, using Sales Navigator’s search action) to identify contacts currently working at those companies.

Alternatively, you can use an enrichment tool that you’re already subscribed to (e.g., ZoomInfo, Cognism, Apollo, Clearbit) or try new providers available with Cargo credits (e.g., Waterfall.io, FullEnrich, PeopleDataLabs).

Make sure to specify additional filters (e.g., job titles, location, seniority) to narrow down only to relevant contacts at these companies who are likely to be involved in the buying decision for your product. Note that each enrichment provider specifies its own format and phrasing of job titles. You can check the documentation of the enrichment provider to align with their formatting when adding job titles, seniorities, etc.

As the search will produce an array of contacts, the rest of the execution flow will proceed inside a group node.

Step 4: Enrich Contact Emails #

This series of nodes ensures that at least one email is found for the contact before it can be inserted into the CRM. You may add further enrichment providers to this waterfall logic to expand coverage as needed.

Step 5: Upsert Contacts to CRM #

This node updates or inserts the contact information into the CRM. Upserting the new contact’s information into the CRM under the account upserted in the parent workflow provides your sales team with multiple contacts to triangulate the conversation.

Additionally, you may choose to send a Slack notification to a dedicated channel to update the team, which includes the sales insights extracted earlier from the AI analysis.

Expected Outcomes

By implementing this workflow, you can:

• Automatically identify companies with relevant hiring needs
• Score and prioritize opportunities based on product fit
• Surface AI-extracted insights to personalize outreach
• Keep your team informed about the latest opportunities in real-time