Track job offers at target accounts

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.

Tracking job offers for target company segments and roles using Cargo#

Step 1 - Set variables#

Set up your input variables for the workflow

Inputs used in the workflow are set up in the variables node at the beginning of the workflow. This node is used to define the parameters that will be passed through the rest of the workflow as inputs to the rest of the nodes.

To power this workflow, the following variables are needed:

• 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.

Step 2 - Extract missions and technographics#

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.

For instance, for a prompt asking to extract any of the new hire's missions as well as the tools being used at the hiring company, we have seen the following work well:

You could use a similar system prompt to the one below:

::: 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 3 - Filter and upsert accounts that meet a score#

Filter and upsert accounts that meet a score

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 4 - Stakeholder search#

Find relevant contacts working 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 5 - Email enrichment waterfall#

Email enrichment waterfall

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 6 - Upsert contact to CRM#

Upsert contact 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.

Conclusion#

By following this template, you can efficiently track job offers for target company segments and roles. This workflow ensures that your team is always informed about the latest opportunities and can take timely action.