Are you looking to boost your earnings on Upwork and scale your business to $20K per month? The secret lies in automation. By leveraging tools like Make.com, you can streamline your workflow, manage multiple clients effortlessly, and save countless hours. I'm going to guide you through setting up automation to take care of monotonous activities in this article so you continue to focus on high-value work and increase your Upwork income without becoming burnt out. Let us delve in and use automation to revolutionize your freelancing business.
The Automation System's Components
These two primary components make up this automation system:
1. OpenAI’s GPT-4: This AI model filters and processes job listings from Upwork, ensuring that only the most relevant opportunities are considered.
2. Airtable: All of the job records are maintained, tracked, and kept in Airtable.
Together, these two elements streamline the job application process from locating possible openings to sending tailored applications. Let's examine each component of this system's operation and how it can support your ability to make steady money.
Step 1: Installing Upwork's RSS Feed
Creating an RSS feed from Upwork is the first step in this automation process. Upwork offers an RSS feed feature that allows freelancers to create specific job queries using Boolean connectors. This feed can be queried every hour or two to identify new job postings that match your criteria.
Creating a Broad Query
To maximize the number of potential job opportunities, I created a very broad query. For example, I used the keyword "automate" to capture any job listings that might involve make.com automation in some capacity. This makes sense since, by widening your search, you can make sure that no possibilities pass you by. There's no need to focus the search right now because AI can handle the filtering later.
- Automate: Specifies the keyword for the job search.
- Sort-recency: Ensures that the most recent jobs appear first.
- Job type-hourly, project: Includes both hourly and fixed-price jobs in the search results.
The feed is configured to return up to 200 items at a time, but since the query runs every 90 minutes, it typically retrieves 10-15 new jobs per run.
Step 2: Parsing Job Descriptions
Once the RSS feed pulls in job listings, the next step is to parse the job descriptions. Upwork job descriptions are typically formatted in HTML, so the first task is to convert this HTML into plain text. This is done using a "Parse HTML to Text" module in Make.com automation, which strips away any unnecessary HTML tags and formatting.
Step 3: Filtering Jobs Using GPT-4
The core of this automation system is the job filtering process, which is handled by GPT-4. This AI model is tasked with analyzing each job description and determining its relevance based on predefined criteria.
Setting Up the Prompt
To filter jobs effectively, I set up a prompt in GPT-4 that includes the following elements:
- System Prompt: Defines the AI’s role as an intelligent administrator that filters job postings.
- User Prompt: Provide context about my business and the types of jobs I’m looking for. In my case, I describe my business as an operations agency specializing in building outreach systems, CRM systems, project management systems, no-code systems, and integrations.
The prompt instructs GPT-4 to filter the job description for relevance and output a JSON object indicating whether the job is relevant or not. If the job is relevant, GPT-4 also generates a short introductory "icebreaker" message that can be included in the job application.
Here’s an example of a user prompt:
You are an intelligent administrator who filters job postings. Below is a job description. Filter it for relevance: true or false. Provide the reason for your decision in JSON format. If relevant, generate a short introductory icebreaker.
Providing Examples for In-Context Learning
To improve the accuracy of the filtering, I provided GPT-4 with several examples of job descriptions and the corresponding desired output. This technique, known as in-context learning, helps the AI model better understand the types of jobs that are relevant to my business.
For Instance, I Provided Examples Like This: GPT Assistant Prompt
- Input: A job description for an Airtable expert.
- Output: `{"result": true, "reason": "Involves automating Airtable, which aligns with your experience.", "icebreaker": "I’m confident I’m the right fit for this job. I have extensive experience automating Airtable systems for high-performing teams."}`
This example teaches GPT-4 how to evaluate job descriptions and generate relevant icebreakers.
Step 4: Parsing and Storing Results in Airtable
After GPT-4 processes the job descriptions, the results are parsed using a "Parse JSON" module in Make.com automation. This module converts the JSON output into a format that can be easily used in subsequent steps.
The next step is to store the results in Airtable. If GPT-4 determines that a job is relevant, the system retrieves additional details, such as the budget and job type (hourly or fixed-price), and stores this information in Airtable. The job listing is then ready for further action.
Step 5: Customizing Job Applications
One of the key features of this system is the ability to generate customized job applications quickly. For relevant jobs, the system uses the icebreaker generated by GPT-4 as the introduction to the application. This introductory message is critical because it makes the application feel personalized, even though it was generated by an AI.
Adding Social Proof
To further strengthen the application, I include social proof by mentioning successful projects I’ve completed in the past. For example, I might say:
I’ve used Airtable to manage a company’s operations that generated $800K in annual revenue. My experience with Airtable interfaces and custom workflows can help streamline your project.
This approach adds credibility and increases the likelihood of getting hired.
Step 6: Handling High-Value Job Applications
For particularly high-value job listings, I take an extra step by recording a Loom video. In this video, I provide a brief introduction, go over my areas of experience, and talk about how I may benefit the client's project. After that, the employment application has a video link.
This personalized touch can make a significant difference, especially for jobs with a high budget or long-term potential.
Step 7: Tracking and Managing Applications in Airtable
Following submission, Airtable acts as the main hub for tracking and administering the applications. A status is attached to every job posting, which could be "Intake," "Applied," "Irrelevant," or "No Longer Available." This facilitates keeping track of the jobs you've applied for and those that are still pending.
You can track your applications performance with Airtable as well. Metrics like the total number of proposals submitted, the success rate, and the money made on each job can all be examined. When it comes to fine-tuning your approach and streamlining your automation system, this data is priceless.
Benefits of Using This Automation System
The automation system outlined in this article brings several important advantages:
Increased Efficiency: Automating the job search and application process allows you to submit more applications without compromising on quality.
Enhanced Personalization: The system creates tailored applications, helping your submissions stand out from the typical, generic responses many freelancers rely on.
Scalability: This approach enables you to scale your freelance business by applying for more jobs, boosting your revenue potential.
Data-Driven Insights: Airtable’s tracking features empower you to make informed decisions, focusing on the most profitable opportunities.
Conclusion
Automating the Upwork job application process using Make.com, GPT-4, and Airtable can be transformative for freelancers and consultants. This system not only saves time but also elevates the quality and personalization of your applications, leading to better outcomes and higher earnings. You may spend more time creating outstanding work by using automation and computers with AI (AI), as the system will take care of the operations. This automatic technology works well for you if you want to grow your freelancing business and consistently earn up to $20,000. a month.
👉 Get in Touch with an Expert: www.growwstacks.com
👉 Learn More on Skool Community: Automation DIY
Kommentare