Thread
The tie between organizations and a successful hire
Overview
Recruiting great tech talent is difficult. Organizations often spend a great deal of time and money in hopes of finding successful hires. Recent data shows recruiting great talent is a high-level challenge for all organizations in the tech industry.
$28,000
amount spent for a single successful hire
18% to 35%
of employee’s salary goes to recruiting costs
74%
of managers and recruiters say they’ve hired the wrong person for a job
The Problem
Currently, organizations typically use referral bonuses or outsource recruiting efforts to find new employers. However, companies spend a great deal of time attempting to connect to quality candidates, but are unsuccessful in finding their perfect match.
Recruitment teams lack knowledge
Hiring managers don’t know the job pool
Not enough time to vet all applicants
Solution
Thread is a digital product that leverages the relationships between people to connect job seekers and hiring managers and cultivate meaningful connections. Companies no longer have to wade through piles of resumes or pay expensive recruiting services. Job seekers are recommended by their existing connections, and hiring managers receive quality applicants.
How might we efficiently connect skilled job seekers with compatible employers to increase employee retention and overall job satisfaction?
Responsibilities and Scope
This project was completed as part of MICA’s Residency program. Over the course of two days, a five-person UX team worked collaboratively to respond to a given prompt. Research was gathered and evaluated on day one, which informed the design and usability phase which took place on day two.
My Role
Desk Researcher
UI Designer
Project Duration
2 days
15 screens
Project Timeline
Understanding the Problem
Desk research was conducted to find out more about how these connections are currently being made, and what is and isn’t working in the industry. From general research, we found that:
$2,500
average employee referral bonus in 2019
4 times more likely
employees recommended by referral are four times more likely to be hired
45%
45% of people employed through referrals stay with the company for more than four years
Initial Analysis
Insights were collected from a total of nine people. They varied in potential user type and ideal motivation for using this product. The main objectives were to collect general information about the industry, identify personal preferences, reveal pain points or confusing experiences.
Given the time constraints, participants were found within the direct network of group members.
Ideal Users
User personas were created to better understand the current audience. This helped solidify their potential motivations for using the product.
Hiring Manager
“Its not just about the skills and the technical ability, but can they work well with others?”
Behavior Traits
Passionate
Thoughtful
Curious
Knowledgeable
Goals
Wants to hire the appropriate candidate
Pain Points
Does not have a lot of time
Is overwhelmed by the job pool
Needs
An efficient way to hire people
Wants someone who can communicate to various people on a team
Connector
“It doesn’t take much incentive for me to refer a friend. I just like to connect people.”
Behavior Traits
Passionate
Advocate
Loyal
Charismatic
Goals
Wants to make additional income
Enjoys making connections with people
Pain Points
Does not have an easy way to suggest friends
Can’t find a side hustle that plays to their strengths
Needs
A platform for connect people
Job Seeker
“I don’t want to work for a place that is hated by everyone who works there.”
Pain Points
Does not have a lot of time
Finds it frustrating to have to retype information
Needs
Any easy way to apply to jobs
Someone to advocate for them
To know where they are in the application process
Behavior Traits
Unsure
Thoughtful
Tech-Oriented
Overwhelmed
Goals
Wants a job that values them
Wants to be qualified for the job
Key Findings
Insights were gained through phone calls and video interviews. The focus was on pain points and frustrations, but we also hoped to gather information specific to the industry. The findings were analyzed and segmented by user group.
Hiring Managers
Employers trust personal recommendations over an algorithm
Soft skills are just as important as technical skills
Companies use recruiters to filter candidates
Companies commonly do not disclose salary
Connectors
Connections take time to make
Connectors feel invested in the outcome
They find it joyful to make connections between people
Job Seekers
Culture is almost as important as salary
Salary insights and job descriptions should be clear
The hiring process should be fast and simple
They want to feel like a qualified applicant
Findings Influence Flow
We brainstormed wants and needs to solve potential pain points uncovered during the hiring process.
Template for job postings to ensure info about culture and soft skills were included
Feedback is automated and instantaneous
Keeping all parties informed along the way
Connectors use their existing network to recommend good matches
Having a mutual connection filter candidates
User Flow
We also built out several user flows, but prioritized the job seeker flow in the interest of time.
Design System
Inspiration was drawn from a tactile connector, which also became the company name. Bright colors were used to inject excitement and fun into the product. A simple mark and type-driven logo was implemented to highlight the content.
Wireframing and Prototyping
A high-fidelity prototype was built in order to test the viability of the product. Key features were prioritized and integrated into the prototype.
A culture rating pulled from GlassDoor to interject transparency
Job posting template to ensure consistency across the product
Incentive pay to aid with product adoption
Connector survey to legitimize job candidate and give employer more information
Testing the Assumptions
The prototype was tested with three participants over the course of one day. Each participant was given a short description of the product and walked through the flow. General feedback was also gathered regarding the overall impression of the product.
Key Takeaways
Negative Insights
66% of participants did not understand the star ratings and were confused by some CTAs
33% of participants wanted more updates on the hiring status and referral bonus
66% of participants wanted to view the job posting again before submitting the recommendation
Positive Insights
66% of participants said they would use the product
100% of participants were able to complete the flow
100% of participants were able to locate the status of their recommendations
Implementing Feedback
After completing user testing, we were able to make some small updates to the prototype.
Wireframes before updating
Our initial idea leveraged the user’s LinkedIn’s connections, but it became clear after testing that it was a bit cumbersome. So we decided to remove that altogether, and center the connections within the product itself.
A referral status screen was added, so the connector can see where the job seeker is in the process, and how close they are to getting that referral bonus. This also interjects some transparency into the process for the job seeker, and would allow them to know where they are in the process, without constantly having to follow up with the employer.
Wireframes after updating
Next Steps
Trustworthiness Rating
Identify connectors that have recommended positive job candidates
Schedule Interviews
Add the ability to schedule an interview into the product
Hiring Manager Flow
Build out the Hiring Manager flow which would take place on desktop
Recommend Yourself
Add the ability to recommend yourself for a job, or apply directly through the product
Test and Iterate
Continue iteration and testing with larger group of participants
Continue Building
Keep building out the product beyond the prioritized user flow