DesignScout Case-Study

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Using Artificial Intelligence to Identify Product Design Traits

Overview

Using Artificial Intelligence to Identify Design Thinking Traits

DesignScout is an AI-powered design recruitment platform built to assess creative talent. I played a key role in identifying early product-market fit, shaping the product vision, and developing custom ranking features that generated strong market pull by enhancing hiring managers' ability to streamline candidate evaluation.

Role

Founding Team Member

Duration

6 months

Category

0-1 Product, User Research, GTM Strategy

Team

Hemant Bothra, Rahul Gottimukkala, Dayton Kelly,

Impact

Early Promise Established, DesignScout is Now an Incorporated Start-up

Runners up @ AfroTech Conference ‘24

Generated 80+ sign-ups in < a month

Conducted 15 usability tests

Conducted Pilots with 2 startups

Problem Space

How Can We Balance Subjectivity & Efficiency?

In the current hiring landscape, design recruitment processes often lack consistency, with many recruiters and hiring managers relying on subjective assessments of portfolios and resumes. Despite numerous recruitment tools in the market, traditional screening fails to capture critical insights into a designer’s thought process and creativity. How can we bridge this gap?

Problem 01

Portfolios weren’t informative

Hiring managers reported that portfolios alone don’t give them enough information to make hiring decisions.

Problem 02

Screenings weren’t predictive

Recruiters reported that portfolios alone don’t give them enough information to make hiring decisions.

Problem 03

Candidates didn’t feel heard

Candidates felt that hiring processes don’t allow them to showcase their thought processes and creativity fully.

Enter,

GenerativeAI.

But,

Would It Truly Help?

Exploratory Research

Users Felt It Had Potential, But We Needed To Validate Further

We held exploratory interviews with close to 15 design leaders and recruiters combined. we wanted to understand current attitudes towards implementing artificial intelligence in the recruitment process.

Key Decision - What Do We Prototype First?

We Prototyped The Candidate Experience

From target segments’ perspective, the candidate experience was critical to employer branding

We felt this was the most critical piece from a customer perspective. We felt that prospective customers wouldn’t want to give potential designers a poor

assessment experience. Furthermore, we were a small team and prioritizing the most critical parts, the parts that would bring us closer to earning revenue

were the most important parts. So, we created a prototype of the candidate experience and showed it to designers and recruiters at Figma’s annual conference, Config.

Candidates would be asked different business questions

Candidate enter their responses through Figma-esque comment boxes

They would have to incorporate context from the product-brief section

Candidates would be given a limited time to give their responses.

But None of The Feedback
Was Around The Candidate Experience!

Initial Insights

Config taught us many things, and gave us more decisions to make....

Observations

Designers just wanted to see evidence of craft, not just thought process.

Designers wanted candidates to use an existing design system.

Design Leaders felt this would be better for product managers.

They wanted to test soft-skills such as collaboration.

Should we create a design test rather than a critique?

Should we create a case-study simulation?

Should we target an entirely different use-case?

Startup founders mentioned that they manually searched for candidates.

Design Leaders at large tech companies felt they had good candidates.

Should we scrap the idea altogether?

Recruiters were most excited about this solution. More than design leaders

Recruiters felt they would want to go back to insights from this tool.

Should we make an ATS?

Should we target recruiters?

Participants thought this was a one-stop hiring solutions . It wasn’t.

Decision Making Criteria

Targeting Recruiters Met My Decision Making Criteria, Here’s Why

We Asked Ourselves these Questions to clarify decision making.

Does it help us build the core product?

Ultimately, the recruiter & manager experience was core.

Will it bring us closer to revenue?

We absolutely needed to demo the recruiter experience during sales calls.

Will it help us attract users?

Having recruiters send evaluations opened virality potential.

Key Decision - What Next after Config

Next We Prototyped & Tested The Recruiter Experience

Recruiters would have multiple assessments running in parallel for different jobs.

Each assessment would be customise based on the seniority of the opening.

Once responses are received, recruiters, would see each candidate in a ranked list.

Recruiter would be able to deep dive into each candidates scoring.

They would also see how each candidate performed on every scoring criteria.

and also see how the responses related to traits being searched for

Usability Testing Insights

The Insights Helped Build The Product Roadmap.

Based on the questions we received, the suggestions that designers and recruiters made, we concluded that these were the main pillars that our core solution needed to revolve around.

Theme 01

Trust

Users weren’t sure how the AI would arrive at an assessment. Could it be hallucinating?