Neol is a AI-Powered Recruitment SaaS Platform for B2B
Neol is a AI-Powered Recruitment SaaS Platform for B2B
Neol is a AI-Powered Recruitment SaaS Platform for B2B
Mini case study and visual showcase
Neol streamlines the hiring process for tech companies across company’s own network or Neol s global expert pool by using AI powered search, analysis and reviews.
Neol streamlines the hiring process for tech companies across company’s own network or Neol s global expert pool by using AI powered search, analysis and reviews.
Problem Statement
Problem Statement
Problem Statement
Home Screen
Home Screen
In the initial dashboard, the prominence of the keyword search bar led to "habitual searching."
Users defaulted to basic keywords, resulting in generic candidate matches and a failure to realize the platform's AI capabilities.
Furthermore, the primary AI chat interface suffered from discoverability issues due to low visual contrast and a cramped text field.
In the initial dashboard, the prominence of the keyword search bar led to "habitual searching."
Users defaulted to basic keywords, resulting in generic candidate matches and a failure to realize the platform's AI capabilities.
Furthermore, the primary AI chat interface suffered from discoverability issues due to low visual contrast and a cramped text field.
In the initial dashboard, the prominence of the keyword search bar led to "habitual searching."
Users defaulted to basic keywords, resulting in generic candidate matches and a failure to realize the platform's AI capabilities.
Furthermore, the primary AI chat interface suffered from discoverability issues due to low visual contrast and a cramped text field.
New Home Screen
New Home Screen
To shift user behavior from "searching" to "prompting," I implemented three key design interventions:
To shift user behavior from "searching" to "prompting,"
I implemented three key design interventions:
To shift user behavior from "searching" to "prompting," I implemented three key design interventions:
Design Decisions
Guided Discovery: I introduced a suite of six starter prompts categorized by search intent. This lowered the "blank page" anxiety and showcased the platform’s specific value propositions immediately.
Visual Prominence: I redesigned the chat interface with a larger footprint and higher contrast ratios to establish a clear visual hierarchy.
Focus Drifting: To further signal the intended starting point, I added a subtle entry animation and glow effect to the chat area, drawing the user’s eye toward the conversational interface upon landing.
Conversational Onboarding: By placing the conversational AI on the left (following natural F-pattern reading logic), I enabled users to describe their "ideal candidate" in natural language, triggering a guided flow rather than a static results list.
Rationale behind why I placed the Conversational AI interface on the left:
Based on our A/B tests, It performed better than right hand-side version and as humans we usually scan in an F-pattern. Putting it on the left made it the literal first thing they see and read.
Guided Discovery: I introduced a suite of six starter prompts categorized by search intent. This lowered the "blank page" anxiety and showcased the platform’s specific value propositions immediately.
Visual Prominence: I redesigned the chat interface with a larger footprint and higher contrast ratios to establish a clear visual hierarchy.
Focus Drifting: To further signal the intended starting point, I added a subtle entry animation and glow effect to the chat area, drawing the user’s eye toward the conversational interface upon landing.
Conversational Onboarding: By placing the conversational AI on the left (following natural F-pattern reading logic), I enabled users to describe their "ideal candidate" in natural language, triggering a guided flow rather than a static results list.
Rationale behind why I placed the Conversational AI interface on the left:
Based on our A/B tests, It performed better than right hand-side version and as humans we usually scan in an F-pattern. Putting it on the left made it the literal first thing they see and read.
Design Decisions
Design Decisions
The Impact of the Redesign
%24.2
Increase in search success rate
Increased the 'Search Success Rate' (users finding a candidate they liked in the first 12 results) by 24.2% due to more specific AI-driven queries.
Increased the 'Search Success Rate' (users finding a candidate they liked in the first 12 results) by 24.2% due to more specific AI-driven queries.
%15.8
Reduced time to first action
Reduced “Time to First Action' by 15.8%; the entrance animation and glow effect successfully minimised cognitive load by signalling the primary starting point.
Reduced “Time to First Action' by 15.8%; the entrance animation and glow effect successfully minimised cognitive load by signalling the primary starting point.
3x
Candidate
save rate
Candidate Save Rate: Users who utilized the AI conversational flow saved 3x more candidates per session compared to those using traditional keyword search.
Candidate Save Rate: Users who utilized the AI conversational flow saved 3x more candidates per session compared to those using traditional keyword search.
Failed Design Experiment
Failed Design Experiment
Failed Design Experiment
Alternative Dashboard Design
In this alternative version, I explored a "Hybrid Dashboard" that displayed the user’s existing network alongside the AI interface. The hypothesis was that seeing their network would provide immediate context.
The Finding: Testing revealed a 19% drop in AI conversations. The additional visual data created "Feature Noise," distracting users from the primary value proposition.
The Pivot: I decided to deprioritize the network view in favor of a "clean-slate" conversational UI. This reduced cognitive load and ensured that the user’s first interaction was high-intent prompting rather than passive browsing.
Alternative Dashboard Design
In this alternative version, I explored a "Hybrid Dashboard" that displayed the user’s existing network alongside the AI interface. The hypothesis was that seeing their network would provide immediate context.
The Finding: Testing revealed a 19% drop in AI conversations. The additional visual data created "Feature Noise," distracting users from the primary value proposition.
The Pivot: I decided to deprioritize the network view in favor of a "clean-slate" conversational UI. This reduced cognitive load and ensured that the user’s first interaction was high-intent prompting rather than passive browsing.
Alternative Dashboard Design
In this alternative version, I explored a "Hybrid Dashboard" that displayed the user’s existing network alongside the AI interface. The hypothesis was that seeing their network would provide immediate context.
The Finding: Testing revealed a 19% drop in AI conversations. The additional visual data created "Feature Noise," distracting users from the primary value proposition.
The Pivot: I decided to deprioritize the network view in favor of a "clean-slate" conversational UI. This reduced cognitive load and ensured that the user’s first interaction was high-intent prompting rather than passive browsing.
The inclusion of the network feed resulted around 18% decrease in AI chat engagement, confirming that a minimalist, focused UI was essential for driving adoption of AI search feature.
The inclusion of the network feed resulted around 18% decrease in AI chat engagement, confirming that a minimalist, focused UI was essential for driving adoption of AI search feature.
Global Search
Global Search
Based on our user interviews and research, recruiters use different methods to look for the ideal candidate. So I designed a starting page where recruiter can use different methods to initiate a search.
These methods are based on:
Based on our user interviews and research, recruiters use different methods to look for the ideal candidate. So I designed a starting page where recruiter can use different methods to initiate a search.
These methods are based on:
Job description
Project brief
Using smart filters
Job description
Project brief
Using smart filters
Filters and Contextual Mapping
Filters and Contextual Mapping
With filters, users can adjust all necessary criteria and see the contextual mapping of their search generated by AI.
It creates semantic tags and includes in the search. User can edit these semantics easily on this screen before committing the search.
With filters, users can adjust all necessary criteria and see the contextual mapping of their search generated by AI.
It creates semantic tags and includes in the search. User can edit these semantics easily on this screen before committing the search.
Advanced Filters
Advanced Filters
This is where advanced filters can be applied to your search. You can include or exclude specific companies, locations, semantics or roles to get a more specific results.
This is where advanced filters can be applied to your search. You can include or exclude specific companies, locations, semantics or roles to get a more specific results.
Hub Overview
Overview shows your full network capacity and features. You can see the breakdown of your networks, skill and role based stats and and latest activities on your networks.
Overview shows your full network capacity and features. You can see the breakdown of your networks, skill and role based stats and and latest activities on your networks.
Slide Deck Cards
Slide Deck Cards
I’ve designed several slide decks for our co-founder to use in investor pitches.
They highlight the platform's value proposition, key features, and core benefits.
I’ve designed several slide decks for our co-founder to use in investor pitches.
They highlight the platform's value proposition, key features, and core benefits.
Thank you for watching
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