MD Portfolio

case study

Predicting Availability using AI

This project was centered around identifying when the freelancers were available for work. It was initiated by the sales team due to their need to see Expert Availability at a granular and bird’s-eye level. The need was due to the business requirement to schedule out upcoming client work. We worked to solve the need for the expert user and the sales user. 

We used AI to check multiple facets that ensure the expert is available at the time of the search. It predicts based on past behavior and preferences.

What problem were we solving?

  • The company faced challenges in determining the availability of Experts for work.
  • The sales team needed to access the schedule of Experts beforehand to schedule them for upcoming work.
  • The Experts required a means to communicate their preferred working hours and when they would no longer accept new work from Paro.

Figma prototype demo

Impact and ROI

  • As a result of our efforts, we successfully reduced matching rejections, leading to a significant increase in the pitching rate of matched experts.
  • Attained 80% feature adoption within the first 45 days
  • Rejection Reason 1 – Job is not a fit for my skill reduced
    • We reduced usage from a monthly average of mid-twenties to low teens

Constraints & Trade-offs

Feeding the Algo
The algo used to determine the probability the Expert was available to work required specific inputs. We had to work within the existing data columns with the ability to build out further. 

Sales Requirements
The sales team insisted on more visibility into the workloads of Experts. They requested the ability to sync calendars with the Experts in hopes of seeing their availability in real-time. Expert surveys indicated they were not willing to share their calendars with the company. We needed an alternate option. 

Conflicts with another roadmap
Our team ran into a hiccup when we bumped into another team’s in-progress work within the same area we needed to access. The miscommunication caused a delay in design production as we had to wait for the delivery of their feature before proceeding.

UX Insights

Our first pass made great strides at the problem of keeping a pulse on Expert Availability.  

  • First, we tackled the issue of lost deals due to availability discrepancies, resulting in improved conversion rates and more revenue opportunities. 
  • Our efforts also led to a decrease in the average number of lost deals per month per representative, showing that our sales efforts are more efficient and effective. 
  • We streamlined the process from lead to signed Statement of Work (SOW), reducing delays and improving our time-to-revenue. 
  • By minimizing the time spent on schedule verification, we freed up our representatives to focus on strategic activities. 
  • Additionally, we took steps to prevent expert burnout by promoting work-life balance and reducing churn caused by overextending availability. These achievements demonstrate our commitment to positive change, financial growth, and long-term success in our business.

Determining User Needs

In order to effectively plan and allocate resources for supply-demand preparedness, revenue forecasting, and staff resources, Paro needed a pulse of the availability of experts. This information allows for optimized operations and data-driven decisions that lead to increased efficiency and profitability.

  • The company faced challenges in determining the availability of Experts for work. 
  • The sales team needed to access the schedule of Experts beforehand to schedule them for upcoming work. 
  • The Experts required a means to communicate their preferred working hours and when they would no longer accept new work from Paro.

The sales team needed – 

  • access to the Expert’s availability outside of 1-week
  • access to all of the Expert’s active proposal data to determine possible flexibility
  • an easy-to-access, central location for finding this information 

The Experts needed – 

  • a way to set their preferred working hours for 1 week and up to 3 months
  • the ability to indicate when they were temporarily unavailable
  • mobile responsive access

 

On-site Workshop

During a week-long design sprint-style workshop with product, data, and engineering teams, I took notes on the whiteboards using photographs and then came back to Figma to notate the requirements and dependencies.

  1. Experts gain a birds-eye view into their future schedules
  2. Ability to indicate when out of office (without getting churned)
  3. Experts can set their availability by week and month
  4. The internal team gains a view of the Expert’s schedule and preferences