A data-driven approach to maximising margins and enhancing user experience. Working end-to-end shaping the way candidates are found and selected for client AI projects.
Not finding the right candidates for scale and at speed hitting revenue & margins.
Automate the process to help identify and develop the right candidates through a matching system.
- Viability: Increased user utilisation by 25% & reduced support tickets by 83%.
- Usability: CSAT score of 81%.
- Feasibility: Identified and prioritised core functionality.
- Value: Time to work reduced by 80%.
Over the a 12 month period, cloudfactory experienced a 25% drop in client retention primarily due to declining worker performance. This trend was particularly noticeable in projects that required high accuracy and fast turnaround times.
We saw a 25% decline in retention rates over the last 12 months, particularly among clients in their second wave of projects. This drop is significant among clients who request rework as it did not meet the initial quality levels benchmarked which ultimately meant a slower speed of delivery.
A data-driven approach to maximising margins and enhancing user experience. Working end-to-end shaping the way candidates are found and selected for client AI projects.
CloudFactory's user onboarding process was highly manual, relying on Google Forms and online calls. This led to low completion rates (60%) and poor engagement (30%). New users found the process tedious, unstructured, and unclear, delaying productivity and leading to a 25% retention rate over 60 days.