MindTitan Case Studies AI-Driven Recommendation Engine Boosts Engagement for Fuzu

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	AI-Driven Recommendation Engine Boosts Engagement for Fuzu MindTitan

AI-Driven Recommendation Engine Boosts Engagement for Fuzu

MindTitan

Technology Category	Analytics & Modeling - Machine Learning Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries	Education Equipment & Machinery
Applicable Functions	Procurement Quality Assurance
Use Cases	Predictive Maintenance Time Sensitive Networking
Services	Data Science Services Training
Challenge	Fuzu, a Helsinki-based company, provides job opportunities, career advice, and new skills to young East African professionals. The company faced a challenge in streamlining its user onboarding experience and boosting engagement through personalized recommendations. The onboarding process was cumbersome due to the need to obtain considerable amounts of information from new users. Additionally, Fuzu wanted to leverage the data from pre-written resumes, cover letters, and diplomas available in the form of text documents to facilitate the onboarding process. The company also aimed to keep users engaged with personalized offers and recommendations. However, the question was how to leverage the data and system to provide additional benefits to the customers. Read More
About Customer	Fuzu is a Helsinki-based company that launched a comprehensive career platform for the East African job market in 2015. The company aims to provide ambitious young East African professionals with job opportunities, career advice, and new skills. Fuzu serves a wide range of job seekers, but a typical user is a young university graduate in a major city, such as Nairobi or Mombasa, who may or may not already have some work experience. Fuzu is often a launch pad for people to land their first job. The company currently serves more than one million users in Kenya, Uganda, and Nigeria. Read More
Solution	Fuzu partnered with MindTitan to create machine learning models that would provide users with a streamlined, hassle-free onboarding experience and relevant job recommendations. MindTitan used the datasets from Fuzu to build and train machine learning models. Free text extracted from the resumes and cover letters uploaded by users was classified into skills, seniority, industry, and education level among others. This not only facilitated the onboarding process but also enabled the platform to provide job recommendations that fit the users' needs. Fuzu also started sending out regular emails with personalized suggestions for jobs that candidates may like to apply for. The platform made recommendations based on users’ previous interactions with the platform, including past job applications. Fuzu also used categorization algorithms to identify and post content from partner platforms that is of interest to their users. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Platform as a Service (PaaS) - Application Development Platforms

Applicable Industries

Education

Equipment & Machinery

Applicable Functions

Procurement

Quality Assurance

Use Cases

Predictive Maintenance

Time Sensitive Networking

Services

Data Science Services

Training

Challenge

Fuzu, a Helsinki-based company, provides job opportunities, career advice, and new skills to young East African professionals. The company faced a challenge in streamlining its user onboarding experience and boosting engagement through personalized recommendations. The onboarding process was cumbersome due to the need to obtain considerable amounts of information from new users. Additionally, Fuzu wanted to leverage the data from pre-written resumes, cover letters, and diplomas available in the form of text documents to facilitate the onboarding process. The company also aimed to keep users engaged with personalized offers and recommendations. However, the question was how to leverage the data and system to provide additional benefits to the customers.

About Customer

Fuzu is a Helsinki-based company that launched a comprehensive career platform for the East African job market in 2015. The company aims to provide ambitious young East African professionals with job opportunities, career advice, and new skills. Fuzu serves a wide range of job seekers, but a typical user is a young university graduate in a major city, such as Nairobi or Mombasa, who may or may not already have some work experience. Fuzu is often a launch pad for people to land their first job. The company currently serves more than one million users in Kenya, Uganda, and Nigeria.

Solution

Fuzu partnered with MindTitan to create machine learning models that would provide users with a streamlined, hassle-free onboarding experience and relevant job recommendations. MindTitan used the datasets from Fuzu to build and train machine learning models. Free text extracted from the resumes and cover letters uploaded by users was classified into skills, seniority, industry, and education level among others. This not only facilitated the onboarding process but also enabled the platform to provide job recommendations that fit the users' needs. Fuzu also started sending out regular emails with personalized suggestions for jobs that candidates may like to apply for. The platform made recommendations based on users’ previous interactions with the platform, including past job applications. Fuzu also used categorization algorithms to identify and post content from partner platforms that is of interest to their users.

Impact #1	The implementation of machine learning models and the collaboration with MindTitan enabled Fuzu to streamline its onboarding process and provide personalized job recommendations. This led to an increase in user engagement and satisfaction. The platform was able to provide companies and headhunters with potential employee profiles with the skill sets they’re looking for. The use of categorization algorithms allowed Fuzu to spend less time on identifying and posting content from partner platforms that is of interest to their users. The company was able to recognize specific industries with a high level of accuracy and pre-fill lots of fields, like educational level and job category, thanks to these predictive models. The collaboration with MindTitan also laid the groundwork for Fuzu to explore new areas where they can use these technologies.

Impact #1

The implementation of machine learning models and the collaboration with MindTitan enabled Fuzu to streamline its onboarding process and provide personalized job recommendations. This led to an increase in user engagement and satisfaction. The platform was able to provide companies and headhunters with potential employee profiles with the skill sets they’re looking for. The use of categorization algorithms allowed Fuzu to spend less time on identifying and posting content from partner platforms that is of interest to their users. The company was able to recognize specific industries with a high level of accuracy and pre-fill lots of fields, like educational level and job category, thanks to these predictive models. The collaboration with MindTitan also laid the groundwork for Fuzu to explore new areas where they can use these technologies.

Benefit #1	Click-through rate for job applications increased by 30%
Benefit #2	Classifies education level with 90% accuracy
Benefit #3	Enabled Fuzu to become increasingly data-driven

Benefit #1

Click-through rate for job applications increased by 30%

Benefit #2

Classifies education level with 90% accuracy

Benefit #3

Enabled Fuzu to become increasingly data-driven

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Overview

AI-Driven Recommendation Engine Boosts Engagement for Fuzu

Operational Impact

Quantitative Benefit