KUNGFU.AI worked with one of the world’s largest job listing websites. Their comprehensive platform is designed to streamline and optimize the hiring process for both job seekers and employers. With a wide range of features and tools, the online platform offers a convenient and efficient solution for finding and hiring top talent. By using their platform, employers can post job listings and reach a vast pool of potential candidates through their extensive job seeker database. In addition, job seekers can search for job opportunities, apply for jobs, and manage their applications using the platform.
The client approached KUNGFU.AI with unique challenges on the employer side of their platform.
For products they wanted to enhance but weren't sure where the change opportunities lay, they collaborated with KUNGFU.AI to conduct in-depth research analysis. The aim was to understand user interactions and uncover valuable insights that could guide product changes and drive revenue growth.
For the products where they have already decided on modifications, the client performs experimentation (i.e., A/B testing) on the platform to gather real-world usage data and assess the potential impact of proposed changes. To ensure the reliability of these experiments and extract meaningful insights from the resulting data, they collaborated with KUNGFU.AI to conduct comprehensive pre- and post- A/B testing analysis. This analysis helps determine the optimal duration of experiments, ascertain the required data volume for statistical confidence, and extract valuable information to inform product decisions, guide the direction of product changes, and make potential launch decisions.
The client wanted to explore potential changes that could be made to a specific feature on their platform, which employers use to manage job applications. Our investigation encompassed various aspects of feature utilization to gain a comprehensive understanding of how and why employers were using it. We analyzed feature utilization based on employer types, observed changes in usage rates over time as employers became more familiar with the feature, examined utilization seasonality, and explored interactions between this feature and other features of the same product. Additionally, we implemented measures to control for potential confounding factors during our analyses. By thoroughly understanding the user journey, KUNGFU.AI and the client identified several key areas where product changes could enhance the user experience and drive revenue growth.
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In another project, the client had aimed to address a known pain point of a feature. They made changes and tested the changes through an experiment. Unfortunately, the experiment did not bring about the desired changes in user behavior or solve the problem. The client collaborated with KUNGFU.AI to determine why the experiment failed to produce meaningful improvements in user experience and behavior. Additionally, KUNGFU.AI examined two crucial and actionable aspects of the product related to the pain point. The results revealed that while both factors were statistically significant in relation to the pain point, one factor had a stronger association with the pain point than the other. Based on these findings, we advised the client to prioritize product changes targeting this particular factor.
In an A/B testing project, the client implemented a product change and conducted an experiment to gather real-world data on how this change would impact user behavior on their platform. The client collaborated with KUNGFU.AI to analyze the collected data and assess the implications of the product change for the next steps. The analysis revealed that the product change had a positive impact on revenue, resulting in a certain percentage increase. The findings also indicated that the product change led to an increase in employers' interactions with the feature and had the potential to create a better job hunting experience for job seekers. However, the results also revealed an increase in certain types of dissatisfaction associated with the product change. We estimated the potential revenue loss attributed to this dissatisfaction. Moreover, the analysis uncovered unexpected behavioral responses to the product change. We provided potential interpretations for these observations and offered recommendations accordingly. Armed with these findings, interpretations, and recommendations, the client was able to make informed decisions and successfully implemented the product changes.
Working alongside our clients, we unlock the true potential of their products and services, harnessing the power of data-driven decision-making. We gain a deep understanding of their product usage, analyze experimental results, and address pain points to provide valuable insights and actionable recommendations. With in-depth findings, insightful interpretations, and actionable recommendations, we empower them to make informed decisions that drive success.
KUNGFU.AI worked with one of the world’s largest job listing websites. Their comprehensive platform is designed to streamline and optimize the hiring process for both job seekers and employers. With a wide range of features and tools, the online platform offers a convenient and efficient solution for finding and hiring top talent. By using their platform, employers can post job listings and reach a vast pool of potential candidates through their extensive job seeker database. In addition, job seekers can search for job opportunities, apply for jobs, and manage their applications using the platform.
The client approached KUNGFU.AI with unique challenges on the employer side of their platform.
For products they wanted to enhance but weren't sure where the change opportunities lay, they collaborated with KUNGFU.AI to conduct in-depth research analysis. The aim was to understand user interactions and uncover valuable insights that could guide product changes and drive revenue growth.
For the products where they have already decided on modifications, the client performs experimentation (i.e., A/B testing) on the platform to gather real-world usage data and assess the potential impact of proposed changes. To ensure the reliability of these experiments and extract meaningful insights from the resulting data, they collaborated with KUNGFU.AI to conduct comprehensive pre- and post- A/B testing analysis. This analysis helps determine the optimal duration of experiments, ascertain the required data volume for statistical confidence, and extract valuable information to inform product decisions, guide the direction of product changes, and make potential launch decisions.
The client wanted to explore potential changes that could be made to a specific feature on their platform, which employers use to manage job applications. Our investigation encompassed various aspects of feature utilization to gain a comprehensive understanding of how and why employers were using it. We analyzed feature utilization based on employer types, observed changes in usage rates over time as employers became more familiar with the feature, examined utilization seasonality, and explored interactions between this feature and other features of the same product. Additionally, we implemented measures to control for potential confounding factors during our analyses. By thoroughly understanding the user journey, KUNGFU.AI and the client identified several key areas where product changes could enhance the user experience and drive revenue growth.
In another project, the client had aimed to address a known pain point of a feature. They made changes and tested the changes through an experiment. Unfortunately, the experiment did not bring about the desired changes in user behavior or solve the problem. The client collaborated with KUNGFU.AI to determine why the experiment failed to produce meaningful improvements in user experience and behavior. Additionally, KUNGFU.AI examined two crucial and actionable aspects of the product related to the pain point. The results revealed that while both factors were statistically significant in relation to the pain point, one factor had a stronger association with the pain point than the other. Based on these findings, we advised the client to prioritize product changes targeting this particular factor.
In an A/B testing project, the client implemented a product change and conducted an experiment to gather real-world data on how this change would impact user behavior on their platform. The client collaborated with KUNGFU.AI to analyze the collected data and assess the implications of the product change for the next steps. The analysis revealed that the product change had a positive impact on revenue, resulting in a certain percentage increase. The findings also indicated that the product change led to an increase in employers' interactions with the feature and had the potential to create a better job hunting experience for job seekers. However, the results also revealed an increase in certain types of dissatisfaction associated with the product change. We estimated the potential revenue loss attributed to this dissatisfaction. Moreover, the analysis uncovered unexpected behavioral responses to the product change. We provided potential interpretations for these observations and offered recommendations accordingly. Armed with these findings, interpretations, and recommendations, the client was able to make informed decisions and successfully implemented the product changes.
Working alongside our clients, we unlock the true potential of their products and services, harnessing the power of data-driven decision-making. We gain a deep understanding of their product usage, analyze experimental results, and address pain points to provide valuable insights and actionable recommendations. With in-depth findings, insightful interpretations, and actionable recommendations, we empower them to make informed decisions that drive success.
