Case Study on Product Analytics
In the evolving landscape of recruitment technology, AI-driven asynchronous interview platforms are becoming a game-changer.
DeepDive Into Customer Journey!
In the evolving landscape of recruitment technology, AI-driven asynchronous interview platforms are becoming a game-changer. Unlike traditional interviews, asynchronous platforms such as InterviewAI, Taptic, JobTwine, and others, allow candidates to participate in interviews at their convenience, akin to on-demand classes. Typically, organisations pose five to seven questions, to which candidates record and submit their responses. This format is particularly effective for initial screening and mock interviews.
The self-serve nature of these platforms is a significant milestone in a startup's journey, substantially reducing operational costs. Building a robust self-serve platform enhances user experience and automates client interactions, which is critical in scaling operations efficiently.
As these platforms transitioned from nascent Minimum Viable Products (MVPs) to growth-stage enterprises, various strategies such as collaborations, partnerships, and diverse marketing approaches were essential. Some opted for targeted marketing, while others leveraged broader strategies, including ad-based outreach. Platforms like AppSumo have also been pivotal for running B2B promotions in the tech space.
Unsupervised clustering techniques are used to understand customer segmentation
Upon implementing several months of promotional efforts, a smart interview platform approached DeepDive Labs to analyse their platform’s expanded customer base and usage patterns. To better understand this growth, traditional customer segmentation often leads to employing unsupervised clustering techniques. However, deciding on the features for clustering necessitates deep exploratory data analysis, driven by extreme curiosity.
Our initial queries included:
What are the most common questions asked in a Level 1 interview?
Which job roles do customers primarily use the platform for?
From which industries do the platform's customers originate?
Why would someone ask a question of 1000 words?
This investigative approach unearthed fascinating insights. For instance, the analysis revealed a right-skewed distribution in the typical length of interview questions. Interestingly, some queries on the platform extended to over 1,000 words.
Further investigation showed that certain entertainment-based companies, such as radio stations and game show organisers, used the platform uniquely. They tasked candidates with reading scripts for movies or hosting game shows to assess qualities like voice friendliness, speaking ability, and body language, which the platform could score.
1000 word questions were given by radio stations and game show organisers to assess qualities like voice friendliness, speaking ability, etc.
These findings highlight the importance of understanding customer segments and tailoring features to specific industry needs as the platform evolves. Knowing who uses the platform and how they use it is vital for continuous improvement and growth. This project not only showcased the diverse applications of asynchronous interview platforms but also underscored the value of curiosity and an open approach in product analytics. Sometimes, what seems like an outlier may lead to discovering a new market or application, driving further innovation.
