Users (talent seekers) were taking too long to engage with their job openings after posting them, leading to a high dropout rate in the platform.
We identified the root cause was the complexity and unclear description of some features in our platform, which were difficult to understand for new users.
To address this, we developed a self-guided tour that briefly explained the most important features in the platform. This initiative resulted in a 7% increase in user retention, a 14% improvement in positive user feedback, and a 37% completion rate for the tour.
Torre is a two-sided platform that connects job seekers with opportunities and helps talent seekers find ideal candidates by analyzing and matching skills and preferences. For talent seekers, the following sections of the platform are particularly relevant:
Job post: View where talent seekers provide all the necessary details about the opportunity, including responsibilities, compensation, location, required skills, contract type, and more.
Pipeline of candidates: A board-style view of the recruitment process for a specific job opportunity. It allows talent seekers to review and organize candidate cards, from initial matches to potential hires.
Candidate's profile: A concise summary of candidate information, including skills, interests, professional experience, compensation preferences, reputation, and compatibility with the job opportunity.
Here is a quick 30 second tour through the three views. The job post, the pipeline of candidates and a candidate's profile. Please ignore the any weird candidate name, since this is a test job opening 😬
Together with the PM and data analyst, we identified two worrying metrics related to talent seeker engagement:
Activation time was too long — many talent seekers weren't engaging* with their job opening after posting it.
Drop-off rate was too high — many talent seekers weren’t returning after posting their first job.
This meant we were losing users early and struggling to retain them long enough to monetize, in other words a lot of churn. Our goal now was to understand why was this happening and propose a solution to solve it.
*Engagement in a job opening from a talent seeker occurs when they match or rule out a candidate.
Step 1: Research
The UXR team interviewed several talent seekers, both active users and recently acquired users, to better understand the challenges they faced when using Torre. Through these interviews, the following issues were identified:
Only 30% of users were able to hire someone through Torre’s platform.
Users felt frustrated by being asked for too much information, particularly when posting a job.
Users felt that Torre required too much time investment—time they didn’t have if they wanted to meet their hiring deadlines.
Users reported confusion around several platform concepts and value propositions, including salary range, match and rank, and automatic scheduling.
75% of first-time users disliked the platform’s dark-themed color scheme.
The team reviewed this analysis and concluded that:
The first issue could be a consequence of poor user retention, as hiring is rarely a quick process.
The last point might also be linked to user churn, though changing the entire color scheme would be a significant effort.
The second through fourth points were clearly related to the problem we identified and are the ones we should focus on.
The feeling throughout the team was that users weren't understanding how Torre's platform and features worked:
Why we asked certain information and how did we used it
How they could use Torre's features to be more efficient in their recruitment process
The most common emotions from active users.
The most common emotions from recently aquired users.
Step 2: Ideation
At the beginning of thinking about potential solutions, the only ask I had from the Product Manager was that the solution should be a part of the platform. To avoid relying on manual onboarding, which would require more work from the Operations team.
So with that constraint in mind, I analyzed how other complex platforms onboarded new users for them to understand how it worked, and recollected some ideas.
I aligned these ideas with the Product Manager, and presented them to the CEO. Finally, we decided to move forward with a self-guided product tour with hotspots because:
It could be implemented faster than the knowledge library which would take much more time and effort.
It allowed us more flexibility than a checklist, as steps could be easily added, edited or removed to update the tour's experience.
It also allowed us to force users to interact with it, different from a checklist or a knowledge base which could be easily ignored or not found.
It allowed us to track at which step talent seekers left the tour and analyze the engagement with it.
Step 4: Hypothesis and define metrics
Our hypothesis was that adding a self-guided tour for the platform's main flows would help users better understand and engage with the functionalities in the platform, having a positive impact on the two metrics we analyzed in the problem section:
Activation time for talent seekers (in hours) — how long it took for talent seekers to engage* with their job opening after posting.
Talent seeker retention (%) — how many users return to post a job after posting their first job in Torre
Other secondary metrics to analyze the effort's impact were:
Overall product tour completion (%) — To see how many users who started the tour completed it.
Positive experience feedback (NPS)
Step 5: Analyzing alternatives
Due to engineering constraints at the moment, the initial idea was to have a third-party provider implement the product tour. I compared several providers in terms of features and pricing to define the best option.
After comparing providers we decided to do a run test with Chamaleon, however branding constraints and a surprisingly quick PoC (proof of concept) developed by one of our engineers made us realize the mistake.
So we took a U-turn and develop the product tour in-house. This approach allowed for faster deployment and seamless integration with our design system.
This mistake delayed the release of the feature around two to three days.
POC for the job post.
POC for the candidates' pipeline and the candidate's profile.
Step 6: Design, specification, and deployment
Finally, I designed and handed-off the design and specs for all the hotspots of the product tour for the three most important flows for talent seekers:
After posting a job
Reviewing a candidate's profile
Reviewing a pipeline of candidates
Given that the tour relied on widely-used and proven UX patterns from top platforms, I argumented that a usability test was unnecessary. However, after development, together with the engineering team we conducted a thorough quality assurance process in a feature flag environment to ensure:
Smooth transitions between steps
Accurate positioning of the hotspots designed
Correct behavior when pausing, restarting or ending a product tour in one of the flows
Running a QA session with my Tech Lead and the engineering team, looking for bugs throughout the product tour experience.
See if you can find the same bugs as we did, there are six in total. 🐛
The effort was released in September 2023. Within the first month of deploying the self-guided product tour, we analyzed the metrics defined in our hypothesis with the data analytics team. The results were as follows:
The activation time for talent seekers remained too variable month-over-month to attribute changes directly to this effort.
Talent seeker retention increased by 7%, measured by whether users returns to the platform to post a second job.
The overall product tour completion rate was 37%.
The positive experience feedback from talent seekers improved by 14%.
Based on these results, we decided to retain the self-guided tour as a core feature. Moving forward, our focus will be on researching and implementing strategies to increase the tour’s completion rate.
The product tour was updated under a new effort, to remove some steps and include new ones in order to increase its completion rate and highlight new relevant aspects of the platform. The tour is currently being tested under a feature flag and you will be able to try it yourself in the following weeks.