TALNT is an executive search start up which tracks executive level job moves, providing business insights, information and analytic data to its users. After reaching MVP the next goal was to increase user growth and user retention. So we decided to enhance the products user experience by introducing TALNT Alerts improving the products personalisation and solving our users pain-points. This case study examines the process and outcomes of integrating the alerts feature, highlighting its impact on user engagement and satisfaction.
UX research, analysis, wire-framing, prototyping, UX/UI design
1 Product Designer (Me), 1 Product Manager, 1 Technical Lead, 2+ engineers.
Apr 2024 - Jun 2024
Figma, Confluence, Pendo, Microsoft Clarity, Google Meets
Users have been notifying us about being overwhelmed by the sheer volume of data from TALNT alerts, lacking the ability to customise their feeds. This resulted in irrelevant notifications and missed important updates. Our goal is to offer more personalised alerts to streamline information.
I want to examine the top pain paints in the process of data gathering on TALNT, so that I can provide a feature that makes data gathering more manageable and enhances the product experience.
After discussions with the product manager we decided that a successful alerts feature would have the following KPI's
1. Increase the amount of daily active users
2. Increase in the time spent on TALNT
3. Increase user retention
4. Increase user satisfaction
For this project I leveraged the data from the research to create a new feature that could be seamlessly integrated into the existing product, allowing the users to personalise the product to their needs minimising their workload and providing them with relevant information.
Was to introduce a feature allowing users to customise their move alerts. This personalisation ensures users receive only the most relevant updates, tailored to their specific interests and preferences.
I began my research with some competitor analysis the results revealed that our competitors offer simple and effective filter options for product personalisation. I analysed several competitors and I identified the common themes in each competitor feature was the ease of use and few amount of clicks when creating an alert.
I Initially had conversations with users, product managers and other stakeholders which led to discussions about introducing this feature, but I wanted to have more discussions and formal interviews to understand how I could further cater the product for the users needs.
"What motivated you to begin using the platform?"
"What is the process you take when attempting to achieve your goals?"
"What is the most difficult aspect of trying to achieve your goals and why?"
"What can we do to aid in your day to day work flow?"
Through interviews with users, product managers, and stakeholders, we identified key motivations and expectations. Users indicated a higher likelihood of using TALNT if custom alerts were available, highlighting the importance of this feature.
TALNT serves a diverse user base, including business owners, researchers, analysts, and recruiters, however this user persona focused specifically on consultants. By identifying and addressing their unique needs, I prioritised key tasks, pain points and goals when mapping out this persona.
Our product experience review of TALNT identified high drop-off rates and low usability scores. This highlighted the need to enhance onboarding, accessibility, and overall user experience. We set goals to create a flexible, simple, and coherent alerts feature, improving usability and consistency across the platform.
TALNT has diverse user base to understand their specific needs, focusing on business owners, consultants, researchers, analysts, and recruiters. This analysis helped us identify critical jobs-to-be-done, informing the development of personalised alerts. These custom alerts ensure timely, relevant updates tailored to each user's requirements, enhancing their experience and workflow efficiency with TALNT.
Bucketing user jobs into the stages of the user journey. User jobs from the Jobs-To-Done exercises helped me see patterns and map out the user journey into five broad buckets. For the MVP.
Based on the research and our product goals, the team discussed what inputs we would need and the user journey then I sketched some design concepts with ideas of how the alerts feature would look and what inputs it would require.
After I presented the sketches and they were reviewed by the team I created Lo-fi Wireframes of the alerts feature illustrating the journey once the create alert button has been clicked.
The lo-fi wireframes allowed me to run early tests which helped me discover priority revisions that needed to be implemented for the high fidelity prototype. I presented the feature to the team and created revisions based on the feedback I received from management.
Name the Alert in the same pop up to reduce steps in the user journey and developer workload.
Removed search as the tech lead felt it wasn’t necessary as users could use suggestions to build alert (I was against this decision).
Alert suggestions included based on data in job move
Included preselected alerts based on the data in job move.
Based on user feedback and standard design principles I convinced the tech lead to add a search to the Alerts pop up, I felt this was beneficial as users could customise the alert based on their specific requirements and the component could be reusable.
Another change was increasing the width of the container so more alerts could appear in the results field and including remove tool tips when hovering over an alert.
The final alerts feature incorporated user and stakeholder feedback, balancing design goals and practical constraints. The added search functionality and improved alert management tools significantly enhancee the user experience.
.gif)
The feature was introduced to reduce user pain points when using the TALNT product providing users with tailored information, which would improve their overall user experience with service. I compromised with the product manager and technical lead on decisions such as labelling on the name and the hierarchy of inputs on the alert. Ideally further testing with users will determine the route we should take to optimise the product.
The results were mixed, we achieved a few of our KPI's, but not all of them. Through clarity I tracked that one month after the release of the alerts feature daily active users increased by 36.75% on the moves page, however there was a reduction in pages per session and scroll depth. User feedback has generally been positive, from analysing the product heat map the alerts is the second most used feature on the moves page after the search which is a positive sign. The next step is gathering more feedback from users and revisiting our goals to why understand the change in metrics and why we didn't achieve all of our KPI's.
