Alright, let's dive deeper into the process…

Over a period of 12-weeks - we partnered with the product team to dive into internal data, aligning our research focus and strategy. We conducted surveys and moderated usability tests, gathered quantitative data to understand the user pain points and needs. We synthesise large sets of those data to uncover key themes, patterns, and actionable opportunities to drive meaningful improvements.

Our first step - was to collect data & understand things internally

We collaborated with the product team to gather internal data, to helped us build a more solid understanding of the problem space and ensured our research goals aligned with the overarching business objectives.

Once we gathered all the data and developed an initial understanding, our goal was to analyse it to uncover behavioural patterns across the funnel based on the data we had. At first, we decided to dive deeper to understand things on an overall funnel level…

Overall funnel analysis

At an overall level, we observed that approximately 50% of the total user base tends to drop off by the end of the funnel on a monthly basis

Interestingly, both user segments — "new" and "existing" exhibit a similar drop-off rate of approximately 50% respectively

This indicates that -

• there's friction within the funnel

• and the challenges would be unique to each segments

Diving deeper into the funnel

The goal was dive deeper to into the funnel by analysing the data to identify patterns or behaviours that could provide a more comprehensive understanding of the users.

Observations

Research Planning

We created an initial research plan to align stakeholders on the direction and priorities. In collaboration with the product team, we decided to conduct two separate studies focusing on the distinct pain points and needs of 'new' and 'existing' users. This approach would have allowed us to generate actionable insights tailored to each segment's challenges, driving improvements to the overall user experience

However…

Things didn’t unfold as we initially envisioned - we underestimated the technical constraints and feasibility challenges of running in-app surveys. The dev team informed us that an implementation of such a survey within the app would require significant developments efforts and and that they were already committed to other high-priority tasks.

This lead us back to the drawing board and after careful consideration & to ensure we don't deviate from our timelines - we decided to focus the research exclusively for 'new' users.

Designing the research study

Looking back at the data, we observed that nearly 49% of new users drop off by the end of the funnel, declining the user base from 16.24K to 8.17K. The majority of this drop-off (44.23%) occurs at the initial stages, particularly at the info screen step. Though the data indicates that there's high intent amongst new users once they pass the info screen step - yet a notable 9.75% of users still drop off in the later stages of the funnel.

This is led us to take a holistic approach while designing the research study by re-focusing our objective 2 key areas -

• identifying the underlying causes of the substantial drop-off of 44.23% at the info screen step

• understanding the reasons behind the 9.75% drop-off in the later stages of the funnel

…diving deeper into the research methodology

The research approach was a combination of user interviews and usability testing to ensure a comprehensive understanding of the user behaviour and it was structured as follows -

• Introduction: We ensured users felt comfortable by providing a clear overview of the session upfront, setting expectations to avoid overwhelming them. This approach helped create a relaxed environment conducive to honest and insightful feedback

  
  

• Interview Questions: the questions were divided into 3 sections ranging from questions related to info screen, about the survey flow and users impressions on the info screen and the website.

  
  

• Task Based Scenario: To delve deeper into user sentiments during the booking process, we observed their interactions and listened to their feedback. This allowed us to uncover emotional responses, identify potential pain points, and understand how intuitive and seamless the process felt to users

  

Who did we talk to…

We conducted interviews with 9 participants from Germany aged between 28 and 38, representing diverse professional and personal backgrounds. While none of the participants had used TeleClinic before, some had prior experience with similar Telehealth services - providing valuable insights into their expectations and preferences.

Collecting the data

By the end of two weeks we had enough qualitative data from our interviews and testing to identify key trends and patterns in the user behaviour. The data provided a foundation for further analysing pain points and validating assumptions.

Sorting and organising the data

Once we gathered the raw data from our interviews - we organised and structured the transcripts to visually represent what users share/said at each point in the journey. This structure approach allowed us to analyse each section in detail providing a deeper understanding of user perspectives and pain points specific to each stage.

You can view the Figjam file here 👉🏻 Link

Synthesising the data

Once we had the data structured and organised - our goal was to gather all individual insights related to the info screen and synthesise our findings. The process involved significant back and forth as we analysed the data. During our initial deep dive, we identified three overarching themes:

• Clarity

• Design

• Process

Once we had an understanding of the overarching themes we started to map the user quotes to each of these overarching themes. What we noticed that some themes happen to fall under more than 1 theme.

You can view the Figjam file here 👉🏻Link

Diving deeper into the insights

We aimed to establish sub-themes to break down the insights into smaller, digestible pieces, making them easier to interpret and help us pinpoint key user pain points and friction within the funnel

….what users had to say

Based on these insights - we recognised that each of these insights carries its own consequences, impacting both the user experience and business outcomes.

Understanding the consequences

At the user level - confusion and frustration led to a negative experience, with users perceiving the process as overly complex. This eroded trust and confidence, further compounding the issues.

From a business perspective - these challenges translated into lower conversion rates, decreased user retention, and increased acquisition costs. Ultimately, these factors resulted in missed revenue opportunities

Strategic directions - improvements and next steps

Once had a good understanding of the pain points and their impact on the users and business - as a team we started exploring design ideas to address these challenges

Next steps….

The next steps involve experimenting with the design recommendations through small user groups to gather real-time feedback. The focus should be on monitoring the data closely to assess the effectiveness of the changes. Additionally, a future research study will focus on understanding the challenges and pain points of existing users, aiming to fully address the 32% drop-off rate and further optimise the user experience.

📝 Note for readers

Please note that this is an ongoing project. For any further updates, I recommend reaching out directly to the team at TeleClinic, as my involvement was limited to the research and strategy phase