Using data to drive product strategy and increase activation
Company
Kraken
Role
Senior Product Designer
Timeline
Q4 2024 - Ongoing
Project summary
By combining qualitative and quantitative data, I pitched and designed a new feature– resend activation code– to help increase account confirmation rates within the onboarding funnel.
Problem
Users were failing account creation
Through user interviews, I noticed that users were struggling to activate their accounts when signing up for Kraken. This was caused by a few reasons:
This email would sometimes be sent to their spam folder.
The “activate account” button in the email would fail when users were switching between devices.
The code itself would be invalid.
Users were experiencing dead ends when trying to mitigate invalid code errors
There are multiple paths that an user can encounter when trying to activate their accounts. Some of these lead to dead ends in the flow where users are prompted to input an activation code or sign into their account with no success. The only option left is to contact our support team, which is not a good experience and costs time and money for the business.
Users testimonials
I worked with the support team to pull queries from Zendesk, regarding activation code issues. This helped bring color to the specific problems users were facing when trying to activate their accounts. I discovered 64% of tickets specified “expired code”. Users were reaching out to the support team to receive a new code to confirm their accounts.
Hypothesis
If we allow users to resend an activation code to their emails, then we will increase account confirmation rates.
Validating my hypothesis
Diving into quantitative data
While I had qualitative data pointing to this issue, I needed to dive deeper into the problem and better understand its size and impact. I dove into Tableau and Mixpanel to gather both back-end and front-end metrics respectively to get a clearer picture on the opportunity.
30% Email confirmation drop-off
I looked at Mixpanel to get more granular data since it captures front-events. When doing so, I discovered that there was more than an 8% opportunity size, as 30% of users were actually dropping off in the flow from submitting the initial Sign Up form and completing the Email Activation Code screen.
Significant drop-off rates across all platforms
When I filtered by platform type, I discovered the highest degree of drop-offs are within the web experience. However, all platforms have a significant amount potential to increase account confirmation rates. This narrowed in my work to focus on web first then mobile.
8% Account activation drop-off
When looking at back-end events in Tableau, I discovered that there is an 8% drop-off from account sign to email confirmation. This is an opportunity for improvement, indicating a some potential to further enhance user engagement and overall conversion. As this was a crucial first step in the onboarding flow, I felt this part of the funnel was low hanging fruit and was worth investigating in for an incremental win.
15% Email confirmation failure rate
In Mixpanel, I filtered specifically for email confirmation failures within the flow. I discovered that 15% of users who submit the initial Sign Up form experience an email code failure. Additionally, the portion of these users who end up successfully activating is extremely low, impacting overall activation rates.
Synthesizing insights
Key takeaway
By assessing both qualitative and quantitative data, I was able to better understand the bigger picture of this issue. I discovered that the opportunity size to make an impact on this part of the funnel was validated by drop-off rates and that what customers were experiencing in user interviews pointed to a wider trend.
This data helped me define my goal for this project, which was to increase account confirmation rate across all platforms by giving users a better way to confirm their accounts.
Gathering context
Technical feasibility
To better understand the scope of the problem, I had a series of discussions with both front-end and back-end engineers to grasp the nuances of the activation code implementation. This collaborative approach allowed me to gather critical context regarding how the code would function within the existing architecture. By engaging with the technical team early, I was able to assess the technical feasibility of different solutions, identifying potential bottlenecks and ensuring alignment between the product's goals and the system's limitations. These discussions revealed key insights into how the activation code would interact with identity verification systems, informing a more cohesive and efficient design approach. This process not only helped define the project's scope but also allowed for more comprehensive design explorations.
The Design
I presented the design to the engineering team to get their idea on the technical feasibility of the feature. I designed what the experience would look like within the onboarding experience, mapping out the interactions and flows.
To build or not to build
Outcome
I’m still working on this project. Currently, I’m exploring various design solutions and presenting the project to stakeholders to build consensus and buy-in for the 2025 roadmap. Come back later to find out the outcome of this project.