Data Driven Development of whitelabel and native apps
This case study explores a digital transformation project aimed at enhancing native and whitelabel apps, focusing on the customer journey.
The goal was to migrate users while implementing key features within an optimal "time to market."
Success was measured by achieving a 4.9-star rating and a 40% conversion rate among web users in the first 12 months.
Learn more about how Data-Driven Design works with me and a data analyst at COFINPRO on Spotify.
My Role
Designlead for two APP-developmentteams, mentor for dev and ux/ui employees, leading workshop, 1st contact person for innovation and user testing
Acknowledging the collaborative effort of the team members is essential. The success of this endeavor wouldn't have been possible without the dedication and expertise of each team member involved, from project managers to designers and developers.
1. Creating a teamvision via businessgoals
The initial challenge lay in the complexity of developing whitelabel apps that meet both user expectations and business objectives. This involved navigating through issues such as aligning features with diverse client needs while ensuring a seamless user experience across various branding contexts.
Insight: Sustainable investment is a booming and attractive thing in Germany. People compare and share their ethical actions with friends and talk about the "good things" they do.
Outcome: As a user, I want to see how much good I have already done.
Driven by the agile transformation, we empowered the whole team with me as a lead experience designer, especially amidst changes in product ownership, would facilitate the development of a backlog crucial for project success.
Despite clear project goals, there were constraints, including the need to balance personalized user needs with industry readiness, particularly within the financial sector. This necessitated compromise solutions to maintain alignment with the overarching vision.
2. Same Knowledge, milestones and language in three companies and lots of hypothesis
Our approach focused on understanding user needs through research and testing, validating concepts with analytics in iterative releases, and applying design thinking for user-centric solutions.
We created a client-specific module library to align teams on key tasks, improving error correction by 30% in 4 months. For documentation, we recommended using charts and visuals for quicker onboarding, easier updates, and faster edits.
3. How to measure success with the right metrics?
What is the status quo of our project and product? How efficient was the last feature implementation. Did we hit our goal?
The aim is to ensure that product & design decisions are made on the basis of analyzing data and are not influenced by opinions, lack of time or political decisions.
Many product owners and teams fall into the trap of always trying to optimize the data, forgetting that this can lead to a poorer user experience and damage the brand image in the long run. The balance between instinct and empirical findings helps to derive the right measures. When data doesn't provide a clear answer or you need to put many different pieces together into a harmonious whole, teams should always rely on their expertise, or come up with new hypotheses and synthesize them. Below is an example of a page from a UX KPI board:
SNEAK INTO MY WORKSHOP FOR DATA-DRIVEN PRODUCT DEVELOPMENT
Most teams have the difficulty that setting up an initial analytics board is cost-intensive in relation to the first outcome. It is therefore important to plan the first step in advance. Not all the data you can generate is helpful, and a board that doesn't help anyone make deductions is not helpful either. Therefore, I follow the buttom-up approach here. Here are a few tips from my workshop to derive initial "requirements" for analytics data in a meaningful way:
Core-Questions:
Question1: Are we before going live or after?
Question2: Which aspects of the features or areas of the application have business relevance?
Question3: Which mapping structures make up a KPI that should be answered for the team or stakeholders?
User testing played a pivotal role in validating design hypotheses and ensuring the usability and effectiveness of implemented features. Feedback gathered from real users helped refine the app experience iteratively.
4. Motivate the team to participate and create continious product visions
To encourage proactive idea contribution and avoid burdening one person with milestone planning, I designed a format for sharing ideas, innovations, user feedback, and opinions on existing or missing features, alongside regular team reviews.