Quester 2.0

Leading the product pivot to a social databasing tool

Changing the business model of a B2C startup with an end-to-end UX redesign project.

TL;DR

  • Leading a From-0-to-1 product design
  • Helping to envision the product’s future based on user research while aligning stakeholders’ interests
  • Co-designing and running usability studies and leading the effort of the team to gather insights that can be transformed into new product ideas
  • Integrating AI features to maximise performance
  • Coordinating the handoff process and ensuring developers implement the right designs while including feedback loops with them

Leading a From-0-to-1 product design

Helping to envision the product’s future based on user research while aligning stakeholders’ interests

Co-designing and running usability studies and leading the effort of the team to gather insights that can be transformed into new product ideas

Integrating AI features to maximise performance

Coordinating the handoff process and ensuring developers implement the right designs while including feedback loops with them

Role

Senior Product Designer

team

Head of Product: Shuowang
Product Manager: Alex
Data Analyst: Clark
Front-end Dev: Desbmita

timeline

Dec 23 – Feb 24

Skills

AI integration, User research, JTBD interviews, Usability tests, Prototyping, Creative thinking, End-to-end UX design, From 0 to 1 design.

While Quester, a Series A social media startup, was trying to find its Product-Market Fit (PMF), the product team had just launched the company’s new Design System, and we were more aligned than ever. Leveraging insights from user research, we identified a compelling new direction for our product, and we took advantage of the momentum to make the company’s biggest pivot to date. 

Understanding the users needs

We had a loyal user base, but we were encountering problems with growth and differentiating ourselves from other solutions in the same sector. We had built a powerful product, but the data indicated that we weren’t shaping it correctly.

We conducted in-depth interviews, JTBD discovery interviews, and competitor analysis to find a new vision and mission.

They don’t need a wiki, they need something else.

Thanks to JTBD interviews, interviews with users of competitor products, and in-depth user research on our own data, we began to see that there was more potential in becoming a social databasing tool for communities rather than trying to be ‘just another’ community platform.

Communities are built around the idea of sharing knowledge, but there is no single tool that allows them to properly manage their own community-curated content. Community leaders were using Notion databases, Google Docs, Wakelet, bookmarking lists, MyMind, and many other services, but all failed in community curation.

Part of the Product Team workshop documentation. The product team worked hard to understand users’ needs and pain points through in-person workshops.

Our research highlighted that:

  • Community leaders resisted transitioning to a new vertical but consistently demanded social databasing services.
  • They needed a scalable, easy-to-use, and bidirectional solution for organizing community-curated knowledge.
  • A wiki or spreadsheet platform alone did not meet their requirements as they are hard to build, and difficult to keep updated.
  • Those leaders lacked the time to manually filter community content and other users’ suggestions, and research showed that this is a bottleneck for communities to grow and evolve.
  • Members of communities want to actively collaborate and share their knowledge with the community, which increases retention due to the investment of time effect, creating a growth loop.

Pivoting strategy

From: 'communities of recommedantions'

to: 'spaces of knowledge for communities'

Assets before this project

Before this pivot, our product was based on collect recommendations within fixed channels owned by Quester. The UX practices were poor, and the flows were difficult to navigate.

Designing with our business in mind

💸 Money is king, and we had very limited time and resources. The product needed to change and evolve alongside the company’s business needs. That’s why we had to ensure our assumptions were correct and we could achieve our goals on time. The company would be pitching at important upcoming events, and delivering on time was crucial.

Can we really scope this huge change? Spoiler alert: YES!

This new vision basically means a new from-0-to-1 product within about three months. However, once aligned on the hypothesis, we were able to start working and deliver value almost instantly.

What does the company need? To validate its monetisation model.

As a Series A startup, we were still exploring avenues to profitability, making investors crucial stakeholders. Working closely with the C-suite, we identified a significant opportunity for monetisation, which was exactly what investors were asking us to prove for the next round. Community leaders can create their own community spaces to grow organically as a side service for their horizontal. We will offer a platform that allows easy curation of content suggested by their community members, all in a space that can be monetised with sponsors from day one.

Optimising our design efforts

Where is our User Value Exchange? → in our ‘Collections’

With over a year of user data, we conducted a behavioural analysis and discovered that our product delivers value through the consumption of recommendation collections. This value exchange significantly increased the likelihood of return users and retention. Users who opened collections were more likely to become retained users.

Our data analyst identified our «Aha!» moment: When users open a collection, the retention ratio grows exponentially.

DEFINE

Social databasing tool with Collections at front-and-center.

Collections as a core moment of User Value Exchange

We would allow each community to create spaces with a homepage centered on collections, while still highlighting the value of individual recommendations.

AI powered

We will incorporate AI features focused on helping the community classify and digest content to offer a seamless consumption experience without needing to leave Quester.

Escalable & easy to manage with low entry commitment

Quester will be positioned as an intuitive tool within your community’s framework, focused on addressing knowledge management challenges. We are not a social network, but rather a tool designed for communities.

Designed to monetise the content

We will provide ways to monetize the spaces, facilitated by our loyal user base within a hyper-niched spaces. Brands will find advertising opportunities appealing within these spaces.

Proof of concepts & lofi prototypes

First proof of concepts (while still finalizing the Design System project). We focused our attention on facilitating the discovery of the right collection quickly.

First iteration

Based on the initial usability study (more details below) and with the Design System already deployed.

usability testing

“The faster you are proven wrong, the less time you will spend being wrong.” - Erika Hall

I love the principles Erika Hall described in ‘Just enough research’, and as soon as we had a prototype to test, we jumped into Maze to design our first usability study and began collecting real data from our users.

Two rounds of usability testing & over 200 insights gathered from 52 users.

We had a solid email list of users willing to assist with research, so we conducted a screening survey to select Quester users based on their behaviour and profile for our usability tests.

Desinging our usability tests

Validating the UI decisions

Especially in the first round, we wanted to determine if the new Information Architecture and UI was fulfilling their purposes. We also aimed to evaluate users’ deep understanding of the flow to find the content they were looking for and how they naturally interacted to find it.

Time-to-value

We aimed to drastically reduce Time-to-Value and increase the number of valuable actions per session, as this has been proven to maximize retention and extend Lifetime Value (LTV).

Optimize for joy

Once we had validated the new solution and optimized it for performance, we also aimed to achieve a high level of user satisfaction in terms of enjoyment. In hyper-niched communities, we want users to experience joy by deepening their engagement with their hobbies, feeling that their time invested was useful and bringing joyful and purposeful feelings.

Note-taking databases

Thanks to teamwork, we were able to create 2 databases with over 200 observations and quotes to identify themes, patterns, and transform them into actionable insights.

Prioritised insights from research​​

This report doesn’t include all the insights due to an NDA.

Usability testing report

Part of the product team’s work was to align all stakeholders with the strategy we designed. Properly communicating the results of our research was key so that everyone could share the same understanding and contribute to making it a reality.

Slide of the report where we explain the changes we will implement in our next iteration, based on the evidence we presented previously using real data from our usability study.

iterating

Optimizing designs, flows & general user experience

Thanks to the outputs of our research, we have gathered many actionable insights that will help us improve our redesign. These insights will enable us to add features and elements that we may have overlooked during our first iteration or that we simply didn’t consider. This will significantly improve our statistics and user base.

Cleaning the homepage layout

Low-Fidelity vs. Second Iteration: Optimizing for performance. Cleaning the layout and removing distractions from the happy path.

Helping users to navigate in spaces and filtering content

Low-Fidelity vs. Second Iteration: Now, the community spaces will be focused on collections rather than other types of assets.

Simplifying flows: Creating a new space in 3 clicks.

Users will be able to create fully customized new spaces in just 3 clicks.

Integrating AI features to instantly organize and classify new content within a space.

Using LLM technology, we assist users when uploading new recommendations by automatically suggesting the best labels to organize the content. We also find existing labels in the system to avoid duplicates.

Integrating AI features to process and digest others' recommendations.

In a space with hundreds of recommendations, users need a way to consume only the most relevant ones for them. In addition to our filtering system, we have developed Quester Digest, which provides an AI-generated summary of linked content, documents, or videos. This digest offers users a summary of the content, estimated reading or consumption time, language level, a gallery of images, and even an insightful report of other members’ opinions about the recommendations based on our social curation tools.

Quester Digests are provided for each recommendation within a given space.

Easy content curation flow as the primary benefit for community leaders

When a member of a space suggests new recommendations, community leaders receive a notification to review them. They can change the title, labels, and the collection where it will be placed, and approve it without leaving their admin panel.

Curation flow in the admin panel, allowing community leaders to curate suggestions across every collection in one place.

results

Where this project took us?

Opening new investors’ doors

This new product enabled us to pitch at a broader range of investor venues. Now, our product can sell itself and effectively explain its value proposition. This has led to invitations to events such as a conference in Dubai hosted by The Private Office of Sheikh Abdulaziz Al Khalifa and meetings with multiple VCs in San Francisco.

MRR: From 0 to 7K

Since the first month with the new product, we will be able to monetize the spaces, generating £7,000 Monthly Recurring Revenue (MMR), which is necessary to access a second investment round.

Our metrics have flipped to the positive side.

Our users noticed the change from the day of deployment. All our metric indicators started showing significant improvements, and our users were able to complete tasks faster and more efficiently on Quester. This increased the rate of new sign-ups while retaining existing users.

User sessions after this project

Sessions tracked with PostHog

In real-life, no project is a 'solo' project

Leading the Development of a New Design System for Quester

The project you just read about is closely tied to the development of a completely brand-new Design System for the company. This new asset was invaluable in helping us make quick yet consistent design decisions. It was also crucial in enabling seamless handoff processes with our dev team. I led that project, and you can discover all the details in the following portfolio project.

To read more about it click in the following project card.

quester brand-new design system

I created the first cohesive design system for a startup, which helped it to iterate at 2x speed.

💻

or drop me a message!

You can email me to sergioriquelmesanchez@gmail.com