Lingua Attack UX design & rebranding case study

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Lingua Attack design case study

Lingua Attack (web platform and mobile applications) innovate in foreign language learning with entertaining and effective pedagogy. The exercises combine video and gaming in an immersive and engaging experience designed for short, daily sessions.

More than one million learners have already embraced Lingua Attack with hundreds of schools, universities, training organizations and governmental organizations using the service in France and around the world.

Problem definition:

Working in EdTech, the company had a rigid, formal, approach on the old website. The users who visited the website in the order to discover the BtoB product, needed to go trough a long scroll to learn about the product. The user data showed that most of the critical data was not even visited as intended. Aesthetically the page looked somewhat outdated.

Concept validation:

With a more relaxed approach, we wanted to modernize the identity of the brand. We decided to reduce the heavy documentation about the product, and show more of the real product with animations, screens and videos to make it easier and quicker to discover the product. We quit the rigid look, for the benefit of a branding heavy approach. After all, the company uses entertainment and gaming technologies as an important aspect of its pedagogy.

The process

The right process is not a single process, but a combination of techniques, mindset, and culture. It can vary in diff teams, context, companies etc.

We focus on three foundations: Continuous discovery with design thinking, continuous delivery with agile development, and principles of Lean startup.

Continuous discovery:

In our design process, we try to focus on the user's problem rather than the solution. Framing the problem is crucial with a definition phase before going into an ideation phase to generate possible solutions.

Root cause of all problems is that the commitments in the product cycle are made too early; before even we know if the solution we deliver will solve the customers real problems.

Our goal, in the product discovery, is to come up with evidence that the feature we want to build, will solve the user's problem. Thus we need to learn fast yet release with confidence. (Source: Marty Cagan, Inspired)

Continuous delivery:

Continuous delivery is the ability to get product improvements, new features, bug fixing, maintenance, into production "safely and quickly in a sustainable way". Continuous delivery makes it possible to get user feedback on a working product, lower the risks by assessing identified problems quickly at a reduced cost.

Lean Startup:

Lean Startup uses a feedback loop called “build-measure- learn” to minimize the risk and gets teams building quickly and learning quickly. Teams build Minimum Viable Products and ship quickly to begin the learning as early as possible.

"The real benefit comes when you bring all three mindsets together. Too often, the question is “lean or agile?”. The answer is “and”, not “or”: It’s Design Thinking, Lean, and Agile."

Design Thinking is how you explore and solve problems; Lean is your framework for testing your beliefs and learning your way to the right outcomes; Agile is how you adapt to changing conditions.

Below are some best practices to implement when combining all three methodologies

1. Working in short cycles

2. Hold regular retrospectives

3. Put the user at the centre of everything

4. Connect the teams with shared knowledge

5. Balance product discovery with delivery work by only testing high-risk hypotheses— The reality is, teams can’t test every task in their backlog.

6. Test with small numbers of participants, but regularly. Broadcast your findings broadly immediately after the test. Show the value of the exercise

7. Review your motivational structure.

(Source: Marty Cagan, Empowered)

Data driven decision making process

Quantitative data offer an indirect assessment of the usability of a design. They can be based on users’ performance on a given task. While quantitative data can tell us that our design may not be usable relative to a reference point, they do not point out what problems users encountered. On quantitative research we ask question like "how many ? "how much" ? We use this type of data to track & evaluate usability over time or compute ROI. (Source: nngroup)

We base our decision making process on collected data about user activity as much as possible. For user privacy reasons, we use Matamo to track user activity. The user data is collected without the use of third-party cookies.

Matomo, is a free web analytics software platform. It provides detailed reports on your website and its visitors, including the search engines and keywords they used, the language they speak, which pages they like, the files they download and so much more.

Matomo offers real time web analytics, reports filtered by any date range, but also provides specific tools to help you better understand your traffic in real time, and view your data at the visit level.

Quantitative vs qualitative studies

While both type of studies are indispensable and complementary; they will focus on Different questions and metrics to gather data.

Qualitative studies (field studies, usability testing, interview..) will generate data based on questions like why or how, whereas quantitative studies (survays, A/B testing etc.) will answer questions like How much or how many. This type of analytical data will help us detect problems, potential pain points and help us prioritize projects. And qualitative data generated with direct observation, will help us understand how to fix these problem.

We gather quantitative data with analytics and survays, while we run qualitative research by doing user interviews, usability testing and field studies.

Lean experimentation

Cross-functional collaboration is very important during the discovery phase. The technical team, takes part in the discovery phase to help review the requirements and validate proposed solutions.

When we experiment and ideate about the solutions, we use low fidelity wireframes and basic prototypes. More we know about the product, more details we add to the designs.

Following the solution discovery phase, to validate the concept, we will share with all involving parties, the high fidelity design to support the technical requirements. (At this point we already have the business validation and the technical validation of the concept).

Once the developers are delivered the high fidelity designs and interactive prototypes, we go trough iterative agile cycles to develop the feature. Uncertainty decreases over time and the feature gets validated to gain commercial availability.