Distinction offers an increasingly broad range of AI solutions tailored to various business needs.
Our solutions are designed to cater to multiple industries, offering custom applications in areas such as finance, healthcare, education, and more.
Each solution is tailored to meet the unique challenges and opportunities of your business, ensuring that you benefit from the most relevant and advanced AI technologies.
The most common mistakes we see in MVP development include:
It's essential to focus on core functionalities that reflect the product's value proposition.
Misinterpreting what the market needs, focusing too much on perfection, and launching too late can also hinder the success of an MVP.
Avoid making big assumptions without proof (ideally backed up by data) and ensure to gather and act on user feedback to iterate and improve the product continuously.
The key components of an MVP include just enough features to satisfy (ideally delight) early customers and provide feedback for future product development.
The essential features are those that solve the core problem for your target audience, which obviously vary from product to product.
The MVP should include a basic user interface, essential functionalities to test the primary hypothesis, and enough value to make the user interested in the product. 'Enough value' is a subjective measure, and will also vary from product to product.
It should also be able to collect user feedback effectively for future improvements. The focus should be on simplicity and the minimum set of features to address the primary need of your target market.
An MVP differs significantly from a prototype and a full-fledged product.
A prototype is a preliminary model to explore ideas and design concepts, not necessarily intended for release to the public. It's more about testing a concept than a market-ready product.
In contrast, an MVP is a simplified version of the product, developed with enough features to attract early adopters and validate a product idea early in the product development cycle.
A full-fledged product is a completely developed product with all intended features and functionalities, ready for the mass market.
We elaborate on the differences between and MVP and a prototype in our journal.
A style guide provides detailed guidelines on the visual aspects of branding (like color, typography, and logo usage).
A pattern library is a collection of design elements (like buttons, forms, and navigation bars).
But a design system integrates these aspects with broader design principles and practices. It encompasses style guides and pattern libraries but also includes coding standards, best practices, and a philosophical approach to design, ensuring a cohesive and consistent user experience across all platforms.
We're agnostic. We use a range of modern technologies tailored to the project's needs, including:
This enables us to choose the right technology stack that aligns with the project's goals and the long-term vision.
You can read more about our technology partners here.
Methodologies employed focus on intuitiveness, ease of use, and aesthetic appeal, ensuring the UI complements the UX while meeting the company's strategic goals.
Prototyping is crucial for visualising the final product and gathering early feedback.
The prototyping service transforms concepts into tangible (often clickable) visuals, bridging the gap between imagination and reality.
This iterative process of prototyping, testing, and refining helps in identifying design issues early, saving time and resources in the long run.
Creating a Minimum Viable Product (MVP) involves identifying and implementing the core functionalities that showcase the product's value, then launching to get user feedback to evolve the product.
The evolution from MVP to a full-fledged digital product is a structured process that entails iterative design, user testing, and feedback incorporation.
This iterative process ensures that the product continually improves and aligns with market demands, eventually culminating in a well-rounded digital product
The essence of user-centricity lies in understanding and addressing user needs and preferences.
We employ a holistic approach to product design that goes beyond aesthetics, focusing on creating experiences that resonate with users. Through in-depth market analysis, user interviews, and feedback loops, user feedback is continuously incorporated into the design process, making the product evolve in alignment with user expectations.
The process is tailored by selecting the right research methods (qualitative vs. quantitative, interviews vs. workshops, online vs. in-person, etc.) whilst remaining true to our approach of empathising, defining, creating, and testing & reporting. You may already have completed some of the research, for example, and we would not need to do it.
The outputs are also tailored to meet the needs of the engagement.
This flexibility ensures that the process uncovers opportunities and identifies risks specific to your project.
The key deliverable is a report, which provides a clearer understanding of user needs. Depending on the project, it is sometimes supplemented by wireframes, UX designs, clickable prototypes, technology recommendations and so on.
The product discovery process lasts approximately 5-8 weeks, but this can vary depending on stakeholder availability and complexity of research.
Having a better understanding of users leads to cost savings by ensuring that the right features/functionality in your product are built right the first time.
It clarifies what users want and how they'll use the product, leading to a better user experience and a more efficient development process.
The product discovery process enhances product-market fit by filtering out bad ideas early on - saving wasted time, money, and effort. It helps focus all efforts on building the right product, for the right audience.
It employs a team of experts to validate your idea against market demand, ensuring a better chance of success.
To validate market demand, the process engages in stakeholder and user interviews, competitor and market analysis. This rigorous validation helps to avoid mis-reading market demand, a primary reason for startup failure.