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Featured-Post-UX-Design (EN) UI/UX Design EN

Focus Group: How to Gather Your Customer Insights and Guide Your Strategic Decisions

Focus Group: How to Gather Your Customer Insights and Guide Your Strategic Decisions

Auteur n°15 – David

In a context where strategic decisions hinge on a deep understanding of user behaviors and expectations, the focus group stands out as a qualitative method that goes beyond mere numbers. It enables in-depth exploration of participants’ perceptions and motivations, uncovering insights often absent from analytics and A/B tests. This article unpacks the available formats, the essential steps to structure a discussion group, and the best practices to turn customer feedback into actionable guidance for your digital projects.

Why the focus group complements your quantitative methods

The focus group provides a nuanced understanding of user behaviors and emotions. It bridges the gap between raw data and product or marketing decisions.

Define objectives and method complementarity

Before organizing a session, clearly define the questions your focus group will address: understanding a use case, validating a concept, or exploring adoption barriers. This preparatory phase guides your choice of format and participant profile.

Unlike online surveys, a guided discussion lets you follow up on participants’ remarks, probe specific points, or clarify intentions. The qualitative insights gained enrich conversion metrics and usage indicators.

This complementarity makes focus groups particularly effective for contextualizing trends spotted on dashboards, adding depth and meaning to the numbers.

Delve into users’ motivations and barriers

By facilitating user-to-user exchanges, focus groups reveal implicit motivations, psychological barriers, or misconceptions about the service—elements often invisible in quantitative analyses.

A cohesive moderator encourages participants to build on each other’s comments, generating interactions that yield unexpected learnings. Moderators can then adjust the discussion flow to explore emergent themes in greater detail.

The richness of spoken testimony provides precise verbatim quotes, essential for crafting more targeted marketing messages or refining the user experience.

Use case: Swiss SME in financial services

A Swiss SME specializing in mobile payment solutions convened ten professional users for a two-hour session. Participants from various sectors (retail, hospitality, healthcare) discussed transaction flows and notification perceptions.

The session revealed a major obstacle: ambiguous confirmation labels. Thanks to direct user suggestions, the product team reworded key terms, reducing support requests related to the refund process by 25%.

This qualitative feedback complemented usage analytics and uncovered an emotional dimension (trust and clarity) unattainable through quantitative tools alone.

Focus group formats and their suitability by objective

Several group formats exist to meet specific needs. Your choice depends on size, duration, and topic sensitivity.

The classic format for in-depth discussions

A traditional focus group typically gathers 6 to 10 participants for 90 to 120 minutes. It fosters collective interaction and covers multiple aspects of the topic using a pre-established guide.

Having all stakeholders present simultaneously ensures a group dynamic where ideas spark off one another, revealing more contrasted opinions.

This format remains the go-to when you aim to obtain a comprehensive overview of perceptions and expectations around a new service or major update.

The duel format for comparing two concepts or prototypes

A duel focus group pits two prototypes or two competing concepts under the same conditions. Feedback focuses on each option’s strengths and weaknesses.

The moderator asks participants to evaluate both proposals in turn, then debate their perceived differences. This confrontation highlights discriminating factors.

This format is ideal for product managers who need to choose swiftly between two design paths.

The mini-focus group for quick, targeted exchanges

When the subject is highly specialized or the target population hard to mobilize, a mini-focus group of 3 to 5 people offers a pragmatic solution. Sessions can be as short as 60 minutes.

Fewer participants ensure everyone speaks freely but require a tightly structured moderation to cover essential topics.

This format is often used for preliminary studies or rapid iterations within an agile approach.

Remote focus group for geographically dispersed participants

With the rise of remote work, conducting focus groups via video platforms has become common. It eliminates logistical constraints and simplifies international participation.

Online moderation tools (virtual rooms, live polls, digital whiteboards) preserve the richness of discussions while offering native recording of interactions.

This format demands special attention to technical quality (connectivity, audio, video) and speaking-time management.

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How to structure your focus group for maximum impact

Preparation largely determines the value of your insights. Each step—from defining objectives to analyzing verbatim—must be rigorous and context-adapted.

Set clear, measurable objectives

Define precise goals: test a feature, assess offer comprehension, or identify cultural barriers. Objectives guide your discussion guide and question selection.

Each question should align with a strategic issue, whether optimizing user experience, refining marketing messaging, or prioritizing development tasks.

Measurable objectives also allow you to benchmark feedback against pre-set KPIs after the session.

Select and recruit relevant participants

Participants should match your target personas: market segments, role in the client organization, or solution usage level. A mix of novice and expert users enriches discussion.

Recruitment can leverage existing panels, customer databases, or partner networks. Aim for diverse perspectives while maintaining thematic coherence.

A qualification form will specify inclusion and exclusion criteria to ensure profile representativeness.

Prepare a structured yet flexible discussion guide

The guide outlines topics and proposes a logical question order, while leaving room for moderator improvisation. Each section starts with a discussion objective.

Combine open-ended, factual, and projective questions to capture concrete experiences and anticipate future uses. Alternate between individual questions and group debates.

A good guide also includes interactive exercises (cards, visual scales) to stimulate creativity and encourage spontaneous expression.

Moderation and logistics: ensure a smooth session

Successful moderation depends on establishing trust, prompting participants, and managing speaking time. Open follow-ups invite nuance without steering responses.

Logistical preparation (venue, note-taking materials, audio/video recording, refreshments) contributes to a professional, comfortable atmosphere.

A technical moderator handling back-office support resolves any issues swiftly, ensuring high-quality exchanges.

Use case: Industrial group in French-speaking Switzerland

An industrial player in Romandy ran a mini-focus group with four business leaders to validate a new dashboard. Participants tested an interactive prototype and suggested label refinements for indicators.

The process revealed a need for additional dynamic filters and a color-coding scheme to highlight critical data. These insights were directly incorporated into the functional roadmap.

This structured discussion phase saved several development iterations and improved end-user adoption.

Analyze and turn insights into strategic decisions

Systematic analysis of verbatim ensures key learnings are captured. Translating feedback into concrete actions delivers pragmatic ROI.

Transcription and coding of qualitative data

Audio or video recordings are fully transcribed for text-based analysis. Each comment is anonymized and timestamped for easy reference.

Coding involves tagging text segments with thematic labels (motivations, barriers, suggestions). This can be done manually or using semi-automated annotation tools.

Thorough classification sets the stage for identifying patterns and correlations among feedback.

Trend identification and prioritization

Once segments are coded, cross-analysis highlights recurring themes, contradictions, and major pain points. Occurrence counts aren’t the sole criterion: emotional intensity and business criticality also matter.

Insights are grouped by category (usability, content, communication, support) and prioritized based on their potential impact against initial objectives.

This synthesis yields a structured report with an issue map and operational recommendations. For example, you can prioritize backlog items.

Integration into product or marketing strategy

Focus group recommendations feed directly into the product roadmap, feature prioritization, and marketing positioning. They validate or invalidate analytics-driven hypotheses.

The project team can plan quick wins (minor tweaks) and strategic initiatives (journey overhauls, new module development) based on expected value.

This approach ensures decisions rely on a documented, nuanced understanding of needs rather than unsubstantiated impressions or internal consensus.

Turn your customer insights into a competitive advantage

The focus group is a powerful lever to enrich customer understanding and guide product or marketing evolution. By combining appropriate formats, rigorous preparation, and structured analysis, you can extract concrete, actionable learnings.

Edana positions itself as a strategic partner to support the planning, moderation, and exploitation of focus groups—whether ahead of a launch or during an optimization phase. Our experts help you translate qualitative feedback into solid, prioritized business directions.

Discuss your challenges with an Edana expert

PUBLISHED BY

David Mendes

Avatar de David Mendes

David is a Senior UX/UI Designer. He crafts user-centered journeys and interfaces for your business software, SaaS products, mobile applications, websites, and digital ecosystems. Leveraging user research and rapid prototyping expertise, he ensures a cohesive, engaging experience across every touchpoint.

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E-Commerce Development (EN) Featured-Posts-Web-Dev (EN)

Operator, Perplexity… How to Prepare Your E-commerce for AI-Driven Purchasing?

Operator, Perplexity… How to Prepare Your E-commerce for AI-Driven Purchasing?

Auteur n°2 – Jonathan

AI assistants such as OpenAI’s Operator or the embedded agents in Perplexity are quietly reshaping online purchasing journeys. These autonomous systems will soon be able to search, compare, and complete transactions on behalf of customers. For e-commerce, marketing, or innovation leaders, this shift demands a rethink of visibility, product architecture, and user experience. How can we anticipate this transition and adapt our digital ecosystems to these “non-human customers”? In this article, we explore four key challenges and offer a practical framework to help prepare your e-commerce platform for the era of AI-driven purchasing.

1. AI Becomes the Customer

AI agents initiate and complete purchases without direct human interaction. These automated actors browse catalogs, evaluate offers, and execute transactions in just a few queries.

Evolution of the Customer Role

Early chatbots merely assisted users; today’s AI agents can act on their behalf. These assistants navigate sites, compare prices, and place orders on third-party platforms via dedicated programming interfaces. They rely on advanced language models to understand the business or personal need they represent. This capability paves the way for scenarios in which companies primarily interact with “buyer robots.”

This shift profoundly changes the very notion of “traffic” and “clicks.” Request volumes may drop on the traditional interface while the AI aggregates and forwards decisions directly to your API. Traditional metrics like click-through rates or average basket value lose relevance. E-commerce managers must therefore track new KPIs, such as the number of AI sessions and the machine-to-machine conversion rate.

How AI Agents Work

An AI agent uses structured prompts to search for a product, assess its attributes, and decide on a purchase. It analyzes the semantic content of your product page, compares available options, and selects the most relevant offer. Compatible platforms expose data via JSON-LD schemas optimized for machines, summarizing price, availability, and delivery terms. The purchase then completes through a payment API or secure webhook.

This automation requires precise, accessible technical documentation. Order flows must be triggerable via an authentication token without a traditional form. Companies that adopt these APIs ensure seamless, resilient integration with AI requests. Without this level of preparation, the agent may halt or misinterpret data, causing failures and drop-offs.

Example of Integrating an AI Agent into an E-commerce Purchase Journey

An industrial supplies retailer recently opened its catalog to an internal AI agent. The company structured its product data in machine-readable JSON-LD and deployed a simplified checkout API. After a few weeks of testing, the agent narrowed searches, compared warehouse rates, and placed orders according to predefined cost-optimization rules.

Result: purchasing managers saw a 30% reduction in time spent on repetitive orders. The agent now processes a batch of 200 items in under ten minutes versus two hours previously. This automation also reduced input errors and improved delivery reliability.

2. The Commerce Experience Moves Off-Site to External Chatbots

The act of sale is no longer confined to your online store. Interactions now begin in a chatbot, a third-party app, or a conversational search engine.

Conversational Commerce

Platforms like Perplexity or mobile apps equipped with AI agents offer a journey where users never visit your site. Search, comparison, and purchase all occur within a conversational channel, whether text or voice. These environments deliver instant responses, powered by your structured data and business rules.

To appear in this new sales funnel, you must index your product content on conversational engines. A simple XML feed is no longer sufficient; you need clear, contextualized snippets. Each response should trigger a secure link to your order API or redirect to the agent’s proprietary interface.

Proactive AI Recommendations

AI agents can suggest products based on purchase history or configurable business rules. They anticipate needs and drive purchases without direct user prompts. This proactive personalization boosts engagement and accelerates the conversion cycle. At the same time, it demands fine-grained segmentation of customer data and rigorous GDPR consent management.

In this context, traditional SEO optimization takes on a “machine” dimension, where keywords must appear in named entities and agent-specific tags. Conversational ranking involves semantic enrichment and alignment with industry ontologies. SEO teams must therefore collaborate closely with data managers.

Example of an Off-Site Product Purchase Experience

An online furniture retailer tested a conversational agent integrated into a third-party group-buying platform. The company provided a public API and a dynamic filter field to tailor product use. Within two months, over 15% of orders originated from this interface, without a single visitor viewing the standard product page.

Beyond volume, the average order value generated by the agent increased by 12%, thanks to complementary product suggestions based on stored preferences. This success convinced teams to extend the setup to other conversational channels.

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3. New Technical and Strategic Challenges

AI agents demand a complete reevaluation of your product architecture and user experience. Data readability, checkout integration, and personalization become critical priorities.

Product Data Readability

Language models consume microdata and ontologies to interpret your offerings. It’s no longer enough to display price or description on a webpage; you must structure all relevant details in technical schemas. Every attribute—dimensions, materials, warranty—must be machine-readable to avoid misinterpretation.

Implementing JSON-LD or appropriate microformats ensures reliable extraction. You should also document use cases, price calculation rules, and special conditions in a continuously accessible data catalog. This step requires collaboration between product, marketing, and data engineering teams.

Integrable Checkout Process

For the agent to finalize a transaction, the purchase funnel must be exposed via a secure API. This involves not only offering one-click payments but also handling authentication, authorization, and confirmation flows. Authentication should use OAuth or JWT tokens, without human intervention, while maintaining high security standards.

A Swiss online pharmaceutical company recently adapted its payment system for AI agents. It implemented a REST API with dual cryptographic validation. The operation now completes in under four seconds and integrates seamlessly into the agent’s workflow.

Personalization and Security

Agents leverage customer data to tailor offers in real time. They cross-reference purchase history, declared preferences, and behavioral data to adjust products and quantities. This personalization increases conversion rates but demands precise access and consent management. Each API call must verify that the agent has the necessary rights to view or modify user data.

Moreover, technical reliability and machine-readable UX are essential. Agents don’t handle error pages or poorly structured forms well. They require clear responses and appropriate HTTP statuses. A flawed implementation can halt the agent or produce unrecoverable errors.

4. Edana as a Tech-Strategy Partner to Evolve Your E-commerce for the AI Era

Preparing your e-commerce for AI-driven purchasing requires a holistic approach combining data, architecture, and UX. Edana supports you in structuring, ensuring AI compatibility, and designing adaptable journeys.

Product Data Structuring

We analyze your catalog and identify key attributes to expose for AI agents. Our approach includes semantic modeling, optimized JSON-LD, and the creation of automated data pipelines. These steps ensure consistency across channels and simplified maintenance.

Working in agile sprints, we adjust the data model based on initial agent feedback. This iteration refines the relevance and accuracy of responses provided by AI assistants. The result is a scalable, controlled architecture.

Compatibility with AI Ecosystems

We assess and implement the APIs needed to expose your catalog and checkout funnel to agents. Our expertise covers OAuth implementation, JWT security, and OpenAPI documentation. We ensure performance, scalability, and regulatory compliance, including GDPR.

With our hybrid approach, we integrate proven open-source solutions to orchestrate these flows and avoid vendor lock-in. You retain control of your ecosystem and can adapt components as agents and standards evolve.

Machine-Readable UX Design

We design interfaces tailored for AI agents, defining optimal endpoints and response formats. Each entry point is crafted to deliver clear, comprehensive, structured data. We systematically test with pilot agents to validate journey robustness.

Simultaneously, we advise on the classic user experience to ensure a seamless transition between human and agent journeys. This duality has become a market differentiator in automated e-commerce.

Prepare Your E-commerce for AI-Driven Purchasing

AI agents are poised to redefine shopping journeys by automating search, comparison, and payment. To remain competitive, you must structure your data, implement an API-first checkout, and ensure a machine-readable UX. This evolution impacts SEO, technical architecture, and transaction security.

Regardless of your digital maturity, it’s essential to build a scalable, modular platform aligned with emerging AI standards. Our Edana experts guide Swiss mid-sized and large SMEs through this transition, from technical audit to operational rollout.

Discuss your challenges with an Edana expert

PUBLISHED BY

Jonathan Massa

As a senior specialist in technology consulting, strategy, and delivery, Jonathan advises companies and organizations at both strategic and operational levels within value-creation and digital transformation programs focused on innovation and growth. With deep expertise in enterprise architecture, he guides our clients on software engineering and IT development matters, enabling them to deploy solutions that are truly aligned with their objectives.

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Featured-Post-UX-Design (EN) UI/UX Design EN

Design Thinking: Definition, Methodology and Concrete Benefits in Digital Innovation

Design Thinking: Definition, Methodology and Concrete Benefits in Digital Innovation

Auteur n°15 – David

In a context where digitalization has become a strategic imperative, Design Thinking proves to be an effective method for structuring innovation and avoiding the pitfalls of overly improvised workshops. This approach places the user at the heart of the process while ensuring coherence with technical constraints and business objectives. Swiss companies, facing global competition and high quality standards, find in it a framework to align all stakeholders. Through a proven methodology, it is possible to accelerate the creation of robust, scalable digital services and products tailored to the real needs of end users.

Design Thinking, a Structured Innovation Lever Beyond Brainstorming

Design Thinking is more than just a collection of ideas; it is a methodical process based on empathy and rapid testing. It brings together user, technological, and business dimensions to ensure relevant solutions.

Immersion and Empathy

The first phase focuses on gaining a deep understanding of the user context. Interviews, field observations, and active-listening workshops are organized to uncover motivations, frustrations, and latent needs. This participatory approach involves both business and IT teams from the outset, allowing multiple perspectives to intersect and preventing misunderstandings during the design phase.

Beyond standard personas, field immersions capture real usage patterns and operational constraints. The goal is not merely to collect data but to interpret subtle cues that will guide the rest of the project. This is where the relevance of the proposed digital solution is determined.

Thanks to this structured empathy, cognitive biases are minimized, allowing focus on genuine issues. The outputs of this phase are synthesized into empathy maps and user journeys, which serve as the guiding thread for all subsequent stages.

Problem Definition and Framing

After exploration, the challenge is to reformulate the problem in a precise, shared manner. The main “pain point” to be addressed is identified and measurable objectives are set. This formalization prevents scope creep and ensures clear alignment among IT teams, product management, and business units.

A structured problem definition is achieved through convergence workshops where each stakeholder validates scope and success criteria. Hypotheses are explicitly listed to steer future iterations and anticipate risks.

This stage transforms a general observation into a concrete, operational, and measurable challenge. It lays the groundwork for ideation and reduces the risk of delivering unnecessary or poorly suited features.

Ideation and Controlled Divergence

Next comes the ideation phase, where a wide range of ideas is generated without self-censorship. Sessions are paced with various techniques—from brainwriting to mind mapping—to stimulate collective creativity. The objective is to maximize the diversity of proposals.

To avoid dispersion, time and thematic constraints are imposed. Each idea is then evaluated based on technical feasibility, user value, and business impact. This prioritization matrix serves as a compass for selecting the most promising concepts.

The chosen ideas are sketched out in storyboards or low-fidelity wireframes. This mapping enables quick visualization of the future user journey and sets the stage for prototyping.

Example: A Swiss financial institution seeking to improve SME client onboarding identified a major pain point in manual data entry. Through a series of empathy and ideation workshops, it defined a new digital journey that included automatic document capture and real-time verification. This process reduced account opening time by 70% during the pilot.

Integrating Design Thinking into the Digital Strategy Process

Design Thinking structures the product journey from ideation to production, fostering interdisciplinary collaboration. It fits within an agile, modular framework to accelerate innovation cycles.

Interdisciplinary Collaborative Work

In a digital transformation context, breaking down silos between design, IT, and business is essential. Design Thinking workshops bring these profiles together to ensure every viewpoint is considered, creating a true culture of co-creation.

Roles are clearly defined: a facilitator guides the sessions, a business expert provides process knowledge, and a product owner ensures alignment with business objectives. This setup balances creativity with rigor.

This way of working boosts team buy-in, as everyone feels invested in the project. Decisions are made with full awareness, reducing resistance to change and smoothing technical implementation.

Fast Iterations and Prototyping

A key advantage of Design Thinking is rapid prototyping. Low-fidelity mockups or proofs of concept are built with open source tools to test hypotheses. This velocity quickly reveals potential blockers.

Each iteration incorporates early user feedback. Adjustments are made in days without heavy development commitments. This minimizes resource waste and optimizes time-to-market.

The methodology is ideally complemented by CI/CD pipelines, ensuring continuous integration of validated prototypes. This approach reduces development costs and paves the way for scaling up to an industrial version.

Validation and User Testing

Before any large-scale deployment, testing sessions are held with a representative panel of users. Interactive prototypes are evaluated based on usability and ergonomics criteria.

Functional or ergonomic pain points are addressed at this stage, using both qualitative and quantitative metrics. Feedback is recorded in a prioritized backlog to guide subsequent development.

This approach guarantees the final solution meets real needs and minimizes post-launch rework, avoiding extra costs and loss of trust.

Example: A Swiss pharmaceutical lab adopted this approach to redesign its internal training portal. Prototype iterations tested with employees and quality managers refined the interface and reduced IT support queries by 50% during the national rollout.

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Concrete Benefits of Design Thinking Workshops for IT, Product, and Business Leaders

A well-structured Design Thinking workshop significantly reduces project risks and accelerates time-to-market. It also boosts stakeholder engagement and prioritizes high-ROI features.

Project Risk Reduction and Stakeholder Alignment

By involving all key actors from the start, a shared vision of scope and objectives is created. Hypotheses are validated before any development, reducing the risk of scope creep and costly rework.

This clarity strengthens governance, as decisions are documented and backed by user data. Trade-offs become quicker and more transparent for steering committees.

Over time, this discipline lowers the failure rate of digital projects and improves adaptability to changing contexts or strategies.

Accelerated Time-to-Market

Rapid prototyping and short cycles facilitate early production releases. Workshop-validated features can be industrialized in parallel thanks to a modular architecture and continuous integration pipelines.

This flexibility enables launching an MVP in weeks, gathering real feedback, and adjusting the product roadmap. Companies thus gain weeks or even months on the initial schedule.

This agility is a decisive competitive advantage in fast-evolving markets.

End-User Engagement and Adoption

Including future users in workshops fosters co-creation. They feel heard and see their needs addressed. This generates buy-in and eases adoption of digital solutions.

Training materials and documentation can be developed from initial user feedback, reducing post-launch support needs and improving the onboarding experience.

In the long run, the company gains a base of ambassador users ready to promote the solution internally and externally.

Example: A Romandy-based real estate company used Design Thinking to revamp its online client portal. Agile management and user testing increased digital account activation by 30% while cutting customer service calls for interface assistance by 40%.

Informed Technology Choices and Robust Software Architecture through Design Thinking

Design Thinking guides technology choices toward modular, open source, and hybrid solutions to avoid vendor lock-in. It also steers the definition of a scalable, secure architecture.

Modular and Scalable Architecture

Mapping user journeys and features identifies critical domains to isolate into microservices. This granularity simplifies maintenance, scalability, and independent evolution of each component.

Such architecture limits the impact of incidents and streamlines version upgrades. It relies on containers and orchestrators to ensure optimal resilience and flexibility.

By adopting this modularity from ideation onward, future needs are anticipated, building a digital foundation that can evolve without a complete overhaul.

Selection of Suitable Open Source Components

Design Thinking can also include technology evaluation during ideation. Mature open source solutions with strong communities and regular updates are favored.

This approach reduces dependency on a single vendor and offers customization freedom. Libraries are chosen based on business alignment and technical compatibility.

Processes for monitoring and automated updates are implemented to ensure long-term sustainability and security of the stack.

Hybridization and Avoiding Vendor Lock-In

To meet specific constraints, existing components can be combined with from-scratch development. This hybrid approach retains the agility of off-the-shelf solutions while ensuring precise customization.

Interfaces are standardized via open APIs, making future component replacement seamless. The ecosystem remains flexible, modular, and adaptable to strategic shifts.

Clear governance over contracts, licenses, and data exchange completes this approach to control total cost of ownership and mitigate lock-in risks.

Example: A Swiss retail group re-architected its e-commerce platform through a Design Thinking approach, decoupling the product catalog, promotions engine, and payment system. This open source–based modularity enabled 200% load growth during promotional peaks without major incidents.

Design Thinking: Make It the Accelerator of Your Digital Innovation

Design Thinking provides a robust framework to ideate, prototype, and industrialize user-centered digital solutions while integrating technological and business challenges from the start. It strengthens collaboration, accelerates innovation cycles, and reduces project risk through early validation.

This method also guides architectural and technology decisions toward modular, open source, and hybrid ecosystems, ensuring solution scalability and resilience. IT, product, and business leaders thus benefit from optimal alignment and shortened time-to-market.

CIOs, CTOs, CEOs, and product managers looking to transform ideas into high-performance digital projects will find in this approach a powerful lever to maximize ROI and anticipate future developments.

At Edana, our experts are available to support you in setting up tailored Design Thinking workshops and structuring your digital innovation process.

Discuss your challenges with an Edana expert

PUBLISHED BY

David Mendes

Avatar de David Mendes

David is a Senior UX/UI Designer. He crafts user-centered journeys and interfaces for your business software, SaaS products, mobile applications, websites, and digital ecosystems. Leveraging user research and rapid prototyping expertise, he ensures a cohesive, engaging experience across every touchpoint.

Categories
Featured-Post-UX-Design (EN) UI/UX Design EN

Product Design vs UX Design: Understanding the Roles to Build a High-Performing Digital Product

Product Design vs UX Design: Understanding the Roles to Build a High-Performing Digital Product

Auteur n°15 – David

In an ecosystem where every design decision impacts the success of a digital product, distinguishing product design from UX design is essential for structuring a project and optimizing resources. These two disciplines, often conflated, have complementary goals: one focuses on product strategy and alignment with business objectives, the other on user experience and ergonomics. By clarifying their responsibilities and establishing clear collaboration processes, companies reduce the risk of misunderstandings and accelerate time-to-market.

Clarifying Roles: From Business Needs to User Experience

Product design defines the overall vision, positioning, and priorities of the product. UX design focuses on interactions, ergonomics, and end-user satisfaction.

Product Design: Vision and Prioritization

The product designer initiates strategic thinking by identifying market opportunities and aligning the roadmap with business objectives. Based on market research and competitive analysis, they structure features into successive phases, prioritizing those with the highest ROI impact. This approach relies on clear metrics (development cost, value delivered, technical risks).

At the core of their role, the product designer also defines the product’s positioning, unique value proposition, and target customer segments. They formalize personas and usage scenarios to guide functional decisions and prevent scope creep during development. This structuring avoids late-stage trade-offs and ensures alignment with the company’s strategy.

UX Design: User-Centered Research and Prototypes

The UX designer, for their part, adopts a user-centered approach from the initial scoping workshops. They conduct interviews, user tests, and co-creation workshops to understand needs, frustrations, and behaviors. These insights inform the creation of wireframes, user journeys, and interactive prototypes.

Each prototype is evaluated through usability testing, enabling rapid identification of friction points and interface adjustments before any heavy development. By conducting multiple short iterations, the UX designer ensures fine-tuned adaptation to real expectations and avoids producing irrelevant or misunderstood features.

Governance and Cross-Disciplinary Collaboration

To ensure seamless collaboration, product and UX designers co-create the specifications: the product designer contributes the functional vision, the UX designer the user perspective. Joint reviews and shared milestones validate both business value and interaction quality.

An agile governance, where both profiles participate in the same rituals (sprint planning, sprint reviews, retrospectives), fosters continuous exchange. Decisions are then made through a dual lens, ensuring both strategic coherence and ergonomic efficiency.

Concrete Example of Separation Between Product Designer and UX Designer

A Swiss industrial company approached us to launch a B2B spare parts ordering platform. Our product designer developed a value proposition canvas prioritizing order speed and stock transparency, while the UX designer conducted workshops with field operators to create a simplified three-step navigation flow. This coordinated approach reduced average order processing time by 30% even at the MVP stage.

Complementarity: From Ideation to Product Validation

When product design and UX design work in concert, the digital platform ensures both business relevance and user adoption. Their cross-disciplinary methodologies accelerate hypothesis validation and optimize investments.

From Product Research to User Testing

The product designer formalizes value hypotheses to test: revenue impact, adoption by key segments, potential for upmarket growth. Each hypothesis is turned into proto-hypotheses to be validated by the UX designer through qualitative and quantitative studies.

User testing (A/B testing, moderated tests, heatmaps) provides objective data to adjust the roadmap. It enables quickly discarding low-efficiency features and reinvesting in higher-value levers.

Iterative Prototyping and Continuous Feedback

A low-fidelity prototype sketches the information architecture, while a high-fidelity prototype refines visual design and micro-interactions. At each iteration, user feedback is integrated into the backlog, feeding product prioritization.

This iterative loop reduces the risk of overdevelopment and encourages the market release of progressive versions, validated at each step by a representative panel.

KPI Alignment and Usage Monitoring

To monitor impact, product and UX designers jointly define key indicators (task completion rate, Net Promoter Score, generated revenue). Analytics and session replay tools provide continuous field feedback.

Usage data guides trade-offs, ensuring the product’s evolution is performance-driven while keeping user satisfaction at the core of decisions.

Concrete Example of Complementarity Between UX Design and Product Design

A Swiss financial services group adopted this approach for its mobile portfolio management app. Product and UX designers conducted moderated session tests, revealing that 40% of testers stalled at the strong authentication step. Thanks to these insights, the team pivoted to a more elegant biometric solution and increased the service activation rate by 25%.

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Adapting Profiles to the Digital Project Lifecycle

At the MVP stage, flexibility is key: favor a product designer who can quickly validate hypotheses and a UX designer focused on lean research. During the scale phase, reinforce teams to structure growth and ensure a consistent experience across all channels.

MVP: Agility and Rapid Validation

When launching an MVP, the goal is to test key hypotheses with a minimal set of features. The product designer focuses on defining these essential features and developing a batch-based roadmap, while the UX designer conducts rapid tests (guerilla testing, paper prototyping) to validate intuitiveness.

This lean setup allows for feedback gathering within weeks and iteration without burdening the structure. Decisions are based on tangible results rather than speculation.

Scale: Structuring and Standardization

Once the MVP is validated, the challenge is to prepare for scale and ensure cross-channel consistency. The product designer broadens the product vision, refines the roadmap, and introduces governance processes (feature reviews, scoring-based prioritization). The UX designer documents UI/UX guidelines and establishes a modular component library to standardize interfaces.

Integrating design systems enhances development speed and facilitates continuous evolution while adhering to a unified visual and interaction language.

Redesign: Expertise and Controlled Transition

In a redesign, the goal is to modernize an existing solution while preserving the user base. The product designer conducts a functional audit and defines a roadmap to migrate critical features without service disruption. The UX designer maps aging journeys, identifies breakpoints, and proposes new interaction patterns.

This phased approach, supported by coordinated iterations, ensures a smooth transition and minimizes impact on satisfaction and adoption.

Aligning Product and UX Design in a Digital Agency

An experienced agency organizes its teams to provide cross-functional product leadership, from defining features to validating with users. It combines agile methodologies, open-source solutions, and a modular ecosystem to ensure performance and scalability.

Overall Scoping and Technical-Functional Roadmap

At kickoff, the agency facilitates multidisciplinary workshops where product and UX designers work with business stakeholders to formalize the vision, objectives, and project milestones. Deliverables include a prioritized backlog and a concrete action plan, aligned with business imperatives and technical constraints.

This initial scoping can be built around open-source blocks and modular microservices to minimize vendor lock-in and ensure the application’s long-term scalability and flexibility.

Prototyping, Testing, and Rapid Iterations

The agency develops interactive prototypes that integrate reusable components, then coordinates testing sessions with representative users. Each finding is documented and prioritized with the product designer to adjust the roadmap.

This iterative approach, based on concrete feedback, limits development waste and ensures functional relevance before significant cost commitments.

Scaling Up and Continuous Monitoring

During deployment, the agency structures an evolving support system: test automation, UX and business KPI monitoring, incremental updates. Product and UX designers remain involved to manage releases and ensure experience consistency as new features are added.

The modularity of the architecture and use of open-source stacks (light front-end, asynchronous APIs, containers) ensure controlled scaling and prevent future bottlenecks.

Concrete Example

An emerging Swiss services company entrusted us with a complete redesign of its B2C platform. The plan was divided into three phases: scoping, A/B-tested prototype validation, and deployment with an Angular-based design system. The iterative cycle allowed for monthly user feedback integration, reducing churn by 18% in six months while adhering to the initial schedule.

Build a High-Performing, Aligned Digital Product

By clearly distinguishing product design and UX design and orchestrating them collaboratively, you maximize business impact and user adoption. The project’s maturity levels—MVP, scale, redesign—dictate the design team’s composition and intensity, while a modular, open-source approach ensures scalability and longevity.

Whatever your context, our Edana experts are ready to support you in designing a digital solution that combines strategy, experience, and technological robustness.

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David Mendes

Avatar de David Mendes

David is a Senior UX/UI Designer. He crafts user-centered journeys and interfaces for your business software, SaaS products, mobile applications, websites, and digital ecosystems. Leveraging user research and rapid prototyping expertise, he ensures a cohesive, engaging experience across every touchpoint.

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Featured-Posts-Web-Dev (EN) Web Development (EN)

Web Eco-Design: How to Build Efficient Products While Avoiding Greenwashing Pitfalls?

Web Eco-Design: How to Build Efficient Products While Avoiding Greenwashing Pitfalls?

Auteur n°3 – Benjamin

In a context where digital technology now accounts for nearly 4 % of global CO₂ emissions, web eco-design stands out as both a performance lever and a commitment. Designing lean digital products improves loading speed, accessibility, and organic search ranking, while controlling infrastructure costs and minimizing carbon footprint. However, without methodological rigor, eco-design can become mere greenwashing, stripped of its substance. This article offers technical decision-makers, project managers, and digital leads a pragmatic, strategic approach to avoid these pitfalls and build sustainable, effective, and convincing digital solutions without compromising user experience.

Why Eco-Design Is a Global Performance Issue

Designing lean interfaces accelerates your sites and boosts your SEO. Digital sobriety directly translates into lower hosting costs and better accessibility.

Improving Speed and User Experience

Reducing page weight and optimizing resource delivery often leads to significantly faster load times. More responsive interfaces ensure smooth navigation and decrease abandonment risk.

By limiting the number of requests, compressing assets, and favoring lightweight formats, you deliver a more pleasant journey—especially on mobile. Speed becomes a competitive advantage and fosters user retention.

A Swiss e-commerce SME we supported experienced this firsthand: after cutting product page weight by 40 %, its bounce rate dropped by 15 % and average session duration rose by 20 %.

Accessibility and Best-Practice Compliance

A lighter page is often more accessible to assistive technologies and slow connections. Eco-design principles align with accessibility recommendations to ensure a universal experience.

Integrating proper contrast ratios, semantic tags, and text alternatives from the outset not only reduces reliance on heavy scripts but also opens your site to a broader audience.

This approach also eases compliance with international standards, reducing sanction risks and enhancing your reputation with regulators and stakeholders.

Reducing Infrastructure and Operating Costs

Less data to store or transmit means fewer servers and lower energy consumption. At the scale of a cloud provider, each gigabyte saved translates into reduced electricity use.

Resource pooling and auto-sleep mechanisms further cut both bills and carbon footprint.

For a major Swiss industrial group, migrating to a leaner architecture reduced annual hosting costs by 25 % and server-related carbon emissions by 30 %.

How to Avoid Digital Greenwashing Pitfalls

Greenwashing stems from unreliable measurement and vague messaging about real goals. True eco-design relies on a rigorous framework and clear indicators.

Define Environmental Performance Indicators

Before acting, quantify impact: measure the energy consumption of requests, average page weight, or the estimated CO₂ footprint per visit.

Dedicated audit and monitoring tools gather the data needed for precise management and track progress as optimizations unfold.

A Swiss financial player implemented monthly tracking of key indicators and cut average page size by 18 % in three months.

Establish Governance and Business Processes

Eco-design must be integrated into project lifecycles: from defining functional scope to delivery, every phase offers an optimization opportunity.

Involving design, development, and infrastructure teams when drafting user stories ensures each feature is evaluated for its technical and environmental impact.

By holding regular impact review meetings, stakeholders maintain a shared vision of objectives and adjust scope based on measured results.

Communicate Transparently and Avoid Vague Claims

Labels and certifications are useful but must be backed by concrete data sharing. Displaying indicators without solid context can be seen as superficial greenwashing.

Publishing a concise report on your services’ digital footprint that details implemented optimizations builds trust and demonstrates genuine commitment.

Rather than claiming an eco-responsible stance without proof, show indicator trends and concrete efforts for each topic.

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Best Practices for Design, Development, and Hosting

Clean design, optimized code, and responsible hosting form the pillars of eco-design. Each stage can be geared toward sobriety without sacrificing user experience.

Eco-Responsible Design and UX

Choosing a limited palette and limiting images and custom fonts lightens initial page loads. Streamlined interfaces enable quick reading and focus on essentials.

Using reusable components and optimizing interactions (light animations, CSS transitions) ensures visual coherence while minimizing CPU load.

A Lausanne SME specialized in online booking reduced its UI weight by 35 % by standardizing its component libraries and limiting external font usage.

Code Development and Optimization

Adopting a modular open-source architecture eases dependency updates and limits vulnerabilities. Using typed languages reduces runtime errors and improves maintainability.

Writing performance tests helps automatically detect regressions in speed or consumption before production deployment.

Breaking into microservices or using serverless for occasional tasks ensures only necessary resources are active, reducing overall consumption.

Sustainable Hosting and Infrastructure

Choosing a provider committed to renewables and certified to ISO 14001 or equivalent ensures your data is handled in eco-responsible data centers.

Enabling automatic instance shutdown during low traffic and right-sizing clusters avoids overcapacity and wasted energy.

For a Swiss telecom operator, integrating autoscaling and dynamic server idling cut its cloud carbon footprint by 28 % in one year.

Technological Trade-Offs for a Responsible Web or SaaS

Choosing languages, frameworks, animations, and media directly impacts carbon footprint. Adopting lightweight, scalable solutions strikes a balance between performance and eco-design.

Lightweight Languages and Frameworks

Non-blocking runtimes, like Node.js with a modular framework, offer highly efficient asynchronous execution. Fewer active threads mean lower CPU consumption.

Typed, ahead-of-time compiled languages reduce runtime errors and optimize build cycles for faster, leaner deployments.

Favoring an open-source ecosystem avoids vendor lock-in and ensures continuous access to performance and security updates.

Controlled Animations and Interactions

CSS transitions and animations based on transform and opacity consume far fewer resources than JavaScript animations. They run directly on the GPU, easing CPU load.

Limiting duration and frequency, and triggering animations only when needed, reduces device workload and energy consumption.

Placeholders and lazy-loading for deferred visual effects ensure animations activate at the right moment.

Media Weight and Optimized Formats

Converting images to WebP or AVIF—more efficient than JPEG or PNG—can halve their weight or better.

Using SVG for icons and vector graphics ensures crisp rendering at any resolution without increasing data volume.

For videos, adapting quality to the device (mobile, desktop) and offering adaptive streams (HLS, DASH) limits unnecessary transfers and improves experience.

Balance Performance and Digital Responsibility Coherently and Effectively

Web eco-design isn’t a list of constraints but a framework to build faster, safer, and more durable digital products. By aligning lightweight design, modular code, and responsible infrastructure, you combine technical performance with environmental footprint control.

Whatever your industry or maturity level, our experts can help you define clear indicators, structure your governance, and choose the right technologies to engage your teams in this transition. Together, we’ll build lasting solutions without resorting to greenwashing that could harm your corporate image.

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E-Commerce Development (EN) Featured-Posts-Web-Dev (EN)

AI Shoppers & AAO: Do We Need to Rethink E-Commerce in the Age of Intelligent Agents?

AI Shoppers & AAO: Do We Need to Rethink E-Commerce in the Age of Intelligent Agents?

Auteur n°3 – Benjamin

The emergence of “AI Shoppers,” these intelligent agents capable of placing orders based on entirely objective criteria, is disrupting the established rules of e-commerce. Brands that relied on branding, storytelling, or interface design must now anticipate a new criterion: the readability and pure reliability of product data. For Swiss decision-makers, this challenge is not theoretical—it requires adapting catalogs, online reputation, and technical solutions to appeal to these automated buyers. In this landscape, AAO (AI Agent Optimization) is set to be as critical as SEO was twenty years ago. This article explores four strategic avenues to prepare your e-commerce for this revolution.

AI Agents: The New Digital Buyers Ready to Overlook Traditional Branding

These agents favor objective data (price, availability, performance) over brand identity. They analyze and compare thousands of items in real time to optimize each purchase.

The AI assistants that purchase automatically operate based on algorithms designed to select the most efficient offer according to precise criteria. They assess perceived quality from factual parameters: delivery times, customer returns, availability history, and reliability scores.

Unlike traditional consumers, these agents are not influenced by sophisticated marketing content or attractive visuals. What matters to them is clear, structured information, accessible via APIs or extracted from intelligible catalog feeds.

Objective Factors Preferred by AI Agents

AI agents run scoring functions that aggregate quantified, normalized data. The most common criteria are total cost of acquisition, logistical processing time, and return probabilities.

Each data point must be provided in a structured format (JSON-LD, microdata, XML) to be easily ingested. A missing attribute can lower a product’s score, excluding it from the agent’s generated results.

Historical consistency also plays a role: an agent values channels that have proven reliable across multiple past transactions. A site with recurring stockouts can be penalized, even if its price is low.

Impacts on the User Experience

The obsession with pure data is reshaping the structure of purchase journeys. Product pages now need to include performance indicators (availability rate, average delivery time, customer satisfaction rate) rather than narrative content.

On the UX side, the goal is no longer just to entice the end user but also to provide a technically reliable interface for bots. Rigorous semantic markup and coherent microformats become essential.

Internally, marketing and IT teams must coordinate their efforts to ensure every data feed is updated in real time and error-free, or risk seeing the AI agent favor a more agile competitor.

Repercussions on Brand Strategy

Brands will lose part of their emotional influence if they do not objectify their value. Differentiation must shift to tangible criteria: service quality, eco-design, manufacturing origin.

Narrative content and branding campaigns remain relevant for human purchases, but they no longer factor into the agents’ calculations. It is therefore necessary to strike a careful balance between technical optimization and emotional marketing.

In practice, a cross-functional collaboration between product managers, data scientists, and UX designers is required to align storytelling with AI-processable formats.

Example: A European online furniture retailer saw AI-generated sales increase by 20% after enriching its product data with sustainability indicators and real-time availability metrics.

AAO: AI Agent Optimization, the New Lever as Critical as SEO

Optimizing for AI agents (AAO) has become a strategic imperative, ensuring visibility and relevance in automated queries. Product data, reputation, and technical architecture must be reinvented.

Just as SEO forced organizations to revise their web content and site structures, AAO demands rethinking catalog structuring and the robustness of IT integrations. The correlation between data quality and business performance is now direct.

Teams must adopt agile workflows, integrating a continuous process of updating and verifying feeds destined for agents. Automated monitoring mechanisms become vital to detect anomalies before they harm a channel’s score.

Structuring Product Data for AI

The first step is ensuring completeness, consistency, and granularity that meet agents’ needs. Each product must include measurable attributes: exact dimensions, weight, standardized colorimetry, certifications.

Catalog-wide normalization allows algorithms to compare offers more efficiently. Format discrepancies between suppliers are eliminated via automated data mapping.

Maintaining this data requires a robust ETL (Extract, Transform, Load) pipeline capable of integrating continuous updates without disrupting production systems.

Managing Reputation and Reviews to Earn AI Agents’ Trust

AI agents also analyze a merchant’s reputation based on customer reviews and logistical reliability scores. A review aggregation and cleansing process ensures an image that reflects operational reality.

Transparency in returns and dispute resolutions is valued. Platforms that clearly publish return rates or resolution times receive higher ratings from assistants.

To anticipate these criteria, companies must implement webhooks and APIs to relay satisfaction and incident-handling metrics in real time.

Technical Optimization and IT Integrations for Scalable Deployment

AI Agent Optimization requires a scalable, resilient infrastructure. API endpoints must handle request peaks and guarantee response times under a few tens of milliseconds.

A modular architecture, favoring open-source microservices, limits contention boundaries and reduces the risk of vendor lock-in. Cloud orchestrations should dynamically allocate resources and bandwidth.

Proactive monitoring (distributed tracing, structured logs) and real-time alerting ensure the continuous availability of critical feeds for agents.

Example: A Swiss electronics equipment distributor doubled its AI Shoppers sales opportunities after overhauling its master data management, automating certified review publication, and deploying a Kubernetes cluster for its product APIs.

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Becoming Objectively Distinct to Withstand Copycat Brands and Appeal to AI Agents

AI agents do not differentiate products by branding if specifications are identical. Only technical and factual uniqueness creates a barrier to replication.

In the era of AI Shoppers, differentiation no longer comes through packaging or slogans but through tangible value: innovative materials, measurable performance, local certifications. These attributes must be documented in a standardized, verifiable manner.

Highlighting Swiss labels, environmental standards, or durability tests becomes a lever to stand out in automated queries. This data feeds into agent scores and enhances the appeal of Swiss offerings.

Importance of Product Differentiation by Technical Characteristics

A product must stand out through clear metrics: energy efficiency, cycle time, stress resistance, extended warranties. Each numeric value contributes to the automated comparison.

These indicators are then exposed via interoperable formats (schema.org, GS1) so agents can prioritize them. The supplier providing the most exhaustive metrics dominates the results.

Internally, this requires a close link between R&D and IT to transform technical documentation into machine-readable markup.

Role of Quality Labels and Local Certifications

Swiss certifications (Oeko-Tex, Swiss Made, eco-labels) serve as objective proof of recognized quality. AI agents consider them as reliability filters.

To be taken into account, these labels must appear in structured product attributes and be updated according to certification renewal cycles.

Compliance data, managed through a central repository, can be published in a dedicated feed that agents access with priority.

Data-Driven Narratives Based on Performance

Rather than marketing descriptions, agents favor comparative test results (benchmarks, technical rankings) documented by recognized third parties.

A self-audit protocol hosted on an accessible portal demonstrates the company’s rigor. Links to these reports, provided in metadata, reinforce algorithmic trust.

This effort turns editorial content into quantified proof, bolstering brand resilience against imitations.

Example: A Basel-based cosmetics SME rose to the top of AI queries after integrating dermatological test data and botanical origin certificates directly into its product feed.

Capitalizing on Swiss Strengths to Attract AI Shoppers

Service quality, fast delivery, local stock, and reputation are tangible competitive advantages. Making them indexable for agents can create a significant differential.

Swiss e-merchants can leverage geographical proximity and logistical reliability to achieve a higher score in automated rankings. However, every promise must be formalized through accessible data.

The information system must convey real-time stock levels, express delivery options, and customer support commitments. APIs should reflect these strengths as a priority.

Highlighting Local Logistics and Delivery Times

A “Shipped from Switzerland” badge or a “+2 working days” delivery indicator directly impacts the agent’s score. This information must appear in a dedicated product catalog field.

Logistics API integrators can synchronize this data automatically, ensuring that an out-of-stock item does not appear as available.

Order tracing, usable by assistants, reinforces confidence in meeting the promised deadlines.

Clarifying Stock Levels and SLAs

AI agencies evaluate the likelihood of transaction success based on the granularity of stock data. Swiss e-merchants must expose not only totals but also warehouse-level breakdowns.

Service level agreements (SLAs) for returns and exchanges then adjust the final score. A 30-calendar-day return period is preferred over a more restrictive process.

Implementing logistical performance indicators (OTIF, shipment accuracy rate) improves algorithmic visibility and justifies recommendation premiums.

Integrating Customer Service into AI Feeds

AI agents don’t stop at purchase: they anticipate post-sales interactions. Access to an automated chatbot or a certified call center appears in their scoring matrix.

It is therefore recommended to make first-contact resolution rates, service hours, and available channels (email, phone, chat) accessible. This information feeds trust in the merchant’s ability to handle incidents.

A structured dashboard, exposed via a dedicated API, allows continuous synchronization of these metrics with AI shopping platforms.

Position Your E-Commerce for the Age of AI Shoppers

To capitalize on this disruption, adopt a holistic approach: fine-grained data structuring, feed automation, reinforced IT reliability, and highlighting local strengths. AAO becomes a cross-functional project involving marketing, data, and IT.

By investing in open-source, scalable, and secure architectures without vendor lock-in, you ensure the longevity of your optimizations. Every enriched metadata and every optimized API contributes directly to your visibility with AI assistants.

Our Edana experts are available to define a tailored AAO roadmap and turn these challenges into growth opportunities.

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Featured-Post-UX-Design (EN) Featured-Post-UX-UI-FR

Prioritizing Tasks in Digital Product Development: Maximizing Your Backlog’s Impact

Prioritizing Tasks in Digital Product Development: Maximizing Your Backlog’s Impact

Auteur n°4 – Mariami

In an environment where digital innovation drives competitiveness, the effectiveness of feature prioritization determines project success. A poorly ordered backlog leads to longer development cycles, budget pressures, and falling behind competitors. Priority decisions must be based from the outset on a strategic vision and business metrics to generate value and maintain a responsive time-to-market. This article offers a pragmatic framework for maximizing backlog impact by combining business rigor and operational agility to manage high-performing, sustainable digital products.

The Costs of Poor Prioritization

Ineffective prioritization results in significant delays and budget overruns. It also leads to growing technical debt and undermines your product’s adoption.

Delays and Budget Overruns

When priorities aren’t clearly defined at a project’s outset, technical teams frequently switch from one topic to another without a real roadmap. This instability disrupts focus and lengthens development cycles, directly impacting time-to-market. Last-minute trade-offs generate overtime and additional costs that erode the initial budget.

IT departments often have to reassign resources to catch up on delays, which disrupts other strategic initiatives. The domino effect on deployment timelines hinders coordination with business teams and slows down planning for subsequent phases. Over time, this budgetary turmoil can even call the project’s viability into question.

Accumulation of Technical Debt

A poorly balanced backlog often favors the rapid release of features deemed priorities but lacking sound design and testing practices. Each load increase or change adds its share of fixes and further technical debt. As these compromises stack up, the codebase grows fragile and costly to maintain.

For example, a Swiss industrial company found that its teams were constantly handling incidents caused by development shortcuts taken to meet initial deadlines. The accumulated technical debt accounted for 40% of maintenance tickets, resulting in a six-month delay on the delivery of a critical enterprise application.

This extra maintenance effort then diverts resources from improvement projects and hampers continuous innovation, reinforcing a vicious cycle of underperformance.

Poor User Adoption

When features are developed without a clear hierarchy based on real user needs, products suffer low adoption rates. End users encounter functional gaps or incomplete interfaces that harm satisfaction and engagement. This disengagement can jeopardize the project’s overall objectives.

Lack of focus on high-value business scenarios prevents optimization of the user experience and fails to address key operational performance challenges. Negative feedback accumulates, and requests for changes multiply, slowing down the structured delivery of future enhancements. Poor adoption thus represents a hidden cost that can exceed technical overrun expenses.

Transforming Your Backlog into a Value Driver Aligned with Business Strategy

Prioritizing according to your strategic objectives turns the backlog into a value-creation engine. Ongoing alignment with the business roadmap ensures every development contributes to desired outcomes.

Identifying Key Business Objectives

The initial backlog analysis begins by translating business goals into prioritization criteria: increasing retention, reducing operational costs, improving customer satisfaction, etc. These indicators guide the selection of top-priority features and ensure consistency between strategic vision and execution.

IT-business steering committees define clear KPIs before each sprint, ensuring shared understanding of objectives. This discipline curbs scope creep and channels effort towards high-impact features. At each sprint review, priorities are adjusted based on measured data (adoption rates, qualitative feedback, technical performance).

Ranking High-Value Features

Once objectives are set, features should be ranked according to their contribution to key indicators. Assigning business impact scores helps identify quick wins and longer-term strategic initiatives. This approach prevents teams from spreading themselves thin on low-value developments.

For instance, a Swiss fintech scale-up used a scoring model to distinguish revenue-generating features from secondary improvements. It focused its resources on a client-scoring module whose deployment boosted conversion rates by 15% in two months.

This precise framing builds decision-makers’ confidence and fosters a virtuous cycle between business objectives and technical delivery.

Creating a Dynamic Roadmap

The digital roadmap must remain a living document, able to incorporate market shifts and new feedback. Milestones are set according to commercial seasons, regulatory deadlines, and pilot test phases. This time-based organization eases dependency management across teams and modules.

A multi-level backlog (strategic, tactical, project) preserves both macro and micro perspectives simultaneously. Detailed stories emerge iteratively without disrupting the initial strategic outlook. Agility is maintained while keeping a clear business direction.
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Choosing the Right Prioritization Method for Your Context

Each prioritization method suits specific contexts—innovation, redesign, or an MVP. Adapting your approach ensures rapid, context-aligned backlog management.

MoSCoW Method for Defining Essentials

The MoSCoW method distinguishes four categories: Must, Should, Could, Won’t. It is ideal for redesign projects or new version launches, where it’s critical to distinguish essentials from nice-to-haves.

By clearly defining what must be delivered, teams stay focused on fundamentals and avoid feature creep. “Could” items are scheduled later or dropped under time constraints, ensuring a realistic scope.

MoSCoW’s transparency also facilitates dialogue between IT, business stakeholders, and decision-makers by clearly showing the value and risk implications of each trade-off.

P0/P1/P2 Classification for Clear Trade-Offs

The P0/P1/P2 model ranks tasks on three levels: P0 for urgent and critical, P1 for important but non-blocking, P2 for the rest. This simple framework suits fast-paced environments like continuous delivery or DevOps teams.

A Swiss retailer implemented this system during an internal SaaS rollout. Blocker incidents (P0) were resolved within 24 hours, while nice-to-have enhancements (P2) were planned in quarterly releases. This discipline cut critical alerts by 30% and optimized resource allocation.

P0/P1/P2 classification boosts responsiveness during peak activity or production incidents while maintaining a clear view of foundational work.

Value/Effort Matrix to Optimize ROI

The value/effort matrix positions each feature along two axes: business impact and technical effort required. This visual tool distinguishes “big wins” (high value, low effort) from low-ROI initiatives.

Features fall into four quadrants: quick wins, major initiatives, fillers (low value, low effort), and traps (low value, high effort). Quick wins are tackled first for rapid, tangible results, while traps are addressed only if extra resources become available.

This straightforward tool drives collective decision-making in backlog-grooming workshops and boosts team buy-in for the defined roadmap.

Evolving Prioritization in an Agile, Adaptive Framework

Dynamic prioritization, integrating feedback and market shifts, increases your product’s resilience. Continuous adaptation ensures each sprint remains value-driven and aligned with real-world conditions.

Incorporating User Feedback

End-user feedback—gathered through tests, interviews, or quantitative analyses—is essential for adjusting backlog priorities. Collected incidents and suggestions provide field insights that complement the initial business perspective.

By integrating this feedback at every sprint review, teams can recalibrate stories, add critical tasks to enhance the experience, and remove underused items. This feedback loop ensures user-centered evolution and product adoption.

The process also quickly identifies pain points and measures the impact of adjustments, strengthening stakeholders’ confidence in the agile approach.

Continuous Reassessment Based on Market Changes

Market shifts, new competitors, and regulatory updates constantly reshape the digital project landscape. Maintaining a watch and regularly reassessing the backlog is essential to anticipate these changes.

Weekly or biweekly backlog-refinement sessions allow priorities to be realigned based on market data and business indicators. Teams thus maintain an adaptable roadmap that can respond to unforeseen challenges.

This approach boosts competitiveness and prevents the development of obsolete or ill-fitting features.

Balancing Business and Technical Trade-Offs

Prioritization decisions rely not only on business value but also on technical feasibility, existing debt, and associated risks. Business-technical trade-offs require close collaboration among IT leaders, architects, and business owners.

Joint workshops weigh expected value against integration cost, maintenance effort, and security. The goal is a balanced approach between immediate gains and solution longevity.

An agile governance framework with regular reviews and clear roles ensures coherent trade-offs and guarantees quality and security throughout the delivery cycle.

Turn Your Backlog into a Growth Engine

Rigorous, strategy-aligned prioritization reduces delays, controls technical debt, and promotes user adoption. By choosing the method that fits your context and continuously integrating feedback and market insights, every backlog item becomes a value lever.

Your agile processes gain clarity and responsiveness, and your teams focus on the most impactful features. With this pragmatic framework, the backlog becomes a true management tool, ensuring the success of your digital projects and the sustainability of your digital ecosystem.

Our Edana experts are ready to support you from the scoping phase onward: prioritization, roadmap development, and business/technical trade-offs. Let’s discuss your challenges and the levers to transform your backlog into a growth engine.

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Mariami Minadze

Mariami is an expert in digital strategy and project management. She audits the digital ecosystems of companies and organizations of all sizes and in all sectors, and orchestrates strategies and plans that generate value for our customers. Highlighting and piloting solutions tailored to your objectives for measurable results and maximum ROI is her specialty.

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Featured-Post-UX-Design (EN) UI/UX Design EN

Digital Accessibility: How AI Paves the Way to an Inclusive Experience for All

Digital Accessibility: How AI Paves the Way to an Inclusive Experience for All

Auteur n°2 – Jonathan

Despite decades of guidelines and standards, a significant portion of the web remains difficult to access for people with disabilities. Artificial intelligence is reshaping the landscape by automating content analysis and correction, personalizing the user experience, and paving the way for multisensory interactions. IT directors, project managers, or CIOs: it’s time to integrate AI into your accessibility strategy to meet legal requirements, societal expectations, and the needs of an aging population, all while delivering an optimized experience for every user.

Why Digital Accessibility Has Become Strategic Today

Regulations are evolving rapidly while societal expectations intensify. At the same time, aging populations and the proliferation of mobile usage place accessibility at the heart of business challenges.

Strengthening Legal Obligations (EU, Switzerland, US)

Since the adoption of European Directive 2016/2102, public websites and apps must comply with WCAG 2.1 standards. This legislation mandates color contrasts, textual alternatives, and fully functional keyboard navigation. In Switzerland, the Federal Act on the Elimination of Discrimination against Persons with Disabilities (LHand) and its ordinance specify similar requirements for digital services of administrations and companies subject to public procurement.

In the United States, the Americans with Disabilities Act (ADA) is increasingly invoked to sue organizations whose digital interfaces are not accessible. Class actions are on the rise, with fines and remediation costs reaching into the hundreds of thousands of francs.

This regulatory tightening is most visible in the financial sector and public services, where controls and sanctions are systematic. Companies failing to comply not only risk penalties but also damage to their reputation.

Growing Social Pressure and Collective Actions

Social media amplify the voices of people with disabilities, turning an accessibility incident into an immediate viral backlash. A malfunctioning voice-command interface can quickly become the focus of online petitions and criticism.

At the same time, associations and digital rights collectives conduct investigations and file group complaints. In Europe, several major organizations have already been forced to overhaul their portals under threat of administrative blockages.

This social pressure also translates into tenders that now include accessibility as a selection criterion. Early adopters gain visibility and trust among partners and clients.

Aging Population and Widespread Mobile Usage

Switzerland has over 18% of seniors aged 65 and above, a figure set to grow in the coming years. Visual, auditory, or motor impairments therefore become strategic issues for capturing this clientele.

Moreover, usage is increasingly mobile: smaller interfaces, touch gestures, and varied contexts of use (lighting, movement). Temporary impairments—broken screens, occupied hands, noisy environments—affect a growing number of users every day.

In this context, a major Swiss retailer tested a dynamic enlargement tool for click zones on its mobile site. Thanks to AI algorithms, interactive areas adjust in real time to how the user holds their phone, reducing input errors by 35% among those over 60.

What AI Can Concretely Transform in Accessibility

AI opens new horizons: automation, personalization, and real-time adaptation. From generating captions to creating multisensory experiences, AI expands the scope of inclusion efforts.

Automatic Generation of Captions, Summaries, and Image Descriptions

Speech recognition and natural language processing solutions transcribe video dialogue instantly, producing synchronized captions. An AI algorithm can also automatically summarize long content, easing reading for people with dyslexia or visual impairments.

Image descriptions, long created manually, can now be generated by computer vision. Each image or illustration receives a detailed alt text, ensuring equivalent comprehension for screen reader users.

For a Swiss e-learning institution, this mechanism reduced the time spent on creating accessible content by 80%. Video courses now come with instant captions and summaries, boosting satisfaction for all learners.

Real-Time Translation and Adaptation (Audio, Visual, Text)

AI-based machine translation services now deliver subtitles comparable to a professional’s. Content can be adapted into over 100 languages, with style and phrasing tailored to technical or marketing contexts.

In audio interfaces, a voice assistant can rephrase responses for hard-of-hearing users, adding on-screen text or offering haptic feedback. This multimodality enriches the experience.

In multilingual settings—trade shows, international training, global platforms—these tools ensure consistent accessibility without additional localization costs.

Automated Website Audits

Intelligent crawlers continuously scan web pages to detect WCAG or RGAA violations. They generate detailed reports, prioritized by business impact and technical severity.

Paired with interactive dashboards, these audits enable progress tracking, fix planning, and ROI quantification for accessibility actions.

A Swiss industrial multinational implemented a daily automated audit. Detected anomalies feed directly into its ITSM tool, ensuring traceability and faster response.

Adaptive Interfaces for Temporary or Situational Impairments

Machine learning allows interfaces to detect noisy environments and automatically offer text transcriptions of audio notifications.

If ambient light is low, AI adjusts contrast and font size in real time to preserve visual comfort.

These contextual adaptations improve the experience for all users without manual configuration overload.

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Limits Not to Ignore: Why AI Alone Is Not Enough for Optimal Accessibility

AI delivers considerable gains, but it cannot replace a comprehensive accessibility approach. Manual testing, quality data, and inclusive design remain indispensable pillars.

Manual Testing Remains Indispensable

Algorithms can miss nuances, such as coherence in descriptive language. User testing, by contrast, exposes the frustrations experienced by people with disabilities.

Validations with screen readers and assistive devices must be conducted regularly, especially during major redesigns or updates.

A Swiss financial institution maintained a panel of employees with disabilities to test every major portal version. These human insights corrected 12% of issues undetected by automated tools.

By combining AI with field feedback, organizations achieve a level of excellence unattainable by either approach alone.

The Quality of Training Data Is Crucial

Computer vision models are only as good as the annotated images that train them. A biased or insufficient dataset leads to inaccurate or discriminatory descriptions.

Algorithms must be fed representative data covering all profiles and use cases, ensuring diversity of genders, ages, and disability types.

Data governance—collection, anonymization, updates—must be rigorous to guarantee results that are reliable and GDPR-compliant.

Without quality data, AI can hinder rather than accelerate, generating costly errors that require manual correction.

Need for Accessible Design from the UX/UI Phase

Before integrating AI, information architecture and user journeys must be crafted to minimize entry barriers.

Structuring HTML code, providing semantic landmarks, and adopting accessible components (ARIA buttons, visual cues) ensure a solid foundation.

AI tools will enrich this base but cannot compensate for interfaces built without these principles.

A Swiss public services agency tested several AI widgets before realizing that unclear navigation elements limited adoption. A prior UX redesign tripled the effectiveness of the assistive tools.

Adopting a Contextual and Scalable Approach for AI-Centered Accessibility

Each accessibility project must be based on a tailored, modular, and secure strategy. Open source, hybrid modules, and scalable architecture ensure sustainable inclusion.

Favor Open Source Solutions and Avoid Vendor Lock-In

Open source libraries offer full flexibility and an active community to quickly address vulnerabilities.

By controlling code and dependencies, organizations ensure the longevity and security of accessibility tools without being subject to a single vendor’s roadmap.

This approach aligns with Edana’s culture, where each component is chosen for its ecosystem and ability to evolve without blockage.

Integrate Accessibility from the Digital Product Design Phase

Ideation and prototyping workshops should involve designers, accessibility experts, and AI developers to define native accessible components.

Technical and usability feasibility tests occur before development to avoid costly retrofits.

A Swiss logistics services company co-created its interfaces with a diverse user panel, guaranteeing WCAG compliance and easing later AI tool integration.

Implement Continuous Auditing and Monitoring

Beyond an initial audit, an automated monitoring system must continually check for accessibility regressions.

AI-generated reports feed a backlog that prioritizes fixes by business impact and technical criticality.

This process ensures iterative improvement and prevents compliance drift as features evolve.

Train Teams and Establish Agile Governance

Developers and project managers must understand accessibility challenges and master associated AI tools.

Regular training and inclusive code reviews maintain a high, shared skill level.

Agile governance, with sprints dedicated to accessibility topics, ensures transparent management and continuous value delivery.

Make Accessibility a Lever of Competitiveness

By combining regulatory compliance, AI’s potential, sound design practices, and agile governance, you create an inclusive and differentiating digital experience. When fueled by quality data and supported by human testing, artificial intelligence becomes a powerful accelerator of inclusion.

In a market where compliance is a prerequisite and user experience a key success factor, integrating accessibility from the outset and enhancing it with advanced technologies is a strategic choice. Our experts are here to help you define the most suitable solution for your context, prioritizing scalability, security, and open source.

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PUBLISHED BY

Jonathan Massa

As a senior specialist in technology consulting, strategy, and delivery, Jonathan advises companies and organizations at both strategic and operational levels within value-creation and digital transformation programs focused on innovation and growth. With deep expertise in enterprise architecture, he guides our clients on software engineering and IT development matters, enabling them to deploy solutions that are truly aligned with their objectives.

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Do You Really Need to Draft a Specification Document for Your Digital Project?

Do You Really Need to Draft a Specification Document for Your Digital Project?

Auteur n°4 – Mariami

Drafting a comprehensive specification document is often regarded as the cornerstone of any digital project. Yet this bulky document can sometimes create gaps between actual needs and initial specifications, weigh down decision-making processes, and slow your teams’ responsiveness. For decision-makers seeking a SaaS solution, a mobile app, business software, or a digital platform, the challenge is to balance agility with discipline. This guide proposes moving beyond the myth of the specification document as a mandatory step by prioritizing collaboration, rapid concept visualization (design-first), and strategic prioritization. With this approach, you quickly define a relevant MVP, focus your resources on delivering real value, and significantly reduce your time-to-market. We illustrate each point with concrete examples from Swiss companies to inspire your strategy.

The Limitations of the Traditional Specification Document

The specification document can sometimes become a too-rigid foundation, incapable of evolving in response to field discoveries. Its creation mobilizes significant resources before the first prototypes even exist, risking an unnecessary extension of your time-to-market.

Rigid Specifications

The specification document sets an exhaustive framework from the outset, detailing every feature, user scenario, and technical constraint. But this approach doesn’t always incorporate insights from early feedback or user testing.

When new requirements emerge, integrating them demands formal revisions, approval cycles, and extra meetings. Each change becomes a project in itself.

Ultimately, this approach can leave the project trapped in dated specification lists, ignoring evolving business needs or market opportunities.

Approval Delays and Time-to-Market

Drafting and approving the specification document often involves multiple countries and departments, generating back-and-forth exchanges and unexpected delays. Scoping meetings pile up, slowing decision-making.

The delays accumulated before development even begins directly impact time-to-market, reducing the company’s ability to seize early opportunities.

This can trigger a domino effect, where a delayed launch of an application or digital platform benefits your more agile competitors.

Lack of Stakeholder Buy-In

Engaging end users, marketing teams, or operations too late in a fixed document reduces their commitment. Stakeholders may perceive the specification as imposed, without real consideration for their specific needs.

Without collective ownership, stakeholders may not engage in testing or validation phases, resulting in late feedback and costly revisions at the end of the project.

For example, a mid-sized Swiss watchmaker spent over three months finalizing its customer platform specification. During the acceptance phase, internal teams flagged major gaps, necessitating two redefinition cycles. The project was pushed back six months, impacting the marketing schedule and user satisfaction.

Risks of a Specification Document: When Formalism Stifles Innovation

The need to comply with a strict specification can suffocate creativity and risk-taking. Obsessing over initial details often disconnects the project from the market’s actual and fluid needs.

Blocking Emerging Ideas

The specification document defines features before any user exploration or design sprint has even been conducted. This rigid anticipation limits the emergence of innovative ideas discovered during product discovery.

When new concepts appear, they’re often deemed out of scope, requiring amendments or budget renegotiations. Teams become reluctant to propose alternative approaches.

As a result, the project stalls on preconceived solutions, missing out on collective intelligence and on-the-ground feedback.

Disconnect from Real User Needs

A static document cannot capture the dynamic evolution of user needs or emerging usage patterns. The personas and use cases initially described quickly become obsolete.

Without regular feedback, development rests on assumptions, increasing the risk of delivering non-priority or poorly adopted features.

This disconnect often leads to low adoption rates and business teams feeling alienated from technological decisions.

Hidden Cost of Rigorous Compliance

Ensuring compliance with the specification document requires tools and monitoring processes (committees, reports, acceptance tests). These resources can account for up to 20% of a digital project’s total budget.

Teams spend more time in meetings and reporting than on development and innovation. Cushions to satisfy every line of the document drag down velocity.

A Swiss financial institution preparing an internal portal found that 18% of its project budget was consumed by validation committees and change management. This overrun delayed the launch and increased the TCO.

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Collaboration and Design-First: An Alternative Approach

Co-design and design-first workshops align business needs and technical solutions. Rapid prototyping enables continuous experimentation, validation, and refinement before any large-scale development.

UX and Design Thinking Workshops

Workshops bring business teams, IT, and end users together around a whiteboard. This rapid pooling of ideas fosters mutual understanding and identification of real priorities.

In just a few hours, teams generate empirical user journeys, test hypotheses, and refine functional requirements before formalizing anything in writing.

This collective engagement builds co-ownership and ensures better buy-in during later development phases.

Rapid Prototyping to Validate Concepts

A clickable prototype or interactive wireframe lets you envision the final product without writing a single line of code. Feedback is immediate and easy to integrate.

Adjustments happen in real time, drastically reducing revision cycles compared to textual specification feedback.

In practice, teams quickly identify misunderstood flows, secondary features, and friction points before any heavy budget commitment.

Iterative Feedback and Continuous Refinement

Based on the prototype, sprints follow with frequent demos to stakeholders. Each iteration progressively enriches the truly useful scope.

This Lean product approach ensures the project stays connected to business objectives and field realities, avoiding variances from initial assumptions.

A Swiss pharmaceutical company used this approach to overhaul its internal training portal. In three successive workshops, it invalidated two secondary features and focused development on an interactive reporting module, cutting the backlog by 40% by the MVP stage.

Strategic Prioritization and Launching an Agile MVP

Defining an MVP (Minimum Viable Product) focuses efforts on the most critical business value. A lightweight governance model ensures agile management, ROI orientation, and continuous adaptation.

Product Discovery and Lean Roadmap

The product discovery phase merges user insights, market data, and technical constraints to rank features. Prioritization workshops (MoSCoW, Kano) guide decisions.

A Lean roadmap is built, segmented into short releases aligned with business strategy, avoiding exhaustive specification gathering.

This balance of long-term vision and quick iterations supports agility while ensuring overall project coherence.

Defining a Value-Driven MVP

The MVP concentrates development on features essential to validate key hypotheses: user acquisition, engagement, and retention.

This approach mitigates financial and technical risk by testing the product’s relevance early on a limited segment.

A retail chain launched its mobile app as an MVP in three months. It validated the basic ordering flow before investing in the advanced payment module, optimizing resources and limiting initial investment.

Agile Management and Lightweight Governance

The project is tracked via a single product backlog, fueled by prioritized user stories reviewed each sprint. Performance indicators (KPIs, OKRs) measure the real impact of new features.

Lightweight governance relies on short rituals (stand-up, sprint review, retrospective) and transparent communication between IT, business teams, and vendors. This replaces the multi-monthly committees of the classic specification approach.

Adjustments are made continuously, allowing course corrections at the first sign of deviation, without waiting for the end of a traditional specification phase.

Launch Your Digital Project by Unleashing Innovation

The specification document remains useful for aligning stakeholders on an initial vision, but its formality must not hinder creativity or responsiveness. By combining co-design workshops, rapid prototyping, and a value-focused MVP, you optimize development cycles, reduce risks, and engage your teams from the first deliverables.

Whether you’re steering a process transformation, launching a SaaS, a business tool, or creating a mobile app, our Edana experts will support you in adapting this agile, context-driven approach to your business challenges. They’ll help you harness collective intelligence and deploy a scalable, secure solution perfectly aligned with your strategy.

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PUBLISHED BY

Mariami Minadze

Mariami is an expert in digital strategy and project management. She audits the digital ecosystems of companies and organizations of all sizes and in all sectors, and orchestrates strategies and plans that generate value for our customers. Highlighting and piloting solutions tailored to your objectives for measurable results and maximum ROI is her specialty.

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Design System: The Backbone of Your Digital Products

Design System: The Backbone of Your Digital Products

Auteur n°15 – David

In a context where portals, applications and platforms are multiplying their features, visual and functional consistency becomes a major challenge for IT and business departments. A structured Design System is much more than a simple collection of graphical components: it establishes shared governance, promotes controlled evolution and secures the user experience across all digital products. Adopting this approach from the design phase ensures controlled scalability and greater responsiveness to business needs. This article details the fundamentals, implementation and strategic benefits of a product-oriented Design System, to transform this technical foundation into a performance lever.

The Design System, More Than Just a Component Library

The Design System is above all a digital governance framework that promotes consistency and reuse. It defines rules, principles and processes that ensure visual and functional unity across all products.

What Is a Design System?

The Design System brings together a set of UI components, styles (typography, color palette) and usage guidelines documented in a centralized manner. It serves as the single source of truth for all teams involved in creating and evolving digital interfaces.

This system also incorporates accessibility guidelines, responsive design and ergonomics, ensuring a consistent user journey regardless of the channel or device used. It helps limit graphical and functional deviations throughout development.

Its adoption accelerates time-to-market by avoiding redundant decision-making with each new feature. By standardizing patterns, it provides a trusted foundation for delivering reliable products quickly.

Components and Strategic Roles of the Design System

Beyond visual components, the Design System includes tokens (colors, spacing, typography) and systemic design principles that guide the creation of new modules. Each token is versioned to manage evolutions without breaking existing implementations.

It serves as a digital governance tool, centralizing decisions and best practices. UX/UI charters and technical guidelines are structured around a shared repository, ensuring smooth iterations between design and development.

With comprehensive documentation and validation processes, the Design System stabilizes the digital ecosystem. Responsibilities are clarified: a steering committee approves changes, while business teams focus on functional value.

Governance and Scalability

A sustainable Design System relies on agile governance. Roles are distributed among designers, developers and business stakeholders, each bringing their expertise to enrich the repository.

Updates follow a planned cycle: recommendations and component evolutions are reviewed and tested in isolated environments before production deployment. This rigor minimizes the risk of incompatibility.

The modularity of the Design System ensures controlled scalability. New projects can gradually integrate existing components and tokens while retaining the freedom to add business-specific features without compromising overall consistency.

Concrete Example of a Design System

A mid-sized Swiss banking institution consolidated its customer portal by creating an internal open source Design System. The team structured color tokens around the internal ESG charter, defined standard components for forms and introduced a CI/CD pipeline to publish each version. The result: a 40% reduction in graphic design time and a consistent experience despite the proliferation of modules (account management, credit simulation, customer support).

The Design System: a Lever for Consistency and Scalability in Digital Ecosystems

Implementing a Design System ensures a uniform experience across all digital touchpoints. It provides a modular architecture capable of scaling without adding complexity.

Ensuring Cross-Product Consistency

In a multi-product context, visual and functional consistency builds user trust and simplifies onboarding. Navigation, form and notification patterns are standardized, reducing cognitive load.

Each team accesses a centralized library, avoiding duplication and reducing the risk of inconsistencies. Charter updates propagate automatically via versioning and delivery automation.

This also simplifies onboarding new team members: the single repository serves as the reference documentation for understanding the UI ecosystem and its usage rules, accelerating their learning curve.

Technical and Organizational Scalability

Design System components are packaged as reusable modules within a package manager (npm, NuGet, Maven). Each module contains associated styles, scripts and tests, ensuring effortless integration.

Updates are managed through an explicit dependency mechanism: projects consume only validated and secure versions, avoiding unexpected fluctuations. Continuous integration runs regression tests on each component.

On the organizational side, governance is tailored to needs: a multidisciplinary committee oversees evolutions, while product squads can propose new patterns validated by the central repository.

Guided Evolutions and Secure by Design

An internal open source approach promotes transparency of contributions and traceability of changes. Pull requests undergo cross-review, involving designers, engineers and security architects.

Guidelines include security rules (focus management, constraints on third-party dependencies, WCAG accessibility) to ensure optimal coverage from the design phase.

Modularity facilitates the removal or rapid update of any component in case of a detected vulnerability, minimizing the impact on the overall ecosystem.

Concrete Example of a Design System Delivering Consistency

An industrial manufacturer in the Lake Geneva region consolidated three intranet solutions into a single portal. The Design System enabled merging UI libraries, streamlining components and deploying a common framework based on React and Storybook. The industrialization of updates reduced security patch integration time by 60% and ensured visual consistency between production monitoring, maintenance and reporting modules.

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Facilitating Cross-Functional Collaboration and Optimizing Productivity

A structured Design System serves as a common language between UX/UI designers, developers, Product Owners and business teams. This shared foundation streamlines communication and accelerates feature delivery.

Aligning Teams Around the Product

The Design System serves as a reference for defining user stories and acceptance tests, as well as designing the user story map. Each new feature relies on proven components, reducing areas of uncertainty.

Co-design workshops use the repository as a starting point, enabling rapid prototyping and validation of choices before development.

The backlog now includes tickets dedicated to enriching or revising the Design System, ensuring continuous governance and ongoing improvement of the common foundation.

Reducing Back-and-Forth and Ambiguity with a Clear, Reliable Design System

With a dynamic, interactive style guide, developers access specifications (dimensions, behaviors, states) directly without repeated exchanges with designers.

Brief changes are tracked in the documentation, ensuring transparency on the history of decisions and avoiding misunderstandings.

Design System versioning and release note management provide clear visibility on new features and fixes.

Accelerated Onboarding and Skill Development

By standardizing the component repository, every newcomer immediately finds all patterns and best practices. A dedicated starter guide illustrates the most common usage scenarios.

Internal workshops and pair designing sessions rely on the Storybook environment, where use cases are showcased. Technical and UX skills spread quickly.

This rapid adoption increases team productivity and reduces dependence on experts, freeing up time for functional innovation.

Concrete Example of a Design System Improving Internal Collaboration

An e-commerce platform for a Swiss retailer integrated a Design System from the redesign phase. Sprints systematically included component refresh and documentation tasks. Collaboration via the Storybook environment reduced UI-related QA feedback by 50% and enabled continuous deployment with fewer visual incidents in production.

Cost Reduction and Sustainable Adoption Thanks to a Solid Product Vision

Applying the Design System with a product mindset ensures sustainable governance and long-term ROI. Evolutionary maintenance becomes predictable and economically controlled.

Maintenance Cost Control

Centralizing components reduces the number of ad hoc developments and undocumented extensions. Bug fixes and updates propagate automatically to all projects consuming the repository.

Systematic reuse minimizes resources devoted to creating new modules, and partial refactoring efforts are limited to token adjustments rather than complete rewrites.

IT budgets stabilize, operating costs become more predictable and teams can anticipate evolutions without surprises.

Onboarding and Continuous Training

A starter kit guides Product Owners and project managers in integrating the Design System into any new build. CI/CD workflows include automatic validations for guideline compliance.

Targeted training and living documentation promote a gradual skill upgrade for teams, limiting external needs and ensuring repository sustainability.

Each iteration includes a Design System review phase, ensuring alignment with business objectives and product portfolio evolution.

Implementation with a Product Vision

Instead of treating the Design System as a mere project deliverable, it becomes a product in its own right, driven by a dedicated roadmap. KPIs (reuse rate, development time, compliance rate) are tracked to measure generated value.

Product ownership is entrusted to a cross-functional group responsible for prioritizing evolutions, organizing user tests, and validating component performance in real-world conditions.

The product approach ensures continuous improvement, increased maturity and adaptation of the Design System to emerging challenges (internationalization, theming, enhanced accessibility).

Concrete Example

A Swiss insurance group launched a product vision dedicated to its Design System. A Product Manager was appointed, with an annual budget allocated to component innovation. Each quarter, IT and design teams publish releases, document evolutions and measure the impact on time-to-production. Maintenance costs decreased by 30% in one year, while internal satisfaction rates exceeded 85%.

Make the Design System a Pillar of Your Digital Transformation

The Design System proves to be a strategic lever for consistency, scalability and productivity across any digital ecosystem. It ensures shared governance, significantly reduces maintenance costs and accelerates the integration of new features. By adopting a product approach, this evolving repository becomes a genuine long-term business asset.

Whether it’s an internal portal, a customer platform or a network of applications, its structured implementation secures future evolutions while freeing up time for innovation.

At Edana, our experts support organizations in the design, governance and deployment of powerful Design Systems tailored to each business context. Get in touch with them now to discuss your objectives and needs and co-create adapted, sustainable solutions.

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PUBLISHED BY

David Mendes

Avatar de David Mendes

David is a Senior UX/UI Designer. He crafts user-centered journeys and interfaces for your business software, SaaS products, mobile applications, websites, and digital ecosystems. Leveraging user research and rapid prototyping expertise, he ensures a cohesive, engaging experience across every touchpoint.