With millions of passengers relying on its services every week, SBB (Swiss Federal Railways) knows that exceptional customer experiences start with deep customer understanding. As part of its 2026 customer-centricity program, SBB is introducing AI-powered personas that help leaders explore different customer perspectives earlier in the decision process, bringing the voice of the passenger into everyday decision-making across the organization.
It’s doing so by combining trusted, accessible research with AI personas that help leaders and teams challenge assumptions, practice active listening, and consider a wider range of passenger needs.
The success story, shared by SBB and Market Logic
In February 2026, Dr. Alexandra Daniela Zaugg, Senior Customer Insights Manager at Swiss Federal Railways (SBB CFF FFS), joined Market Logic’s Joseph Rini and Michael Vincent for the webinar “Inside Swiss Federal Railways’ 2026 Customer-Centricity Journey: The Rise of AI Personas.” The session traced SBB’s journey from a practical knowledge-management challenge to a broader ambition: making customer centricity something people can practice in daily work.
The story continued at Market Logic’s Zurich Innovation Roundtable in March 2026. Dr. Eva Krueger, Co-Head Customer Centricity & Analytics at SBB, described how easier access to research and new persona-based perspectives are supporting a wider operating model built around customer pain points, early exploration, and human-led decision-making.
Case study: At a glance
| Company | Swiss Federal Railways (SBB CFF FFS) |
|---|---|
| The challenge | Trusted customer research existed, but it could take days to locate and interpret. At the same time, employees’ own familiarity with rail travel could make it difficult to see experiences beyond their personal perspective. |
| The solution | Market Logic DeepSights: multilingual, source-linked access to a curated research base, complemented by DeepSights Personas that make different passenger and stakeholder perspectives easier to explore. |
| Use cases | Self-service insight discovery; reuse of existing studies; leadership development; perspective-taking and active listening; early ideation; customer-pain-point exploration. |
| Approach | A focused, governed rollout with curated content, role-relevant access, a clear distinction between exploration and evidence, and customer centricity reinforced from both the top down and bottom up. |
| Program context | SBB made 2026 its Year of Customer Centricity, introducing DeepSights at its annual leadership conference and incorporating persona conversations into leadership discussions. |
| Industry / region | Public transport, Switzerland |
| Products | DeepSights Explore, DeepSights Personas |
| Early signals | Research that previously took days to locate is now retrieved through natural-language questions with source-linked answers. Checking existing evidence has become the first step in new research planning. Personas are being introduced through leadership development, with pilot participants reporting that the conversations surfaced different perspectives and challenged preconceptions. SBB is candid that broader behavior change takes time. |
The challenge: Customer insight was valuable, but not always available when decisions were made
Swiss Federal Railways is a central part of Switzerland’s public transport system, serving people with very different reasons for traveling, levels of familiarity, mobility needs, language preferences, and expectations. Customer understanding is therefore not a single viewpoint. It must account for commuters and leisure travelers, international visitors, younger people traveling independently, passengers with reduced mobility, infrequent public-transport users, and businesses operating in and around stations.
SBB had accumulated a substantial body of customer research. Yet finding the right evidence could be difficult even for the customer insights team. A request could trigger a search through SharePoint, follow-up questions to colleagues, and a handover of multiple files for the requester to interpret. The process could take several days to a week, and the quality of the answer depended partly on who happened to receive the question. Valuable knowledge could also leave with experienced colleagues.
There was a second, more cultural challenge. Many SBB employees use the railway themselves and care deeply about the passenger experience. But personal familiarity can create a blind spot: one person’s regular journey does not represent the needs of every customer. Engineering and operational excellence remain essential, but customer centricity also requires teams to step outside their own experience, listen actively, and consider how a decision affects people whose journeys may look very different.
The core question
How could Swiss Federal Railways make trusted customer knowledge available at the moment of decision – and help leaders and teams bring perspectives beyond their own into the room – without confusing early exploration with research evidence?
The foundation: DeepSights turns trusted research into accessible multi-language answers
Swiss Federal Railways began with a focused knowledge-management use case. Its requirements were clear: employees needed to ask questions in natural language, across German, French, and Italian; customer insights teams needed a low-maintenance way to add research without extensive manual metadata; and every answer needed transparent links back to controlled, high-quality sources.
DeepSights gave SBB a curated, AI-powered research environment that synthesizes findings into ready-to-use answers rather than returning only a list of files. Selected team members control what enters the knowledge base, and users can trace answers back to the underlying evidence. The model is software as a service, reducing the internal development and maintenance burden after security and data-protection requirements are met.
Swiss Federal Railways deliberately chose focus over volume. Rather than uploading every historical asset or giving every employee the same access, it prioritized relevant, good-quality studies and the colleagues who use customer insights in their work. Most of the selected research dates from 2015 onward, with a small number of older studies retained where they remain useful.
This focus shaped a practical new habit: before commissioning new research, teams first check what SBB already knows. Existing findings can answer the question, narrow the scope of a new study, or reveal where fresh evidence is genuinely needed. That helps Swiss Federal Railways reuse past investment while making insights available much closer to the decision.
If there is that deciding meeting and we don’t know about the insight, that’s a problem. Now it’s really easy to access the insights with AI.”
Dr. Eva Krueger, Co-Head Customer Centricity & Analytics, SBB CFF FFS
Market Logic Zurich Innovation Roundtable, March 2026
Market Logic Zurich Innovation Roundtable, March 2026
The next step: DeepSights Personas make different customer perspectives tangible
Once trusted research was easier to access, Swiss Federal Railways began using synthetic personas — in the form of purpose-built DeepSights Personas — to support another part of the customer-centricity journey: helping people experience perspectives beyond their own.
SBB started working with personas in December 2025 and created a set of ten ad hoc, or scenario-based, AI personas covering a broad range of passenger and stakeholder needs. They are not derived from a statistically representative customer segmentation.
The set of synthetic personas includes, for example, an international visitor unfamiliar with Switzerland’s transport system and local languages; a price-sensitive young adult; a passenger with reduced mobility who needs a predictable and accessible journey; a 12-year-old beginning to travel independently; an infrequent public-transport user; a sustainability-focused traveler; and a station retail or hospitality partner. The purpose is not to reduce people to labels. It is to make different needs specific enough that teams can discuss them, ask better questions, and see where a one-size-fits-all assumption breaks down.
Swiss Federal Railways is transparent about how these synthetic personas should be used. The initial ad hoc personas were shaped through the expertise of customer insights managers and existing knowledge, rather than a dedicated quantitative and qualitative segmentation program. They are therefore most appropriate for culture, empathy, perspective-taking, and early exploration – not final validation.
At the Zurich roundtable hosted by Market Logic Software, SBB also described a complementary direction: bringing established customer segments to life as research-based personas while continuing to use additional scenario personas to make less familiar experiences visible. The distinction matters because the data foundation should determine the level of confidence and the business decision a persona can support.
Use the right synthetic persona for the right question
Swiss Federal Railways’ framework separates three broad uses:
- Research-light exploration: When both the synthetic persona and its answers are grounded in customer research, teams can use the output as an early signal for visuals, messaging, or ideas – while still validating important decisions with real customers.
- Innovation and creation: Research-based AI personas with more generative answers can help teams explore concepts, compare reactions, and open new directions. The output is a conversation starter, not a forecast.
- Culture and empathy: Ad hoc synthetic personas with synthetically generated answers help employees practice active listening, challenge their own assumptions, and consider a wider range of needs. This is SBB’s primary current use in the customer-centricity program.
It’s a first step, but it doesn’t replace insights.”
Dr. Alexandra Daniela Zaugg, Senior Customer Insights Manager, SBB CFF FFS
On the role of SBB’s ad hoc personas, February 2026 webinar
Use case 1: Bringing the customer perspective into leadership development
Swiss Federal Railways designated 2026 as its “Year of Customer Centricity” and launched the theme at its annual leadership conference, attended by approximately 1,500 line and specialist managers. DeepSights Research and DeepSights Personas were among the initiatives demonstrated at an exhibition booth, giving participants a direct way to explore customer evidence and experience the conversational persona format.
SBB treated the conference as a strong signal from senior leadership, but not as a complete behavior-change program. The next layer was a series of leadership discussions designed to turn the theme into practice. SBB planned up to 20 sessions of roughly 20 participants, each lasting about three hours.
Before a session, participants speak with different DeepSights Personas about customer experiences. In the session, they compare what they heard, discuss how needs differ, practice active listening and relevant questioning, reflect on their own attitudes, and translate the learning into daily work. The goal is not to train leaders to accept persona output uncritically. It is to help them notice which customer is missing from a discussion and create room for teams to act on what they learn.
This makes the management focus on a multiplier strategy rather than an executive-only use case. Leaders can model customer-centered decision-making, create scope for action, and carry the approach into their teams, while colleagues who work directly with insights continue to access research and personas from the bottom up.
The personas give different answers, which is really important for our leaders to understand: there is not just one customer, and one size does not fit all.”
Dr. Alexandra Daniela Zaugg, Senior Customer Insights Manager, SBB CFF FFS
February 2026 webinar
Use case 2: Changing the conversation before solutions are fixed
Personas can also change the starting point of an innovation or service discussion. Instead of moving immediately into a debate about a feature and how to implement it, a team can ask how different people might experience the proposed change, what benefit it creates for each of them, and where new barriers could emerge.
In the webinar, Alexandra Zaugg reported that pilot participants found persona conversations helped them clarify questions, challenge pre-formed opinions, and examine a product or problem from several angles. The experience was intentionally low-risk: colleagues could practice asking questions, see how wording shaped the response, and learn before engaging real customers.
At the Zurich roundtable, Eva Krueger connected this approach to SBB’s broader innovation model. Swiss Federal Railways is bringing data together to identify customer pain points and, in an agile cycle, selects eight to ten customer problems every three months as starting points for improvement or innovation. Personas do not replace that evidence base, but they can bring additional perspectives into the early-stage conversation.
You can use personas as a catalyst for customer-centric thinking. It’s very easy. It’s very hands-on. It shifts the mindset.”
Dr. Alexandra Daniela Zaugg, Senior Customer Insights Manager, SBB CFF FFS
February 2026 webinar
A responsible approach: Helpful does not mean definitive
One of the strongest parts of the Swiss Federal Railways story is its explicit boundary between usefulness and proof. A fluent answer can feel convincing, especially when it is immediate and easy to understand. SBB therefore emphasizes data literacy, source transparency, and critical assessment.
DeepSights Research is grounded in a governed set of SBB research and provides source links so users can inspect the evidence. Synthetic persona conversations require a second judgment: users must understand whether they are speaking with a research-based segment or an ad hoc scenario persona, and what type of decision that foundation can reasonably support.
SBB’s position is practical. AI personas are useful for bringing perspectives into the room, shaping questions, testing an early direction, and preparing for deeper research. They are not a substitute for primary research when the decision carries significant customer, operational, financial, or reputational consequences.
With AI, thinking is never optional.”
Dr. Alexandra Daniela Zaugg, Senior Customer Insights Manager, SBB CFF FFS
February 2026 webinar
Early signals – without overstating the outcome
The knowledge-management value is already concrete: users within the organization can now access existing studies through natural-language questions, ask follow-ups, and receive synthesized, source-linked answers instead of waiting for a manual file search. With DeepSights implemented in their workflows, Swiss Federal Railways is also using the platform to make checking existing evidence the first step in new research planning.
The persona work is at an earlier stage. The leadership-discussion pilot team responded positively, reporting that the conversations surfaced different perspectives, clarified questions, and challenged preconceptions. By March 2026, SBB was introducing personas through leadership training, while acknowledging that broader adoption and measurable behavior change take time.
Swiss Federal Railways is also careful not to overclaim. Its customer-pain-point program tracks which problems are selected and solved, but when something improves, it is hard to say how much came from the tools and how much from the leadership discussions and ways of working around them. What the evidence supports today is faster access to research, richer conversations early in a project, and a change-management approach that is working — not a claim that AI alone has transformed customer outcomes.
What SBB learned about making customer-centricity practical
1. Start with a real friction point
Swiss Federal Railways did not begin with AI for its own sake. It began with a clear problem: valuable customer research was difficult to find, slow to retrieve, and inconsistently interpreted. Solving access created a credible foundation for the broader customer-centricity program.
2. Focus and governance build trust
SBB limited the initial scope, curated the research base, controlled who could upload content, and prioritized users who apply customer insights in their work. More content and more licenses were not treated as automatic measures of success.
3. Make customer centricity experiential
A presentation can explain why customer centricity matters. A synthetic persona conversation makes people practice it. Asking a question, hearing a different answer, and reflecting on that response turns an abstract principle into a hands-on experience.
4. Use leaders as multipliers — and combine top down with bottom up
The leadership conference created visibility and senior sponsorship. Leadership discussions were designed to build behavior, while direct access to insights and personas supports colleagues who need customer understanding in daily work. Both directions matter.
5. Match the evidence level to the use case
Research-based personas can support early, research-light exploration. Ad hoc personas are better suited to empathy, culture, and reframing. The foundation must be visible so users know how much confidence to place in the output.
6. Customer-centricity requires scope for action
Empathy is not enough if teams cannot respond. SBB links a human-centered mindset and active listening with the authority to search for solutions and improve the customer experience in daily decisions.
7. Keep people in the lead
DeepSights makes evidence and perspectives easier to access, but people still frame the question, assess the answer, decide when more research is required, and take responsibility for what changes.
Human-centered customer understanding by design
Swiss Federal Railways describes a customer-centric mindset through four connected elements: a human-centered perspective, active listening, empathy, and scope for action.
DeepSights supports each element in a different way:
- Explore provides evidence.
- Personas create space for perspective-taking and practice.
- Leadership discussions turn those inputs into reflection and team behavior
- Human judgment determines what happens next.
This is especially relevant in a complex transport organization. The goal is not to replace engineering discipline with intuition. It is to connect operational and technical decisions more consistently to the people who experience their consequences.
Swiss Federal Railways’ leadership principle
Each decision counts: everything SBB does should improve the customer experience, directly or indirectly.
Looking ahead: Embedding customer perspectives into everyday decisions
SBB’s journey is still evolving. The organization is continuing to introduce synthetic personas through leadership development, explore the relationship between research-based segment personas and additional scenario perspectives, and connect early customer understanding to its customer-pain-point innovation cycle.
The long-term opportunity is not simply faster search or more engaging AI. It is an environment in which trusted customer evidence is available when a decision is being made, and where teams routinely ask whose experience is represented, whose may be missing, and what they need to learn before moving forward.
By combining curated intelligence with practical perspective-taking, Swiss Federal Railways is turning its Year of Customer Centricity into more than a communications theme. It is building the habits, tools, and leadership conversations that make the customer perspective easier to bring into everyday work.
