XBOOST: Integrated Journeys, Data Platforms and Agentic AI Are Becoming Key Competitive Factors

B2B buying behaviour clearly shifts towards self-service – but relevance is the real differentiator

Data shows that the XBOOST topics are not “nice to have”, but reflect real market pressure.

B2B buying behaviour is becoming more digital – but also more selective

Customers expect self-service, but also maximum relevance. Irrelevant communication is systematically ignored.

• 61% of B2B buyers prefer a fully “rep-free” buying experience (digital research, self-service instead of classical salesperson interaction).
• 73% avoid vendors who send irrelevant outreach communications.

Omnichannel is the norm – integration remains the challenge

Customers naturally move across multiple channels. Breaks in the journey occur not in the front-end, but in the systems and processes behind it.

• 69% encounter inconsistencies between website information and what sales teams communicate.

AI is established – differentiation comes from execution

Most companies already use AI. Competitive advantage does not come from technology itself, but from data quality, governance and concrete use cases.

• 88% of companies use AI in at least one function, but most gain limited value because they fail to embed it into processes.
• Only about one third truly scale AI across the organisation.

Sources:

Gartner 2025, McKinsey 2024, McKinsey 2025 

Four Key Insights from XBOOST

1. Integrating Commerce and Sales: From Channel Thinking to End-to-End Process Chains

A web shop does not replace sales – but it fundamentally changes its role.

Instead of isolated touchpoints, companies need a continuous process logic:
Lead → Configuration → Quotation → Order → Service

In reality, customers do not move linearly through these steps. They jump between research, concrete purchase intentions and service topics – often simultaneously. Breaks occur exactly where systems and data are not connected.

An event example illustrated this with a typical B2B journey: from initial research via a trade fair contact, configuration in the web shop, coordination with sales, through to after-sales service. Without integrated data, these steps stay isolated and sales teams work without context.

The decisive lever is integration:

• Shared data foundation for customers, products and interactions
• Transparency on digital activities (e.g., configurations or pricing queries in the shop)
• Deriving concrete sales impulses (“Next Best Action”)

Usage-based scenarios make this especially clear: if machine or usage data shows that a component needs replacing, a tailored offer can be generated automatically – visible in the portal and to sales simultaneously.

The same applies to indirect sales: integrated dealer models allow manufacturers, dealers and end customers to work on one shared data foundation – with clear roles, but without information loss.

2. Data-driven Sales: Moving from Experience to Steerability

Many sales organisations have large volumes of data but make little effective use of it.

The real issue is not lack of data, but lack of steering logic.

As customer journeys grow more complex, experience-based sales reaches its limits. At the same time, teams spend a disproportionate amount of time on non-value-adding tasks.

The key shift is:
Stop producing more reports – start enabling decisions.

The XBOOST outlined a clear approach:

1. Define business objectives
2. Identify drivers
3. Derive KPIs
4. Define concrete actions

Example: Rather than merely measuring revenue, analyse which factors influence it, such as lead quality, deal size or closing speed – and derive corresponding actions.

Operationalisation happens via:

• Value maps instead of isolated metrics
• CRM playbooks that structure and standardise sales processes
• A staged evolution from reporting to active steering

In practice, this was seen in global sales cockpits based on harmonised data as a single source of truth, or in standardised quotation processes that significantly reduce processing time and increase win rates.

Typical barriers remain:

• Low team adoption
• Weak governance
• Too many reports without clear usage

Insight: Sales does not improve through more data, but through consistent use of data within processes.

3. Customer Portals as Central Platforms: The Path Out of Tool Fragmentation

Many companies have built digital touchpoints over years – often disconnected. For customers this means: multiple logins, inconsistent information, and media breaks.

The target picture is clear:
One portal as the central access point for all interactions.

This is not about replacing systems, but connecting them meaningfully.

A key approach discussed at XBOOST:
An Access Layer acting as an umbrella over systems like the shop, service cockpit or document management. Users have one login; specialist systems continue to work in the background.

Success factors include:

• Identity and Single Sign-On as foundations
• Integrating existing applications rather than rebuilding them
• Clear prioritisation of use cases based on business impact

A portal strategy is not a one-off project, but a continuous evolution driven by user needs and business goals.

4. Agentic AI in Action: From Assistance Systems to Active Process Steering

Agentic AI was a central topic of the event – marking the next stage beyond classical AI.

The difference:
Not just providing information, but actively supporting processes and preparing decisions.

Examples shared at XBOOST:

• In complex product environments, AI supports quotation configuration using historic knowledge and rule sets.
• Tenders and documents are automatically analysed and transformed into draft proposals – significantly reducing manual effort.
• In commerce, “Smart Shopping Assistants” guide customers through the buying process and build suitable bundles.
• In service, high ticket volumes can be handled more efficiently through automatic classification, prioritisation and partial automation.

The key success factor:
Agentic AI must be understood as an architectural approach, not as isolated use cases.

A layered model is required:

• Source systems
• Integration/data layer
• Agent layer
• Application layer

Data from SAP and non-SAP sources is made “AI-ready”, agents access this data as modular building blocks, and are integrated into CRM, portals or shops.

This enables technology to be added or replaced (new model, additional agent, different data platform) without rebuilding the foundation.

Sustainable scaling follows a clear order:
Stabilise data and process foundations → add agents → orchestrate agents.

XBOOST Format: From Orientation to Concrete Implementation

The XBOOST was deliberately not a classical conference. Instead of tool demos or abstract strategies, the core question was:

How can concrete business problems be solved today?

Participants gained:

• Robust classification of current trends
• Practical real-world examples
• Actionable operating models
• Peer-level exchange

Particularly valuable were authentic insights from companies like Goldhofer and Krombacher, who openly shared their transformation journeys.

Conclusion: What Decision-Makers Should Now Take Away

XBOOST Sales & eCommerce 2026 highlighted one overarching message:
Challenges in Sales, Commerce and Service can no longer be solved in isolation.

The decisive capability is to connect processes, data and systems in a way that creates a consistent, steerable and scalable customer journey.

Companies that continue treating sales and commerce processes separately risk creating exactly the breaks customers no longer tolerate. Simply adding tools or collecting more data will not help. The real value comes from translating data into decision logic and embedding it into operations.

For AI, the same holds true: Agentic AI only unfolds its value as part of a coherent architecture with clean data foundations and governance.

Customer portals as access layers play a central, connecting role. They enable consistent information availability and ensure interactions do not fail at system boundaries.

Decision-makers should focus on integrated end-to-end approaches.
Those who can build end-to-end processes, link data meaningfully and integrate AI into operational workflows will not only increase efficiency, but – above all – strengthen their market relevance.