Rewriting Digital Commerce: From Presence to Real Maturity in Industrial B2B

Yet behind the numbers, there’s a different reality. High online share does not necessarily mean digital maturity. Customers still struggle with friction across channels, internal organisations wrestle with data and change, and the real potential of AI and automation remains largely untapped. The next phase of industrial digital commerce will not be defined by more technology, but by how effectively organisations align that technology with customer expectations, internal capabilities, and commercial strategy.

The panel discussion between Simon Tholstrup, Dr. Heiko Dirlenbach, Philipp Höfner, Mike Hayers, and Lisa Hellqvist at E-Connect Europe Business Platform 2026 – Power of 50 highlighted this pivot point. Their consensus is that industrial companies are no longer trying to catch up to B2C. They are dealing with an entirely different game defined by complexity, configuration, relationships, and long-term value.

The difference now is that the questions have changed. It is no longer “How do we go online?” but “How do we turn digital into real, continuous growth without alienating customers or overwhelming our own organisation?”

From Digital Presence to Digital Maturity

Many manufacturers still equate being digital with having a transactional website, an online catalogue, or a customer portal. Yet, digital presence means visibility, while digital maturity is the ability to serve complex customer needs effectively and profitably across channels.

Several stages of evolution can be observed:

• Basic presence: corporate website and PDF catalogues;
• Product availability: searchable online catalogues and documentation;
• Transactional capability: ability to place orders online;
• Portal thinking: customer-specific access, pricing, and account views;
• Towards agentic experiences: more intelligent, context-aware digital interactions.

The key is understanding that maturity is not measured by the existence of tools, but by the quality of outcomes. Digital maturity means:

• Customers can find, configure, and purchase what they need without unnecessary friction.
• Internal teams can rely on data and systems that are integrated, up-to-date, and usable.
• The organisation can adapt commercially and culturally to new buying behaviour without fragmenting.

Manufacturers that have already moved the majority of their revenue online show that complexity can be digitised. Highly engineered, configurable products no longer require an engineer on the phone for every order. However, this maturity was achieved by systematically aligning user experience, data, and commercial models with how customers buy.

The Hidden Friction in Frictionless Journeys

Frictionless experience has become a standard in B2B commerce. The reality inside many manufacturing organisations is more nuanced. Friction has simply moved from initial access to specific moments that matter most for customer trust and internal efficiency.

• Checkout and order confirmation

Even with strong online adoption, many organisations still encounter friction when orders are finalised. Rigid backend processes, legacy ERP logic, and inflexible workflows create delays and manual work. Customers experience this as unclear confirmations, slow responses, or last-minute clarifications.

• System performance and perceived speed

Advanced configurators now allow customers to build highly complex solutions digitally, replacing what previously required dedicated engineering offices. Technically, these tools can be transformative. However, when performance lags because of deep integrations with backend systems, perceived slowness undermines the perceived value.

If customers understand what the system is doing for them, for example, eliminating hours or days of engineering work, they are more willing to tolerate short processing delays. The challenge is not only technical optimisation, but also communicating the value of what happens behind the click.

• Omnichannel consistency

Many industrial companies now operate multiple digital entry points, such as e-commerce portals, partner platforms, marketplaces, and configurator-based tools. Without a coherent omnichannel approach, customers encounter disjointed experiences:

• Different account handling and onboarding flows;
• Fragmented data on orders, preferences, or authorisations;
• Inconsistent visibility across channels for both customers and sales teams.

Resolving this requires more than technical integration. It demands a clear design for how customers should move between touchpoints, how data flows, and how different internal teams share ownership of the experience.

• The AI friction no one talks about: LLM-driven traffic

A newer form of friction is emerging outside traditional websites. A growing share of traffic to industrial brands comes from large language models (LLMs) such as ChatGPT. Most industrial organisations are still optimised for search engines, not for AI-driven interfaces that synthesise and recommend products.

If product and content data is not structured, exposed, and maintained in a way that LLMs can interpret and trust, companies risk becoming invisible in the new discovery layer. This is already changing how potential buyers search and shortlist vendors.

Data: From Overload to Actionable Insight

Every manufacturer now recognises data as a strategic asset, yet many are paralysed by its volume and complexity. The core challenge is no longer collecting data, but transforming it into insight and action without overwhelming either the organisation or the customer.

Internally, three success factors stand out:

• Audience-specific views

Not every stakeholder needs or can handle the same level of detail. Effective data strategies now differentiate between strategic metrics for top management, indicators for middle management, and operational KPIs for frontline teams. By tailoring data to its audience, organisations avoid dashboard fatigue and encourage action rather than passive reporting.

• Focus on actionable insight

The most effective approaches do not flood teams with everything that can be measured. Instead, they surface the next best action, such as identifying which customers should be guided toward self-service, which products drive the most support requests and need improved content, and where in the checkout process orders are most likely to be abandoned or require manual handling. Customer data platforms and unified profiles can support this, but the real value comes from designing for decisions, not for maximum data visibility.

• Accepting that unused data is wasted effort

When information overload occurs, people naturally start ignoring what feels irrelevant. If certain data is never used, why is it being collected, processed, and maintained at all? Clarifying the purpose of each dataset, who will use it, for what decision, and how often, helps reduce noise and focus investments where they create business value.

AI in Industrial Commerce: Beyond the Hype

AI is moving from novelty to necessity in industrial B2B, but its most meaningful impact today is pragmatic rather than futuristic. The industry is experimenting actively, yet the pattern of AI that augments existing workflows is gaining traction faster than AI that attempts to fully replace human roles.

AI for discoverability is becoming critical as large language models like ChatGPT increasingly serve as entry points for product research. Industrial companies now need to ensure that product descriptions, specifications, and documentation are structured in a way AI systems can interpret, that reviews and references are accessible and trustworthy, and that their brand appears when engineers query for “the best solution for X in Y industry.” Manufacturers that have not yet tested how their products surface in such tools are already at a disadvantage, as understanding how AI sees their data is becoming as important as traditional SEO.

AI for support and knowledge access is proving highly effective in streamlining both customer and internal workflows. It can transform large technical communities and forums into responsive, searchable knowledge layers, suggest relevant documentation or troubleshooting steps based on problem descriptions, and support sales and service teams by consolidating information from multiple systems into concise, role-specific insights. Rather than replacing expertise, AI accelerates access to it, improving responsiveness and efficiency.

AI for configuration and solution design represents the next frontier. In theory, AI systems can interpret a problem or application scenario and generate suitable configurations across complex product portfolios. In practice, however, results are still evolving. Early trials show promise but also variability. For manufacturers dealing with safety-critical or highly engineered solutions, this requires a cautious and controlled approach, though over time AI is likely to become a powerful companion in guiding both customers and sales teams through complex configuration processes.

The Real Work: Organisational Alignment and Change Management

If technology is 20% of the effort, the remaining 80% sits squarely in organisational and cultural change. Digital initiatives in industrial B2B repeatedly hit the same barriers.

Misaligned strategies between sales and IT often prevent even the best tools from delivering value. As sales teams worry about channel conflict or e-commerce cannibalisation, IT departments become overwhelmed by a surge of unfiltered digital and AI initiatives, and digital teams push for speed while governance processes slow things down. Without a shared, customer-centric commercial vision, digital channels remain disconnected add-ons rather than growth drivers.

Change fatigue and partial adoption mean that, despite new tools being introduced, usage typically remains limited to a small group of enthusiasts while the broader organisation engages only sporadically. Lasting impact requires clearly demonstrating role-specific value (such as reducing preparation time for sales), embedding new behaviours directly into everyday workflows instead of adding extra systems, and ensuring visible, ongoing sponsorship from top management.

Balancing automation with human relationships is essential in industrial B2B, where customers still value personal interaction for complex decisions. Rather than forcing digital-only engagement, leading companies segment their approach, automating routine, transactional tasks while preserving human touchpoints for high-value activities like solution design and negotiation, and in some cases reflecting this distinction through pricing, so that digital tools enhance relationship-driven sales.

Signals That Digital Strategies Are Truly Working

As more revenue moves online, industrial leaders need reliable signals that their digital strategies are driving long-term growth instead of simply shifting orders between channels.

• Self-service that genuinely replaces manual work

Success is not counted only in online order share, but in the reduction of internal effort per transaction. If customers can configure, select, and order without back-and-forth clarifications, and if those orders flow straight through without manual intervention, digital is delivering its promise.

• Customer and sales feedback, not just KPIs

Qualitative feedback remains a powerful indicator. When customers and sales teams start describing digital tools as “really helpful” rather than “mandatory” or “confusing,” digital has moved from obligation to value creation.

• Online channels enabling conservative cultures to shift

In organisations with conservative customers or long-tenured salesforces, a notable signal of progress is the softening of resistance. When previously sceptical sales professionals start viewing digital channels as support rather than competition, digital maturity has crossed a cultural threshold.

• Incremental, evidence-based scaling

A recurring recommendation is to pursue “pilots, not programs.” Instead of rolling out grand, multi-year schemes at scale, leading organisations:

• Identify receptive customer segments or regions;
• Test specific digital capabilities (e.g., a new AI tool, a new buying journey);
• Measure impact in terms of revenue, cost to serve, and satisfaction;
• Use proven results to secure further investment and internal buy-in.

This disciplined, iterative approach protects core business while building a robust case for scaling.

Looking Ahead: Where the Next Advantage Will Be Won

Over the next two to five years, industrial digital commerce will be shaped less by whether manufacturers are online, as most already are, and more by how they orchestrate three interconnected capabilities:

• Omnichannel without friction: The ability to deliver consistent experiences and data across all touchpoints will become a baseline expectation. Customers will not differentiate between online and offline, and will expect to pick up seamlessly where they left off, regardless of channel.
• AI-integrated customer journeys: From discovery via LLMs to problem diagnosis, product selection, and support, AI will increasingly sit between industrial companies and their customers. Those who intentionally shape how their products and content interact with AI systems will be discovered more often and trusted more readily.
• Stronger commercial clarity around digital investment: As digital becomes a primary route-to-market rather than an experiment, industrial leaders will need clearer views of total cost of ownership, incremental value, and return on digital initiatives. This includes not only platform and integration costs, but also the substantial investment in change management, skills, and process redesign.

The defining competitive advantage will lie with those who can navigate this complexity while maintaining what has always differentiated industrial leaders: deep application expertise, long-term relationships, and the ability to solve real operational problems for customers.