B2B Sales This is how generative AI prepares the customer journey for the future

Related Vendor

Wuxi InfiMotion Technology Co., Ltd.

The digital transformation and the use of generative AI models provide companies with an innovative solution to make sales processes future-proof. However, implementing this vision requires overcoming various complexity drivers.

Fabian Tönnesmann is a partner and Managing Director at Eraneos Germany.

Nikolai Roll works as a Senior Manager at Eraneos Germany.

Our digital world is changing expectations of selection and ordering processes: Today, 94 percent of B2B buyers prefer to purchase goods and services online. 68 percent expect a customer experience tailored to them through personalised processes. 64 percent of B2B executives would switch providers to receive personalised real-time pricing. And 73 percent of tech-savvy millennials are involved in the purchase. This presents promising opportunities along the sales process, but also business-critical challenges. Manufacturing companies in Germany are technologically not yet able to meet these challenges in many areas. However, more and more manufacturers are recognising the urgency of modernising and actively managing their customer journey. Only in this way can they create contemporary customer experiences and remain competitive. Our vision is a new approach to the customer journey: generative AI models help to realise a conversational commerce platform and thus future-proof the sales processes.

The problem: unclear structures and complex products

Manufacturing companies are currently subject to a very high level of complexity. Complicated structures meet unclear, silo-like operational models and outdated technological foundations. At the same time, many business areas are still not able to function without manual processes. In this confusing environment, companies have to sell demanding and explanation-needing products and services. For this to succeed, it is important to design the customer journey seamlessly. In a goal-oriented control of the process, the manufacturer comes into contact with the customer at every stage. Companies that digitalise interaction for this purpose must meet high demands. Yet, the tasks quickly exceed the available capacities and competencies.

Five complexity drivers in the digital sales process

The following complexity drivers often stand in the way of implementing an orchestrated digital sales process:

• Different customer roles - such as users, development engineers, or procurement staff - need to be balanced and addressed. This creates a new quality of customer complexity.

• The customer journey runs along internal structures, so that different touchpoints and changing responsibilities affect the customer experience.

• The various sales structures from direct sales to distributors require high flexibility in orchestration.

• Digital processes and digital channels - such as product lifecycle management or a complete customer view - only function based on professionally organized data. However, product and customer information is often scattered across departments and incomplete.

• Many companies rely on inflexible and non-scalable legacy systems, such as older CRM versions. Market-wide solutions are rare. Lack of system integration and data migration ultimately hamper effective cooperation and data-driven decision-making.

Generative AI creates conversational commerce.

A possible answer to the challenges described is Conversational Commerce, or C-Commerce for short. Here, sales take place via automated interaction in real time with the customer - realised with technical tools like digital voice assistants or chatbots. We have developed a visionary approach for a successful customer journey in C-Commerce including Configure Price Quote (short: CPQ) and aftersales on revenue-oriented websites. Generative Artificial Intelligence acts here as a kind of hyperpersonalisation machine to create personalised buying experiences for users. The AI models learn the patterns and structures of the entered training data like texts, images or other media and develop new data based on this - for example, personalised information for users of a website that is generated and played out in real time.

Let's imagine the fictitious company Ineq, which sells complex production plants for various industries. Ineq lacks the human resources to manually create and maintain current personalised content, such as product advantages for every conceivable target group, on its own website and in other digital channels on a large scale. Our approach consists of the following modules for a future-proof C-Commerce platform using generative AI.

Dialogue-based technology: Dialogue-oriented entry points offer user-centered content. This creates a personalized shopping experience. Based on continuous communication with the potential buyer, the AI provides personalized landing pages for the offers. The data is interpreted in real time. This allows the products to be configured automatically and personalized based on the respective specific customer requirements.

Service Integration: At check-out, the customer automatically receives offers for personalized product-specific services. Unified user movements on the website through active control allow uncomplicated upselling of service offers during the customer journey.

Simplified purchasing process: Users who make contact are directed straight to the purchasing department. This way, they find a competent contact person without detours and time loss, and the company saves personnel resources. At the same time, the risk of losing potential buyers on the way to the responsible contact person is reduced.

On-Device: Our vision is based on an agnostic approach to the end devices. This means in practice: The customer orders spare parts via the user interfaces of their machines. A production employee receives, for example, information directly from the machine he is operating, such as when a part is worn out. He can also immediately initiate the purchase, without having to first request it from the procurement department. The ongoing process is instead automatically forwarded to other devices, such as the tablet of the responsible procurement employee.

The implementation is carried out via a headless commerce platform. Since the backend and frontend are separated, multiple frontends are possible without affecting the backend infrastructure. The created on-device access allows seamless communication with the customer's staff. The interaction takes place directly at the machine and is enriched by generative AI with individual data from previous communication. This way, the user can make data-based and therefore informed decisions when ordering.

The result: Lower costs, more sales, satisfied customers.

If the fictitious company Ineq implements all the recommended measures, the following effects can be expected: The multifunctional personalized support strengthens trust in the brand and reduces customer inquiries. The fully automated and generative offer system increases the users' willingness to buy, thus boosting sales. The generative AI streamlines processes, improves data-driven purchase decisions, and creates additional customer benefits. This saves time for both customers and Ineq's employees, customer satisfaction and loyalty grow, and sales increase. Hybrid sales enable 50 percent more revenue because customers are more involved and a broader employee pool is used than in traditional sales.

The good news: the prerequisites are in place.

The scenario described is not a vision of the future, but is already within reach today: everything manufacturers need to implement our vision for INEQ in their operation is either close to market readiness or even already in use. Meanwhile, the competition is not sleeping and is creating the technological prerequisites, as figures from 2022 show: for example, 26 percent of manufacturers were already using a headless commerce solution. 50 percent of companies that were able to increase their market share by more than ten percent had previously introduced new sales technologies. And customers are already prepared for the technological change: 88 percent have had a first experience with a chatbot. Up to 80 percent prefer digital and self-service sales contact. Now it's a matter of gradually preparing the technical infrastructure and internal processes for a future-proof C-Commerce platform using generative AI.

Creating the foundations for the future in five steps.

Manufacturers should prepare for the changes in the sales environment now. Small steps towards the future are preferable to large and complex change projects. The recommended measures are already providing immediate added value for the manufacturers today.

Prepare content: The task is to create transparency about the content available and to structure the processes for creating new content with clear responsibilities. This ensures the company's ability to create digital content on a large scale.

Additional benefit: Efficiency and effectiveness of digital marketing improve significantly.

Expand digital sales: Digital sales channels should be introduced and developed based on headless platforms to build critical infrastructures and competencies.

Additional benefit: Manufacturers integrate digital sales, thus strengthening their positioning in the competition.

Digitalize service and workflows: Processes in the value chain can already be digitalized and automated today, for example in research and development, production, and service.

Additional benefit: Workflows become more efficient and transparency is increased.

Automate price setting: The workflows behind pricing and offers should be analyzed and optimized with the goal of automating and personalizing prices.

Additional benefit: Pricing becomes more competitive and fact-based, with optimized margins.

Implementing data management: A holistic data strategy with clear responsibilities, workflows, control mechanisms and transparency should actually already be implemented in every company.

Additional benefit: Data-driven use cases can be quickly developed and executed, and data exchange is facilitated.