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Data & AI in B2B Commerce – Recap Commerce Masters 2023

Written by diconium 24 Apr, 2024

The most important facts in 20 seconds

Before using AI, applications with the greatest impact on value creation must be identified, evaluated, and prioritized.
Data is the central key to AI success.
From content creation and product development to personalization, customer service and marketing: AI has a significant impact on the commerce value chain and the associated customer experience.
The right mindset and customer understanding, the necessary certainty of objectives and an incremental approach are considered by companies to be important success factors for their data and AI strategy.

Agenda

AI-supported data use is no longer just hype, but a real game changer that can successfully boost business with a dynamic flywheel effect. According to recent studies, the impact of AI is 10 times faster and 300 times more powerful than the first industrial revolution. And yet, many companies are still unsure whether AI serves a purpose and how it can be used profitably. With a lack of AI knowledge, many companies lack an AI strategy. At the diconium Commerce Masters 2023 in Stuttgart, we joined 40 decision-makers from various sectors of the German economy to shed light on what is important for such a strategy and what role data plays in the AI-driven transformation.

How companies are harnessing the full power of data and AI

In her inspiring keynote speech, Swantje Kowarsch (managing director at diconium data) discussed the things that companies should be aware of before using AI. It quickly became clear that now is the time for companies to proactively integrate AI into their business models. But before doing so, they should be clear about where the transformative power of AI comes from and in which areas it can create a competitive advantage. Whether for the automation of recurring processes, the prediction of trends and key business developments, or the improvement of the product and service offering: to generate decisive added value, AI must first be translated into specific use cases or fields of action, and the necessary resources and expertise must be created and integrated into the existing organizational culture.

One thing is clear: the successful application of AI can be an overwhelming task. The field is evolving almost exponentially, and it's hard to keep up with the growing algorithmic advances, use cases, initiatives, and startups. But even if organizations are only at the beginning of an AI journey, it's important to act now and create the right AI environment. Because only those who create the right conditions today will be able to harness the enormous potential of the AI revolution to fundamentally change their business models and drive sustainable economic growth.

In focus: Data and AI are revolutionizing commerce

In the "Data Strategy & Artificial Intelligence" workshop, Andreas Grund, Pascal Dagne, and Adnan Bicaj focused on a particularly exciting area that is being revolutionized by data and AI: commerce. In their introduction, they vividly demonstrated the great potential of (generative) artificial intelligence to exert a significant influence on the commerce value chain and the associated customer experience. From content creation and product development, personalization, and customer service to marketing, sales, CRM, or pricing: AI can completely rethink the value chain in commerce. This was also exemplified by practical examples from Coca-Cola with Create Real Magic for increased engagement through co-creation and from Carrefour with a smart chatbot for enhancing the customer experience. Further insights into the potential and development of AI-supported chatbots were provided by diconium's Dicobot. Projects like these are made possible by a scalable and customer-centric data platform.

After the comprehensive input on data strategies and AI, the participants continued in a total of three small groups. Each workshop group directly reflected on the processes and procedures relating to artificial intelligence using specific use cases to assess the impact on their company.

Wrap-up: Three key recommendations for successful data and AI strategies

In the final wrap-up, the participants summarized the most important findings and key takeaways from the group work. The following learned strategies were particularly important to them in creating a successful data and AI strategy:

Mindset: Data and AI innovations require the right mindset with the necessary amount of courage and openness to successfully tackle change with all the company's employees.
Customer Understanding: For tailored data strategies and AI solutions, it is important to know and understand the target group precisely to meet the requirements and needs of customers.
Target Alignment: Companies should regularly review their objectives for data strategies and AI to ensure that they are adapted to current developments and that the desired objectives remain relevant.
Step by Step: When introducing AI projects, it is advisable to proceed incrementally to minimize potential risks, continuously adapt to changing requirements and technologies and constantly improve the customer experience.

Want to get started with AI in commerce? We are happy to support you and your company! You can find more information about our services and consulting in the field of e-commerce here.