A Powerful Combination: AI and the SAP Commerce Cloud

In E-Commerce, effective AI technology deployment has the potential to deliver step improvements in customer experience (CX) while increasing sales revenues and reducing the cost of sales. While it has already achieved tangible benefits through applications such as chatbots and product recommendation engines and remains a key technology topic for e-Commerce organizations, much of this potential is still to be realized.

Many organizations have focused their e-Commerce efforts on establishing competitive digital sales capabilities. Those starting to engage fully in AI may encounter hurdles to effective deployments, such as:

• Challenges in identifying specific use cases where AI can quickly add tangible value to the business. 
• A lack of existing use cases to build from. These use cases exist but may not be visible to the organization.      
• Allowing preconceptions of AI in eCommerce to limit the scope, such as seeing AI as primarily a  business-to-consumer (B2C) tool, missing its potential in business-to-business (B2B sales)

This blog article describes a data-driven approach that enables sales organizations to realize the full potential of AI, detailing the wide range of data that can be collected and applied to deliver AI-powered optimization of e-Commerce processes, and highlighting how SAP CX and Arvato Systems support customers in maximizing value from their data with market-leading AI capabilities. Start with understanding the business’s e-commerce maturity level.

Arvato Systems experts created the B2B e-commerce maturity model as a roadmap for B2B sales organizations to plan and track their e-commerce journey. Maturity increases as more elements – customers, product lines, services, and ordering processes – are added to the E-Commerce platform, and integration between the elements grows.

Understanding the business’s e-commerce maturity level is a key foundation for a successful, data-driven approach to deploying AI. Data is the essential fuel for AI, so the greater the range and volume of data available, the more value AI can deliver.

Mapping business priorities against the maturity model can help pinpoint where AI can add the greatest value and what data is needed to fuel it. For example, an organization that has achieved excellence with its e-shop offering could look to the maturity model to identify where it could go next,  such as using AI to deliver greater customer personalization.

Each maturity stage requires more data points and processes to support it, so referring to the model helps validate if these are already in place and the business is ready.

Customer Relationship Management (CRM) has evolved to take every touch point in the customer experience (CX). SAP’s CX portfolio seamlessly combines functions and data from commerce, marketing, sales and service to give a single, unified 360° perspective on the customer, enabling the insights and intelligent action maximize customer value.

SAP CX’s comprehensive reach means a wide variety of information can be collected from it to fuel AI, from data on customers and the products and services they purchase to data on the use of the customer portal. This may include:

Access to this comprehensive range of data enables targeted, AI-powered optimization of e-commerce processes. Fueled by this data, the SAP BTP (Business Technology Platform) provides an environment in which AI-supported processes can be individually implemented and operated. This way, the stored data can be processed and used to automate and optimize business processes.

Evaluating AI priorities starts with understanding the needs and goals of the business, set within the context of its e-commerce maturity level. This identifies what data is required and available to fuel the AI capabilities to deliver those goals. 

Some example of e-commerce processes that AI can optimize: