Analyst Perspectives

While I do not have an MBA, I have a very academic degree in economics and three decades of experience in different facets of business. Why is this important or relevant? Well, an entire industry has sprung up to promote the latest business ideas, the adoption of which will, supposedly, if not guarantee success, improve the probability of success in any endeavor. And while some of these ideas have merit, many fall in the “interesting but so what” category.

This brings me back to the value of foundational elements: the why as much as the what and the how. And this is what academic study gives you, as with the classics in understanding language or literature, the principles of double entry bookkeeping, the foundations of accounting and banking or, as the case here, the economic theory underpinning markets and trade.

In essence, the purpose of a market is to match buyers with sellers. In conjunction with currency as a medium of exchange, buyers and sellers are matched without the inefficiencies of barter. Over the years, physical markets were established with rules and standardized practices to add protections for both buyers and sellers. In fact, every innovation and improvement has come about to make markets more efficient in reducing friction and mismatches between buyers and sellers.

These changes led to the rise of the digital marketplace, more commonly referred to as e-commerce. I recently attended Salesforce’s Connections event at the McCormick Place convention center in Chicago. The big announcement was the introduction of generative AI and the relaunching of Salesforce Data Cloud (formerly known as Genie).

If generative AI does nothing else, it has rekindled energy and interest in the technology space after the previous year’s continual news of layoffs and momentum-killing discussion of an impending recession. But I believe generative AI holds the promise of much more than just improving tech morale and buoying buyer interest.

Combining Data Cloud ‒ and its focus on data context and quality ‒ with generative AI has the potential to make markets more efficient. At the Connections conference, Salesforce showed numerous examples of how Data Cloud pulls together, aligns and normalizes data from disparate sources ‒ both first- and third-party data ‒ in support of a better understanding of customers’ needs, wants and behaviors. It is a prerequisite for any organization wishing to understand increasingly smaller groups of customers, whether business-to-consumer or business-to-business. I have previously written on this topic in my Analyst Perspective, Salesforce Commerce Cloud Targets the Segment of One. In being able to fine-tune and personalize outbound messaging as well as promotional offers and recommendations to ever-narrower groups, marketers and promotion managers are better able to target relevant buyers, making the market more efficient, as it were.

Adding generative AI takes us one step further. In addition to using generative AI to more efficiently write copy for outbound emails and offers or have more dynamic localization through translation services, Salesforce also announced enhancements to more of the blocking and tackling of e-commerce, such as easier and more drag-and-drop composable storefronts with the ability to have storefronts dynamically configurable based on who is visiting. The example given was of a geo-based filter enabling rainwear to be displayed more prominently if a region ‒ such as the U.S. Northeast ‒ was experiencing higher-than-normal rainfall. There were also announcements of more comprehensive, organization-configurable payments for B2C and B2B use cases and a B2B self-service reorder functionality that references previously negotiated rates and terms.

But the theme that captured the most attention was not, unsurprisingly, the role of generative AI. In numerous sessions at the event, Salesforce executives repeatedly stressed the importance of human creation and control when using large language models and generative AI. This message attempts to assuage fears of ripped-from-the-headlines stories of generative AI models confidently outputting wrong and made-up answers. And they are right to emphasize caution, but there is no doubt that both vendors and customers are excited by the possibilities.

In B2B e-commerce and Salesforce’s Commerce Cloud, generative AI promises to further the journey of making markets ever more efficient. The digital interaction between buyer and seller moves to a different plane, personalizing not just the offer but the entire interaction for buyers to articulate their needs and sellers to respond in kind. Models that enable buyers to better describe their needs could replace functions like traditional configure, price and quote. The generative AI response more readily and accurately can be used to articulate customer needs. Equally important, it presents options in language together with a tailored value proposition that best fits the customer’s hierarchy of values. Although propensity to buy is not currently part of the Commerce Cloud solution, this functionality’s inclusion would be another rung along the market evolutionary curve.

We assert that by 2025, 1 in 10 B2B organizations will experiment with digital commerce and digital delivery of products and services to reduce the cost of sales as part of an omnichannel engagement model. This is probably on the conservative side. If yours is one of those organizations soberly trying to ascertain how generative AI and LLM could enhance the sales and revenue process, I recommend a broader view than how sales and marketing teams can more effectively write emails and copy or how generative AI can enhance e-commerce website storefronts. Consider how enhanced customer data clouds and generative AI could fundamentally alter B2C sales and buyer engagement motions and how B2B self-service and e-commerce could become the predominant buying channel. This won’t happen overnight, but the foundations are being laid now.

Regards,

Stephen Hurrell