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Salesforce continues to set up great stores with generative AI.
On Sunday at the National Retail Federation conference in New York City, Salesforce unveiled new retail-focused tools that run on the Einstein 1 platform.
These tools are just the latest examples of Salesforce’s gung-ho AI stance. Last June, Salesforce announced generative AI capabilities integrated into its Commerce and Marketing Cloud that automate tasks such as creating and personalizing content, building audience segments, and customizing offers.
Two months later, in September, Salesforce rolled out Einstein 1, a CDP-like data repository. This will allow marketers to feed data from the Data Cloud into generative AI tools, said Jay Wilder, vice president of product marketing for Salesforce Marketing Cloud.
Newcomer to the AI Crew
Two new AI-powered tools from Salesforce are almost ready for prime time. One for segmentation and one that helps retailers price promotions to different audiences across channels.
Both are in beta and will be generally available next month.
Segment creation tools allow retailers to build segments and, in turn, campaigns and customer journeys that target customers with messaging and offers “based on where they are in their relationship with the brand” in terms of engagement and affinity. It can be done, Wilder said.
For example, retailers can target casual shoppers who come into the store for once-a-season deals, customers who visit the store regularly (and thus may be candidates for Salesforce’s referral marketing programs), and lapsed customers. can be identified.
Global promotion management tools allow marketers to use customer data from Data Cloud to predict what pricing and benefits are best for loyal customers and infrequent shoppers.
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For example, a company might offer a 20% discount to everyone and add 100 bonus points to loyalty members, Wilder says. On the other hand, customers with high lifetime value may get early or exclusive access to your product.
Salesforce can also use predictive AI to predict the positive or negative impact that offers will have on revenue generation and margin compression. For example, a promotion that ultimately hurts the company’s profits may not be worth running.
Fascinated, (A) I’m sure
Wilder said that while generative AI is clearly an investment priority for Salesforce, the company is taking precautions to ensure its enterprise customers can use the technology safely and methodically.
For example, Salesforce has struggled to generate AI-powered responses that are “highly tailored” to the look and feel of a particular brand without compromising the privacy and security of brand data, he said. Ta.
Wilder said Salesforce uses something called the Einstein Trust Layer to protect personally identifiable information that is used to query large-scale language models (LLMs) such as ChatGPT, Cohere, Anthropic’s Claude 2, and Google models. “Mask”.
Once a response is generated, Salesforce automatically removes brand-sensitive information and requests that LLM not retain or use the data to train models. “This is a prerequisite for working with customers at Salesforce,” Wilder says.
Wilder said Salesforce also tests AI-generated content for bias and “what we would consider harmful hallucinations,” and importantly, for processes involving multiple users. The company says it is creating an automatic audit trail.
In other words, it’s important to “keep all your receipts,” and not just for compliance purposes, he said.
“If we analyze that information, we can get broader insights,” Wilder said. For example, users can take a closer look at his Tableau (acquired by Salesforce in 2019) or “drill down” to where the trust layer detected toxicity or bias to understand how and why that outcome occurred. can be understood.
Salesforce is introducing audit trails in other products as well. For example, the Marketing Cloud records every journey, content created, and message sent.
Wilder said the safeguards Salesforce has in place may be why the company’s generative AI content creation capabilities for its marketing cloud have been rapidly adopted by customers since its debut last October.
“There is great urgency,” he said. “Brands and businesses don’t want to sit on the sidelines with generative AI right now.”
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