Dive Brief:
- Salesforce executives touted the cloud-based software company’s CX use cases at Saks, FedEx and Air India on a Q1 2025 earnings call Wednesday, amid lower-than-expected earnings.
- Saks unified all of its customer data to deliver more personalized experiences through Salesforce Einstein 1 and Data Cloud, and FedEx was able deliver personalization at scale through the CRM platform’s Journey Builder software, according to CEO Marc Benioff.
- Salesforce is counting on enterprise generative AI investments — and the need for good data to power it — to propel the company forward. “Because we are the number one CRM provider, we're now managing more than 250 petabytes of data for our customers. This is going to be absolutely critical as they move into artificial intelligence,” Benioff said on the call.
Dive Insight:
Salesforce stocks tumbled Thursday after it missed revenue targets, but Benioff pointed to CX use cases, particularly those at Air India, as a bright spot.
Air India used Salesforce Data Cloud to unify customer data across loyalty, reservations, flight systems and data warehouses on one platform. This “single source of truth,” as Benioff called it, helps the company handle more than 550,000 service cases a month.
Einstein, which now includes AI Cloud, Einstein GPT and other GPT products, helps the airline classify and summarize customer inquiries. It then sends those inquiries to an agent that specializes in that area, along with recommended next steps, Benioff said.
“Even when things happen like a flight delay, our system is able to immediately intervene and provide the right capability to the right customer at the right time,” Benioff said. “All of that frees up agents to deliver more personal service and create more personal relationships.”
Despite promising case studies, the rate of software sales at Salesforce declined in Q1. Benioff framed the slowdown as temporary, sister publication CIO Dive reported, with businesses preparing for AI adoption and the CRM provider primed to meet such demands.
“The one thing that every enterprise needs to make AI work is their customer data, as well as the metadata that describes the data, which provides the attributes and context the AI models need to generate accurate, relevant output,” Benioff said.
