Salesforce returned to the US investment-grade market on 11 March issuing US$25 billion senior unsecured bonds. Book to build for the various tranches came at 1.4 as investors worry about the agentic AI impact of software-as-a-service business models. Salesforce has earmarked the proceed to fund an accelerated equity buy back.
The deal was split into eight tranches maturing in 2028, 2029, 2031, 2033, 2036, 2046, 2056 and 2066. According to Salesforce’s pricing term sheet, the transaction comprised US$3.5 billion of 4.50% notes due 2028, US$4.25 billion of 4.65% notes due 2029, US$3.75 billion of 4.90% notes due 2031, US$2.75 billion of 5.20% notes due 2033, US$4.5 billion of 5.55% notes due 2036, US$1.5 billion of 6.40% notes due 2046, US$3.75 billion of 6.55% notes due 2056 and US$1.0 billion of 6.70% notes due 2066. The filing showed final spreads pricing ranging from 90 basis points over Treasuries on the 2028 tranche to 185bp on the 2066 notes.
Market sources reported a final order book of US$36 billion, implying cover of 1.4 times the amount of issue. Concessions had been indicated up to 195 basis point on the long end tranche before tightening into final pricing. For comparison, this is much lower than a recent jumbo deal by Oracle on 2 February when it priced a US$25 billion multi-tranche sale that drew more than US$129 billion of orders, or just over five times cover.
Read more: Oracle balances debt issuance with equity reflecting investor caution
Salesforce’s 11 March term sheet showed the new notes at A2 with a stable outlook from Moody’s and A+ with a negative outlook from S&P. S&P said it revised the outlook to negative because leverage is likely to rise as the company executes sizeable buybacks.
Salesforce stock reacted positively closing up 3% at 199.28 on 12 March.
While Salesforce management framed the debt for stock issuance as showing confidence in the business value, on 27 February analysts Karl Keirstead and Dean Marriott at UBS gave a US$200 price target on Salesforce after earnings taking into consideration AI disruption risk.
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