Palantir Technologies estimated fourth-quarter revenue above market expectations on Thursday, citing high demand for its new artificial intelligence platform from customers including US federal agencies.
In premarket trade, shares of the Colorado-based corporation were up 7%.
According to LSEG statistics, the business forecasts sales between $599 million and $603 million, with the midpoint exceeding analysts’ average expectation of $600.5 million.
Palantir said it was witnessing considerable interest in the “AI boot camps” it introduced in October to provide customers access for one to five days, indicating potential demand for its new platform.
“By the end of November, we’re on track to conduct boot camps with 140 organizations, and half of those will take place in (that month),” Chief Revenue Officer Ryan Taylor said.
Users of Palantir’s AI platform almost quadrupled between July and September, according to Taylor in an interview.
In the third quarter, sales increased 17% to $558 million, slightly above expectations.
However, revenue from government customers, a crucial source of sales, increased by 12%, falling short of Wall Street projections and the 15% rise seen in the previous quarter.
Budgetary limitations by the government have caused some short-term concern in the industry, but Palantir remains optimistic about demand in light of global tensions, according to the firm.
Commercial revenue increased by 23% to $251 million, with half of it coming from the United States, where demand has been higher than in Europe.
Adjusted net income attributable to shareholders was $155 million, up roughly 30% from the previous year.
Businesses create a wide range of data that contains valuable insights, and data analytics is the key to unlocking them. Data analytics may assist a company with anything from tailoring a marketing pitch for a specific consumer to recognizing and reducing business hazards. Let’s look at five of the advantages of adopting data analytics.
Customers’ data is collected by businesses via a variety of channels, including traditional retail, e-commerce, and social networking. Businesses may get insights into consumer behavior and deliver a more customized experience by employing data analytics to generate full customer profiles from this data.
Organizations may further enhance the customer experience by running behavioral analytics models on customer data. A company, for example, may build a predictive model using e-commerce transaction data to identify which goods to promote at checkout to improve sales.
