Pinterest Raises Q1 Revenue Forecast After tvScientific Acquisition
Pinterest increased its first-quarter revenue forecast on Wednesday, reflecting the financial impact of its newly acquired connected TV (CTV) advertising platform, tvScientific. Following the announcement, Pinterest shares climbed more than 3%.
The updated guidance was issued less than a week after the company’s previous forecast.
Pinterest now expects first-quarter revenue between $958 million and $978 million. Its earlier outlook ranged from $951 million to $971 million. The midpoint of the revised forecast exceeds analysts’ expectations of $964.9 million, according to LSEG data.
EBITDA Outlook Adjusted Due to Integration Costs
While Pinterest raised its revenue forecast, it lowered its adjusted EBITDA guidance. The company now projects adjusted EBITDA between $163 million and $183 million, compared with its prior estimate of $166 million to $186 million.
The adjustment reflects integration-related expenses and upfront investments associated with the tvScientific acquisition.
Stock Under Pressure Amid Advertising Concerns
The revised guidance comes after a volatile period for Pinterest stock. Shares dropped more than 20% last week after the company warned that tariffs affecting major U.S. retailers could pressure earnings. The warning raised concerns that advertisers might reduce spending in the coming months.
Pinterest stock is now down more than 40% year to date. The decline highlights investor concerns over softer advertising demand and intensifying competition in the digital advertising market.
tvScientific Deal Strengthens CTV and AI Capabilities
Pinterest announced the acquisition of tvScientific in December 2025. The deal marks its first major acquisition since 2022.
tvScientific operates an outcome-based connected TV advertising platform. Pinterest plans to integrate the platform into its broader performance advertising ecosystem.
The acquisition will also expand Pinterest’s Performance+ AI tools. By incorporating connected TV into its machine-learning framework, the company aims to automate media buying, improve campaign optimization, and enhance cross-screen attribution.
