Bloomberg Tech
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Bloomberg Tech

@bloombergtech

Macro · 500k–1MView channel ↗

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740K

Subscribers

11.1K

Average views

across 15 recent videos

1.5%

Reach quality

of subscribers watch, on average

Below typical for macro-sized channels

this creator 1.5%macro median 9.9%

Below the macro median for macro-sized channels — a large subscriber count that comparatively few videos reach.

182.5M

Total views

14.2K

Videos

2026-10-03

Data updated

15-video sample

About

Welcome to the Bloomberg Tech YouTube channel. Subscribe to see the latest videos on game-changing technologies, profiles on innovators, live conversations with experts, and breaking technology news & analysis from Bloomberg TV. Our programs offer in-depth interviews and analysis centered on industry leaders and global tech trends. Sign up for the Tech Daily newsletter to get exclusive reporting and analysis on tech and AI. https://bloom.bg/4bUP7rF

About Bloomberg Tech

Bloomberg Tech, operating under the handle @bloombergtech on YouTube, functions as the digital video extension of Bloomberg’s broader technology journalism division. The channel serves as a repository for high-level reporting on global technology trends, profiles of industry innovators, and live-streamed conversations featuring subject matter experts. With a library of 14,248 videos, the channel emphasizes institutional-grade analysis rather than consumer-focused product reviews. Its content strategy centers on the intersection of technology, finance, and global policy, providing viewers with context on how emerging innovations impact market structures and corporate leadership. The channel’s editorial output is closely tied to Bloomberg TV, often featuring segments that distill complex industry developments into accessible video formats. Beyond its video library, the channel acts as a lead-generation tool for the Bloomberg Tech Daily newsletter, which provides subscribers with exclusive reporting on artificial intelligence and broader tech sector developments. The channel’s longevity and high volume of uploads suggest a commitment to consistent, daily coverage of breaking news, positioning it as a primary information source for professionals interested in the macro-level implications of technological advancement. By focusing on industry leaders and global trends, Bloomberg Tech maintains a distinct editorial identity compared to independent tech reviewers, prioritizing institutional authority and data-backed reporting over lifestyle-oriented content.

Bloomberg Tech's estimated sponsorship rates

The estimated cost for a video integration on the Bloomberg Tech YouTube channel ranges from $222 to $355, with a typical valuation of $278 per placement. These figures are derived from an algorithmic analysis of the channel’s recent performance, specifically utilizing an average view count of 11,108 per video. The pricing structure is heavily influenced by the channel's niche, which falls into the technology and news sectors—categories that generally command higher CPMs due to the professional and high-intent nature of the audience. The niche CPM band for this channel is calculated between $20 and $32, with an anchor point of $25. Several factors contribute to these rate estimates. First, the channel’s status as a macro-tier creator (740,000 subscribers) provides a baseline of credibility that appeals to B2B and institutional advertisers. Second, the professional nature of the content ensures that the audience is likely composed of decision-makers and industry professionals, which typically allows for a higher CPM than entertainment-focused channels with similar subscriber counts. While the channel maintains a high volume of total views—182,492,304 to date—the integration rate is primarily anchored to the performance of recent, individual video uploads rather than the cumulative historical total. Advertisers looking to engage with this channel are paying for access to a highly targeted, news-literate audience that is actively seeking information on market-moving technology developments. For a detailed breakdown of how these specific variables interact to produce these estimates, please refer to our methodology page.

Who should partner with Bloomberg Tech?

The audience for Bloomberg Tech is characterized by its interest in high-level technology news, corporate strategy, and the economic impact of innovation. Given the channel’s editorial focus, the viewer base likely includes professionals in finance, software development, venture capital, and corporate management. Unlike channels that focus on consumer electronics or hardware unboxing, Bloomberg Tech attracts viewers interested in the business of technology, including AI policy, semiconductor supply chains, and market analysis. This audience is particularly valuable for advertisers in fintech, online brokerages, enterprise software, and personal-finance education platforms. When comparing Bloomberg Tech to other creators in the tech space, such as Lemur (739,000 subscribers) and Perfect Gadget (729,000 subscribers), it becomes clear that Bloomberg Tech occupies a unique position. While creators like Lemur or Perfect Gadget may focus on product-specific utility, Bloomberg Tech’s audience is tuned in for institutional insight. The channel’s subscriber base of 740,000 places it in a competitive cohort with other established tech channels like ITFACTS (700,000 subscribers) and Nathie (811,000 subscribers). However, the demographic profile of the Bloomberg Tech viewer is distinct, leaning toward an older, more professional, and potentially higher-net-worth segment. This audience is less likely to be influenced by consumer-grade hardware trends and more likely to engage with content regarding long-term industry shifts and corporate governance. Advertisers targeting this channel are typically seeking to reach a professional demographic that values data-driven analysis and objective reporting over the personality-driven content often found elsewhere on the platform.

Bloomberg Tech's growth and performance

The growth trajectory of Bloomberg Tech is characterized by steady, incremental gains in its subscriber base. Based on the snapshot history provided, the channel grew from 732,000 subscribers on July 23, 2026, to 740,000 subscribers by October 3, 2026. This represents a total increase of 8,000 subscribers over a period of 72 days. This growth rate averages to approximately 111 new subscribers per day. While the channel has a massive library of 14,248 videos, the current growth data reflects a mature channel that relies on consistent, high-frequency updates rather than rapid, viral spikes. This pattern is consistent with institutional media channels that prioritize brand retention and daily news cycles. We do not yet have view-count history data to correlate these subscriber gains with specific content releases or seasonal trends. However, the consistent addition of subscribers over this 72-day window indicates that the channel continues to maintain relevance within its niche, successfully converting viewers into subscribers through its regular programming schedule.

How our pricing estimate works for Bloomberg Tech

The pricing estimates and performance metrics provided for Bloomberg Tech are generated using a proprietary algorithmic model. This model calculates the value of a creator’s inventory by synthesizing several key data points, including total subscriber count, niche-specific CPM (Cost Per Mille) bands, and platform-specific format multipliers. For this profile, we utilized an anchor CPM of $25, which reflects the professional and high-intent nature of the technology and news categories. The valuation is further refined by the channel’s average view count of 11,108, which serves as the primary basis for the cost-per-integration estimate. This algorithmic approach ensures that valuations are grounded in objective performance data rather than subjective assessment. By applying these multipliers, we provide a standardized range that allows for consistent comparison across different creators and niches within the InfluencerUnion database. For a comprehensive explanation of the variables, confidence intervals, and the mathematical framework used to derive these figures, please refer to our methodology page.