Beam+ is the editorial and business analytics tool built for news media

Beam+ is a real-time content analytics platform built specifically for news publishers. It’s designed for three groups: editorial teams who need to know what’s resonating right now, strategy and audience teams tracking the reader journey from first visit to subscription, and leadership who need ready-made performance dashboards without waiting for custom reports.

GA4, although widely adopted and used by many newsrooms, is a generic web analytics tool, not built for editorial decision-making. Also, mid-sized newsrooms are hitting the limits of the free tier and are not able to afford the paid GA360 access. Most analytics tools measure real-time engagement but don’t tell you much about audience loyalty or what to do with the data. Beam+ combines real-time content performance with a loyalty segmentation system, automated editorial recommendations (ROSA, see explained below), channel-level audience quality analysis, and AI traffic detection, all in one place, on your own infrastructure. The data stays yours.

ROSA is Beam+’s automated recommendation system. It evaluates every article on two dimensions: performance (pageviews, sessions, unique browsers) and engagement (recirculation, interactions, scroll depth). Each article is then labeled with one of four actions: Replicate content that’s working well and should be produced more, Optimize articles that got clicks but didn’t hold attention, Stop investing in content that reached almost no one and kept no one reading, or Amplify pieces that resonated deeply but didn’t reach a large enough audience. Editors get a clear next step on every article without needing to interpret the numbers themselves.

Beam+ uses the RFV scoring system (Recency, Frequency, Volume) originally developed by the Financial Times to segment every reader based on their behavior over the last 30 days. Readers are placed into five tiers: New (first-time visitor), Fly-by (visited once or twice but didn’t return), Casual (occasional reader who knows the brand but isn’t habitual), Loyal (regular visitor who identifies with the brand and is likely to convert), and Lover (your most engaged reader, visits almost daily and reads multiple stories). These segments update daily.

This is one of Beam+’s most distinctive features. It shows which traffic channels bring which type of reader. For example, if Social mostly brings Fly-bys while Direct traffic brings Lovers, that tells you your newsletter strategy is working but your social content isn’t building lasting relationships. This analysis changes how you allocate editorial promotion and retention effort across channels.

The six core KPIs are Total Engaged Minutes (aggregate reading time across all visitors), Average Engaged Time (how long readers spend with each article), Pageviews (total traffic volume), Quality Views (pageviews where the reader spent at least 15 seconds or actively interacted with the content), Browsers (unique visitors), and Recirculation (the percentage of readers who continued to another article after finishing one). Beyond these, Beam+ tracks an Engagement score per article, which combines traffic, consumption, interactions, sharing, virality, and recirculation into a single comparable number. You can also adjust the weighting of each component to match your editorial priorities.

Yes. Beam+ automatically identifies and tags traffic from AI tools, including ChatGPT and Perplexity, under the medium label “AI.” This flows into all dashboards so you can track AI-driven traffic volume over time, see which content performs best when referred by AI tools, and understand how AI visitors behave compared to readers from Search or Social, including where they land in the loyalty funnel.

Yes. The filter bar at the top of every dashboard lets you filter by Author, Section, and Tag simultaneously. The Content Insights dashboard also lets you pivot between Article, Author, Section, and Tag views with a single click, without leaving the page. You can also cross-filter by clicking directly on any element in a chart, such as selecting a specific article to see all related data update across the dashboard instantly.

It breaks your traffic down by medium (Social, Search, Direct, Aggregators, Other) and then by specific source within each medium. Under Social you’ll see Facebook, Instagram, Telegram, and X. Under Search you’ll see Google, Bing, Yahoo, Ecosia, Brave, and Seznam. Under Aggregators you’ll see Google Discover, Google News, Microsoft Edge, and regional platforms. There’s also a paid vs. organic split and per-channel article leaderboards for Social, Google Search, and Google Discover.

On your own infrastructure. Beam+ is built on REMP Beam, the open-source analytics layer created by Denník N and supported by Google News Initiative. Unlike SaaS analytics platforms where your audience data lives on vendor servers, Beam+ is self-hosted. Your data doesn’t disappear if you stop paying, and it isn’t used by anyone else.

Beam+ is built on the open-source Beam analytics module, which is part of the installation bundle when Beam+ is purchased. Real-time Beam accounts are open-source and not subject to per-seat pricing. Most REMP (The Readers’ Engagement and Monetization Platform) users on the editorial side use Beam for real-time analytics. As for Beam+, it runs on Power BI, and you can purchase as many seats as you need.

We are not sharing the prices publicly, sorry (but they are very competitive). Reach out, and you get a demo and a product sheet. There is a one-time setup fee, currently under early bird pricing, which covers core setup and single-site implementation. Then there is an ongoing monthly service fee, which includes hosting, updates, monitoring, and support. Pricing is flat and transparent; it does not scale with team size or traffic volume.

Hosting, updates, monitoring, and technical support. Support is handled directly by the engineers who built the product.

Beam+ is built on the REMP open-source stack, so it integrates naturally with other REMP tools. A deeper integration between Beam+ behavioral data and REMP CRM is planned for 2026, which will allow publishers to connect reader behavior patterns to subscriber records, build segments based on content engagement, identify what content moves readers from Casual to Loyal to Subscriber, and automate paywall personalization based on real-time loyalty status.

Book a demo at fatchillimedia.com.