Smartocto

Where Smartocto sits

Smartocto is editorial analytics built for newsrooms rather than marketing teams. The Dutch company (Nijmegen) sells a content analytics system that tries to close the gap every editor knows: you have dashboards full of numbers, and nobody on the desk has time to turn them into a decision. Smartocto's answer is to translate performance data into concrete advice — what is working and why, what is not and how to fix it, which stories need attention now — and push that advice to the people who can act on it. The company says it serves around 300 media brands, and its thinking is closely tied to the User Needs model, a framework for classifying stories by the audience need they serve (update me, educate me, give me perspective, connect me, inspire me and so on).

That framing separates it from general analytics suites. Smartocto is not trying to replace your data warehouse; it is trying to make story-level performance legible to non-technical journalists and to nudge editorial strategy using evidence. Under CEO Erik van Heeswijk the company has spent 2025 and 2026 pushing that further into AI-assisted territory, with a newsroom assistant called Decisions and a growing training operation around the User Needs methodology.

What it actually does

At its base, Smartocto continuously measures how published stories perform — reach, attention time, engagement, conversion and loyalty signals depending on the publisher's business model — and reports on it in real time. The packages let publishers steer toward loyalty goals, run A/B tests on headlines and presentation, and set notifications that flag what actually pays off rather than what merely spiked.

The differentiator is the translation layer. Instead of charts you have to interpret, the system generates tips: which stories are underperforming against expectations, where an opportunity is being missed, what to do next. In March 2026 Smartocto formalised that idea with an official WoodWing integration, putting a real-time performance dashboard and automated story tips directly inside WoodWing Studio — the tip lands in the editor's CMS inbox at the moment the story is published, tailored to the publisher's business model. The integration comes in three configurations: a Starter package with a default reach dashboard and ten customised notifications starting at €8,000, a Pro package adding customisable multi-metric and goals dashboards with unlimited notifications starting at €12,000, and an Expert package with deeper AI integration priced on request. The fee covers hosting, implementation, support and ongoing maintenance.

Then there is the AI layer. Launched in October 2025, smartocto Decisions is a newsroom assistant that reads the performance data, detects patterns and speaks in recommendations rather than metrics: summarise what changed since this morning, highlight what matters most, suggest the next step, and join the editorial conversation about why a trend matters. The company's framing — "people think in words, not in numbers" — captures the design intent. At launch it was being refined with selected partner newsrooms.

The methodology and training side is unusually central for a software vendor. Smartocto runs User Needs Labs, a year-long programme helping news organisations build audience-centric strategy on the User Needs model, delivered with FT Strategies and strategist Dmitry Shishkin. The Labs baseline includes analysis of more than 5,000 articles per participant to establish where the newsroom stands, and the programme pulls in automated content tagging, AI-generated headline alternatives and the Decisions system. The homepage currently promotes a Labs 4.0 edition starting in October 2026. The company also publishes useful industry benchmarks from its own data team — its 2025 median page depth benchmark (average articles visited per session) was 1.92.

My testing notes

My access here ran through the demo and published materials rather than a live newsroom deployment — Smartocto is sales-led, and a production evaluation means a conversation with the team. Two things stood out.

First, the tips model is real and specific, not a rebranding of alerts. The WoodWing integration is the clearest demonstration: performance data lands in the CMS the moment a story publishes, and the advice stream is tuned to the publisher's business model rather than generic thresholds. Watching the flow, the value is timing — feedback arrives while the editor can still do something about the story. The User Needs evidence backs the approach: in the Nederlands Dagblad case, a newsroom producing mostly "Update me" and "Educate me" stories found that stories aligned with other user needs drew higher median pageviews and stronger engagement. That is a concrete, checkable editorial correction of the kind dashboards rarely produce.

Second, the framework does work that raw analytics cannot. Tagging content by user need and comparing medians across needs turns strategy into a measurable question — are we overproducing the needs our audience engages with least? In my testing of the material, the benchmark data is presented honestly by data scientists (median page depth 1.92 for 2025, with interpretation attached), and the Decisions assistant's summaries-of-change format is the right shape for a morning conference. I would want a full trial before trusting the AI layer wholesale, since the assistant is young and was still in partner refinement at launch.

The competitive context is worth one paragraph. Most newsrooms already have traffic analytics — Google Analytics, Chartbeat, Parse.ly or a mix — and Smartocto's pitch is not measurement but interpretation. Its own editorial writing makes the case plainly: having the data and knowing what to do with it are two different problems, and the second one is where desks stall. In my reading of their published material, including an October 2025 INMA piece on making data storytelling usable for non-technical end users, the company is consistent about this distinction. Whether the AI layer delivers on it at your newsroom is exactly the question a pilot should answer, but the problem it targets is real and unsolved everywhere I have looked.

What it does not do

There is no public pricing beyond the WoodWing integration packages, and those start at €8,000 for the Starter configuration — this is enterprise software for professional publishers, and small or independent operations will likely find the entry point prohibitive. Everything is sales-led: you request a demo and negotiate, with no documented self-serve trial. The scope is deliberately narrow — editorial analytics for publishers — so there is no value here for anyone outside newsrooms and content-driven media businesses.

On product maturity: Decisions launched in late 2025 as a partner-refined feature, and AI-generated headline alternatives and automated tagging arrived through the Labs programme; these are recent capabilities, not decade-old ones. The WoodWing integration is the only deep CMS embedding documented publicly at the time of writing; elsewhere the delivery of advice runs through Smartocto's own dashboards and notifications. And the value of the system depends heavily on newsroom adoption — the User Needs methodology is not a condition of use, but the strongest published results come from publishers who committed to the framework and the training.

Verdict

Smartocto does one thing seriously: it converts story performance into editorial advice at the moment it can be acted on, and it backs the method with a framework newsrooms can measure. I rate it 3.7 — weighted 40% core functionality depth (real-time analytics, tips engine, A/B testing, Decisions assistant), 20% value (credible ROI for publishers, but enterprise pricing and no public numbers hold it back), 20% usability (built for non-technical editors, tips delivered inside the CMS), 10% support and ecosystem (WoodWing integration, FT Strategies partnership, User Needs Labs), 10% reliability signals (roughly 300 media brands, established methodology, young AI layer). For a newsroom that has outgrown dashboards and is ready to act on user-needs evidence, it earns the demo; for a small publisher, the price of entry is the deciding factor.

Sources

• https://smartocto.com/
• https://smartocto.com/solutions/news/
• https://smartocto.com/company/news/smartocto-decisions-ai-newsroom-assistant/
• https://smartocto.com/company/news/smartocto-woodwing-integrated-editorial-analytics/
• https://smartocto.com/company/news/third-edition-of-user-needs-labs
• https://smartocto.com/blog/metrics-that-matter-in-2025-useful-editorial-analytics-benchmarks
• https://smartocto.com/research/userneeds/
• https://theaudiencers.com/how-the-user-needs-approach-boosts-engagement/
• https://www.inma.org/blogs/big-data-for-news-publishers/post.cfm/ai-s-potential-role-in-data-storytelling-empowers-decision-making
• https://smartocto.com/company/news