Marketing teams are asked to do more with less. We build AI that scales content production, sharpens targeting and turns campaign data into decisions — so your team spends time on strategy and creative, not busywork.
Last updated: 11 June 2026
Marketing generates huge volumes of content, campaigns and data, and most teams can't keep up by hand. AI helps on every side — drafting and localising content, optimising spend across channels, scoring leads, and turning scattered analytics into clear next actions — while a human keeps the brand and the strategy.
We build on your brand guidelines, tone and first-party data, with GDPR-compliant handling, so AI accelerates the work without going off-brand or off-message.
Draft and localise blogs, ads, emails and social copy from your brand voice and briefs.
Optimise bids, budgets and targeting across Google, Meta and LinkedIn to cut wasted spend.
Segment audiences and personalise messaging and offers from real behaviour.
Score and route leads so sales focuses on the ones most likely to convert.
Turn multi-channel data into clear attribution and next-best-action recommendations.
Find topics, gaps and questions to target, and brief content that ranks and gets cited.
We find the biggest time-sinks and wasted spend, and the data and tools you already use.
By the second call you get a working prototype on your use case — not a spec.
We integrate with your CRM, CMS, GA4 and ad platforms, with brand guardrails built in.
We track output quality and campaign ROI so the tools keep earning their place.
Most marketing teams already touch AI somewhere — a copy assistant here, an automated bid strategy there — but the tools sit in silos and nobody owns the outcome. The shift that pays off is moving from scattered experiments to a few AI marketing systems that are wired into your CRM, your content pipeline and your reporting, then measured against revenue. That is the work Crux Digits does: not selling licences, but designing, building and handing over AI that a marketing team in the Netherlands can run and trust.
We are a boutique AI consultancy, founded in 2022 and based in Nieuwegein in the province of Utrecht, working across the whole Netherlands and Europe. We are not a marketing or web agency and we do not compete with yours — we are the AI engineering partner behind the campaigns. That distinction matters, because building reliable AI content generation, predictive scoring and attribution is a data and software problem, not a creative one, and it rewards senior engineering rather than a rebranded WordPress shop.
For Dutch teams the practical questions are concrete: can we draft and localise bilingual EN/NL content without it sounding like a machine, can we stop wasting ad budget on the wrong audiences, and can we tell which channel actually drove the sale. Those map directly onto the use cases already on this page. Underneath them sit three capabilities worth naming on their own.
The fear most marketing leads voice about AI content generation is legitimate: generic copy, off-brand tone, and confident statements that are simply wrong. We design around all three. Generation is constrained to your tone-of-voice guide, a curated fact base and your existing top-performing assets, with a human approval step before anything is published. The model proposes; your editor decides.
For a bilingual market this is where the leverage shows. Producing parallel Dutch and English variants of a campaign by hand doubles the work; an AI pipeline that localises from a single brief — respecting that Dutch is not just translated English — cuts that to a review pass. The same engine briefs SEO content, drafts ad and email variants for testing, and keeps product copy consistent across a catalogue. If you want to see how we build this layer, our generative AI service page covers the architecture, and our wider AI consulting work shows where it sits in a broader programme.
A bare large-language-model subscription will write something for anyone. The difference between that and a production system is governance: where the facts come from, who signed off the tone, what happens when the model is unsure, and how you audit what was published. We build that scaffolding in — retrieval over approved sources, guardrails on claims, and logging — so the output is defensible, not just fast. LLM optimisation is part of this: choosing and tuning the right model for the job rather than paying premium rates to over-spec every task.
The second half of AI for marketing is the quieter, higher-value half: automation and prediction that act on data your team already collects but cannot read fast enough. Marketing automation here means stitching your stack together so the boring, error-prone steps run themselves — list hygiene, enrichment, lifecycle emails triggered by real behaviour, and lead routing that puts the right opportunity in front of the right rep at the right moment.
Predictive analytics for marketing adds the judgement layer on top. Instead of treating every lead the same, a scoring model ranks them by likelihood to convert; a churn model flags accounts before they go quiet; a forecasting model tells you what next quarter's demand looks like so spend is planned, not reactive. Attribution modelling closes the loop by showing which touches genuinely contributed, so budget follows results rather than the last click.
None of this requires ripping out your tools. We integrate with HubSpot, Salesforce, your CMS, GA4 and the Google, Meta and LinkedIn ad APIs, and we build on first-party data so you are not dependent on signals the cookie deprecation keeps eroding. The deeper integration patterns live on our AI automation page.
The honest constraint on predictive analytics for marketing is data, not algorithms. A scoring or churn model is only as good as the history it learns from, so the first thing we check in an audit is whether the signal exists at all: how clean your CRM records are, whether outcomes (won, lost, churned) are labelled consistently, and how far back usable history runs. Where the data is thin, we say so plainly and start with the automation and content work that pays back immediately, then layer prediction on once enough labelled history has accumulated. That sequencing is deliberate — a model trained on messy or sparse data produces confident-looking scores that quietly mislead, which is worse than no model at all.
When the data is there, the build is methodical rather than magical. We establish a baseline from your current process, train against held-out history so the numbers are honest, and measure lift against that baseline before anything touches a live campaign. The model ships with its reasoning exposed, so a rep can see why a lead scored high and a marketer can see which features drive a forecast. That transparency is what turns a prediction into a decision people will actually act on, and it is the same engineering discipline — clean pipelines, interrogable models, documented hand-over — that runs through every engagement we take on.
Marketing is exactly where AI and privacy law collide, because it runs on personal data and increasingly on automated decisions. For a Dutch organisation that means two regimes at once. The GDPR/AVG governs how you collect, store and act on customer data — consent, purpose limitation, access control and the right to an explanation. The EU AI Act adds obligations around how AI systems are built, documented and supervised, with heavier requirements as the risk rises.
We treat both as design inputs, not paperwork bolted on at the end. Personalisation uses first-party data with proper consent and access control; automated scoring keeps a human in the loop where decisions affect people materially; and the systems we build are documented well enough to answer a regulator or a customer who asks why. This is the difference between an AI marketing programme that scales and one that has to be switched off after a complaint. It is also why a senior-led partner matters here — getting compliance right is not a junior task you outsource to a template.
Search demand in the Netherlands runs in two languages — teams look for AI voor marketing as readily as the English phrasing — and the work itself is bilingual end to end. Everything on this page exists in Dutch on our AI voor marketing page, and the systems we build serve EN and NL audiences from the same pipeline rather than as bolt-on translations. For Dutch MKB marketing teams in particular, that bilingual capability is a competitive edge most generic AI tools handle poorly.
The Dutch market gives marketing teams two unappealing options for AI. The large enterprise consultancies — the Xebia, Xomnia and Capgemini tier — bring real capability but at a price and pace that rarely fits an MKB marketing budget, and they often staff projects with rotating juniors. At the other end, a wave of web and "AI" agencies rebrand a chatbot plugin as transformation and disappear when it breaks. Crux Digits sits deliberately between them: senior people who stay on the project from audit to launch, and a deliverable you own outright rather than rent.
That ownership principle runs through how we price and how we work. The engagement follows a transparent, fixed-step ladder (all prices excluding VAT) so there is no open-ended meter:
Day-rate guidance sits around EUR 150/hour for work that falls outside the ladder. The full breakdown is on our pricing page, and our about page explains the senior-led model behind it.
We have delivered 13 case studies across healthcare, computer vision, natural-language processing and forecasting; client names stay confidential, but the engineering patterns — clean data pipelines, models you can interrogate, systems handed over rather than locked in — carry straight into marketing work. You can read more on our case studies page.
A good first step is the audit. Tell us where the work piles up — content production, wasted ad spend, lead quality or reporting you can't trust — and we will map the fastest, most defensible win, with the EU AI Act and AVG handled from the start. The aim is not more dashboards or another tool to babysit; it is AI for marketing that quietly produces more on-brand content, sharper targeting and clearer attribution, owned by your team and built to last. Reach us at info@cruxdigits.nl or +31 6 44384676 to book a free consultation.
Yes — we ground generation in your brand voice, guidelines and approved facts, with a human reviewing before anything ships.
Your CRM (HubSpot, Salesforce), CMS, GA4 and ad platforms (Google, Meta, LinkedIn) via their APIs.
We use first-party data with GDPR-compliant handling, consent and access control — personalisation without crossing privacy lines.
No — it removes busywork and sharpens decisions so your team spends more time on strategy and creative.
Tell us where the work piles up — content, campaigns or reporting — and we'll map the fastest win in a free consultation.
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