Private beta - by invitation

Your full data analytics team, on demand.

Datacompany plugs a complete analytics function into your business. No hiring, no warehouse build, no six-figure setup. Connect your ad accounts and start cutting wasted spend within weeks.

Built by ex-Coolblue. Independent of any ad platform.
Live - updated 4 minutes ago
Last 26 weeks
Attributed revenue
€328,500
+14.2% vs. previous period
Channels
Google Ads€124,8k
Meta€71,2k
LinkedIn€42,1k
Organic search€38,9k
Brand uplift€31,4k
Today's insight
Scale Google Ads brand back by 18%. Holdout confirms incremental ROAS dipping below the 3.4 threshold.
The problem

You spend on marketing. You can't tell what actually worked.

Five compounding reasons every marketing manager is flying half blind — and why hiring your way out costs more than it saves.

01
Every platform claims your conversions
Google attributes them, Meta attributes them, LinkedIn attributes them. Add the platforms together and you often end up at 130–150% of your actual sales. Who's right? None of them.
02
Last-click is blind to offline
Billboards, podcasts, radio, sponsorships — 15–25% of your real lift comes from channels with no trackable click. Last-click reports them at zero.
03
Cookie walls + iOS = half the data
Between cookie consent and iOS tracking restrictions, 30–40% of your conversions are no longer correctly measured. You're steering on half a dashboard.
04
Agency MMM is stale on arrival
A consultancy delivers an MMM report once a quarter as a slide deck. By the time it lands, your channel mix has already moved on.
05
An in-house data team isn't profitable
A data engineer plus a data scientist is €200–300k per year — more than most marketing budgets. And good luck hiring them.
What changes

Last-click misses what actually moves the needle.

Same business, same revenue, same month. Two views. Last-click can only see channels with a trackable click on the path. Our model is built on holdouts and incrementality, so the channels that genuinely drove revenue show up at the share they earned.

Last-click view
GA4 / Ads
What your current analytics tool reports.
Google Ads
42%
Meta
28%
LinkedIn
8%
Organic search
22%
Podcast sponsorship
0%
Billboards
0%
Bus shelter (abri)
0%
Brand uplift
0%
Four channels are missing - last-click cannot see them.
Datacompany view
MMM + holdouts
What actually drove revenue this month.
Google Ads
22%
Meta
17%
LinkedIn
9%
Organic search
11%
Podcast sponsorship
12%
Billboards
9%
Bus shelter (abri)
8%
Brand uplift
12%
Blue bars: channels last-click can't measure.
Offline and local channels, finally measured.

We model podcasts, billboards, bus shelter ads, sponsorships and local activations into the same view as your digital spend. No more guessing whether the radio buy paid back. It either lifted sales in the treatment region or it did not.

What makes us different

One independent measurement of what actually works.

Datacompany combines Bayesian MMM, attribution and incrementality experiments into one source of truth — refreshed weekly, validated against real-world holdouts, and explained by AI with a senior data scientist one click away.

MMM + attribution + incrementality in one
Three measurement approaches triangulated into a single source of truth. No need to glue together a reporting tool, an attribution vendor, and an experimentation platform.
Campaign-level, with confidence bands
Classical MMM tells you 'Google Ads works'. We tell you which campaign, which keyword, and with what certainty. And we never inflate the numbers to look better.
Independent of every platform — including offline
We don't sell ads and we don't run your campaigns. Billboards, podcasts, radio, sponsorships land in the same view as your digital spend.
Refreshed weekly, delivered to Slack or Teams
Fresh attribution and anomaly alerts appear where your team already works. No analyst needed to interpret a dashboard before you can act on Monday.
Ask in plain language. Human on standby.
Type your question in Dutch or English. Our AI writes the query and answers with the underlying chart. Not convinced? One click escalates to a senior data scientist. No ticket system, no extra invoice.
Validated with geo holdouts — and priced for SMEs
Every recommendation is backed by a real-world experiment, not just correlation. All this for less than half a day of an agency, per month. No consultants, no data team to hire.
How it works

From connected to confident in weeks.

01
Connect
OAuth into Google Ads, Meta, LinkedIn and your CRM. No CSVs, no warehouse build, no engineering effort on your side.
02
Model
We run a Bayesian MMM tailored to your business, calibrated against geo holdouts so the numbers reflect real incrementality.
03
Recommend
You get prioritised actions: which channels to cut, which to scale, which holdouts to run next. With margin per goal baked in.
04
Validate
An analyst reviews the run before it reaches you, and is one message away whenever you want to challenge a recommendation.
Inside the platform

See exactly what moved the needle.

Channel-level incrementality, holdout-validated attribution and campaign-level causal measurement. Built on PyMC-Marketing, explained in plain English.

Holdout results
LinkedIn brand holdout - NL north
p = 0.018
Treatment
€31,840
Control
€26,420
Measured lift
+20.5%
95% confidence interval: 11.8% - 29.2%
Significant. Incremental.
Real geo experiments behind every recommendation.
Budget reallocation
Budget reallocation - proposedProjected extra revenue: +€48,300 / mo
ChannelCurrentProposedΔIncremental ROI
Google Ads - brand€24,000€18,000-25%6.2x
Google Ads - generic€31,000€36,000+16%3.1x
Meta prospecting€22,000€14,000-36%1.4x
Meta retargeting€12,000€15,500+29%4.8x
LinkedIn brand€8,000€13,500+69%5.4x
What happens to revenue if you shift €10k from A to B.
Campaign impact
Campaign experiment
De Ondernemer Podcast × Acme SaaS — sponsorship weeks 5–12
Treatment regionControl region
Podcast start+24%W1W3W5W7W9W11100
Measured lift
+24.3%
Incremental revenue
€ 43,200
Significance
p < 0.05 · Sig.
Causal lift from a specific sponsorship, isolated from background noise.
Monthly reports

An analytics team's monthly output, ready to forward.

On the first business day of every month, a 14-page PDF lands in your inbox. It tells the story of what happened to your marketing, what we did about it and what should change next. Written by AI on your real numbers, validated by a senior data scientist before it reaches you.

Delivered first business day of the month, 08:00 CET
D
Datacompany·Acme BV
October 2026

Monthly marketing attribution report

Attributed revenue
€328,500
+14.2% MoM
Incremental ROAS
3.61
+0.42 vs Sep
Avoidable spend
€27,400
-€11k saved
Executive summary

October closed at €328,500 in attributed revenue, up 14.2% versus September and ahead of plan. Brand-driven channels, in particular podcast sponsorship and Dutch billboards, carried more of the growth than last-click reporting suggested. We recommend pulling 18% of Google Ads brand budget back and reallocating it to LinkedIn brand and the Q4 podcast slate, where the calibrated incremental ROI sits above 4.8x.

Attributed revenue by channel, last 6 months
Google Ads84k
Meta56k
LinkedIn38k
Organic32k
Podcast41k
Billboards28k
Top recommendations
  1. 1Reduce Google Ads brand by 18%, reallocate to LinkedIn brand
  2. 2Extend Q4 podcast slate by two episodes; incremental ROI 5.4x
  3. 3Run a billboard holdout in Noord-Holland for two weeks
Generated 1 Nov 08:00 CET, Datacompany, confidentialPage 1 of 14
What is inside
  • 01
    Executive summary in plain language
    Three paragraphs your CMO and CFO can read in two minutes. No jargon, no dashboards, just the story.
  • 02
    Per-channel attribution and incrementality
    Holdout-validated contribution per channel with confidence intervals. What is real, what is overstated.
  • 03
    Per-country and per-goal deep dives
    Margin-weighted ROI per market and per business goal, so the recommendations land in euros, not just ROAS.
  • 04
    Concrete recommendations
    Prioritised actions with expected impact. Scale this, cut that, run this holdout next.
  • 05
    Model accuracy and audit trail
    MAPE, RMSE, residual patterns and every assumption we made. Defensible in any board meeting.
Capabilities

An analytics team that works while you sleep.

Every capability below is shipping in beta today. Together they replace what an in-house data team would do, at a fraction of the cost.

Slack · Teams · Email
Anomaly alerts to Slack and email
Tracking pixel down. Spend stalled. A channel quietly going negative. You get a Slack message or email within hours, not after the monthly review. Severity-tagged so the critical ones cut through.
With bands
Confidence intervals on every number
No bare point estimates. Every attribution number comes with a confidence band so you can tell what's certain and what's a guess. We never inflate the numbers to look better — uncertainty stays uncertainty.
Mondays 08:00
Weekly summary, auto-narrated
Every Monday at 08:00, a one-page narrative lands in your inbox. Written by AI on your real numbers, reviewed by a senior data scientist, ready to forward to your CMO.
Causal evidence
Geo holdouts, found automatically
We continuously scan your spend data for natural experiments: country pauses, regional tests, calendar gaps. Each becomes a difference-in-differences causal proof behind a recommendation.
Optimiser
Budget reallocation, every cycle
A linear optimiser tells you exactly which channels to scale and which to cut, with the expected revenue impact attached. Margin per goal is already baked in, so the recommendation is in euros, not just ROAS.
Monthly PDF
Boardroom-ready PDF reports
Auto-generated monthly PDFs with AI commentary, per-country deep dives, model accuracy and the actions taken since last month. Send straight to your board without rewriting a line.
Ask anything

Ask in plain language. A senior analyst one click away.

Every other attribution tool gives you a dashboard and walks away. We give you a question box — and if the AI answer doesn't satisfy you, a real data analyst takes over. No ticket system, no extra invoice. This is the part nobody else does.

D
Datacompany·Live example
● Live
You
Why did our LinkedIn ROAS drop in France last week?
Datacompany AI
Query written
SELECT channel, country, week, roas FROM attribution WHERE channel='LinkedIn' AND country='FR' ORDER BY week DESC LIMIT 8
Answer
ROAS dropped from 4.2x to 2.8x in week 41. The cause is a budget shift: the 'FR · Decisionmakers' campaign moved €4,300 into prospecting where CPMs were 38% higher. Adstock from the previous flight is still bleeding in — true incremental ROAS this week is closer to 3.4x.
LinkedIn ROAS · France · last 8 weeksChart auto-attached
Not satisfied with the answer?
Within one working day a real data scientist takes over — with full context. No ticket, no extra fee.
Jeroen Oosterveld·Founder · Datacompany
I dug into the holdout we ran in FR week 38. Adjusting for the carry-over, the actual incremental LinkedIn ROAS for week 41 is 3.6x — not 2.8x. Here's the breakdown with confidence bands…
How it works
  1. 01
    Step 1
    You ask
    Type your question in English or Dutch — like you would in ChatGPT. No SQL, no metrics setup, no dashboard hunting.
  2. 02
    Step 2
    AI answers
    Our LLM writes the query against your live data, runs it, and answers with the chart and the assumptions it made — all auditable.
  3. 03
    Step 3
    One click to a human
    Not convinced? Click 'Escalate'. A senior data analyst picks it up within a working day, with full context of your question and the AI's answer.
What makes us different
Triple Whale gives you AI summaries. Agencies give you a human (project-priced). Nobody else gives you both — instantly, included in the subscription.
Why us

Independent, transparent, with a human in the loop.

There is no shortage of AI tools that promise marketing miracles. Most are wrappers around the same platform APIs they are supposed to evaluate. We are built differently.

Independent of ad platforms
We do not run your campaigns and we do not sell media. We have no incentive to make any channel look better than it is.
No black box
Every recommendation traces back to a model output and, where it matters, a real-world holdout. You can audit the maths.
Human escalation, always
When you want to challenge a result, a real data scientist responds. Not a chatbot that paraphrases the dashboard.
Built for SMEs
Enterprise-grade methodology, priced for businesses that cannot hire a full in-house team.
Connectors

Plug it in. We handle the pipes.

API-first ingestion across 200+ marketing, CRM, e-commerce, finance and analytics sources. No exports, no spreadsheets, no engineering tickets.

Live in beta232+ sources connected
Google AdsFacebook AdsLinkedIn AdsGoogle Analytics 4Microsoft AdsTikTok AdsPinterest AdsSnapchat AdsTwitter AdsReddit AdsAmazon AdsApple Search AdsHubSpotSalesforcePipedriveShopifyKlaviyoMailchimpGoogle Search ConsoleStripeGoogle BigQuerySnowflake
Need something exotic? Custom CRM, internal data warehouse, niche ad network. Send us the spec; we ship connectors continuously.
Pricing

One plan. From €199, capped at €1,000.

You pay 1% of your monthly ad spend — minimum €199, maximum €1,000. Pricing will always be published openly.

Datacompany
Beta
€1,000
/ mo max.
per month max. — 1% of ad spend, minimum €199, whichever applies.
Calculate your price
Monthly ad spend
€25,000
Your price
€250/ mo
€1,000€200,000+
1% of your monthly ad spendExpected savings at 10% waste reduction: €2,500
  • Full marketing mix model, rebuilt continuously
  • Daily, weekly and monthly insights
  • Holdout experiments planned and analysed
  • Direct line to a senior data scientist
  • All standard connectors included
  • Custom CRM connector on request
Apply for the beta
Beta access by invitation. We onboard a small cohort each month.
iWe will always publish pricing changes openly before they take effect.
Who is behind this
Jeroen Oosterveld
Jeroen Oosterveld
Founder, Datacompany
ex-Coolblue
Photo: Wouter Brem

Built by someone who’s been in your seat.

Jeroen Oosterveld previously led data and growth work inside Coolblue, one of the largest e-commerce companies in the Benelux. Datacompany exists to make the same caliber of analytics available to businesses that do not have a hundred-person data team. A small group of senior freelancers supports the build.

Connect on LinkedIn
Beta waitlist

Join the beta. We onboard a few companies each month.

Tell us a little about your business. We will reach out personally when your slot is ready.

Prefer to call? +31 50 211 5978

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