Marketing measurement, finally honest

Find your
ideal mix.

Pareto is the marketing measurement platform that tells you where every euro went — and where the next one should go. Bayesian model under the hood. No PhD required.

Avg. ROAS lift
+0%
Wasted spend caught
0.0M
Time to first insight
0h
Channels modelled
0+
Trusted by marketing teams that ship
BOLT
Tessellate
WAYFAIR
Lumen.co
Northstar
Maven.io
+34%avg. ROAS lift
€2.8Mwasted spend caught
72htime to first insight
28+native connectors
<2 weeksto first model
94%model recall
0consultancy retainer required
+34%avg. ROAS lift
€2.8Mwasted spend caught
72htime to first insight
28+native connectors
<2 weeksto first model
94%model recall
0consultancy retainer required
How it works

From CSV chaos to
"that's where the money goes."

Four steps. No PhD. No consultancy retainer. The whole thing can be live in your stack in two weeks.

01

Plug in your data

Connect Google, Meta, TikTok, your DWH, even that one CSV your CFO loves. We handle the joins.

G
M
T
Y
x
02

Run the model

A Bayesian model trained on your 2+ years of spend, conversions and external signals. Adstock, saturation, baseline — handled.

03

Find your mix

Saturation curves per channel. The optimizer picks the allocation that maximises your KPI under your constraints.

+42%
04

Ship it. Track it.

Push the new mix to your media plan, then keep the model fresh as new data comes in. Weekly. Monthly. Whatever.

Google Search▲ €240k
Meta Ads▲ €80k
Display▼ €120k
The hierarchy

From the mix down to
the next campaign brief.

Other tools give you ONE layer of analysis. Pareto cascades — strategic decisions at the top, line-item actions at the bottom. Each level feeds the next.

01
STRATEGIC

MMM

The mix.

Where does revenue come from? Channels, baseline, halo. Bayesian decomposition over 24+ months — the answer your board cares about.

What's working?What's saturating?Where to shift?
OutputChannel contribution & marginal ROI
Google · 28%Meta · 22%TikTok · 14%Baseline · 24%
feeds
02
GRANULAR

Attribution

The touchpoints.

Inside each channel, who actually drove the conversion? Data-driven attribution layered on top of MMM priors — last-click finally goes to therapy.

Which touchpoint?What's incremental?What's just along for the ride?
OutputPer-touchpoint incrementality
SearchSocialVideoDisplayCONVERSION+42%incremental
feeds
03
TACTICAL

Campaign analysis

The line items.

Drill into each campaign, ad group, audience. Which creative is fatiguing? Which audience is still scaling? Which placement is bleeding budget?

Which campaign?Which creative?Which audience?
OutputPer-campaign health & opportunity score
IT_prosp_lookalike
fatigue
3 ads in fatigue · CTR −34% / 14d
ES_search_adv_25-34
scaling
CPA stable · room +€18k/mo
FR_tt_creator_25-34
scaling
ROAS 4.1× · 2 hooks winning
DE_yt_demandgen_30-49
watch
Plateau · test 25-34 segment
UK_pmax_lookalike
cut
Incrementality 0.18 · cannibalises brand
feeds
04
ACTIONABLE

Performance actions

What to do Monday.

Concrete recommendations for the performance marketing team. Push this campaign, pause that one, refresh creative here, expand audience there. Ranked by expected lift.

Push.Pause.Refresh.Expand.
OutputPrioritised action list
REFRESH
IT_prosp_lookalike
Why · 3 of 5 ads in fatigue · CPM +28%, CTR −34% (14d)
Do · Refresh creative on ad_v07, ad_v12, ad_v18
+€8.2k88% CONF
PUSH
ES_search_adv_25-34
Why · Below saturation · marginal ROAS 4.6×
Do · Push +€18k/mo · raise tCPA cap to €22
+€42k92% CONF
EXPAND
DE_yt_demandgen_30-49
Why · Plateau on 30-49 · 25-34 unserved
Do · Duplicate to 25-34 · same creative pack
+€15k est.76% CONF
PAUSE
UK_pmax_lookalike
Why · Incrementality 0.18 · cannibalising brand search
Do · Pause immediately · reallocate to Search
saves €12k94% CONF
The result

Your performance marketing team stops debating what to test next — and starts shipping a prioritised plan, every Monday.

Features

Everything your
analytics stack promised
and never delivered.

Six modules. One platform. Built for marketing teams that have outgrown attribution dashboards but don't want to hire a Bayesian statistician.

  • 01Bayesian MMM
  • 02Budget optimization
  • 03Channel ROI & ROAS
  • 04Forecast & what-if
  • 05Real-time dashboard
  • 06Integrations
Bayesian MMM

Marketing mix modeling, served warm.

We run a fully Bayesian MMM on your data — adstock, saturation, baseline, the works. You get response curves, contribution decomposition, and credible intervals you can actually defend in a board meeting.

Response curvesContributionBaseline
Saturation per channel · last 24 months
Current spend
Google
Meta
TikTok
YouTube
Try it · No login

Drag the sliders.
Watch your CFO smile.

A toy version of our optimizer, running on synthetic but realistic response curves. Move budgets around. Hit Optimizeto see Pareto's recommendation. Yes, this is what the real one feels like.

Allocate your budget
Monthly · €1,200k
Google Search
33%
€400k/mo
Meta Ads
25%
€300k/mo
TikTok
10%
€120k/mo
YouTube
13%
€150k/mo
Display & PMAX
15%
€180k/mo
OOH
4%
€50k/mo
Total monthly spend€1,200k
Live model · synthetic
Predicted revenue
2.13M
+€0k vs. baseline
Blended ROAS
1.78×
+0.00× vs. baseline
Marginal channel
TikTok
▲ next euro best spent here
Channel contribution
35%
23%
13%
12%
10%
Google Search
Meta Ads
TikTok
YouTube
Display & PMAX
OOH
💡 Pareto says: looks fine. Try the optimizer — there's almost always more revenue hiding.
Pareto AI · powered by your data

Ask in plain English.
Get answers,
not 14-tab spreadsheets.

Pareto's AI sits on top of your MMM. It reads model outputs, anomaly logs, and your media plan — then explains what happened, what to do next, and why your CMO's gut feeling was right (or wasn't).

Why did revenue drop last week?
Talk to us

Let's find
your mix.

Drop your details. We'll come back with a 30-min walkthrough on your data within 48 hours.
No 4-step discovery funnel. Just a demo.

Time to first model
2 weeks
Connectors built-in
28+
Avg. ROAS lift
+34%

Book a demo

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