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Service · Data Analytics

Stop guessing which half of your spend works.

KreativeHub is a UK analytics agency that builds marketing attribution and return on investment (ROI) models for medium and enterprise brands. We trace the full path to purchase, credit every channel fairly, and prove which spend actually causes revenue, so you can move budget toward what works and defend the call. Start with a free analytics audit.

demand-index.livesnapshot
+78%Y/Y client growth
3.4×Median ROAS · paid
98%Retention · cumulative
−34%CPL · B2B engagements
LIVE

Measured in pipeline, not pageviews. Senior operators only. Five clients per quarter, capped on purpose.

— studio note
Frame · Notes

Last click is lying to you, and it is costing you budget

Last-click attribution hands all the credit to the final touch, usually a branded search ad or a discount email. The channels that created the demand in the first place, your paid social, display, content and organic search, get written off as wasted. So you cut them, demand dries up, and the numbers get worse.

Marketing attribution fixes that picture. It maps the real customer journey across every channel and assigns credit based on what each touchpoint contributed, not just where the conversion landed. ROI modelling takes it further and connects that spend to actual revenue, customer acquisition cost (CAC) and lifetime value (LTV).

We do not hand you a dashboard and walk away. We build the model on data you can trust, validate it against real incrementality tests, then sit with your team to reallocate budget and watch it hold. This work sits inside the wider data analytics system: attribution is only as honest as the tracking underneath it. Start with a free analytics audit.

Frame · Manifesto · 3 positions
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How we measure what each pound actually does

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Multi-touch attribution for the full journey

Most buyers touch several channels before they convert. Multi-touch attribution gives credit across that whole path, so the awareness channels that start the journey are not buried under the branded search ad that finishes it. We pick a model that fits how your customers actually buy, whether that is a data-driven model, a position-based split or a custom rule set, and we explain the trade-offs in plain terms rather than defaulting to whatever the platform reports.

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Marketing mix modelling for spend you cannot track

Not everything leaves a clean click trail. For larger brands, and for offline, brand and privacy-affected spend, we use marketing mix modelling (MMM): a statistical approach that correlates spend with revenue while accounting for seasonality, promotions and external factors. It gives you a top-down read on channel contribution that survives cookie loss and iOS privacy changes, and it pairs well with the bottom-up detail of multi-touch attribution.

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Incrementality testing to prove cause, not credit

Attribution shows correlation. Incrementality testing proves causation. We run holdout and geo experiments that compare audiences exposed to a channel against ones that were not, so you can see the revenue a channel actually caused rather than the conversions it claimed. This is how you catch the campaigns that look profitable in the platform but would have happened anyway, and how you justify scaling the ones that genuinely lift sales.

Frame · Capabilities · 6 pillars
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What our attribution and ROI modelling covers

The measurement work that tells you where to spend the next pound.

See how attribution fits the full analytics system
  • 01

    Multi-touch attribution modelling

  • 02

    Full customer journey mapping

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    Incrementality and holdout testing

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    LTV to CAC and payback analysis

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    Ad spend efficiency and reallocation

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    Offline and call conversion tracking

Frame · Method · 4-phase flow
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How we build an attribution model you can act on

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01. Unify the data

Attribution falls apart on messy data, so we start by pulling every touchpoint into one warehouse: ad platforms, your website, the customer relationship management (CRM) system and offline conversions. We check it against what your platforms report and fix the gaps first, because a model built on broken tracking just gives you confident wrong answers.

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02. Build the model

We choose the approach that fits your business: multi-touch attribution for click-trackable journeys, marketing mix modelling for spend you cannot track, or both together. We assign credit across the path to purchase and connect it to revenue, CAC and LTV, so the output speaks in money rather than conversions you cannot bank.

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03. Test for incrementality

Before you move real budget, we validate the model with holdout and geo experiments. This separates the channels that cause revenue from the ones that simply take credit for it, and it tells you which lines are over-valued and which are quietly carrying the account.

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04. Reallocate and review

We sit with your team and shift budget toward the channels that earn it, then track the result against the model. Attribution is not a one-off report. We rerun it on a regular cadence as your mix, seasonality and market change, so the numbers stay honest and the decisions keep paying off.

Frame · FAQ · 7 questions
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Attribution and ROI questions, answered

Every question we get asked on first calls. Answered in writing — decide before you book.

It is not useless, but it is misleading. Last-click gives all the credit to the final touch, usually branded search or a discount email, and ignores the paid social, display, content and organic work that created the demand. Brands that optimise purely to last-click tend to cut the channels that drive their pipeline, then wonder why performance falls. We use multi-touch attribution and incrementality testing to show what each channel genuinely contributes.
Multi-touch attribution is bottom-up: it tracks individual customer journeys click by click and works best for digital, trackable spend. Marketing mix modelling (MMM) is top-down: it uses statistics to correlate total spend with revenue, so it captures offline, brand and privacy-affected channels that no longer leave a clean click trail. They answer different questions, and for most medium and enterprise brands the strongest read comes from running both and reconciling them.
Attribution tells you which channels were involved in conversions. Incrementality testing tells you which conversions would not have happened without the channel. We run holdout and geo experiments that compare exposed audiences against control groups, so you can measure the revenue a channel actually caused. It is the difference between a channel claiming credit and a channel earning it, and it is how you avoid scaling spend that was always going to convert anyway.
A multi-touch attribution build on clean, unified data usually takes 3 to 4 weeks. Marketing mix modelling needs more historical data and typically takes longer, since the model has to learn from past seasonality and spend patterns. If your tracking is broken or scattered across platforms, we fix that first during the analytics audit and size the exact timeline against the state of your data.
Yes, and it is one of the main reasons attribution and ROI modelling matter more now. Client-side tracking increasingly fails to ad blockers, cookie limits and iOS privacy changes, so click-based attribution alone leaves blind spots. We pair server-side tracking with marketing mix modelling, which does not depend on individual user tracking, so you keep a reliable read on channel contribution even as the trackable signal shrinks.
Revenue. Conversions are a proxy, and they hide the differences that matter: order value, margin, repeat purchase and lifetime value. We connect attribution to actual revenue, customer acquisition cost (CAC) and LTV, so you can compare channels on what they contribute to the business rather than on how many events they fired. That is what makes a budget decision defensible to finance, not just to marketing.
That is the usual starting point, and it is fine. A model is only as good as the data under it, so we audit your tracking first, identify what is broken or double-counting, and fix the foundations before we build anything. Most historical data can be salvaged. Where it cannot, we tell you plainly and rebuild from a clean baseline rather than modelling on numbers you cannot trust.
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Frame · Apply · new file
apply · q2-2603/05 open
Three slots remain · Q2 ’26

Find out which channels are really paying off

Tell us how you currently measure marketing and where the budget goes. In the free analytics audit we will show you where attribution is misleading you, which channels are over and under-valued, and the highest-leverage fixes, before we ever send a proposal. Senior team, full transparency, no fixed packages.

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