Who we build for
Every company knows more than half of their analytics data is missing. We build for the operators who refuse to keep making decisions on top of it — regardless of sector, country, or revenue band.
Every company running digital marketing already knows the problem. More than half of their analytics data is missing. Around 30% of sales never reach the dashboard. Of the 70% that do, channel attribution is wrong in ways that cannot be untangled after the fact.
This chapter is not about teaching you that — you already know it. It is about the line between companies that have made peace with broken data and companies that refuse to. We build for the second group, regardless of sector, country, or revenue band.
The numbers everyone already knows
The pain shows up in three layers. Each one is measurable, broadly known among practitioners, and not specific to any industry or geography.
of analytics data is silently lost
Consent rejection, ad blockers, browser restrictions, and modelling gaps combine to push the measured share well below what the dashboard suggests.
of sales never reach the report
Transactions complete on devices, sessions, or paths the tag-based collector does not see. They show up in the ERP. They do not show up next to the channel that drove them.
of visible sales are misattributed
Last-click on partial data assigns credit to whichever channel happened to be measurable when the conversion fired — usually direct, branded search, or whichever platform self-reports most aggressively.
The compound result: marketing teams optimise budget against a sample that is incomplete, biased, and wrongly labelled — and they know it. The cascade behind the first number is detailed in chapter 03.
The operator we build for
The differentiator is not the size of the company. It is not the industry. It is not the headquarters. Companies that fit our profile operate in every market we ship to — retail, travel, finance, subscription, B2B — and across every continent we have measured.
What sets them apart is one decision: they have stopped accepting the dashboard as ground truth.
- Refuses to make material budget decisions on broken data.When the spend gets large enough that misallocation costs more than measurement, the question stops being “what does GA4 show?” and becomes “what actually happened?”
- Has tried the patches and seen the results.Consent-rate optimisation. Server-side GTM. Modelled conversions. Each closes a small fraction of the gap; none of them changes the underlying number. The operator who has been around long enough has stopped expecting the next patch to work.
- Is held accountable for outcomes, not for dashboards.The CFO does not care that the analytics platform claims a 4.2 ROAS. The CFO cares whether revenue tied to spend reconciles against the ERP. This mindset is the one we close.
"The common factor is the refusal, not the profile. Customers fit our model across revenue bands, industries, and continents. What connects them is that they stopped pretending the dashboard was enough."
The personas who push for change
Three roles tend to drive evaluation. Each one cares about a different layer of the same problem.
CMO / VP Marketing
OwnsThe budget that gets misallocated.
YesWhen the conversation moves from “analytics tool” to “the math that makes the budget defensible to the rest of the executive team”.
Head of Growth / Performance Marketing
OwnsThe day-to-day decisions GA4 informs.
YesOn the difference between last-click on complete data and modelled multi-touch on the visible fraction.
Head of Analytics / Head of Data
OwnsDashboard reliability and data quality.
YesOn the architecture, the sub-processor list, query-time freshness, and exportability — not on the slides.
The DPO, CTO, and procurement leads come in later, after the marketing function has decided the product is worth pursuing.
When we don't fit
Honest disqualifications save quarters. None of them is about sector, country, or revenue band. They are about the relationship to the problem.
- Material digital marketing spend
- Measures transactions, signups, or revenue events
- Has stopped accepting GA4 as ground truth
- Wants defensibility, not just dashboards
- Will add a measurement layer alongside the existing stack
- Comfortable optimising on platform-reported numbers
- Brand or impression metrics are the primary KPI
- Paid acquisition spend is too small to move the budget
- Needs session replay or individual-level tracking
- Mobile-app-only — we measure web
Three patterns worth naming explicitly:
- You are content with what GA4 shows. If the dashboard meets your needs and your reporting line accepts it, the value of replacing it is small. The cost of switching is not zero.
- Your measurement problem is something other than attribution. Audience analytics, ad-impression tracking, content ranking, and brand lift are different measurement problems handled by different tools.
- You need individual-level behavioural tracking. Session reconstruction, cross-device journey mapping, and CDP-style profiles are not what we ship. Chapter 09 covers this in detail.
For the cases where the product fit is wrong and the situation needs other hands, we work with four implementation partners. We do not take commission from referrals — we make them when the product is the wrong answer.
Product Hackers
Growth-marketing-led implementations. Strong on cross-channel attribution and CRO workflows.
3dids
Technical implementations. Strong on tag management, data-layer architecture, and CMP migrations.
Ayesa
Enterprise consulting partner for larger transformations across multiple business units.
Datarmony
Data and analytics consultancy. Strong on measurement strategy, dashboard design, and bridging analytics with business decisions.
If the product is not the right answer for your situation, ask us — the answer will be honest, not branded.
Continue with chapter 03 — What complete data means.
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