We analyzed the campaign data of an international corporation. The result: the simplest management questions can't be answered — even though all the data is there.
Each agency has its own naming logic. Each works locally. None is compatible with the others.
| Country | Label | Language | Level |
|---|---|---|---|
| France | Heat pump/Air conditioning | English | Ad set |
| Belgium | Warmtepomp | Dutch | Campaign |
| Belgium | Warmtepompen | Dutch (plural) | Campaign |
| Sweden | BERGVÄRME | Swedish | Campaign |
| Sweden | LUFTVÄRME | Swedish | Campaign |
Even within Belgium, "Warmtepomp" and "Warmtepompen" exist as separate campaigns — singular and plural, impossible to reconcile without manual mapping.
The platforms deliver KPIs that share names but measure different things. A direct comparison looks possible — but is methodologically invalid.
| KPI | Facebook (FR) | Google (BE/SE) |
|---|---|---|
| Clicks | "Link Clicks" (link clicks only) | "Clicks" (all clicks) |
| CTR | Based on link clicks | Based on all clicks |
| Conversions | Separate: Website Conversions + Website Leads | Combined: "Conversions" |
| Reach | Available | Not available |
| Impression Share | Not available | Available |
| Currency | EUR (explicit) | Unknown |
A CPC comparison between Facebook and Google is methodologically invalid with this data — because the platforms count different things as a "click."
Campaign names are optimized for agency billing, not for client decision-making. The Swedish agency wrote its internal order number (ONR: 19825) into the campaign name — useful for their invoicing, useless for the client.
On top of that: in many companies, the ad accounts — Google Ads, Meta Ads — don't belong to the company. They belong to the agency. The client receives their own data as a manual CSV export. Automated data access through ETL tools is frequently blocked.
Workarounds don't work either: Landing pages and UTM parameters could theoretically serve as cross-channel grouping criteria — but they suffer from the same standardization problem and aren't even present in this data.
Instead of three conventions, one unified schema — language-independent and machine-readable:
Because the structure is clean, for the first time: budget shifts across all markets in one operation. Budget cuts with instant impact on all financial KPIs. New budget processes at the push of a button instead of a 4-week marathon.
Cross-channel performance comparison in hard currency. Automated aggregation across all countries and channels. ROI analysis at the product level instead of the campaign level.
Three files, one brand, one quarter — and zero ability to meaningfully aggregate the data. Not because of missing technology, not because of bad tools, but because the fundamental data structure is missing.
Four blocker layers: Naming chaos (5 names for one product). Agency optimization (names built for billing, not decisions). Account ownership (agencies block ETL access). No workaround (landing pages and UTMs don't help either).
Any tracking tool would import this data and display it "aggregated" — based on incompatible conventions, unclear currencies, and different KPI definitions. The result: organized data waste in pretty dashboards.
Mykorisa solves the problem one layer deeper: at the data structure. Only when "Warmtepomp" and "BERGVÄRME" and "Heat pump" are recognized and uniformly named as the same product does tracking become possible at all.
In 30 minutes, we'll determine if the same problem exists in your marketing data — and where the biggest leverage lies.
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