Performance Marketing
Marketers are told to combine MMM, MTA, and experiments for a complete view of performance. In practice, triangulation often fails: broken attribution, weak experiments, and historic-only MMM lead to conflicting signals and decision paralysis. Here are 5 reasons why marketers should rethink this approach.
Read morePerformance Marketing
Monday morning: a tariff changes, energy prices jump 15%.Two weeks later: demand moves because the weather changes.Then a competitor launches a new offer in one region. And the media budget? Still split exactly like it was in the planning meeting last month 😉 This is probably the biggest difference we see in energy compared with […]
Travel and mobility have one very obvious problem: customer demand is moving all the time; it is not just seasons it’s travel behavior trends and changes, geopolitics, global warming, etc. For example: a route suddenly becomes popular, another destination is almost full, a train/plane or ship has plenty of seats left. A competitor changes prices […]
Performance Marketing
ROAS is great, everybody understands it, it updates fast, and it gives you a nice number to put into a dashboard. Great 😉But it can also make budget allocation look much easier than it really is. Lets take an example: Imagine Campaign A has a ROAS of 800% and Campaign B has a ROAS of […]
KI & Marketing
Performance Marketing
A cheap lead is not always a good lead, and that sounds obvious. But a lot of paid media optimization still works as if it were not true. Example: An insurer sees a calculator entry, a bank sees an account application, the ad platform sees a conversion and starts optimizing for more of them. Great […]
We built better measurement, but forgot to move the budget 😉 Marketing teams love dashboards. We built reporting layers, attribution models, CRM integrations, weekly reviews, and increasingly sophisticated measurement stacks. That was necessary, but there is an uncomfortable question I keep coming back to: How often does better measurement actually help us change where the […]
TL;DR: From 1 June 2026 on, Google Ads keeps your hourly, daily and weekly data only for 37 months, and reach and frequency for 3 years. Monthly and yearly aggregates survive 11 years, but those are useless for modeling future measurement. So the data your model needs most is the google ads data that disappears […]
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