Marketing has always generated data — what changed is the ability to use it to decide. Moving from "we think this campaign went well" to "we know exactly what it returned" is the difference between spending on marketing and investing in marketing.
The problem with vanity metrics
Likes, followers and reach look great in reports but rarely explain whether the business grew. They are vanity metrics: they feel good, they do not help you decide. Data-driven marketing starts by swapping them for metrics tied to revenue.
The metrics that matter
- CAC (customer acquisition cost): how much, on average, it costs to win a new customer.
- LTV (lifetime value): how much a customer returns over the relationship.
- LTV/CAC ratio: for every euro spent acquiring, how much comes back — below 3 is usually a warning sign.
- Conversion rate by channel: where investment actually turns into customers.
Attribution: crediting who deserves it
A customer rarely buys on first contact — they see an ad, read an article, get an email, and only then convert. Attribution tries to understand which channels contributed. Simple models (first/last touch) mislead; it pays to look at the full journey before cutting a channel that seems not to "sell".
From report to decision
Marketing data only matters if it changes the next move: reallocating budget from the channel with the worst LTV/CAC to the best, tuning the message that converts, or stopping what does not pay. If a dashboard changes no decision this week, it is decorating, not informing.
In practice
Pick two or three revenue-linked indicators, measure them by channel and review them regularly. Data-driven marketing is not having more charts — it is spending every euro where it returns most. Do you know today which channel has your best LTV/CAC?
