Understanding attribution in Meta Ads matters just as much as understanding ROAS. Many marketers check results daily without realizing how first click versus last click completely changes what those numbers actually mean.
What the Meta Ads dashboard shows
Before getting into attribution models, the core metrics worth knowing: total clicks (how many people clicked the ad — more clicks signals higher interest), amount spent (total campaign spend), total revenue (how much the ads actually generated), total orders (number of purchases or conversions), and ROAS (return on ad spend — if ROAS is 2.15, every $1 spent generated $2.15 in sales; green ROAS means profitable, red means losing money).
First click attribution: top-funnel credit
In first click, the first ad a customer clicks gets 100% of the credit — even if they buy days later through a completely different ad. This model is best for brand awareness, cold audience testing, and identifying which ads actually attract people initially. Using first click shows which campaign opened the funnel. Meta’s own attribution documentation covers the mechanics directly.
Last click attribution: bottom-funnel credit
In last click, the final ad clicked before purchase gets the credit. This model is best for measuring conversions, optimizing ROAS, evaluating retargeting performance, and testing which offers actually close the sale.
Why smart advertisers use both
Relying on only one model tells an incomplete story. First click shows what attracted the customer; last click shows what converted them. Comparing both reveals which ads build awareness, which drive purchases, where the customer journey starts and ends, and which campaigns actually deserve more budget.
Further reading
Related reading on this blog:
Final takeaway
First click versus last click was never really about choosing one model forever — it’s about understanding how each shapes the numbers. Read the data correctly, and scaling gets easier, ROAS becomes clearer, budget waste gets eliminated, and decisions get sharper. The numbers don’t lie — they just need the right interpretation.