One Italian Marketplace Advertiser Is Using TikTok as a Creative Testing Lab

A single advertiser accounted for the paid TikTok activity in a 90-day Italian retail-marketplace dataset. That makes the data unsuitable as a market benchmark, but it offers a useful case study in how one brand is allocating spend across creative.

All 28 ads in the observed set were videos. Median spend per ad was €101.85, while the 25th and 75th percentiles were €72.75 and €1,600.50, respectively. The distribution suggests a mix of modest deployments and a smaller number of substantially higher-spend ads. It is consistent with a test-and-scale approach, though the data alone cannot confirm the advertiser’s intent or the performance of individual creative. ¹

Treat early spend as a way to learn

The practical lesson is not that every advertiser should start with a specific budget. It is that early spend can be designed to answer a question before a team commits more money.

Marketplace marketers can separate creative learning into three questions:

1. Does the opening earn attention?
2. Does the product or value proposition hold attention?
3. Does the idea remain effective when spend increases?

Testing these questions together can make results harder to interpret. If a campaign changes its creative, targeting and budget at the same time, it may be difficult to tell what drove a change in performance. A staged approach can make the learning process more legible: launch with a defined hypothesis, review the evidence, then decide whether to stop, revise or increase investment.

Low observed CPM does not replace creative judgment

The median CPM among ads with CPM data was €0.291. CPM values were available for 22 of the 28 ads, so this figure describes the observed subset, not every ad in the dataset. ¹

A low observed CPM can make paid delivery inexpensive, but it does not show whether an ad drove product-page visits, purchases or profitable customer acquisition. Nor does it establish that the same price or results would be available to other advertisers. Media cost is only one part of the decision; teams still need to judge whether the creative reached the right audience and produced useful downstream outcomes.

For a testing program, make each creative hypothesis distinct enough to evaluate. Possible angles include price, breadth of selection, convenience, trust or discovery. A set of videos featuring different products may still represent only one test if the opening, claim and retail mechanic are effectively the same.

Labeling each test before launch helps teams compare like with like. A creator-led product demonstration and a price-led montage, for example, are different communication approaches, even if both feature the same item. The review should assess the idea as well as the individual edit.

Establish a clear promotion rule

The spend percentiles show a wide gap between typical ad spend and upper-quartile spend in this dataset. That may reflect selective allocation, but it does not reveal why particular ads received more investment or whether higher spend produced better results. The figures are a prompt to ask how a team makes budget decisions, not proof that one threshold is universally effective.

Before launching tests, agree on what evidence merits the next budget tier. Delivery efficiency may be one input, but the promotion rule should also account for the outcome that matters to the business: product-page visits, app actions, add-to-cart activity, new-buyer acquisition or contribution margin.

A weekly creative review can focus on four decisions:

1. Stop: There is not enough evidence to keep developing the premise.
2. Revise: The idea looks promising, but an execution detail needs work.
3. Promote: The available evidence supports a larger test or budget tier.
4. Develop variants: The premise merits new openings, creators or product examples.

For marketplace advertisers, the broader takeaway is to use low-cost delivery, where available, to support disciplined learning rather than to assume that cheap impressions are success. This single-advertiser dataset shows video-only activity, a modest median spend and a much higher upper-quartile spend. It cannot establish a general TikTok strategy for Italy, but it illustrates why teams should define what they are testing and what will earn further investment.

Footnotes

1. Paid TikTok retail-marketplace activity in Italy, observed over 90 days. The dataset contained 28 ads from one brand. CPM data was available for 22 ads; median CPM among those ads was €0.291. ↩ ↩²