Italy’s YouTube Sales Ads Leave Images on a Smaller Budget
In a 90-day Italian retail marketplace sample, image ads received near-text median spend for traffic but far less for sales. Here is what the data does and does not show.

Italian retail marketplace advertisers use text as their default YouTube ad format, whether the stated objective is traffic or sales. The striking difference is how they fund images: image ads receive median spend close to text for traffic, but much less for sales.
Over the 90-day measurement window, the traffic cohort included 3,349 ads from three brands. The sales cohort included 4,449 ads, also from three brands. This is a concentrated advertiser sample, not a census of the Italian marketplace sector. Even so, the contrast in median spend by format is pronounced. [^paid-traffic] [^paid-sales]
| YouTube objective | Text ads: median spend | Image ads: median spend | Image spend relative to text |
|---|---|---|---|
| Traffic | €6,848.39 | €6,036.11 | About 88% |
| Sales | €6,787.64 | €1,081.98 | About 16% |
For traffic, the median image-ad spend is about €812 below the text median. For sales, the gap grows to more than €5,700. Text spend is almost unchanged between objectives, while image spend is sharply lower in the sales cohort. The evidence points to a format-specific difference in budget allocation, rather than a general pullback in paid support. [^paid-traffic] [^paid-sales]
Images are funded differently when the objective is sales
The cohort data suggests that advertisers are willing to give images a meaningful role in traffic campaigns. Their median spend is close to that of text ads, making images a substantial alternative in the traffic mix.
In sales campaigns, images appear to receive much less investment. They may be used as limited tests or supporting variants, while text remains the principal format. That is a description of observed spending, not proof that advertisers distrust images or that image ads convert less effectively.
Operator read: Treat the budget gap as a hypothesis to investigate, not a verdict on creative performance. The sample shows what advertisers spent by format. It does not show which ads generated more sales.
The distinction matters when a team moves a campaign from traffic to sales. An image that was funded at a level comparable to text in a traffic plan may not carry the same budget in a sales plan. Teams should make a fresh creative and measurement plan for that transition rather than assuming the format will be funded the same way.
This is an allocation benchmark, not a performance ranking
The paid-cohort data includes no CPM values. Reach-per-day percentiles are zero, so they do not provide a useful basis for comparing reach either. The figures therefore do not establish that text buys cheaper impressions, that images generate weaker conversion rates, or that either format performs better in the auction.
What the data does show is a difference in budget architecture:
- Traffic: Text leads, but image ads receive median spend close to text.
- Sales: Text remains at a similar median spend, while image spend is much lower.
For operators, the practical test is whether an image-led concept can earn a larger sales budget after demonstrating value. That requires comparing formats on the campaign’s actual business objective, not relying on spend patterns from other advertisers as a measure of effectiveness.
Organic YouTube can help generate test ideas
The organic sample is broader, with 2,693 posts from 17 brands. A median post received 3,933 views and 184 interactions, with a 3.47% engagement rate. At the 75th percentile, posts received 18,875 views and 952 interactions, with a 7.35% engagement rate. [^organic]
The distance between the median and upper-quartile results suggests that organic posts can help teams find concepts worth investigating. A product demonstration, offer framing, creator treatment, or visual hook that attracts strong viewing and interaction may provide a useful starting point for paid creative.
That does not mean every organic winner should be turned into an image-led sales ad. A more disciplined process is to:
- Identify organic concepts with unusually strong viewing and interaction results.
- Adapt a promising concept into both a text-led sales control and an image-led challenger.
- Give the image challenger a credible traffic test, where the cohort shows images receive funding closer to text.
- Increase its sales investment only if it meets the relevant business performance threshold.
The current sample shows a clear difference in how three advertisers fund image ads across objectives. It does not settle whether images can sell effectively. Until performance testing answers that question, text is the more consistently funded sales format in this cohort, while images remain a meaningful traffic option and a source of hypotheses to test.
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