AI Infographic for Product Listings: What Goes on the Slide and What Doesn't

Building an AI infographic for product listings comes down to two steps: generate a scene with the product, then lay text on top. The first part almost never causes problems. The second one does, because whatever you write on a listing image is a claim you're on the hook for.

The tension that runs through everything

An infographic has to sell, which pushes you toward overpromising. It also has to match the real product, or you end up with returns and complaints.

Every slide gets tested against that tradeoff. "Lasts 10 years" on a pot with nothing in the spec sheet to back it up isn't marketing copy, it's a liability.

That's the rule Flami's team doesn't bend on: the infographic only says what's already in the product description and backed by actual specs.

What to generate, what to overlay

Generate the scene, the background, the product in context, graphic elements, icon backgrounds.

Overlay every single word of text. No exceptions.

Here's why. Here's why. Few models handle baked-in text well, and even the good ones start drifting once a phrase gets long. And if you catch a typo after the fact, overlay lets you fix it in a few seconds, while baked-in text means regenerating the whole frame from scratch.

If the words genuinely have to live inside the scene, say they're printed on the packaging itself, that's when Ideogram 3.0 or GPT Image 2 earn their keep. How much quality swings between models is something we measured separately.

A slide structure that actually works

Slide one answers "what is this." The whole product, large, unmistakable.

Slide two kills the category's biggest objection. For electronics that's compatibility, for apparel it's fit, for food it's the ingredient list.

Slide three sets the scale. A familiar object or a person standing next to the product.

Slide four covers what's in the box.

Slide five closes out the quality question: a close-up on stitching, material, a mounting bracket.

I go back and forth on slide five. In half the categories nobody scrolls that far, and I sometimes wonder if it's worth keeping at all.

The order can shift, but the first two slides carry more weight than the rest. Not everyone scrolls past them.

Mistakes that show up again and again

Text too small. On a phone, the listing image takes up a third of the screen, and eight-point captions just don't read.

Five ideas crammed onto one slide. One idea, one slide.

Text sitting over a face or over the one detail that actually sells the product. Leave room for copy when you generate the scene, not after.

Other brands' logos sneaking into the frame. Models love adding them in on their own, and there's a separate piece on that.

Slides that look nothing like each other in style. The fix is generating every background in one batch, with the same palette and lighting description.

The batch workflow for an AI infographic for product listings

Start by writing all the copy for every SKU first. Text before images, always, otherwise the scene gets built around words that don't exist yet.

Next, generate backgrounds and scenes as one batch, with identical lighting and palette notes.

Then assemble the slides in an editor and lay the text on top.

Last, check everything on a phone. Not a monitor.

The full listing workflow is laid out separately, and on Flami you can run a whole batch of scenes at once so the palette doesn't drift between SKUs.

FAQ

Can an AI infographic for product listings be built entirely by a model? The scene and background, yes. Text is safer added on top in an editor. Text rendering inside a generated image is inconsistent across models, and a correction means regenerating instead of just swapping a layer.

How many slides does a listing need? Usually four to six. The first two matter most, since they explain what the product is and knock out the category's main objection.

What text is safe to put on an infographic? Only claims backed by the product specs. Promises without backup lead to returns, complaints, and sometimes a pulled listing.

Why doesn't the text on my slide read well? It's almost always too small. Listings get viewed on phones, where the image is a fraction of the screen. Always check readability on a phone, not a desktop monitor.

How do I keep slides visually consistent? Generate every background in one batch, with a shared palette and lighting description, rather than one at a time on different days. That's what makes slides read as a set instead of a pile of mismatched images.

Sources

1. Flami: infographics and text on a product image
2. Flami: text rendering across AI models
3. Flami: other brands showing up in the frame