Guides

Lifestyle product images for the whole catalog - without a photoshoot

A white-background photo shows what a product is; a lifestyle photo shows how it looks in life. What Google allows in lifestyle_image_link, where these pictures work on Meta, why AI is finally good enough - if the product stays the product - and how to make them for thousands of products at once.

By Evaldas Gudavičius, Karolis Sukackas and Julijus Bogdanovas · 19 October 2026 · 8 min read

Lifestyle product images for the whole catalog - without a photoshoot

Most catalogs have one photo per product: the product on white. It is the right photo for the job it does - it shows exactly what you sell. What it cannot show is how big the sofa is in a real room, how the coat falls when someone walks, whether the earrings are delicate or bold. That is the job of a lifestyle photo, and it is the one most stores never have, because a photoshoot does not scale to 3,000 products and 40 new arrivals a week.

This guide covers what Google and Meta accept, where lifestyle pictures help, what changed with AI - and the one rule that decides whether an AI picture is an asset or a liability.

Two photos, two different jobs

Google has a separate field for each job. image_link is the main image: the product alone, clearly visible. lifestyle_image_link is for "a lifestyle image" of the product - Google’s own examples are "clothing worn by a model" and "furniture staged within a room" (Google). The two do not compete: the main photo stays, the lifestyle pictures travel next to it.

image_link: the product alone on a plain light background, every product needs one, no scene or text; lifestyle_image_link: the product in use in a real setting, at least 600 × 600 px, AI images allowed with AI metadata, no text, prices, logos or borders

The rules for lifestyle_image_link, from Google’s specification (Google):

Up to 5 lifestyle images per product, at least 600 × 600 pixels.
No promotional elements or text - no calls to action, prices, logos or barcodes - and no borders or padding to reach the aspect ratio.
AI-generated images must say so in their metadata (for example the IPTC DigitalSourceType value TrainedAlgorithmicMedia), and the metadata must not be stripped (Google).
Where they show: Google describes them as images shown in free listings for the product.

Never put a lifestyle picture into image_link. The main image still has to show the product clearly on its own; the scene belongs in the lifestyle field.

Where lifestyle pictures help

Google free listings - through lifestyle_image_link, next to your main photo.
Meta catalog ads - Facebook and Instagram take extra product images from the catalog, and a picture of the product in use is the kind of image a feed placement is made for. Here you may also add a price or a badge, which Google’s lifestyle field does not allow.
Stories and Reels - a tall 9:16 picture fills the screen; Google does not take that shape, Meta does.
Your own channels - category pages, emails and social posts, where a consistent look across hundreds of products is otherwise out of reach.

AI is good enough now - if the product stays the product

Image models can put a product into almost any scene in seconds. The risk is not an ugly background; it is a picture that quietly changes the product: a logo redrawn, a watch dial with the wrong numbers, a sneaker with an extra stripe, a pattern "improved". On a product listing that is not a creative choice, it is a misdescription - and the customer who orders it sends it back.

So the useful question about any AI tool for catalog images is not "how pretty" but "how does it know the product did not change?" Look for three things:

It starts from your photo. The product is drawn from the product photo in your feed, not from its title.
It checks every picture against that photo - shape, colours, materials, every printed word and number - and throws away the ones that fail.
It keeps the file as generated, so the AI metadata Google asks for is not stripped by re-encoding.

Every category, its own scene

A good scene is specific to the product: a bed seen from above, a puffer jacket on a snowy street, a milk jug at an espresso bar, a watch on a wrist at the wheel of a boat. One scene for the whole catalog looks like a template; one per category looks like a shoot.

Eight products from different categories with their product photos and the lifestyle pictures drawn from them: a linen double bed from above, a red puffer jacket on a snowy street, a copper milk jug at an espresso bar, a diver watch on a wrist at a boat’s wheel, a sunscreen spray bottle by a pool, a wooden balance bike in a garden, a white ceramic cat bowl on a window sill with a cat, a smartwatch on a runner’s wrist at sunrise

When you write the scene yourself, describe the place, the camera and the light - never the product. "A bright Scandinavian living room with a big window, photographed from far" works for every sofa in the catalog. Leave out text, prices and logos: they are refused in Google’s lifestyle field anyway, and on Meta they belong on a separate layer, where they stay sharp and follow the feed.

One product, several shots

Google takes up to five lifestyle images per product, and the shots that sell are different ones: a close-up of the fabric, the product at eye level, the whole room. Asking for a different camera position is enough - the product stays the same, only the picture changes.

One feed photo of a teal mid-century armchair and six lifestyle pictures drawn from it: close-up, from close, eye level, from far away, from above and from a low angle

How to do it for the whole catalog

In PPCDATAFEED this is Lifestyle images, a template type in the Image Editor. It reads the product photo from your feed and writes the pictures into a field of their own - the main photo is never touched.

Pick the catalog and the field. The data source, the photo field it reads, and the field the pictures are written to.
Set a scene per group of products. One row per category or brand - a scene from the prompt library of 145, your own sentence, or Auto, which picks a fitting place for each product. The top row that matches a product wins.
Choose how many pictures. One to five per product, each with its own scene and size: 1:1 or 4:5 for Google and Meta, 9:16 for Stories and Reels.
Look at free previews on four of your own products, change a scene, try again.
Switch it on. The whole catalog is drawn in the background and written to the feed. After that, only new and changed products are drawn.

PPCDATAFEED Lifestyle images template on the Demo store catalog: free previews of a rust velvet corner sofa, a brass arc floor lamp, a chef knife and white leather sneakers, each drawn in a sunlit living room, with the setup panel on the right

Every picture is checked against the product photo before it reaches the feed. A picture with a different product, changed text or numbers, added writing or a broken shape is drawn again, up to three times; if it still fails, the product simply keeps its own photo. You pay only for the pictures that pass - previews and failed tries cost nothing. The step-by-step setup is in the help article.

The Prompt library in PPCDATAFEED: the scene Sunny loft - the whole room, with a slider between the product photo of a rust velvet corner sofa and the lifestyle picture, the prompt text and the buttons Use this prompt and Edit as my own prompt

Checklist

The main image_link stays the product alone; lifestyle pictures go to lifestyle_image_link.
At least 600 × 600 px, no text, prices, logos, borders or padding in the lifestyle field.
AI pictures keep their AI metadata - no re-encoding that strips it.
Every picture is checked against the product photo; a changed product never reaches the feed.
One scene per category or brand, written as place, camera and light.
Several shots per product where it helps: close-up, in use, the whole room.
Prices and badges only on Meta, as a layer that follows the feed.