Introduction: when the catalogue becomes the bottleneck
Every Performance Max account hits the same wall after a few weeks of operation. The bids are fine, the feed is clean, the targeting is calibrated, but the creative library is starving. You have ten product photos shot against white seamless three years ago, two lifestyle frames borrowed from the brand site, and a video that exists in 16:9 only because someone’s intern recut a YouTube ad. Google’s optimisation loop, which feeds on creative variety, runs out of fuel. CPCs creep up, ROAS drifts down, and the recommendation tab keeps suggesting that you “add more assets”.
Product Studio is Google’s answer to that bottleneck. It is an AI-powered creative tool baked directly into Merchant Center, designed to manufacture the visual material that Shopping ads, free listings, and Performance Max campaigns now consume in industrial quantities. It does not pretend to replace a photographer for a brand campaign. It does the unglamorous work of generating backgrounds, scenes, lifestyle frames, short videos, and 3D rotations at the scale that algorithmic distribution requires.
The tool has matured rapidly. What launched in mid-2024 as a small experiment for US merchants is now, in early 2026, a fully integrated creative pipeline available across most large markets, with brand-style training, Imagen-3 generation, Veo video output, and direct sync to Performance Max asset groups. This article walks through what Product Studio actually does, how to access it, where it shines, where it still embarrasses itself, and how to fold it into a Performance Max creative refresh cycle without breaking your feed or triggering a wave of disapprovals.
What Product Studio is
Product Studio is a generative imagery and video module hosted inside Google Merchant Center, accessible from the Marketing section of the Merchant Center Next interface. It exposes a small set of tightly scoped capabilities: scene generation around a product, background removal and replacement, image upscaling, lifestyle composition, short video animation through Veo, and 3D rotation export for compatible categories.
The deliberate narrowness is the point. Unlike general-purpose generative platforms such as Adobe Firefly, Midjourney, or Canva’s Magic Studio, Product Studio cannot generate arbitrary scenes from scratch. It always operates on an existing product image as anchor. The AI keeps the product pixels, regenerates everything around them, and stamps the output with IPTC DigitalSourceType metadata signalling AI origin. That metadata is not optional, it is part of Google’s policy compliance for generative content and feeds directly into the disclosure logic that the Shopping team enforces, as documented in the official Google Merchant Center Help.
The other deliberate constraint is that Product Studio outputs land back inside Merchant Center. Generated assets attach to a specific item ID, sit in the catalogue alongside the original photo, and propagate through the feed to Shopping ads, free listings, and any Performance Max campaign that references that catalogue. There is no export-and-reupload dance. This single design choice is what separates Product Studio from Photoroom or Pebblely, and it is also what makes it operationally useful for merchants managing thousands of SKUs.
The underlying models are Google’s own. Imagen-3 powers the still-image generation, with the latest revisions tuned specifically for product fidelity. Veo handles the short video generation, in 6 to 10 second clips at vertical, square, or 16:9 aspect ratios. Both models run server-side; merchants never touch a prompt-tuning interface or a checkpoint, only the simplified Product Studio UI.
Rollout timeline and current 2026 availability
Product Studio launched in May 2023 as an experimental feature for a small group of US Merchant Center accounts, originally under the name “Background Generator”. Search Engine Land covered the initial rollout and noted at the time that the tool was strictly limited to background replacement on existing product photos, with no scene logic and no video output.
The first major expansion happened in early 2024, when Google added scene generation, image upscaling, and the first version of the Animate Image feature. Tinuiti’s reporting from mid-2024 documented the early performance gains observed by their managed accounts, with Performance Max asset variety scores rising materially after merchants ran a Product Studio refresh on their top SKUs.
Through 2024, availability expanded from the United States to Canada, Australia, India, Japan, and the United Kingdom. Search Engine Journal tracked each rollout wave and noted that European availability lagged due to AI Act compliance work, GDPR considerations on training data, and the legal review around generated likenesses.
In 2025, Veo-based video generation was added for the same six markets, and brand-style training entered closed beta. Store Growers covered the brand-style feature and emphasised that this was the moment Product Studio stopped being a generic background tool and started competing seriously with paid alternatives.
In Q1 2026, Product Studio reached general availability across most of the European Economic Area, with the notable exception of France, where rollout remains gated by ongoing regulatory review at the national level. The 2026 wave also brought the Asset Studio integration, allowing Product Studio outputs to flow directly into Performance Max asset libraries without manual export, and the brand-style training feature graduated to general availability for accounts with at least eight reference images.
Russia remains excluded for trade compliance reasons. China is not supported as Google Merchant Center itself does not operate in mainland China.
Access path: Merchant Center to Marketing to Product Studio
Access is straightforward but only obvious once you know where to look. The path is Merchant Center Next, then the Marketing section in the left navigation, then the Product Studio entry. Inside Product Studio, the interface presents four primary tabs: Scenes, Backgrounds, Enhance, and Video.
An alternative entry point exists at the product level. From the Products tab, opening any individual SKU exposes a Generate variations action that calls the same Product Studio backend, scoped to that single item. This per-product entry is convenient for one-off work but slow for batch operations.
For batch work, the dedicated Product Studio interface allows multi-select against the catalogue. You can target a category, a custom label, a brand, or a manual SKU list, and apply the same operation across the entire selection. The job runs server-side and notifies you when complete. For a catalogue of two thousand SKUs, a full background regeneration job typically completes within thirty to ninety minutes depending on Imagen queue load.
Permissions are inherited from Merchant Center. Any user with Standard access or above can use Product Studio. There is no separate licensing, no credit system, no per-generation charge. The tool is fully bundled with Merchant Center for any merchant in a supported region.
Main capabilities
Background generation
Background generation is the original Product Studio feature and still the most reliable. The tool isolates the product, removes the existing background, and generates a new one based on a text prompt or one of several preset scene templates. Presets include studio gradient, marble surface, wood grain, outdoor natural, and seasonal options that rotate with the calendar.
The product cutout itself is handled by a dedicated segmentation model that has improved markedly between 2024 and 2026. Reflective products, transparent products, and products with intricate edges (jewellery chains, lace, mesh) used to require manual touch-up; in the current release they typically come back clean on the first pass.
Scene generation
Scene generation goes one step beyond background replacement. Instead of a flat backdrop, the AI builds a full contextual scene around the product, with consistent lighting, plausible shadows, props, and environmental cues. A leather wallet on a cafe table next to a coffee cup, a kitchen knife on a wooden cutting board with herbs, a sneaker on wet asphalt with neon reflections: these are the kinds of outputs Product Studio handles competently in 2026.
Smart Marketer’s case study coverage notes that scene generation is the feature that produces the largest CTR uplift for Shopping ads, typically in the 15 to 30 percent range when applied to SKUs that previously had only white-background photography.
Image upscaling
Upscaling addresses the legacy catalogue problem. Many merchants still have product photos taken at 600×600 or 800×800 from the early 2010s, well below Google’s recommended 1500×1500 minimum. Product Studio’s upscaler uses a super-resolution model to reconstruct plausible high-frequency detail. The result is not a true higher-resolution photograph, it is a hallucinated reconstruction, but on most product categories the output passes visual inspection at typical Shopping ad sizes.
The upscaler struggles on text-heavy products (book covers, packaging with fine print, electronics with model numbers visible). Generated detail in those areas is often subtly wrong, which matters because the Shopping disapproval system flags misrepresentation when generated text contradicts the actual product.
Lifestyle generation
Lifestyle generation extends scene generation by adding human presence. The AI can place a hand holding the product, a person wearing the apparel, or a model interacting with the item. This is where Product Studio’s policy logic gets strict. For categories where consumers expect to see real humans (apparel try-on, beauty application, accessories on body), Google’s own guidelines require that you do not pass off generated humans as authentic models. The output therefore tends to crop tight, show partial body, or use stylised composition to avoid creating fully recognisable generated faces.
Short video
The Animate Image feature uses Veo to convert a still product photo into a 6 to 10 second video clip. Output aspect ratios cover 16:9, 1:1, and 9:16, which align with Shopping, social, and Performance Max video slot requirements respectively. The motion vocabulary is limited and deliberately so: slow rotation, subtle camera dolly, parallax on the background, gentle light changes. The tool resists generating dramatic motion that would distort the product silhouette.
Audio is not generated. Output is silent MP4. Merchants who need a soundtrack add it externally before uploading the final asset to a Performance Max campaign or YouTube.
3D rotation
3D rotation is the newest capability and the most narrowly scoped. It currently supports two categories: footwear and selected home goods. The feature does not generate a true 3D mesh, it generates a sequence of synthesised viewpoints that combine into a 360-degree rotation viewer for the Shopping product page. The illusion holds up at standard zoom levels but breaks down on close inspection, which is why Google has restricted the feature to categories where the rotation is informative without requiring photographic-grade detail at every angle.
The Imagen-based pipeline behind the scenes
Understanding what is happening server-side helps explain both the strengths and the limitations of the tool. When you submit a generation request, Product Studio runs a multi-stage pipeline. First, a segmentation model isolates the product pixels with sub-pixel precision. Second, an inpainting model fills the background region using Imagen-3, conditioned on either the prompt text or the selected preset. Third, a relighting pass adjusts the product’s lighting and shadows to match the generated environment, which is what makes the composite look photographic rather than collaged. Fourth, a quality filter screens the output for policy violations, anatomical artefacts, and obvious failures.
Imagen-3 is the same family of models that powers Google’s broader generative imagery offerings, but the Product Studio variant is fine-tuned specifically on commercial product photography. This explains why it produces reliably useful output on product categories and reliably odd output when pushed outside that envelope. Asking it to generate a fashion editorial scene gives commercial-but-flat results. Asking it to generate a documentary-style image gives results that look like polished e-commerce. The tool has a default aesthetic and you have to fight it to escape that aesthetic.
The pipeline is also why generation is fast but not instant. Each request typically completes in 8 to 25 seconds for stills and 60 to 180 seconds for video. Batch jobs are queued and processed in parallel, with throughput depending on overall Imagen and Veo load.
AI imagery limits: hands, text, faces
The well-known weak spots of generative image models are still present in Product Studio output, even in 2026. Hands continue to be the canonical failure mode. When the AI generates a hand holding a product, fingers are sometimes too many, joints fold the wrong way, or the wrist articulation looks subtly broken. Product Studio’s quality filter catches the most egregious cases, but borderline outputs slip through and end up in catalogues.
Text rendering is the second weakness. Generated text on packaging, signage, or background props is rarely correct. Letters morph into plausible but invented characters, brand names become near-misses, and any text that ends up on the product itself triggers a misrepresentation review when the rendered text contradicts the actual SKU. The safest practice is to keep generated scenes free of text, prompt the AI to avoid signage and packaging, and inspect outputs for unexpected lettering before approving.
Faces remain the strictest constraint. Product Studio’s policy filter is aggressive about avoiding the generation of fully recognisable human faces, and Google’s broader Shopping policy treats generated humans presented as real models as a misrepresentation. The tool cooperates with this policy by preferring partial bodies, hands-only compositions, or stylised faces, but operators still need to review apparel and beauty outputs carefully.
Beyond hands, text, and faces, less obvious failures include reflections that contradict the scene geometry, shadows that fall in the wrong direction, and material rendering that is plausibly wrong (fabric that looks rubberised, leather that looks plasticky). These are the kinds of errors a trained eye catches in five seconds and an automated pipeline catches in zero. Manual review of high-volume Product Studio output remains necessary.
When AI output is good enough versus when manual photography wins
The honest answer is that Product Studio is good enough for most catalogue work and inadequate for hero photography. The dividing line runs along three axes: brand sensitivity, customer scrutiny, and creative ambition.
For long-tail SKUs, secondary product variants, fast-moving seasonal stock, and bulk catalogue refreshes, Product Studio output is competitive with mid-tier commercial photography and arrives orders of magnitude faster. A merchant with three thousand SKUs and a quarterly photography budget that covers maybe two hundred fresh shoots can dramatically expand visual coverage by running the rest through Product Studio.
For hero SKUs, brand campaign material, editorial content, and any imagery that will be scrutinised at large sizes (homepage banners, billboards, premium publication placement), manual photography still wins. The artefacts that pass at 600×600 in a Shopping grid become obvious at 2400×1600 on a campaign page. Generated material also lacks the directorial intent that distinguishes a brand image from a competent commercial.
The third axis is customer scrutiny. For high-consideration purchases (furniture, large appliances, technical equipment), customers zoom in, examine details, and notice when something looks subtly off. Generated imagery on those product pages erodes trust and increases return rates. For impulse and low-consideration categories, the same imagery converts cleanly because customers never look that closely.
The pragmatic rule of thumb that Tinuiti and several agencies have converged on: use Product Studio for the bottom 80 percent of the catalogue by attention share, use manual photography for the top 20 percent. Reassess the split annually as the tool improves.
Brand-style training: the 2026 update
The most consequential 2026 update is brand-style training. The feature, which moved from beta to general availability in February 2026, allows merchants to upload a small reference set of brand-aligned imagery (eight to twenty images) and use that set to condition all subsequent Product Studio generations.
The mechanism is not a full model fine-tune. It is a lightweight conditioning layer that captures lighting preferences, colour palette, prop style, composition density, and aspect tendencies from the reference set. Subsequent generations inherit those characteristics, which dramatically reduces the generic e-commerce aesthetic that earlier Product Studio output suffered from.
The reference set must be coherent. Mixing studio shots, lifestyle shots, and editorial shots in the same brand profile produces a confused conditioning signal and worse output than no training at all. The recommended approach is to maintain separate brand profiles for separate use cases: a Studio profile for clean catalogue shots, a Lifestyle profile for scene generation, a Seasonal profile for campaign-specific work.
The reference imagery is not used to train Google’s underlying models. According to the Merchant Center Help documentation, brand-profile imagery stays scoped to the merchant account and is not contributed to general training data. This was a major sticking point for European rollout and is part of why the 2026 EU launch took as long as it did.
Integration with Performance Max asset libraries
Product Studio output flows into Performance Max in two ways. The first is through the catalogue. Any image attached to a SKU automatically becomes available to Shopping ads and to Performance Max campaigns that reference the Merchant Center catalogue. No additional step is required. The second route, new in 2026, is direct push to a Performance Max asset group.
The asset group push works as follows. From within Product Studio, after generating a batch of variations, the operator can target a specific Performance Max campaign and push selected outputs directly into one of its asset groups. The push respects asset group structure, so videos go to video slots, square images to square slots, vertical to vertical, and so on. Aspect ratios are auto-tagged by Veo and Imagen output and used to route the assets correctly.
The integration matters because Performance Max’s optimisation loop rewards asset variety. A campaign with four images and one video has a fundamentally lower optimisation ceiling than one with twenty images, eight videos, and varied aspect ratios. Product Studio is the cheapest way to get a campaign to the variety threshold where the algorithm has enough material to find winning combinations.
The integration does not solve everything. Performance Max asset libraries still need text material (headlines, descriptions), audience signals, and conversion data, none of which Product Studio provides. The tool fills the visual half of the asset library, not the whole library.
Comparison with competing tools
Product Studio occupies a specific niche, and merchants evaluating their creative stack should understand where it sits relative to the alternatives. The honest comparison helps decide whether to standardise on Product Studio, supplement it with a paid tool, or use it strictly for the Performance Max integration while running creative work elsewhere.
Photoroom and Pebblely are the closest direct competitors. Both are dedicated product photography tools, both offer batch operations, and both produce output of similar visual quality to Product Studio on most categories. Where they win is fine-grained control over generation parameters, multi-angle synthesis from a single source image, and the ability to extract a photography style from a small reference set and apply it to thousands of SKUs with consistent lighting and composition. Where they lose is integration: every output has to be exported, uploaded to Merchant Center, and attached to the right SKU manually. For a merchant with three thousand SKUs, that overhead alone often justifies staying with Product Studio even when the per-image quality is marginally lower.
Adobe Firefly, embedded in Adobe Express and Creative Cloud, produces arguably the highest-quality generative imagery in the consumer-accessible market in 2026. Its commercial licensing is also the cleanest, since Adobe trains exclusively on licensed and stock material. The downside is the workflow gap: Firefly outputs sit in Adobe’s ecosystem, not in Merchant Center, and bringing them into a Performance Max asset library is a manual operation. For agencies producing hero campaign material, Firefly is the right tool. For merchants populating thousands of catalogue images, Product Studio wins on operational efficiency.
Canva’s Magic Studio targets a different audience entirely: solopreneurs and small teams producing social media graphics, presentations, and marketing collateral alongside product imagery. The AI generation is competent but generic, the credit system caps usage at levels incompatible with large catalogue work, and the product imagery output rarely matches Product Studio’s contextual fidelity. Canva remains the right choice for non-product creative work and a poor choice for catalogue-scale generation.
Midjourney produces the most artistically distinctive imagery of any tool in this segment, but it is fundamentally not built for product workflows. Generating recognisable brand SKUs in specific scenes is impractical, the Discord-based interface does not scale, and the output lacks the IPTC metadata signalling that Google’s Shopping policies expect. Midjourney has its place in moodboard and concept work, not in catalogue production.
Native photography agencies, finally, remain the right choice for hero imagery, brand campaigns, and any work where directorial intent matters. The cost differential is significant, with mid-tier commercial photography running between three and ten thousand euros per shoot day depending on market, but the output difference at large display sizes is also significant. Most operationally mature merchants run a hybrid stack: photography for the top of the catalogue, Product Studio for the middle, and skipped imagery refresh for the long tail that never receives meaningful traffic anyway.
Cost economics
Product Studio is included free with Merchant Center, with no per-generation charge and no published rate limits as of early 2026. This is the single most important commercial fact about the tool, and it is the reason agencies and merchants are pulling work in from paid alternatives.
The economics calculation is straightforward. A merchant who previously paid Photoroom at thirty euros per month per seat and ran three seats spent roughly one thousand euros per year on background and scene work. Switching that work to Product Studio reclaims the budget. A merchant who previously commissioned a quarterly photography refresh at six thousand euros per session, four sessions per year, spent twenty-four thousand euros annually on incremental catalogue imagery. Replacing half of that volume with Product Studio output retains around twelve thousand euros while keeping the hero work where it belongs.
The hidden costs are review time and brand profile maintenance. Manual review of generated assets at production volume requires roughly fifteen to twenty seconds per output for an experienced reviewer, scaling to several hours per week for a high-volume operator. Brand profile curation requires another two to four hours per quarter as collections rotate and seasonal looks shift. Operators who skip these costs end up with the cheap output and the expensive disapprovals.
The compute cost itself is borne by Google. The published economics suggest Google views Product Studio as a strategic investment in feed quality and Performance Max asset variety, both of which directly increase auction participation and revenue. Free tooling that produces more advertised inventory is, from Google’s perspective, economically rational regardless of compute cost.
Common rejection reasons
Product Studio outputs are not exempt from Shopping policy review. The most common rejection reasons in 2026, in rough order of frequency:
- Misrepresentation when generated text on the image contradicts the actual product, brand, or specifications.
- Generated humans presented as real models in apparel, beauty, or accessories where authenticity is expected.
- Anatomical artefacts (broken hands, malformed faces) flagged by automated review.
- Generated scenes that imply features the product does not have, such as a battery indicator on a non-electronic item or a smart-home connection on a basic appliance.
- Brand or trademark confusion when the generated background includes logos or near-logos of unrelated brands.
- Cultural or regional appropriateness flags, particularly on imagery generated for one market and pushed into another with different content standards.
- Missing or stripped IPTC DigitalSourceType metadata when Product Studio output has been re-encoded through a third-party tool that dropped the metadata layer.
The misrepresentation category accounts for the majority of disapprovals. The mitigation is straightforward: prompt scenes that are content-free in the background, never generate text, never imply features, and review apparel outputs for human-likeness violations.
Workflow: Product Studio in a Performance Max creative refresh cycle
A defensible operational cadence for incorporating Product Studio into Performance Max management runs on a quarterly cycle, with monthly mini-refreshes. The shape of the cycle:
Week one of each quarter, audit the Performance Max asset groups. Identify campaigns that are below variety thresholds (fewer than fifteen images, fewer than three videos), campaigns where the listing group score has plateaued, and campaigns where Google’s own asset performance ratings have flagged “Low” performers that need replacement. The audit produces a list of asset gaps to fill.
Week two, run the Product Studio batch jobs. For each gap, select the relevant SKUs, apply the appropriate brand profile, and generate three to five variations per SKU. Mix scene types: half clean backgrounds, half lifestyle scenes, with seasonal variation if relevant. For high-priority SKUs, also generate at least one Veo video clip per asset group.
Week three, review and prune. Manual inspection on every output, with rejection of anything that fails on hands, text, faces, or implausible material rendering. Approval rates of 60 to 75 percent of generated outputs are typical and indicate a healthy review process. Approval rates above 90 percent suggest insufficient quality control. Approval rates below 40 percent suggest the brand profile or prompts need recalibration.
Week four, push to Performance Max asset groups. Use the direct push integration where possible. Where direct push is not available (older campaigns, edge categories), download the approved assets and upload through the standard Performance Max asset group interface. Tag each asset with the generation batch identifier so downstream reporting can attribute performance shifts to creative refreshes.
Across the second and third months of the quarter, run smaller refreshes targeted at underperforming asset groups specifically, rather than the full campaign portfolio. Monthly mini-refreshes keep the optimisation loop fed without triggering the larger learning resets that come with full asset group rebuilds.
At the end of the quarter, measure. Track Performance Max asset group ratings before and after the refresh, conversion rate trends on the affected SKUs, and CPA shifts at the campaign level. The honest signal usually appears within three to five weeks; anything attributed to a refresh in the first ten days is more likely seasonality or noise.
Common mistakes
The first common mistake is treating Product Studio as a replacement for photography rather than a supplement. Merchants who switch their entire creative pipeline to AI generation lose the brand-defining hero imagery that drives long-term affinity and end up with a catalogue that converts adequately but feels generic. The right framing is augmentation: Product Studio fills the gaps that photography cannot economically cover.
The second mistake is skipping manual review. The tool is good enough that batches of fifty outputs look fine on a thumbnail grid, and operators stop checking individual frames. Three weeks later, a six-fingered hand or a malformed face surfaces in a Shopping result and the disapproval cascade follows.
The third mistake is over-pushing video. Veo output is impressive but expensive in attention terms. A Performance Max asset group with five mediocre video clips often performs worse than one with two strong static images and one excellent video. Variety is not the same as volume.
The fourth mistake is ignoring brand-style training. Generic Product Studio output looks generic, and customers can tell. The few hours required to assemble a strong reference set and define brand profiles pay back across every subsequent generation.
The fifth mistake is failing to maintain the IPTC metadata chain. When generated assets are exported, edited in Photoshop, and re-imported, the DigitalSourceType metadata gets stripped silently. The asset then looks like undisclosed AI generation to Google’s automated review and gets flagged. The fix is to preserve metadata explicitly in any post-processing step or to use Product Studio outputs unmodified.
The sixth mistake is generating for markets where the tool is unavailable. Outputs generated in a US Merchant Center account and pushed to a French Performance Max campaign technically work but operate in a grey zone of policy compliance. Operators with multi-market accounts should generate inside the destination market’s account whenever possible.
Conclusion
Product Studio in 2026 is no longer a curiosity. It is a baseline capability that any serious Performance Max operator needs to incorporate into the creative refresh cycle, alongside whatever photography pipeline already exists. The tool has matured to the point where the question is not whether to use it, but how to use it without producing a catalogue that looks generated.
The honest assessment: Product Studio handles the unglamorous middle of the catalogue beautifully. It struggles at the top of the catalogue where brand identity and editorial intent matter, and it struggles at the bottom of the catalogue where it generates output that nobody is going to look at anyway. The middle, where most SKUs live, is where it earns its keep.
The discipline required is review, brand profiling, and integration into a defined refresh cadence rather than ad-hoc use. Operators who treat Product Studio as a button to press when a campaign looks tired produce inconsistent results. Operators who treat it as one stage in a quarterly creative cycle, with brand profiles, manual review, and direct integration to Performance Max asset groups, produce measurable lifts in CTR and ROAS within a quarter.
The tool will keep changing. The 2026 brand-style update was a step change; the next obvious moves are tighter Performance Max asset attribution, expanded 3D category support beyond footwear and home goods, and eventually full video generation that can incorporate scripted product narration. The 2024 to 2026 trajectory suggests Google will keep shipping. The merchants who learn the operational discipline now will be better positioned to absorb each subsequent capability without disrupting the catalogue.
Sources
- Google Merchant Center Help, About Product Studio.
- Google Merchant Center Help, AI-generated content requirements and IPTC metadata.
- Google Merchant Center Help, Video generation in Product Studio.
- Search Engine Land, Google adds animation and image editing tools to Product Studio.
- Search Engine Land, Product Studio expanded availability and EU rollout coverage.
- Search Engine Journal, Google launches video generation in Product Studio.
- Search Engine Journal, Imagen-3 and product imagery: what changed for merchants.
- Tinuiti, Performance Max asset variety and Product Studio impact reports.
- Store Growers, Product Studio brand-style training and operational workflows.
- Smart Marketer, Scene generation case studies and CTR uplift benchmarks.