Good morning.
This week, we’re looking at three parts of running an online brand: getting discovered, improving the store, and producing the assets that help products sell. Each has a new AI announcement worth understanding.
Here’s what matters for your team.
In this week’s brief:
- Google expands visibility into AI shopping discovery.
- Noibu connects store problems to proposed fixes.
- Raspberry AI brings fashion workflows into one platform.
- A quick product-information check you can try this week.
🛍️ Google gives merchants a clearer view of AI discovery
Image source: Google, original announcement.
The update: On September 16, Google announced wider availability of AI performance insights in Merchant Center.
The details:
- Available in Australia, Canada, India, New Zealand, and the US.
- Compares brand share of voice across surfaces including AI Mode and AI Overviews.
- A separate US beta brings Business Agent into YouTube ads so viewers can ask product questions.
Why it matters: Eligible teams have another way to investigate their visibility in AI shopping. My recommendation: use it to identify questions worth investigating, then check the affected product information. Visibility alone doesn’t establish sales impact.
🔧 Noibu wants to turn store problems into proposed fixes
Image source: Noibu, announcement artwork. The headline shown is the company’s framing.
The update: In a September 15 company post, Noibu described its workflow for moving from store data to drafted changes, human approval, and measurement.
The details:
- Agents use store behavior and technical signals to identify problems.
- Proposed changes can include test plans or code fixes.
- Noibu says a human must approve changes before they reach a live store.
Why it matters: This could be useful for teams with a backlog of known problems and limited implementation time. In a demo, I’d ask the vendor to follow one issue through the full process: evidence, proposed fix, approval, and verification. The announcement describes the vendor’s system; we haven’t tested it ourselves.
🎨 Raspberry AI connects design work with commerce assets
Image source: Raspberry AI, official launch-video thumbnail, embedded in its announcement.
The update: On September 16, Raspberry AI announced an expanded platform connecting fashion design, merchandising, wholesale, marketing, and e-commerce workflows.
The details:
- The company describes workflows spanning moodboards, design iterations, and on-model visualizations.
- Product work can carry into lookbooks, campaign creative, and product-page assets.
- Teams guide and review outputs throughout the process.
Read Raspberry AI’s announcement.
Why it matters: For apparel brands, I’d evaluate whether this reduces repeated work between teams. Test one product across several outputs and inspect whether its material, color, construction, and fit stay accurate. The company’s cost-saving claims need validation against your own workflow before they become a business case.
🧪 Try this: turn three customer questions into better product information
Pick one best seller and three questions customers ask before buying.
- Find the published answer to each question.
- Mark it clear, incomplete, or missing.
- Have someone who knows the product verify the facts.
- Improve the most consequential gap.
For a rain jacket, useful questions might cover ventilation, packability, and weight. For furniture, they might cover dimensions, assembly, and access through a doorway.
Your output is one clearer product listing. Keep the questions grounded in actual customer needs and avoid adding claims you can’t substantiate.
🧰 Tool to check: Shopify’s Catalog search preview
If your admin has the Agentic section, its search preview lets you inspect Shopify Catalog results. It’s useful for investigating product discoverability, but Shopify cautions that individual AI channels can reorder those results.
Use it as a clue to investigate, rather than a prediction of exactly what a shopper will see. This is an existing capability worth checking, not a new launch this week. Shopify’s documentation.
One question before you go: Which would help your team most right now—better product discovery, faster store fixes, or easier creative production?
Reply with your pick. It’ll help shape what we investigate next.
— Said