Google AI Overviews: A Flashy Feature or a Revenue Driver?

🚨 Feed optimization is about to get a whole lot more important. Brodie Clark noticed Google is quietly testing a new “Ask stores” section inside the Shopping tab — and you might see it show up in your results. Search for something like “flowers” and you’ll see a new block featuring stores like Lowe’s or eBay with a “Get advice” button. Click it, and Google opens a chat window where you can talk directly with the store’s AI shopping assistant. It asks what you’re looking for (“live plants,” “cut bouquets,” “artificial flowers”) and recommends products pulled straight from the store’s catalog. 🧠 This is the start of agentic commerce — where discovery, conversation, and conversion all happen inside Google. Here’s the catch 👇 ➡️ These assistants rely entirely on your product feed and structured data. ➡️ Clean titles, rich attributes, and optimized descriptions = smarter AI recommendations. ➡️ Feed optimization isn’t just for ads anymore — it’s your ticket into Google’s conversational layer. Google is giving us a glimpse of what’s next: AI-powered storefronts where your product data does the selling. If your feed isn’t optimized, your brand won’t be part of the conversation. #ecommerce #googleads #shopping #ai #feedoptimization #digitalmarketing

Search is moving fast, and AI is reshaping how people search, discover, and buy. It really is sink or swim for advertisers. Last Thursday at BrightonSEO, a few things were made clear in all the ecom-related talks: That in an AI world, trust and data quality matter more than ever if you want to cut through the noise. Here’s what that means for brands running on Google Ads: 🤝 Trust signals are conversion drivers Delivery timelines, shipping costs, return policies etc, aren’t admin details, they’re trust signals. Google can show these details in shopping ads, and when everyone’s AI-optimised ads competing for the same ad spots, trust and credibility will influence who gets the click. 🧠 Inputs beat hacks Don’t get caught up on shiny objects or “playing the algorithm”. Smart bidding, asset automation, audience signals, they all rely on one thing: quality inputs. You don’t control the algorithm anymore, but you control what fuels it. 🛒 Feeds are your foundation Performance Max is only as good as the data you feed it. Detailed, accurate product attributes (titles, GTINs, product types, delivery times, prices) are what separate the top performers from the pack. In a keywordless Pmax campaign, your success will depend on your feed quality. Brands that win Q4 will be the ones whose data is clean, ads are clear, and experience feels human + trustworthy. These are the shifts I’m already helping brands navigate. Follow along if you want practical insights that go beyond the buzzwords.

Google just rolled out Shopping inside Google AI Mode - and the game has officially changed. We’re watching the shift from searching for products to simply asking for them… and getting a fully curated shopping journey directly inside AI. This is the clearest signal yet: AI answers are becoming the new storefront. If your brand doesn’t appear in these AI-generated shopping flows, you’re invisible at the exact moment of purchase intent. Three implications for brands: 👉 Traditional SEO isn’t enough. AI Mode pulls from structured facts, citations, and trusted sources - not just keyword-optimized pages. 👉 Share-of-Answer becomes the new acquisition metric. If your products aren’t mentioned, compared, or cited, you’re out of the customer journey. 👉 GEO (Generative Engine Optimization) becomes mandatory. Brands must optimize for AI discovery, not just web rankings. Google just made it obvious: AI assistants aren’t a side channel - they are the new shopping funnel. Time to adapt or fall behind.

𝗠𝗼𝘀𝘁 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀𝗲𝘀 𝘂𝘀𝗶𝗻𝗴 𝗚𝗼𝗼𝗴𝗹𝗲 𝗔𝗱𝘀 𝗶𝗻 𝟮𝟬𝟮𝟱 𝗮𝗿𝗲 𝗺𝗮𝗸𝗶𝗻𝗴 𝗼𝗻𝗲 𝘀𝗶𝗹𝗲𝗻𝘁 𝗺𝗶𝘀𝘁𝗮𝗸𝗲... 𝗧𝗵𝗲𝘆’𝗿𝗲 𝘀𝘁𝗶𝗹𝗹 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝗵𝘂𝗺𝗮𝗻-𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱 𝗰𝗮𝗺𝗽𝗮𝗶𝗴𝗻𝘀 𝗶𝗻 𝗮𝗻 𝗔𝗜-𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱 𝘄𝗼𝗿𝗹𝗱. 𝗪𝗵𝘆 𝗜 𝘀𝗮𝗶𝗱 𝘁𝗵𝗮𝘁:   • I’ve seen brands spending thousands on ads every month, yet missing 40–60% of potential conversions.   • Not because their offers are bad.   • But because they haven’t adapted to Google’s new AI-driven ecosystem. 𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁’𝘀 𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴 (𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂 𝗻𝗲𝗲𝗱 𝘁𝗼 𝗸𝗻𝗼𝘄): ✅ 𝗔𝗜 𝗶𝘀 𝗻𝗼𝘄 𝘁𝗵𝗲 𝗯𝗿𝗮𝗶𝗻 𝗼𝗳 𝗚𝗼𝗼𝗴𝗹𝗲 𝗔𝗱𝘀.   • Smart Bidding, Responsive Search Ads, and Performance Max are powered by machine learning that learns faster than any human.   • If you’re not feeding it the right data, you’re basically giving it junk food. 🔹 𝗠𝗮𝗻𝘂𝗮𝗹 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗶𝘀 𝘀𝗵𝗿𝗶𝗻𝗸𝗶𝗻𝗴.   • Google is slowly removing traditional targeting and keyword options.   • That means AI decides who sees your ad and when.   • Scary? Maybe.   • But powerful—if you understand how to guide it. ✅ 𝗙𝗶𝗿𝘀𝘁-𝗽𝗮𝗿𝘁𝘆 𝗱𝗮𝘁𝗮 𝗶𝘀 𝗴𝗼𝗹𝗱.   • The days of relying on third-party cookies are over.   • In 2025, businesses that integrate CRM, website, and conversion data directly into Google Ads will dominate.   • Feed the machine your own customer signals. 🔹 𝗖𝗿𝗲𝗮𝘁𝗶𝘃𝗲 𝗱𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 𝗶𝘀 𝗻𝗼𝘄 𝗮 𝗺𝘂𝘀𝘁.   • Google’s AI tests thousands of ad combinations automatically.   • So, one static ad won’t cut it anymore.   • You need 5–10 variations with different tones, CTAs, and visuals to truly let AI learn what works best. ✅ 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 > 𝗺𝗮𝗻𝘂𝗮𝗹 𝘁𝘄𝗲𝗮𝗸𝗶𝗻𝗴.   • Stop obsessing over daily CPC changes.   • Instead, train your AI campaigns with better conversion tracking, audience signals, and clear objectives. 𝗠𝘆 𝘀𝗶𝗺𝗽𝗹𝗲 𝗿𝘂𝗹𝗲 𝗳𝗼𝗿 𝟮𝟬𝟮𝟱: Don’t fight the algorithm. Feed it better data, guide it, and watch it scale. 𝗙𝗶𝗻𝗮𝗹 𝘁𝗵𝗼𝘂𝗴𝗵𝘁: AI isn’t replacing Google Ads experts. It’s replacing those who refuse to evolve. 👉 What’s your biggest challenge with AI-driven Google Ads right now? Let’s talk in the comments.

To understand what makes a page visible inside Google’s AI Overview snippet, we first need to understand user intent - the real problems people are trying to solve. Every search query (each user problem) falls into one of 4 core types: ✔ Informational ✔ Commercial Investigation ✔ Transactional ✔ Navigational (Note: with a local modifier (for example, “matcha near me”), Google triggers the Maps instead of the AI Overview). For product pages, the most strategic focus is Commercial Investigation intent. Why? 1) Higher volume More users search for “matcha vs coffee reviews” than “buy matcha discount today.” Commercial Investigation queries are high-intent, but still early-stage. This is where your brand can win new customers, not just convert visitors already in the funnel. 2) Your generic PDP becomes a mini-landing page A good PDP doesn’t just list product details. It becomes a buyer’s guide, answering: ✔ Customer testimonials – real experiences (motivators) ✔ Why matcha instead of coffee? ✔ How to prepare matcha and how to store it ✔ Common myths and misconceptions (frictions) Your product page becomes a story, not just a SKU. This structured content is exactly what Google uses to build AI Overviews. 3) Commercial Investigation queries drive NEW customer acquisition. Such searches bring users when they are: ✔ Open to alternatives ✔ Ready to be educated ✔ Not loyal to any brand yet Your PDP can outperform competitors at this stage and earn a spot inside AI Overviews. Why informational content matters as well? Informational content doesn’t compete with your PDP, it supports it. By linking informational articles back to your product pages (for example, from an FAQ → Read more → blog article), you create a semantic web around matcha. This helps Google understand: ✔ What your site is about ✔ How your pages relate to each other ✔ Which page matches which intent ✔ Why your PDP deserves to appear in AI Overviews When done right, informational content helps build brand authority and expand your presence in the Knowledge Graph In short: informational content boosts the ecosystem that supports your commercial pages and increases your chances of appearing in AI Overviews. Why do NOT focus on transactional queries? For transactional searches, Google already has a very strong interface designed to prioritize: ✔ Shopping Ads ✔ Product grids ✔ Sponsored listings ✔ Google Merchant Center data These elements dominate the top of the page and push organic results much lower. I’m happy to share a simple 20-point checklist from my Shopify experience.

I share a lot of data here, but rarely does a chart make me want to SCREAM. Sadly, this one does. What's so bad? Let me tell you: The technological idea behind AI Max – a keywordless method of matching search queries and landing pages – is now *triplicated* in Google Ads. It exists in both Dynamic Search Ads (DSA) and PMax The technologies are all overlapping and mutually redundant. 1 in 5 advertisers using AI Max also use DSA. 1 in 4 also use PMax. And HALF of them are using ALL THREE. The trouble is, selection bias kicks in and the advertisers most likely to adopt Broad Match, PMax, and DSA are also the advertisers most likely to adopt AI Max. If things go further in this direction, it is a catastrophe for account hygiene. It's perfectly clear that DSA will end up on the chopping block and there will be a migration or "upgrade" or whatever. But sit down friend, because AI Max is NOT ready for primetime. The performance delivery is dubious compared to Broad Match and DSA, and the targeting needs heavy interventions, particularly in mature search builds where there's little to no low hanging fruit, or even "medium hanging fruit" lol. I have nothing inherently against AI Max – I was actually pretty excited when Google announced it. I like the amount of transparency that's baked into it. I like that it's a layer on top of existing campaign types, not a replacement. I like that it's configurable. But this situation is a fire alarm. You need to look at the tech deployed across your account and MAKE A CHOICE.

Google’s AI Overviews Are Changing How Shoppers Research — But Not How They Buy A new BrightEdge analysis reveals a clear shift in how people interact with search. Between Sept. 1–Oct. 15, Google’s AI Overviews dominated the research phase of online shopping — helping users explore, compare, and evaluate — but when it comes to buying, traditional search still wins the sale. 🔹 Key Insights: - AI Overview visibility peaked at 26% in September, then dropped to 9% in October. - 30% of keywords remained after the pullback. - A massive 82% YoY keyword churn — only 18% overlap from 2024. - 56.8% overall decline in AI Overview coverage — 10× more than last year! 🛒 Categories that stayed stable: - Grocery & Food – 56% - TV & Home Theater – 43% - Small Appliances – 37% 🛋️ Categories hit hardest: - Furniture – 3% - Home Décor – 7% - Apparel – 23% 💡 Takeaway for eCommerce marketers: - AI Overviews shape discovery and education. Traditional search still drives conversions. - As BrightEdge puts it — “November is the discovery window; December is the purchase month.” So now’s the time to strengthen your educational and comparison content — because by the time shoppers reach December, their decisions may already be made. #SEO #AIOverviews #Ecommerce #SearchMarketing #BrightEdge #GoogleAI #AIO #GEO #DigitalMarketing #ContentStrategy BrightEdge Source - https://lnkd.in/eSqPVdgc

AI won’t save your 2026 number. It might hurt it! Unless your GTM matches how AI-era buyers discover, evaluate, and buy. Do that, and AI becomes a growth engine. Here are #6 #ExposureNinja plays across Traditional Search + AI Search + Brand Experience. Recent results: top-3 for ~4.9k keywords, +288% organic revenue, +451% content revenue. 1️⃣ Lead with topic-first SEO (not keyword whack-a-mole) Group content into buyer-relevant topics. For each, create one hub with top → mid → bottom pieces. Give every page one clear intent and link to the hub and next step. Add expert bylines. Measure at the topic level, not page-by-page, beasue clusters win as a unit! 💗 Result: prevents cannibalization, reveals gaps, and builds authority that ranks (and earns AI citations). 2️⃣ Turn search into movement, not just traffic Design every article/category page to advance the visit. For each page, set one clear intent (learn → compare → act). Add helpful blocks that move people forward: embed products/demos where it fits, use comparison tables when choice is hard, include simple tools (calculators/checklists) on top– and mid-funnel pages. Use CTAs that match said intent (read next → compare → add to cart / book demo). 💗 Result: higher search-to-conversion > more readers become buyers; BOFU closes faster. 3️⃣ Win AI answers by earning citations Make key pages easy to quote and trust: clean architecture, correct schema (Org/Product/FAQ), fast load, expert bylines, and unique data/visuals. Keep claims consistent with third-party profiles (G2, Trustpilot, retailers) and build reputable mentions / partner features! 💗 Result: more inclusion in AI overviews/chat answers → qualified, assisted conversions. 4️⃣ Make your catalog agent-ready (eCommerce) Standardize titles/specs, add Product schema to every SKU, keep live price/stock current. Expose real-time feeds (Merchant Center) and MCP endpoints/tools; plan for ACP (Agentic Commerce Protocol) for secure, tokenized checkout. Show reviews and clear descriptions. 💗 Result: shopping assistants and agentic systems include and complete your products more often, lifting assisted orders and revenue. 5️⃣ Clarify positioning (tidy that messy website >> less = more) Write one line: “We help [who] get [result] with [how].” Put it in your hero, category headers, and ads, and back it with 2–3 proofs (case, metric, review). Keep headlines and copy aligned across your site and key third-party profiles (consistent footprint) 💗 Result: a clear, consistent message makes you the obvious pick for people and for AI. 6️⃣ One message across many doors = Sales / Marketing Alignment! Choose one promise for the quarter. Reuse it across channels. Build a shared creative kit. Help teams stay consistent. Link every touch to the same next step. 💗 Result: a cohesive journey that lifts response rates and moves more buyers to inquiry or purchase. Ship these and be easier to find, trust, and buy from >> for both people and AI. #GTM

AI Max for Search was great... until it wasn’t. Google released AI Max for Search that promised to “take […] Search campaigns to the next level” - directly quoted from the Google Ads blog. AI Max for Search is supposed to provide the following to advertisers: - Incremental reach and performance - More control - More transparency We saw early performance improvements when enabled on existing search campaigns. But now, months down the line, performance is slipping. And I'd argue that control and transparency were never part of the mix. I’m disappointed, because I really was excited about the release - it seemed like Google Ads finally pushed a high-value feature. Oh well… An interesting note, if you’re still testing - we have anecdotal data suggesting that new AI Max for Search campaigns performs better than standard Search campaigns that have AI Max for Search enabled after creation. Not enough data to be conclusive, but it's looking to be the case.