After tracking an incredible 2 million ChatGPT prompts, I found a surprising trend: shopping appears in less than 10% of them. Diving deeply into the data over nine months, it was clear that a staggering 79% of prompts simply never activated a shopping response.
What intrigued me further was the persistence of those that did trigger shopping. There was an impressive 83% chance they would do so again the following day. However, this persistence isn’t indefinite. Model updates seem to wash away those triggers overnight.
In my quest to understand these patterns, I analyzed 26 million prompts across 13,000 categories. The goal was to pinpoint where shopping emerges, how reliable this occurrence is, and what insights this holds for brands shaping their strategies on a platform where responses are sparsely shopping-oriented.
For years, I relied on a straightforward ecommerce model: Google attracted visitors to my site, where transactions were completed. Success was measured through rankings, clicks, and conversion rates. That scenario has drastically changed.
With Google’s Universal Commerce Protocol (UCP) combined with AI Mode, it’s possible for Google to uncover, evaluate, and finalize purchases within its AI framework. The dynamic is shifting from merely directing traffic to facilitating transactions. Now, the visibility of my products hinges on whether Google’s AI includes my data in its algorithm.
When AI can recommend and close sales, the optimization challenge moves even farther upstream. The vital question now isn’t just about my ranking; it’s about whether my products get chosen by AI.
So, let’s explore these changes and what strategies those involved in SEO and AI optimization should adopt next.
On January 11, Google introduced the Universal Commerce Protocol, or UCP. This innovative open standard empowers AI agents to explore, assess, recommend, and purchase products seamlessly across the web within Google’s own AI settings.
What caught my attention was not just UCP itself but the entire ecosystem Google devised around it. UCP was created in collaboration with platforms like Shopify, Etsy, Wayfair, Target, and Walmart, with pre-existing payment networks incorporated. This level of planning signifies a long-term vision, rather than a fleeting experiment.
Simultaneously, Google introduced three platform-level features that make this transformation tangible in everyday shopping experiences:
Business Agent: Brands now have an AI-powered ambassador in Search and the Gemini app. Shoppers can inquire about products, compare choices, and receive brand-specific advice without the necessity to visit a separate site.
Direct Offers: This feature allows merchants to incorporate exclusive discounts directly into Google’s AI Mode, embedding promotions within the recommendation engine itself.
Checkout in AI Mode: Google now facilitates purchases directly within its interface, transitioning from a traffic broker to an integral transaction facilitator.
What’s even more remarkable is how Google transforms routine conversations into commerce. Instead of waiting for users to type product-related queries, Gemini can respond to natural language prompts like “help me plan a camping trip” or “what will get wine out of my couch” by sourcing up-to-date inventory, pricing, and availability from retailers, completing the transaction in the same interaction.
In the era where AI navigates the purchasing journey, brands must compete within the AI’s recommendation system, not just in search results.
Throughout my career, ecommerce consistently functioned on a model where search engines, ads, and marketplaces aimed to divert users to my site, so it could handle the sales. UCP reshapes that perception entirely.
Now, AI takes charge of the complete journey. It understands the customer’s needs, assesses different options, and can even finalize the purchase. Under this model, the quality of my website’s homepage or category page matters less if AI doesn’t prioritize my product at the outset.
I recently discovered the transformative power of optimizing my eCommerce brand for AI answer engines. Engaging with platforms like ChatGPT and Google’s AI Overview can significantly enhance my brand’s visibility, trust, and ultimately drive more sales.
Understanding how to tailor my content for these AI platforms ensures that my products appear as helpful, relevant answers to potential customers’ inquiries. It’s about more than just visibility; it’s about building a credible connection with my audience.
By weaving in the best practices of AI Search and AI Optimization, I’ve begun to see a noticeable increase in brand engagement and authority. It’s a journey worth exploring for anyone looking to stay ahead in the competitive eCommerce landscape.
ChatGPT has significantly impacted e-commerce site conversions, with traffic from ChatGPT converting 31% better than non-branded organic search across 94 sites in 2025. Despite this impressive performance in conversion rates, it still contributes only a small fraction of the overall revenue. This insight comes from a detailed year-long analysis by Visibility Labs, covering from January to December 2025.
Why I’m Interested. This data is crucial because it highlights how AI referral traffic, while not yet dominant, is showcasing higher conversion potential compared to traditional non-branded search traffic. It indicates a growing value in AI-driven referrals, supplementing rather than replacing existing channels.
Higher Conversion Rate. The analysis found that ChatGPT traffic converted at 1.81% compared to 1.39% for non-branded organic traffic, translating to a 31% higher conversion rate. This trend was consistent for 10 out of the 12 months analyzed.
Visibility Labs points to intent compression as the key reason behind this high conversion rate. Users often use ChatGPT to refine their product preferences, arriving at product pages with a clearer purchase intent compared to visitors from typical search channels.
Key Observations. While ChatGPT shows a conversion advantage, the overall growth has decelerated, and the traffic volume remains modest.
Significant Traffic Growth: There was an astonishing growth of 1,079% in ChatGPT visits, escalating from 1,544 in January to 18,202 in December. In comparison, non-branded organic traffic increased by 17% during the same timeframe.
Lower AOV: The average order value (AOV) for ChatGPT was $204, compared to $238 for organic traffic, marking a 14.3% difference.
Increased Revenue Per Session: Despite the lower AOV, ChatGPT generated $3.65 in revenue per session versus $3.30 from organic, yielding a 10.3% higher earning per session.
Minor Revenue Share: ChatGPT accounted for $474,000 in revenue against $32.1 million from non-branded organic traffic, amounting to 1.48%, which rose to 2.2% in the latter half of 2025.
Growth Correlated with Updates: The increase in traffic during the first half is linked to the introduction of shopping carousel features in April 2025. However, growth rates began to stabilize around August.
Overshadowed by Organic Traffic: Overall, non-branded organic traffic was 70 times larger than ChatGPT, narrowing to 47 times in Q4. Early 2025 saw variability, with conversions ranging from 15 to 37 per month, which limited confidence levels until the middle of the year.
The Attribution Challenge. GA4’s referral data may not fully capture ChatGPT’s impact. According to Visibility Labs, many users receive recommendations through ChatGPT, then search for brands via Google before making a purchase, which are typically tracked as branded organic conversions.
To better capture AI-influenced sales, it’s advised to implement post-purchase surveys.
Data Insights. Visibility Labs’ analysis included GA4 data span over 12 months (January to December 2025), gathered from 94 e-commerce brands with seven- and eight-figure turnovers, comparing 9.46 million non-branded organic sessions to 135,000 ChatGPT referral sessions. The study focused exclusively on visits with commercial intent, excluding homepage and blog traffic.
The Complete Report. Find the detailed report here.
I’ve noticed how beauty brand visibility in AI searches is increasingly influenced by social discovery and third-party validation.
Even before a user inputs a prompt, AI search visibility is shaped by conversations on social platforms. Brands featured in generative responses are typically those actively discussed and validated across these channels. By the time someone turns to AI search, the groundwork has often been laid.
Using beauty as an example, I’ve explored how social discovery impacts brand visibility and why AI search reflects these signals.
Discovery Didn’t Move to AI – It Fragmented
Brand discovery is now fragmented across many platforms. While AI tools affect the middle of the funnel, much discovery happens before someone engages with a prompt.
Social platforms significantly influence the signals determining AI visibility. By the time users reach decision points in generative search, their opinions and perceptions may already be shaped. Delaying influence until AI search might narrow the window of opportunity.
Social interactions are a major upstream influence. According to eMarketer research, about two-thirds of U.S. consumers use social platforms like search engines.
It’s not just Gen Z—this trend shows how people validate information and discover brands. These platforms are frequently cited in AI results, particularly in the beauty sector.
In a study I worked on with a beauty brand, platforms like Reddit, YouTube, and Facebook often topped the list of cited domains in AI Overviews and ChatGPT.
While Reddit might seem anti-brand, YouTube frequently appears in citation data, posing a valuable, yet often overlooked, opportunity for citation optimization.
It’s easy to be drawn to stats about AI usage, from prompt numbers to daily activity levels. Yet when you compare these figures against business goals like traffic or transactions, the reality shifts.
Social platforms are a core part of mainstream search behavior. For many, searching on TikTok or YouTube is second nature. In fact, almost 40% of TikTok users search the app multiple times a day, with 73% doing so at least once daily.
Referral data highlights the difference. In a 12-month review of 973 ecommerce sites, only about 0.2% of traffic came from ChatGPT referrals, while Google’s organic search was nearly 200 times larger.
Though AI search is growing and valuable, social platforms and traditional search still dominate in terms of behavior, sessions, and transactions.
The Validation Loop: Why AI Needs Social
Optimizing for social is akin to optimizing for AI. Large language models don’t serve as primary truth sources. Instead, they reflect human consensus from the data they process.
AI systems often regard brand-owned sites skeptically. A study showed that just 25% of sources in AI-generated responses were brand-managed.
Conversely, these engines prioritize third-party validation. Research by OtterlyAI showed up to 6.4% of AI citation links came from Reddit, surpassing many traditional publishers.
A measurable link exists between sentiment and visibility. Positive brand sentiment on social platforms correlates with higher visibility in AI results.
Seeing video solely as a social or branding channel rather than a search surface misses the mark.
On platforms like TikTok and YouTube, AI uses spoken language, text, and captions to assess trust. Within beauty, for example, Google’s daily search volume dwarfs ChatGPT’s, yet “how-to” prompts find favor with video due to its detailed advice.
Beauty has split into two realms according to Yotpo’s analysis. Brands like Paula’s Choice excel in AI for their detailed educational content, while traditional marketing brands lag.
Terms like “dermatologist recommended” rank high in AI as language models prefer expert endorsements for ranking.
Breaking the High-Production Barrier: Content at Scale
Budget is often seen as a blocker. Many assume Hollywood-level production is needed for success. This is an outdated view.
Today’s landscape rewards authenticity over perfection with viewers seeking real stories, not polished ads.
Effective video optimization doesn’t require film school. Brands can tap into internal skills without new hires.
Partner with creators: Using platforms like Billow or Social Native, brands can collaborate with creators for as little as $500. This investment can translate into tangible search visibility.
Utilize social-savvy staff: Often, your best asset is internal. Encourage team members who use social media to generate authentic content while fostering a creative culture.
Focus on strategy: Major followings aren’t essential. I’ve seen a TikTok account start modestly with a part-time creator end up generating significant views in months by targeting valuable search terms.
Starting fresh with a limited budget doesn’t mean limited reach. Businesses need clarity on their goals and a disciplined approach.
Agentic AI is now a hot topic among executives. I’m here to break down precisely what’s happening, what remains unchanged, and how e-commerce brands should adapt.
As an SEO leader working with e-commerce brands, I’m often in the position of clarifying the realities behind buzzwords like ‘agentic AI’. Executives frequently inquire about its implications for growth, risk, and competition.
Executives crave facts over hype. They seek concise explanations, grounded insights, and actionable advice.
My role as an SEO leader becomes essential here, not in predicting the future, but in enlightening leadership about the changes, the constants, and how to proceed pragmatically. Here’s my roadmap.
Start with Defining ‘Agentic’
First, I focus on demystifying the term. Agentic systems don’t replace customers; they work on their behalf. While the intent and preferences originate from individuals, the execution is taken over by the software.
The working dynamics shift, where tasks like discovery, comparison, and even execution are now managed by software, processing data faster than any human.
In discussions with executive teams, I emphasize simple illustrations:
“We’re not losing customers; instead, we’re incorporating a new decision-maker, which is the software acting as a customer proxy.”
Understanding this calms the conversation and steers focus away from fear towards preparation.
Manage Expectations to Avoid Hype
Another key role I play is in tempering expectations. Agentic AI won’t sweep over all at once. Its effects will be gradual and varied across different categories.
Some industries, with standardized products and organized data, will adapt faster. Others will face more challenges due to complexities and regulatory hurdles.
I often see leadership teams falling into two detrimental traps:
Panic: Hastily altering strategies and budgets without clarity.
Dismissal: Ignoring changes until it impacts performance, leading to rushed responses.
I offer a steady perspective, noting that agentic AI merely accelerates existing trends. It’s not about chasing new features but reinforcing strong fundamentals.
I encourage conversations to evolve beyond search rankings. When agents lead the journey, the critical question becomes, “Are we eligible to be chosen?”
Eligibility hinges on clear, consistent, and trustworthy data. Agents must grasp your offerings, target audience, pricing, availability, and risk factors associated with choosing your brand.
Raising thoughts about data consistency, pricing reliability, and whether policies add or reduce uncertainty positions SEO as a practical bridge between strategy and execution.
SEO Beyond Marketing
There’s a misconception that SEO is confined to marketing. Agentic behavior challenges this notion.
Selection by an agent involves variables beyond marketing, like data accuracy, technical integrity, inventory management, and payment reliability.
My explanations revolve around broadening SEO’s scope—it’s about ensuring the business is machines-readable, trustworthy, and consistent.
SEO becomes vital in helping leaders identify system or data gaps that could hinder the brand’s selection, highlighting its connection to both risk management and operational resilience.
In most e-commerce brands, agentic systems affect the top of the funnel first. Discovery shifts towards more personalized, conversational interactions.
Instead of brief search phrases, users convey needs, constraints, and preferences, which the agent then transforms into actions.
This decreases the significance of owning category head terms. If an agent has comprehensive user data, it acts like a knowledgeable repeat customer.
This presents a new reporting challenge. Not all SEO work will appear as direct demand creation, yet it still impacts outcomes. Leaders need to anticipate this shift.
Rethink Consideration
The consideration phase evolves too. Traditionally, it involves hosting reviews, comparisons, and reassurances.
With agentic intervention, consideration morphs into a filtering process, retaining only the options that align with user preferences.
This necessitates a quality over quantity strategy in content, emphasizing structural trust signals and consistent, verifiable information.
Brands might be selected without user awareness. While this could boost conversions, it also poses a risk to brand recognition if not addressed elsewhere.
Measurement often concerns executives, and agentic AI complicates this. With more processes happening inside AI, fewer interactions leave traceable or clear data.
I address this early by stressing that while this isn’t a failure of optimization, it merely highlights the analytics limits in a complex digital landscape.
The focus should shift to directional indicators and blended performance over precise attribution, acknowledging the new decision-making landscape.
Advocate Proactive, Low-risk Responses
The crux of leadership dialogue is next steps. Fortunately, most appropriate responses to agentic AI carry low risk.
Enhancing product information, eliminating inconsistencies, strengthening reliability signals, and addressing technical vulnerabilities benefit the business now and pave the way for the future.
Building brand trust outside search also plays a critical role. Trusted brands are more likely to be selected by agents performing comparisons.
This strategy reassures leaders that success doesn’t require radical change but calls for focused improvement.
Agentic AI: Focus Shifts, Fundamentals Persist
For us SEO leaders, agentic AI modifies our focus. Instead of solely optimizing for visibility, we aim to protect eligibility, reduce ambiguities, and illustrate influence.
This demands confidence and clear articulation, challenging hype with grounded perspectives. Agentic AI renders SEO more strategic and no less crucial.
Agentic AI isn’t an imminent threat or foolproof advantage. It’s a transformation in decision-making approaches.
For e-commerce brands, the winners are those who stay composed, communicate effectively, and transition their SEO approach from driving clicks to securing selections.
This transition forms the backbone of the current SEO leadership discussions.
In our latest report, I’ve dug deep into the world of Shopify Plus agencies to bring you the cream of the crop for 2026. With an exhaustive analysis of 84 agencies globally, my research focused on crucial factors like mastery of the Shopify Plus platform, customer reviews, and unique enterprise capabilities.
After meticulously evaluating each agency, I honed in on six standout contenders by ranking their abilities in areas such as technical expertise, B2B implementation success, and customer satisfaction rates. Below, I’ve summarized who made the cut and why they shine.
The Top Shopify Plus Agencies of 2026
Here, I’m unveiling the top Shopify Plus specialists! This table showcases each expert agency based on a comprehensive assessment of their technical prowess and customer delight.
With over 15 years of experience, Atwix stands as a beacon for B2B eCommerce transformation. Founded by Slava Kravchuk, Atwix leverages its vast Shopify Plus expertise, bringing innovative custom development and integration services to manufacturers and distributors.
What sets Atwix apart is their ingenious Sirius integration platform, a vital tool that links various enterprise systems with ease, ensuring real-time data accuracy. Their 96% client retention rate is a testament to their ability to offer solutions that scale as businesses expand.
Clients laud Atwix as “true professionals” providing “quick responses” and “elegant solutions” to complex challenges. Their “deep technical expertise” and proactive management are consistently highlighted.
Eastside Co: Masters of Conversion Rate Optimization
At Eastside Co, the name of the game is conversion rate optimization through precise A/B testing strategies. My insights show this agency emphasizes performance metrics, helping brands maximize their growth potential in the Shopify Plus ecosystem.
Their targeted services benefit direct-to-consumer brands, reflecting their commitment to driving results using data-driven methodologies. Though they excel in conversion, their scope might be too narrow for businesses needing expansive ecommerce solutions.
Clients commend Eastside Co for their “focus on performance metrics” and systematic approach to achieve “ROI improvements.” Their dedication to analytics stands out, though some mention the need for additional partners for broader projects.
We Make Websites: Experts in UK Headless Development
In the UK, We Make Websites is synonymous with expertise in headless commerce and performance optimization. My research indicates their focus on Core Web Vitals and innovative technical practices makes them a powerhouse for UK markets.
While they are adept at creating high-speed, dynamic experiences, their strategies focus primarily on the UK, which might pose challenges for international companies with more complex needs.
Location: London, UK
Established: 2008
Price Range: $$$$
Average Review Score: 4.8/5
Services Offered: Headless Commerce, Performance Optimization, Custom Development, API Integration, Technical SEO
Summary of Online Reviews
Clients praise them for their “attention to performance” with “lightning-fast storefronts.” However, their strong UK-centric approach can be challenging for global firms.
Digital Silk: Crafted for Large-Scale Fashion Brands
For those in the fashion arena, Digital Silk offers exceptional design-centric Shopify Plus services. Their commitment to aesthetic excellence is ideal for high-end fashion brands focused on stunning visual identity over operational intricacies.
While their creativity in design sets them apart, their services might not suit businesses looking for robust, functional ecommerce solutions with sophisticated technical requirements.
Location: New York, NY
Established: 2013
Price Range: $$$$
Average Review Score: 4.7/5
Services Offered: Brand Design, Shopify Plus Development, Visual Identity, Digital Marketing, UX Design
Summary of Online Reviews
Clients appreciate their “design quality” and the ability to craft “experiences” that highlight brands, though some note their focus on aesthetics can sometimes overlook functional needs.
Studio Rotate: Embodying Australian Commerce Design
Studio Rotate blends local market knowledge with design prowess to serve the Australian market effectively. My insights reveal their visually compelling solutions cater magnificently to regional audiences.
While their boutique approach is a boon for Australian brands, it might not match the needs of international or large enterprises seeking extensive capabilities and scalability.
Location: Melbourne, Australia
Established: 2016
Price Range: $$$
Average Review Score: 4.5/5
Services Offered: Shopify Plus Development, Australian Market Focus, Design Direction, User Experience, Local Commerce
Summary of Online Reviews
Clients remark on their “deep Australian market knowledge” and ability to craft “local designs.” However, regional focus can limit scalability for international markets.
Charle: Masters of UK Creative Solutions
Since 2018, Charle has charmed ambitious UK brands with their creative and performance-driven Shopify Plus development. With a focus on people-first strategies, they’ve built a remote-first culture that encourages innovative collaboration.
However, while offering captivating creative designs, their capacity to address comprehensive B2B functionality is limited, particularly outside the UK market.
Location: London & Manchester, UK
Established: 2018
Price Range: $$$
Average Review Score: 4.4/5
Services Offered: Shopify Plus Development, Creative Design, UK Market Focus, Platform Migration, Brand Development
Summary of Online Reviews
Clients describe their experience with Charle as “an absolute dream” due to their “creative approach” and seamless process, though their focus on UK limits global expansion capabilities.
The Top Shopify Plus Agencies in the US by Specialty
To aid you further, I’ve classified these exceptional Shopify Plus agencies into specialized categories based on detailed research. This should help you align with partners who resonate with your project goals and growth aspirations.
When I first heard about Performance Max, I was skeptical. It seemed like an unfinished product, but over the past 18 months, Google has made significant improvements in transparency and control. If you haven’t revisited Performance Max since its early days, now is the perfect time to take another look.
As I learned from Mike Ryan at SMX Next, the advancements are worthy of attention.
Taking a Fresh Look at Performance Max
Performance Max evolved from Smart Shopping campaigns, introduced with much excitement in 2019. Yet, industry experts quickly pointed out issues with transparency and control, which Google is only now beginning to address.
Smart Shopping took away vital controls critical for managing campaigns effectively. Essential features like promotional controls and search term reporting vanished, leaving many of us feeling limited.
Fortunately, Performance Max reintroduces much-needed functionality, enhancing what was once lacking.
Understanding Performance Max Search Terms
In my experience, search terms are crucial for understanding the effectiveness of our campaigns. With Performance Max, Google has added a unique match type that brings detailed and scriptable data, allowing us to optimize with precision.
Search Term Insights vs. Campaign Search Term View
Initially, Google introduced search term insights, grouping queries into categories. Unfortunately, these lacked depth as they didn’t provide essential cost data.
The game-changer, though, is the new campaign-level search term view, offering access to more metrics and clearer visibility on performance.
While these insights are only available at the search network level, they offer significant improvement over past limitations.
Search Theme Reporting
Through Performance Max, I’ve realized search themes act as a positive targeting method. By checking conversion data and the source of traffic, I can ascertain the value of search themes, identifying whether they contribute effectively or remain underutilized.
Search Term Controls and Optimization
Negative Keywords
At first, negative keywords in Performance Max were limited, which was frustrating. But now, they are fully supported and much more robust, giving me the control I need to fine-tune performance.
Brand Exclusions
While Performance Max tends to favor brand queries because of their high intent, I’ve noticed that using negative keywords provides a stronger solution for ensuring optimal performance without leakage.
Optimization Strategy
My strategy involves identifying non-performing search terms with higher-than-average clicks but zero conversions, making them strong candidates for exclusion. This approach prevents overcorrection while maintaining a focus on impactful terms.
Modern Optimization Approaches
Instead of spending countless hours manually reviewing search terms, I leverage automation. Using the API for high-volume accounts and scripts for mid-range volumes significantly optimizes my workflow.
Channels and Placements Reporting
Channel Performance Report
One of the tools I now rely on is the channel performance report, offering insights across different networks like Discover and Display. Though interpreting some diagrams can be tricky, it provides valuable data on how different channels perform.
Channel and Placement Controls
Placement Exclusions
Through API and Report Editor data, I focus on excluding specific placements that seem irrelevant or pose risks, particularly in sensitive content areas like politics and children’s videos on YouTube.
Tools for Placement Review
For reviews, especially in other languages, I’ve found that using Google Sheets’ translation function is effective. It helps me quickly determine the relevance of YouTube placements without relying on external systems.
Search Partner Network
The inability to opt out of the Search Partner Network can be frustrating. However, I mitigate this by prioritizing exclusions where performance is subpar compared to the Google Search Network.
Device Reporting and Targeting
Device Analysis
Analyzing device performance provides deeper insights into how specific products perform across different devices. This often reveals advantages or challenges when compared to competitors.
Device Targeting Considerations
Splitting campaigns by device can hurt data volume, impacting machine learning effectiveness. It’s crucial to weigh the benefits of splitting against the potential for data fragmentation.
Conclusion
Reflecting on Performance Max’s evolution, it’s evident that Google has made impressive strides in offering advertisers like myself more control and transparency. While it’s not without flaws, it’s a far more effective tool for ecommerce success now than ever before.
The key lies in understanding available data, using modern tools to streamline processes, and applying performance insights strategically to achieve the best results.
When Google introduced Demand Gen campaigns in 2023, I saw them as a promising way to boost engagement across platforms like YouTube, Discover, and Gmail.
Initially, they felt experimental, straddling the line between awareness and performance, but they’ve come a long way since.
Now, the creative flexibility and enhanced audience control make Demand Gen a go-to campaign type for my ecommerce clients.
This strategy allows me to scale revenue in a controlled manner, maintaining brand consistency while testing creative approaches to drive conversions.
I’ve found that Demand Gen delivers the best results when strategically paired with Performance Max and Search campaigns.
Advertising with Demand Gen is ideal if you crave more control.
One major drawback of Performance Max is its lack of transparency and manual control.
If precise targeting, placement, or creative control is essential, Demand Gen stands out as the better option.
Performance Max auto-generates ads from your uploads, relying on Google’s AI to mix and match for the best performance.
This makes it crucial to provide top-notch creative assets.
For example, a fitness brand might create separate asset groups for products like leggings, shorts, and vests.
While this helps target relevant audiences, the control isn’t exhaustive.
However, Demand Gen offers far superior flexibility.
It allows me to upload, preview, and tweak ad combinations before launch, adapting each creative to its unique placement.
For instance, I can customize YouTube ads for in-feed, in-stream, and Shorts placements.
This control is perfect for ecommerce brands focusing on creative precision, message testing, and maintaining a strong visual identity.
Using Demand Gen alongside Performance Max can be incredibly effective if you leverage their roles within the customer journey. They enhance each other rather than compete.
Demand Gen builds awareness and sparks interest by reaching higher-funnel audiences before they actively start product searching.
Conversely, Performance Max focuses on converting lower-funnel users who are primed to purchase.
For example, a fitness retailer might utilize Demand Gen for lifestyle videos and discovery ads promoting their latest activewear.
When a potential customer begins to research or exhibit purchase intent, Performance Max engages with tailored Shopping and Search ads to finalize the sale.
I’ve set up feed-only Performance Max campaigns, providing only a product feed within the asset group.
This restricts Performance Max activities to Shopping placements, focusing it sharply on direct conversions.
Meanwhile, Demand Gen operates across platforms like YouTube, Gmail, Discover, and Shorts, covering the upper and mid-funnel with more visual, creative content focused on awareness.
This configuration minimizes overlap between campaign types while ensuring user engagement throughout the funnel, from brand discovery to purchase.
For larger accounts with flexible budgets, this dual structure drives holistic performance and clearer attribution.
In contrast, smaller accounts seeking efficiency should prioritize mastering high-intent campaigns before layering in Demand Gen once the core conversions are stable.
The diverse campaign types now offer advertisers more flexibility than ever, yet it requires understanding Google’s restructuring of video and discovery products.
It streamlines Google’s visual placements into one campaign type, including YouTube in-stream, Shorts, in-feed, Gmail, and Discover.
This change is significant. VAC was successful for ecommerce, particularly for conversion-centric video. Its removal underscores Google’s encouragement to embrace Demand Gen.
The advantage is that Demand Gen provides stronger creative control and diverse testing options across YouTube placements.
If you previously ran VAC campaigns, they are now under Demand Gen. Ensure your top-performing assets and audiences have migrated correctly, then use the new controls to optimize performance.
Audience control is a significant benefit of Demand Gen, and it’s a reason why I consistently use it for ecommerce.
Demand Gen allows precise audience creation, letting me decide who sees the ads.
I can select placements, merge audience types, and allocate the budget strategically.
It’s the only Google Ads campaign type supporting lookalike audiences, valuable for brands focused on acquiring quality leads.
While Performance Max utilizes audience signals over fixed targeting, Demand Gen excels for control, testing, and segmentation strategies.
In mid-2025, Google rolled out an open beta for advertisers to opt out of specific Demand Gen channels manually.
This means I can now control ad display, excluding Discover or YouTube Shorts if they don’t align with my objectives or creative format.
This small but significant update offers more control, a feature often lacking in many of Google’s automated campaign types.
In early 2025, Google introduced product feed integration for Demand Gen campaigns. This change allows me to link the Google Merchant Center feed, incorporating live product data directly into visual ads.
This development bridges performance and branding for ecommerce, enabling storytelling through creative visuals while displaying actual products.
For instance, a fashion retailer can showcase a new collection in a video advert while featuring shoppable product cards below.
This update positions Demand Gen as a hybrid between Shopping and Display, a much-anticipated capability among ecommerce advertisers.
Demand Gen typically demands a larger budget than other campaign types.
Google recommends starting at about £100 per day per campaign or 20 times your target CPA/tROAS, whichever is higher.
Practically, the £100-per-day baseline is a viable starting point for effective data collection and optimization. Lower budgets restrict data flow and slow progress.
Demand Gen complements your broader Google Ads strategy, rather than replacing Search or Performance Max.
It’s a premium, visually led campaign type that boosts awareness leading to conversions, particularly effective when you have accurate measurement, a clean product feed, and clearly defined audiences.
The table compares Demand Gen and Performance Max on key aspects that matter to advertisers.
I’m excited to share my insights from our in-depth report on the top eCommerce SEO agencies of 2026. After carefully analyzing 49 companies between November 2025 and January 2026, our experts pinpointed the leading agencies based on several critical factors.
We evaluated these agencies based on the following criteria:
Notable Clients (25%): This involved a nuanced review of each agency’s previous clients, focusing on the size and prominence of their top three partners.
Average Review Score (35%): This score reflects the average ratings on major review platforms, with an emphasis on eCommerce clients, while removing excessively positive reviews to ensure fairness.
Company Size (20%): We assessed the number of employees to understand each company’s growth and stability.
Years in Business (10%): This metric highlights the company’s ability to navigate various market and economic challenges.
Estimated Media References (10%): We gauged how frequently each agency was cited by reputable media outlets.
Our detailed table, below, includes an overview of the top agencies, highlighting their unique SEO approaches and providing links for those interested in learning more.
The Top eCommerce SEO Agencies of 2026
Each agency on our list has been meticulously evaluated, and I hope my findings help you find the perfect partner to enhance your eCommerce success.
