I see Profound’s MCP evolution as a meaningful shift for Marketing Engineers. It now connects agents to a knowledge graph and adds 15 new capabilities built around how marketing teams actually work.
For retailers, I believe this demands a serious reframe. Answer engines are already shortlisting products and shaping purchase decisions long before shoppers ever land on retail or ecommerce websites. That compresses the shopping funnel and makes traditional search less reliable as the primary channel for customer acquisition.
Instead of waiting for shoppers to arrive through search, I need to think about how retailers can be recommended throughout the entire shopping journey. That means understanding how people use answer engines for Christmas gifting, how brands earn mentions and citations in relevant AI responses, and how visibility can be maximized across AI search experiences.
I see this report as a practical edge for retailers preparing for the next holiday cycle. It uses real shopper behavior from Christmas 2025, analyzed through Profound’s AI visibility lens, to show how people are using AI to shop for the holidays.
Most importantly, it turns those insights into actionable takeaways. By understanding where answer engines influence discovery, comparison, and purchase decisions, I can see how ecommerce teams should optimize product visibility before the 2026 season ramps up and compete more effectively for the AI shelf this Christmas.
I’m adjusting how I refer to Google’s shopping platform now that Google has dropped “Next” from Merchant Center Next. Going forward, the product is simply called Google Merchant Center.
Google made the change official in a Merchant Center announcement, saying, “The platform you use today will simply be referred to as Google Merchant Center.” For anyone managing product feeds, shopping campaigns, or merchant accounts, this is mainly a naming update rather than a product change.
I remember when Google Merchant Center Next was introduced in 2023 as the newer version of the old Google Merchant Center. Over the past few years, more merchants, site owners, and advertisers moved into that updated experience.
At this point, it appears that Merchant Center Next has effectively become the standard experience. So Google is removing the “Next” branding and returning to the simpler name: Google Merchant Center.
Rows of illuminated data cabinets and paper files stretch into the distance, capturing the pressure on marketers to turn fragmented customer data into a smarter performance engine.
Google said users will start seeing the “Next” branding removed from Help Center articles, email communications, and the Merchant Center interface.
Google also clarified that no action is required and that the name change does not affect existing accounts. In other words, I do not need to update settings, migrate anything, or make account-level changes because of this rebrand.
Why does this matter? When I talk about Google’s merchant tools now, I can leave off “Next” and just call the platform Google Merchant Center. Honestly, that is what many of us were already calling it anyway.
I’m seeing product feeds become far more important in ChatGPT Shopping, especially as AI systems look for clean, structured product information they can trust and cite.
Product detail pages still matter, but I no longer think brands can rely on PDPs alone when ChatGPT searches for product information. The signals that power AI shopping results appear to come from a broader mix of feeds, product data, availability, pricing, and clear brand-owned content.
After looking at what more than 1 million ChatGPT shopping offers revealed, I’d treat product feeds as a core visibility asset, not just a backend ecommerce requirement. If my feed data is incomplete, inconsistent, or hard to match to the product page, I’m making it harder for AI shopping systems to understand and recommend my products.
For brands, the takeaway is clear: I need to strengthen both my product feeds and my PDPs. The better my product data is structured, aligned, and easy to verify, the better chance I have of being cited higher in AI Shopping experiences like ChatGPT.
Every so often, I see a product launch turn into a marketing lesson bigger than the product itself. Selena Gomez’s Rare Beauty did that with a new fragrance, but it was not only the scent that drew attention. The bottle became the story. Its accessible, easy-to-use packaging sparked conversation, earned praise from accessibility advocates, and reminded me how powerful inclusive design can be when it is built into the product from the start.
For me, the lesson is clear: accessibility is not a side note. It can become the campaign. One thoughtful design choice created cultural impact that would be hard to buy with media spend alone. It also showed why accessibility can build loyalty, strengthen brand reputation, support compliance, and drive measurable growth.
Accessibility as a campaign strategy
I do not see Rare Beauty’s accessibility work as a one-off moment. From packaging to pricing to its ongoing mental health advocacy, the brand has consistently made inclusivity part of its identity. That matters because consumers can usually tell when a brand is chasing attention versus when it is acting from a real strategy. They reward brands that lead with values and follow through.
Rare Beauty is not alone. I see leading brands across industries using accessibility as a differentiator, not a footnote. Apple often frames accessibility features as part of product innovation. Microsoft has brought inclusive design into mainstream campaigns, including adaptive gaming products that positioned accessibility as a source of creativity and connection. In fashion and retail, brands like Tommy Hilfiger and Unilever have put adaptive design into product launches and brand identity instead of treating it as a niche offering.
Studies from Edelman and McKinsey show why this shift matters. According to those studies, 73% of Gen Z choose to buy from brands they believe in, and 70% say they try to purchase products from companies they consider ethical. I do not see those as fringe preferences. I see them as mainstream expectations that should change how marketers build trust and growth.
The $18 trillion market marketers overlook
More than 1.3 billion people globally live with a disability. Together with their friends and family, they control more than $18 trillion in spending power, according to the Return on Disability Group. I believe marketers should view this as more than a compliance issue. It is a growth opportunity, a reputation opportunity, and a trust-building opportunity with one of the world’s largest and most passionate consumer groups.
That passion often turns into advocacy. In discussions with AudioEye’s A11iance Team, a group of individuals with disabilities who regularly share feedback on real-world accessibility experiences, one member said, “If I find a website that works and works very well for me, I will always recommend it to friends and family because I want people to have the same experience that I have.”
Another A11iance Team member, Maxwell Ivey, put it this way: “The cheapest form of advertising is word of mouth, and people with disabilities can have some of the loudest voices when we find people willing to make the effort. Because it’s that sincere effort over time that really counts with us.”
When accessibility becomes part of the customer experience, I see it create something media budgets cannot easily buy: trust and loyalty that scale through advocacy. But the reverse is also true. In a survey of assistive technology users, 54% said they do not feel eCommerce companies care about earning their business.
That should get every marketer’s attention. Too many brands are still fighting for the same crowded audience segments while overlooking a major opportunity in plain sight. When they do, they leave loyalty, advocacy, and revenue on the table.
Here is where I see many brands stumble: accessibility often stops at the shelf. Marketers invest heavily in packaging, store displays, and product design, while digital experiences lag behind. Yet those digital experiences are often the first and most important touchpoints customers have with a brand.
As accessibility-led design earns more attention, loyalty, and earned media, the gap between physical product innovation and digital experience becomes harder to ignore.
AudioEye’s 2025 Digital Accessibility Index found an average of 297 accessibility issues per web page detectable by automation alone. Each issue can create friction in the customer journey, cost a conversion, or introduce compliance risk under frameworks such as the Americans with Disabilities Act (ADA) and the European Accessibility Act (EAA).
I would not launch a campaign without a brand review or a legal check. In the same way, I do not think any digital touchpoint should go live without an accessibility review.
Four moves marketing leaders can make
Too often, I see accessibility treated as a risk to manage instead of an advantage to use. The marketers who gain ground will be the ones who change that mindset. I would start with four practical moves.
1. Make accessibility your campaign hook
I would not hide accessibility in the fine print. I would lead with it. Brands like Rare Beauty have shown that inclusive design is the story. Build campaigns where accessibility is not an afterthought, but the differentiator that earns attention and loyalty.
2. Bake it into your brand system
Accessibility should not sit off to the side. I would make Web Content Accessibility Guidelines (WCAG) alignment part of the brand system, right alongside typography, logos, and tone of voice. When accessibility is documented and expected, it becomes easier to apply across every campaign.
3. Use data as your proof point
Marketers are storytellers, but numbers strengthen the story. I would track accessibility improvements such as fewer user-reported barriers, higher accessibility scores, stronger alt text, better color contrast, and more usable forms. Then I would connect those metrics to business outcomes like conversion, reach, and sentiment to show how accessibility drives ROI, not just compliance.
4. Protect accessibility like brand safety
I would treat accessibility with the same seriousness as brand safety. Every update, seasonal campaign, and product drop should be monitored for accessibility. Trust and reputation are too valuable to leave exposed.
The competitive advantage
Rare Beauty’s fragrance launch proved something important to me: when a brand leads with accessibility, the story can write itself. Loyalty builds more authentically, and momentum feels more natural because the value is real.
The larger opportunity is that many brands still do not see it. They continue to treat accessibility as a compliance checkbox when it can be a growth strategy.
For marketers, that is the wake-up call. Accessibility builds loyalty. It strengthens brand reputation. It supports compliance. And it can drive measurable growth across marketing efforts.
Rare Beauty showed how accessibility can capture attention at the shelf. Now I see the next opportunity clearly: making sure that same accessibility carries through online. When every touchpoint welcomes everyone, every campaign has a better chance to deliver its full impact.
I’ve always been fascinated by how technology can change the way we interact with advertisements, and Amazon’s latest innovation, Alexa+ Agentic Ads, is a game-changer.
This incredible new format allows us to browse, inquire, and purchase products within the comforting interface of an Alexa conversation, dramatically simplifying the buying process.
Introducing Alexa+ Agentic Ads. Today, Amazon unveiled this forward-thinking advertising solution that seamlessly transitions users from viewing an ad to making a purchase, all without leaving the Alexa environment.
They’ve partnered with key players like Papa Johns for food orders and artists like Beck, Jill Scott, and Omar Courtz for concert ticket sales, making this experience accessible on Echo Show devices.
The Impact. By eliminating the typical handoff between an ad and a checkout page, Alexa+ Agentic Ads aim to enhance conversion rates and reduce drop-off. This could be especially beneficial for early adopters looking to engage high-intent customers right at their moment of decision.
How It Operates. Unlike traditional ads that redirect you to another platform, Alexa+ Agentic Ads maintain the entire purchasing journey within a dialogue.
With interactive capabilities, it enables us to ask questions, compare options, check availability, and finalize purchases through natural conversations with Alexa, minimizing friction between desire and acquisition.
Concerts and Culinary Delight. The format is initially being utilized for live events and dining experiences.
Imagine seeing an ad for a concert; you can inquire about show specifics, compare seat options, and buy tickets—all directly through Alexa. Tickets are then seamlessly added to your Ticketmaster account, bypassing the need for additional apps or sites.
Similarly, when pondering dinner plans, a Papa Johns ad may spark immediate ordering as Alexa+ employs past interactions and preferences to suggest your favorite toppings before completing the order—all within the same conversation.
Looking Ahead. As we witness the evolution of digital advertising through Alexa+ Agentic Ads, we’re glimpsing a future where AI assistants are pivotal commerce platforms, offering brands a revolutionary way to engage consumers right at the point of action.
I’ve always been fascinated by the evolving nature of SEO, especially in an era dominated by artificial intelligence. For over twenty years, SEO heavily relied on keywords. But with the rise of generative AI and conversational tools like ChatGPT, we’re now seeing a shift toward prompts as the backbone of search visibility.
Understanding the prompts my audience uses with large language models is crucial. Otherwise, my content might never see the light of day in search results. Let’s explore how prompts vary by industry and their impact on search visibility.
How Prompts Differ by Vertical
It’s clear to me that the context holds paramount importance in the responses generated by large language models (LLMs). Different industries have specific patterns that dictate how users construct their prompts. I need to tailor my content to these unique frameworks to ensure maximum relevance.
Healthcare: Symptom-driven and Cautious Language
In the healthcare sector, I’ve observed users leveraging AI as an initial triage tool. Instead of a vague term like “chronic fatigue,” detailed prompts narrate specific symptoms.
The prompt pattern: These healthcare prompts are rich in personal context, symptom mapping, and cautious constraints. Questions often revolve around symptom lists and safety considerations linked to age or medication.
Anatomy of a healthcare prompt: Consider a prompt like: “I’m a 45-year-old female experiencing sudden joint pain and a rash after starting [Medication X]. What side effects should I monitor, and when is it critical to seek medical help?”
The content shift: To stand out here, my content cannot simply define medical terms. It must align with a patient’s decision-making process.
The action: I focus on structured FAQs, clear risk factors, and headers addressing specific symptoms combinations to engage effectively.
B2B: Comparison-heavy and ROI-driven
In B2B contexts, I see users turning to AI for detailed comparisons and ROI evaluations, bypassing traditional marketing materials.
The prompt pattern: B2B prompts are analytical, featuring deep dives into financial justifications. Requests often include data for presentation-ready tables or matrices.
Anatomy of a B2B prompt: Typical requests might be like: “Compare CRM ‘Brand A’ and ‘Brand B’ for a 500-user company, with implementation timelines and ROI over three years formatted in a table.”
The content shift: Without transparent, data-rich content, my B2B efforts remain invisible to LLMs.
The action: I need to publish open comparison pages with hard data, ensuring technical details are structured in an easily extractable format for AI systems.
Ecommerce: Intentional Clusters of ‘Best,’ ‘Cheap,’ and ‘Reviews’
The ecommerce landscape, as I see it, is an interactive shopping experience with AI-driven, personalized recommendations.
The prompt pattern: Queries often combine quality markers like “best reviewed” with budget constraints like “under $150” within specific contexts.
Anatomy of an ecommerce prompt: An example might be: “What are the best-reviewed running shoes for overpronators under $150, excluding brands with poor durability?”
The content shift: Beyond simple keyword targeting, I must infuse my content with the semantic depth necessary for LLM validation.
The action: I optimize my merchant feeds with conversational attributes, ensure crawlable user reviews, and connect product specs to consumer value.
Why Prompt Structure Impacts Your Search Visibility
Understanding why prompt structures matter is key for me. They shape whether my site appears in LLM responses, based on how a user constructs their inquiry.
The Power of ‘Reasoning Lift’ and Direct Citations
By optimizing for direct citations and structured data, I could boost the visibility of my content by up to 40%, according to research from Princeton and the Allen Institute for AI.
It’s intriguing how more than 80% of links in AI-driven searches come from domains not ranking in traditional top searches. This emphasizes the importance of content quality and structure over legacy backlinks.
Operationalizing Prompt Research
Shifting my focus from keywords to prompts is crucial. I need to revamp my content strategy to align with conversational search trends, ensuring my brand stays visible.
Stop tracking isolated keywords: Instead, I’ll search for conversational data within search logs and consumer interactions.
Audit for LLM readability: My content must be easily parseable by AI, underpinned by modern standards and structured data.
Write for the follow-up: Rather than focusing solely on initial queries, I’ll anticipate and address follow-up questions within the same content.
To stay ahead, aligning my content with AI interaction patterns is non-negotiable.
Tuesday was quite a day as I experienced a significant Shopify disruption impacting essential commerce functions. Many merchants, including myself, found it challenging to manage our stores, while customers faced difficulties completing their purchases.
The big picture. Shopify confirmed that issues affected multiple services, such as storefronts, checkouts, the admin dashboard, and Retail POS. I’m sure other merchants felt the effect just as I did, struggling to maintain access to Shopify Support during this downtime.
What happened. Shopify first acknowledged the problem at 9:27 a.m. EDT. We were informed that merchants might face access issues with:
Shopify Admin
Retail POS
While dealing with my own frustrations, I realized customers may encounter issues with storefronts and checkouts, making the day particularly challenging for those relying on Shopify Support.
Why we care. It’s crucial to monitor storefronts and checkouts; their unavailability means paid traffic can’t convert to sales, risking wasted ad spend and misaligned campaign performance data. For those running ads on platforms like Google or TikTok, keeping a close eye on performance during such outages is vital in assessing campaign results.
Latest status. By 10:37 a.m. EDT, Shopify reported identifying the root cause, noting improvements. “We’ve identified the problem and are seeing recovery from our mitigation efforts,” Shopify updated us, pledging continued monitoring.
Earlier updates at 9:45 a.m. EDT mentioned Shopify actively investigating the situation. It’s a relief to see progress, but vigilance remains necessary.
Between the lines. Given Shopify’s vast reach, even brief interruptions can immediately affect merchants’ revenue, especially when checkouts are compromised. This outage was a stark reminder of how pivotal continuous platform availability is for businesses.
For anyone with ongoing promotions or high-traffic campaigns, disruptions translate into lost sales and frustrated customers, something we all dread as business owners.
What to watch. While Shopify mentioned recovering services, I, like many, will keep monitoring until the incident is declared entirely resolved. It highlights our dependence on core platform providers like Shopify for crucial ecommerce functions.
The outage serves as a potent reminder of how much ecommerce relies on a few key platforms. Ensuring diversifications and contingencies is more important than ever.
First spotted. A heads-up on this issue came from Senior Paid Media Manager Ayisha Yousef, who encountered an error message and shared it on LinkedIn. This alerts us of how even internal team members aid in monitoring ongoing situations.
When I search for products on Google, I’ve noticed significant changes to the results page. Now, product packs and scrollable carousels appear multiple times within a single results page, reshaping my shopping experience.
As part of my ongoing journey to boost ecommerce visibility, I constantly analyze data. Recently, I’ve tracked searches presenting up to 60 individual organic product listings on one page. These premium placements increasingly mark the beginning of the purchase journey for many users.
This transformation is gradual, and interestingly, I see many brands still adjusting their strategies. It’s crucial to revisit these changes because the opportunity for traffic through product packs is immense, with fierce competition. Today’s leading brands approach this differently.
Thanks to Nozzle, I’ve delved into data from over 63,000 merchants across a wide array of ecommerce keywords from January 2025 to January 2026. Here’s what I discovered that really caught my attention.
Defining Success: Appearances vs. Actual Traffic
I found that just appearing in product packs and actually capturing traffic are two distinct achievements, and the difference between them can be substantial as the data shows.
For instance, in this dataset:
eBay appears in product results for 874,621 keywords.
Home Depot has a similar presence, appearing for 831,699 keywords.
However, the estimated traffic paints a contrasting picture:
eBay garners about 3.2 million visits from these pack appearances.
Home Depot, meanwhile, generates nearly 28.8 million visits from a slightly smaller keyword range.
The secret? Quality position within the pack. Home Depot’s products consistently snag prime, visible, above-the-fold spots that attract shoppers’ clicks.
For eBay, many keywords involve long-tail marketplace terms that dilute overall impact. Understanding Google’s use of product packs to drive purchase decisions for common goods is crucial for brands aiming to compete effectively in this space.
For marketers: Dissecting product pack performance means wisely segmenting data, focusing on categories with significant search volumes to optimize visibility within the packs. That’s how to pinpoint where the genuine opportunities lie.
The Critical Gap: Distinguishing Product Pack Visibility
Product carousels scroll horizontally, increasing exposure for the first few slots, while listings tucked further back remain unseen. This distinction is crucial for assessing true reach.
Disparities among major retailers further illustrate this point:
REI has a massive catalog of 3.8 million products, yet 1.52 million of these require scrolling before they are visible.
Walmart finds itself in a similar spot, with 1.29 million of its 3.5 million unique products are relegated to non-visible placements.
Even industry titans often miss out on optimal visibility, skewing the perceived benefits of their presence. Analyzing visible versus non-visible appearances is essential for identifying where optimizing product data and feeds can yield substantial returns.
For CMOs: When using total product pack appearances as a metric, it’s wise to ask how many of those appearances are truly visible. Understanding this ratio better reflects the channel’s contribution to the business.
Does Discounting Drive Product Pack Visibility?
It’s a common belief that discounted items might secure better placement in Google’s product packs. However, data from the top 10 merchants doesn’t necessarily support this notion.
Amazon.com leads the pack with 49% of its catalog discounted, achieving a 72% visibility rate, placing it squarely mid-tier.
eBay, on the other hand, discounts only 8% of its products yet matches the highest visibility rate in the dataset at 81%.
Walmart Seller discounts 24% of its items, reaching 81% visibility, while Walmart itself discounts 27% but ranks lower at 62% visibility.
This irregularity indicates that discounting is just one of many factors. It doesn’t solely determine a product’s chance of securing a prominent spot. Feed quality, category relevance, reviews, and image standards wield greater influence.
For retail teams: If your strategy for product packs relies heavily on promotions, you might need to pivot. The current landscape favors strategies aligned with where purchasing decisions occur over sheer pricing tactics.
Specialist Brands Competing with Giants and Winning
A refreshing realization from this data is that product pack success isn’t exclusive to the retail giants. Specialist brands, leveraging focused expertise, compete exceptionally well against far larger competitors.
Camp Chef, for instance, appears in results for 155,299 keywords—just a small fraction of Walmart or eBay’s footprint—yet it pulls in an estimated 2.6 million visits, thanks to advantageous product placements.
Brands like Fellow, expanding into niches such as high-end coffee makers, find opportunities for growth through strong organic channels.
These brands achieve impressive product pack traffic against much larger rivals because they prioritize category relevance and high-quality product feeds over sheer scale.
For brands traditionally overshadowed in traditional SEO, product packs present a chance to compete on a more level field. Detailed product data, competitive prices, quality imagery, and favorable reviews can supersede a larger competitor for crucial category keywords.
For agencies: This channel awards dedication and quality over brute scale. Brands with depth in a category can translate that expertise into superior product pack performance, outpacing broader competitors.
Staying Informed on Product Pack Visibility Shifts
Examining the entire dataset, I noticed a consistent pattern: nearly all merchants experience shifts in product pack visibility throughout the year.
Brands holding strong positions during parts of the year sometimes see fluctuations as Google adjusts how it surfaces product results. Some grew steadily midyear only to recede in Q4, while others surged during promotions before reverting to previous levels.
This fluidity is typical of the channel. Google regularly updates its criteria for product pack placements, influenced by factors like feed quality, product availability, review counts, pricing, and images.
The brands thriving are those with sustained visibility into performance, staying agile and responsive to changes before they impact revenue.
With Google’s future announcements and AI integration like Gemini 3 looming, the foundational structure of product packs will shift, influenced by agentic commerce and the Universal Commerce Protocol.
As Google navigates balancing paid and organic visibility, a two-tiered search economy emerges. Securing AI Overview citations becomes vital for brand recognition, impacting both organic and paid product pack performances.
The Bigger Picture
Google’s product packs have morphed from merely supplementary to pivotal touchpoints in commercial searches.
The extensive Nozzle data analysis of over 63,000 merchants reveals that competition is already fierce in this domain. Leaders are distancing themselves, and the gap between attentive and indifferent brands manifests tangibly in traffic and revenue disparities.
The silver lining is that the essentials for success in this space are accessible to most brands: robust product data, strategic pricing, high-quality creative, and vigilant monitoring.
These require not a colossal budget but focus, the right tools, and asking the right strategic questions within the right organizational levels.
I recently discovered a fascinating development from OpenAI that has the potential to revolutionize e-commerce advertising. They’ve started transforming product catalogues into automated ads within ChatGPT, allowing retailers to seamlessly scale their campaigns.
Retailers now have the option to connect their product feeds directly to ChatGPT. This integration means that the platform can generate ads automatically, using product names, images, and other attributes. Gone are the days of manually crafting campaigns!
For users, these ads will still appear beneath responses and remain clearly labeled as sponsored content. There’s no change here in terms of user experience.
As someone interested in how e-commerce brands operate, I’m intrigued by this update. It significantly reduces the barriers that retailers with large inventories face when running scaled ads.
Brands have the flexibility to establish rules on which products are featured, allowing the system to efficiently generate ads. It reminds me of how shopping campaigns function on platforms like Google, leveraging structured feeds for both organic and paid visibility.
Previously, ChatGPT could use product data for answering queries but not for advertising purposes. Now, with this advancement, the same data supports both functions, bridging the gap between organic presence and paid campaigns.
This shift signals how OpenAI is looking to monetize shopping. Instead of taking a slice of transactions, they’re targeting ad budgets typically spent on platforms like Amazon and Meta.
Industry analyst Debra Aho Williamson calls this shift to feed-based automation a necessity, highlighting ChatGPT’s unique approach to serving ads based on conversational intent, a distinct advantage.
According to ad tech partners like StackAdapt, the integration with existing feeds is straightforward, easing the adoption process.
This latest move is part of a series of updates that focus on performance, including cost-per-click bidding and new conversion tracking tools. Cost-per-action models are reportedly in development, suggesting an even deeper focus on performance advertising.
I’m eager to see more retailers experimenting with ChatGPT as a performance channel. The ease of setup might make this an attractive option, but the real test will be if conversational intent can drive conversions as efficiently as traditional methods.
The bottom line is that OpenAI is effectively turning product feeds into ads, making ChatGPT a more potent, scalable channel for e-commerce advertising.
I’ve noticed it’s not uncommon to come across articles proclaiming that AI agents are about to revolutionize Google Ads, SEO, or social media. Initially, these AI agents seem promising, at least in theory.
But when I dive deeper into what data these agents actually utilize, it’s almost always platform-native. For Google Ads, this translates to impressions, clicks, conversions, and ROAS.
This simplistic approach is why PPC AI agents often stumble right from the start. If they only have platform-specific data, managing true marketing strategies becomes impossible.
Why Many PPC Agents Are Just AI Assistants
Many tools labeled as PPC agents are mostly AI assistants, focusing on tasks such as:
Generating various headline options
Describing product images for Responsive Search Ads
Drafting CTAs for Performance Max asset groups
While these tasks are beneficial in freeing up time, they’re not quite the PPC agents they claim to be—they’re just dressed up generative AI tools.
A true PPC agent operates directly on an ad account by analyzing performance data and making strategic decisions, like adjusting budgets and optimizing campaign structures based on informed insights.
How AI Agents Create a Closed Loop
Google Ads has a limited view of your business data, causing AI agents to often optimize a closed loop focused solely on improving platform metrics, which may negatively affect business performance.
For instance, Google Ads doesn’t know specifics like average deal size or which products have high margins. This ignorance can lead to suboptimal decisions.
Performance Max: A Precursor to AI Challenges
This conundrum isn’t new. PMax campaigns already demonstrated the pitfalls without adequate data, as they often optimized towards the wrong goals without necessary business insights.
PPC Agents Risk Misalignment Without Business Data
AI agents exacerbate the speed at which misaligned strategies can cause harm. Even the best systems need backend business data to make informed decisions, just as your agent would.
3 Essential Types of Business Data for PPC AI Agents
To enhance PPC agent performance, integrating CRM, product, and operational data is crucial.
1. CRM Data
CRM data is vital for understanding lead values beyond mere conversion counts. You can bridge this gap with offline conversion tracking or direct CRM access for a deeper analysis.
2. Product Margin Data
Understanding product margins is essential for eCommerce success. This data should come from supplementary feeds or direct backend connections, allowing for more strategic budget allocations.
3. Operational Data
Operational signals, like fulfillment capacity, also impact decision-making. Effective coordination and data flow help prevent suboptimal choices that might appear beneficial only theoretically.
Questions to Ask Before Building a PPC AI Agent
Before developing a PPC AI agent, pinpoint the essential business data required to optimize campaign performance, starting with OCT and progressing to direct CRM links for comprehensive insights.
Ultimately, the challenge isn’t building the agent but integrating it seamlessly with business realities for genuine value extraction.
