<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/07/Why-phrase-match-is-losing-ground-to-broad-match-in-Google-Ads.png" class="attachment-large size-large wp-post-image" alt="Why phrase match is losing ground to broad match in Google Ads" style="margin-bottom: 15px;" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2025/07/Why-phrase-match-is-losing-ground-to-broad-match-in-Google-Ads.png 1920w, https://searchengineland.com/wp-content/seloads/2025/07/Why-phrase-match-is-losing-ground-to-broad-match-in-Google-Ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/07/Why-phrase-match-is-losing-ground-to-broad-match-in-Google-Ads-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google clarified that exact keywords don’t serve ads in AIOs — but they also no longer prevent broad match keywords from triggering those placements.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/07/Why-phrase-match-is-losing-ground-to-broad-match-in-Google-Ads.png" class="attachment-large size-large wp-post-image" alt="Why phrase match is losing ground to broad match in Google Ads" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/07/Why-phrase-match-is-losing-ground-to-broad-match-in-Google-Ads.png 1920w, https://searchengineland.com/wp-content/seloads/2025/07/Why-phrase-match-is-losing-ground-to-broad-match-in-Google-Ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/07/Why-phrase-match-is-losing-ground-to-broad-match-in-Google-Ads-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Ginny Marvin, Google’s Ads Liaison, is clarifying how keyword match types interact with AI Overviews (AIO) and AI Mode ad placements — addressing ongoing confusion among advertisers testing AI Max and mixed match-type setups.</p>



<p><strong>Why we care.</strong> As ads expand into AI-powered placements, advertisers need to understand which keywords are eligible to serve — and when — to avoid unintentionally blocking reach or misreading performance.</p>



<p><strong>Back in May</strong>. Responding to questions from Marketing Director Yoav Eitani, Marvin confirmed that an ad can serve either above or below an AI Overview <em>or</em> within the AI Overview — but not both in the same auction:</p>



<ul class="wp-block-list">
<li>&#8220;Your ad could trigger to show either above/below AIO or within AIO, but not both at this time.&#8221; Marvin confirmed.</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="597" height="488" src="https://searchengineland.com/wp-content/seloads/2025/12/Screenshot-2025-12-16-at-19.27.38.png" alt="" class="wp-image-466331"/></figure></div>


<p>While both exact and broad match keywords can be eligible to trigger ads above or below AIO, only broad match keywords (or keywordless targeting) are eligible to trigger ads within AI Overviews.</p>



<p><strong>What’s changed</strong>. In a follow-up exchange with Paid Search specialist Toan Tran, Marvin clarified that Google has updated how eligibility works. Previously, the presence of an exact match keyword could prevent a broad match keyword from serving in AI Overviews. That is no longer the case. </p>



<ul class="wp-block-list">
<li>&#8220;The presence of the same keyword in exact match will not prevent the broad match keyword from triggering an ad in an AI Overview, since the exact match keyword is not eligible to show Ads in AI Overviews and hence not competing with the broad match keyword.&#8221; Marvin said.</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><a href="https://x.com/adsliaison/status/1999188199629844709?s=20"><img decoding="async" width="611" height="357" src="https://searchengineland.com/wp-content/seloads/2025/12/Screenshot-2025-12-16-at-19.23.00-1.png" alt="" class="wp-image-466333"/></a></figure></div>


<p>Since exact and phrase match keywords are not eligible for AI Overview placements, they do not compete with broad match keywords in that auction — meaning broad match can still trigger ads within AIO even when the same keyword exists as exact match.</p>



<p><strong>The big picture</strong>. Google is reinforcing a clear separation between traditional keyword matching and AI-powered intent matching. Ads in AI Overviews rely on a deeper understanding of both the user query and the AI-generated content, which is why eligibility is limited to broader targeting signals.</p>



<p><strong>The bottom line</strong>. Exact and phrase match keywords won’t show ads in AI Overviews — but they also won’t block broad match from doing so. For advertisers leaning into AI Max and AIO placements, broad match and keywordless strategies are now essential to unlocking reach in Google’s AI-driven surfaces.</p>


Ginny Marvin, Google’s Ads Liaison, is clarifying how keyword match types interact with AI Overviews (AIO) and AI Mode ad placements — addressing ongoing confusion among advertisers testing AI Max and mixed match-type setups.
Why we care. As ads expand into AI-powered placements, advertisers need to understand which keywords are eligible to serve — and when — to avoid unintentionally blocking reach or misreading performance.
Back in May. Responding to questions from Marketing Director Yoav Eitani, Marvin confirmed that an ad can serve either above or below an AI Overview or within the AI Overview — but not both in the same auction:
“Your ad could trigger to show either above/below AIO or within AIO, but not both at this time.” Marvin confirmed.

While both exact and broad match keywords can be eligible to trigger ads above or below AIO, only broad match keywords (or keywordless targeting) are eligible to trigger ads within AI Overviews.
What’s changed. In a follow-up exchange with Paid Search specialist Toan Tran, Marvin clarified that Google has updated how eligibility works. Previously, the presence of an exact match keyword could prevent a broad match keyword from serving in AI Overviews. That is no longer the case. 
“The presence of the same keyword in exact match will not prevent the broad match keyword from triggering an ad in an AI Overview, since the exact match keyword is not eligible to show Ads in AI Overviews and hence not competing with the broad match keyword.” Marvin said.

Since exact and phrase match keywords are not eligible for AI Overview placements, they do not compete with broad match keywords in that auction — meaning broad match can still trigger ads within AIO even when the same keyword exists as exact match.
The big picture. Google is reinforcing a clear separation between traditional keyword matching and AI-powered intent matching. Ads in AI Overviews rely on a deeper understanding of both the user query and the AI-generated content, which is why eligibility is limited to broader targeting signals.
The bottom line. Exact and phrase match keywords won’t show ads in AI Overviews — but they also won’t block broad match from doing so. For advertisers leaning into AI Max and AIO placements, broad match and keywordless strategies are now essential to unlocking reach in Google’s AI-driven surfaces.

Google clarified that exact keywords don’t serve ads in AIOs — but they also no longer prevent broad match keywords from triggering those placements.

Google: Exact match keywords won’t block broad match in AI Max

<div><img width="800" height="457" src="https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-800x457.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-800x457.jpg 800w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-592x338.jpg 592w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-198x113.jpg 198w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-1536x878.jpg 1536w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Semrush analyzed 10 million keywords and found volatility, more ads, stronger CTRs, and AI Overviews expanding beyond informational intent.

<div><img width="800" height="457" src="https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-800x457.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-800x457.jpg 800w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-592x338.jpg 592w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-198x113.jpg 198w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920-1536x878.jpg 1536w, https://searchengineland.com/wp-content/seloads/2025/04/google-robot-on-phone-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google rapidly expanded AI Overviews in search during 2025, then pulled back as they moved into commercial and navigational queries. These findings are based on a new Semrush analysis of more than 10 million keywords from January to November.</p>



<p><strong>AI Overviews surged, then retreated</strong>. Google didn’t roll out AI Overviews in a straight line in 2025. A mid-year spike gave way to a pullback, suggesting Google moved fast to test the feature, then eased off based on user data:</p>



<ul class="wp-block-list">
<li><strong>January:</strong> 6.5% of queries triggered an AI Overview</li>



<li><strong>July:</strong> AI Overview visibility peaked, appearing in just under 25% of queries.</li>



<li><strong>November:</strong> Coverage fell back to less than 16% of queries.</li>
</ul>



<p><strong>Zero-click behavior defied expectations.</strong> Surprisingly, click-through rates for keywords with AI Overviews have steadily risen since January. AI Overviews don’t automatically reduce clicks and may even encourage them.</p>



<ul class="wp-block-list">
<li>AI Overviews still appear more often on searches that already tend to drive no clicks.</li>



<li>But when Semrush compared the same keywords before and after an AI Overview appeared, zero-click rates fell from 33.75% to 31.53%.</li>
</ul>



<p><strong>Informational queries no longer dominate. </strong>Early 2025 AI Overviews were almost entirely informational:</p>



<ul class="wp-block-list">
<li>January: 91% informational</li>



<li>October: 57% informational</li>
</ul>



<p>Now, AI Overviews are appearing for commercial and transactional queries:</p>



<ul class="wp-block-list">
<li>Commercial queries: Increased from 8% to 18%</li>



<li>Transactional queries: Increased from 2% to 14%</li>
</ul>



<p><strong>Navigational queries are rising fast.</strong> In an unexpected shift, AI summaries are increasingly intercepting brand and destination searches:</p>



<ul class="wp-block-list">
<li>Navigational AI Overviews grew from under 1% in January to more than 10% by November.</li>
</ul>



<p><strong>Google Ads + AI Overviews. </strong>Earlier this year, ads rarely appeared next to AI Overviews. Now they’re common:</p>



<ul class="wp-block-list">
<li>Ads alongside AI Overviews rose from about 3% in January to roughly 40% by November.</li>



<li>Ads show at the bottom of around 25% of AI Overview SERPs.</li>
</ul>



<p><strong>Science is the most impacted industry. </strong>By keyword saturation, Science leads all verticals for AI Overviews at 25.96%. Computers &amp; Electronics follows at 17.92%, with People &amp; Society close behind at 17.29%.</p>



<ul class="wp-block-list">
<li>Since March, Food &amp; Drink has seen the fastest growth in AI Overviews of any category.</li>



<li>Meanwhile, Real Estate, Shopping, and Arts &amp; Entertainment remain lightly affected, with AI Overviews appearing on fewer than 3% of keywords.</li>
</ul>



<p><strong>Why we care. </strong>AI Overviews are unevenly and persistently reshaping click behavior, commercial visibility, and ad placement. Volatility is likely to continue, so closely monitor performance shifts tied to AI Overviews.</p>



<p><strong>The report. </strong><a href="https://www.semrush.com/blog/semrush-ai-overviews-study/" target="_blank" rel="noopener">Semrush AI Overviews Study: What 2025 SEO Data Tells Us About Google’s Search Shift</a></p>



<p><strong>Dig deeper.</strong> In May, I reported on the original version of Semrush&#8217;s study in <a href="https://searchengineland.com/google-ai-overviews-13-searches-455057">Google AI Overviews now show on 13% of searches: Study</a>.</p>


Google rapidly expanded AI Overviews in search during 2025, then pulled back as they moved into commercial and navigational queries. These findings are based on a new Semrush analysis of more than 10 million keywords from January to November.
AI Overviews surged, then retreated. Google didn’t roll out AI Overviews in a straight line in 2025. A mid-year spike gave way to a pullback, suggesting Google moved fast to test the feature, then eased off based on user data:
January: 6.5% of queries triggered an AI Overview
July: AI Overview visibility peaked, appearing in just under 25% of queries.
November: Coverage fell back to less than 16% of queries.
Zero-click behavior defied expectations. Surprisingly, click-through rates for keywords with AI Overviews have steadily risen since January. AI Overviews don’t automatically reduce clicks and may even encourage them.
AI Overviews still appear more often on searches that already tend to drive no clicks.
But when Semrush compared the same keywords before and after an AI Overview appeared, zero-click rates fell from 33.75% to 31.53%.
Informational queries no longer dominate. Early 2025 AI Overviews were almost entirely informational:
January: 91% informational
October: 57% informational
Now, AI Overviews are appearing for commercial and transactional queries:
Commercial queries: Increased from 8% to 18%
Transactional queries: Increased from 2% to 14%
Navigational queries are rising fast. In an unexpected shift, AI summaries are increasingly intercepting brand and destination searches:
Navigational AI Overviews grew from under 1% in January to more than 10% by November.
Google Ads + AI Overviews. Earlier this year, ads rarely appeared next to AI Overviews. Now they’re common:
Ads alongside AI Overviews rose from about 3% in January to roughly 40% by November.
Ads show at the bottom of around 25% of AI Overview SERPs.
Science is the most impacted industry. By keyword saturation, Science leads all verticals for AI Overviews at 25.96%. Computers & Electronics follows at 17.92%, with People & Society close behind at 17.29%.
Since March, Food & Drink has seen the fastest growth in AI Overviews of any category.
Meanwhile, Real Estate, Shopping, and Arts & Entertainment remain lightly affected, with AI Overviews appearing on fewer than 3% of keywords.
Why we care. AI Overviews are unevenly and persistently reshaping click behavior, commercial visibility, and ad placement. Volatility is likely to continue, so closely monitor performance shifts tied to AI Overviews.
The report. Semrush AI Overviews Study: What 2025 SEO Data Tells Us About Google’s Search Shift
Dig deeper. In May, I reported on the original version of Semrush’s study in Google AI Overviews now show on 13% of searches: Study.

Semrush analyzed 10 million keywords and found volatility, more ads, stronger CTRs, and AI Overviews expanding beyond informational intent.

Google AI Overviews surged in 2025, then pulled back: Data

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/The-enterprise-blueprint-for-winning-visibility-in-AI-search.png" class="attachment-large size-large wp-post-image" alt="The enterprise blueprint for winning visibility in AI search" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/The-enterprise-blueprint-for-winning-visibility-in-AI-search.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/The-enterprise-blueprint-for-winning-visibility-in-AI-search-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/The-enterprise-blueprint-for-winning-visibility-in-AI-search-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>What it takes to operationalize entities and schema across large organizations, without breaking governance or increasing technical debt.

We are navigating the “search everywhere” revolution – a disruptive shift driven by generative AI and large language models (LLMs) that is reshaping the relationship between brands, consumers, and search engines.
For the last two decades, the digital economy ran on a simple exchange: content for clicks. 
With the rise of zero-click experiences, AI Overviews, and assistant-led research, that exchange is breaking down.
AI now synthesizes answers directly on the SERP, often satisfying intent without a visit to a website. 
Platforms such as Gemini and ChatGPT are fundamentally changing how information is discovered. 
For enterprises, visibility increasingly depends on whether content is recognized as authoritative by both search engines and AI systems.
That shift introduces a new goal – to become the source that AI cites.
A content knowledge graph is essential to achieving that goal. 
By leveraging structured data and entity SEO, brands can build a semantic data layer that enables AI to accurately interpret their entities and relationships, ensuring continued discoverability in this evolving economy.
This article explores:
The difference between traditional search and AI search, including the concept of comprehension budget.
Why schema and entity optimization are foundational to discovery in AI search.
The content knowledge graph and the importance of organizational entity lineage.
The enterprise entity optimization playbook and deployment checklist.
The role of schema in the agentic web.
How connected journeys improve customer discovery and total cost of ownership.
The fundamental difference between traditional and AI search
To become a source that AI cites, it’s essential to understand how traditional search differs from AI-driven search.
Traditional search functioned much like software as a service. 
It was deterministic, following fixed, rule-based logic and producing the same output for the same input every time.
AI search is probabilistic. 
It generates responses based on patterns and likelihoods, which means results can vary from one query to the next. 
Even with multimodal content, AI converts text, images, and audio into numerical representations that capture meaning and relationships rather than exact matches.
For AI to cite your content, you need a strong data layer combined with context engineering – structuring and optimizing information so AI can interpret it as reliable and trustworthy for a given query.
As AI systems rely increasingly on large-scale inference rather than keyword-driven indexing, a new reality has emerged: the cost of comprehension. 
Each time an AI model interprets text, resolves ambiguity, or infers relationships between entities, it consumes GPU cycles, increasing already significant computing costs.
A comprehension budget is the finite allocation of compute that determines whether content is worth the effort for an AI system to understand.
4 foundational elements for AI discovery
For content to be cited by AI, it must first be discovered and understood. 
While many discovery requirements overlap with traditional search, key differences emerge in how AI systems process and evaluate content.

1. Technical foundation
Your site’s infrastructure must allow AI engines to crawl and access content efficiently. 
With limited compute and a finite comprehension budget, platform architecture matters. 
Enterprises should support progressive crawling of fresh content through IndexNow integration to optimize that budget.
Ideally, this capability is native to the platform and CMS.
2. Helpful content
Before creating content, you need an entity strategy that accurately and comprehensively represents your brand. 
Content should meet audience needs and answer their questions. 
Structuring content around customer intent, presenting it in clear “chunks,” and keeping it fresh are all important considerations.
Dig deeper: Chunk, cite, clarify, build: A content framework for AI search
3. Entity optimization
Schema markup, clean information architecture, consistent headings, and clear entity relationships help AI engines understand both individual pages and how multiple pieces of content relate to one another. 
Rather than forcing models to infer what a page is about, who it applies to, or how information connects, businesses make those relationships explicit.
4. Authority
AI engines, like traditional search engines, prioritize authoritative content from trusted sources. 
Establishing topical authority is essential. For location-based businesses, local relevance and authority are also critical to becoming a trusted source.
The myth: Schema doesn’t work
Many enterprises claim to use schema but see no measurable lift, leading to the belief that schema doesn’t work. 
The reality is that most failures stem from basic implementations or schema deployed with errors.
Tags such as Organization or Breadcrumb are foundational, but they provide limited insight into a business. 
Used in isolation, they create disconnected data points rather than a cohesive story AI can interpret.
The content knowledge graph: Telling AI your story
The more AI knows about your business, the better it can cite it. 
A content knowledge graph is a structured map of entities and their relationships, providing reliable information about your business to AI systems.
Deep nested schema plays a central role in building this graph.

A deep nested schema architecture expresses the full entity lineage of a business in a machine-readable form.
In resource description framework (RDF) terms, AI systems need to understand that:
An organization creates a brand.
The brand manufactures a product.
The product belongs to a category.
Each category serves a specific purpose or use case.
By fully nesting entities – Organization → Brand → Product → Offer → PriceSpecification → Review → Person – you publish a closed-loop content knowledge graph that models your business with precision.
Dig deeper: 8 steps to a successful entity-first strategy for SEO and content
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See terms.
The enterprise entity optimization playbook

In “How to deploy advanced schema at scale,” I outlined the full process for effective schema deployment – from developing an entity strategy through deployment, maintenance, and measurement.
Automating for operational excellence
At the enterprise level, facts change constantly, including product specifications, availability, categories, reviews, offers, and prices. 
If structured data, entity lineage, and topic clusters do not update dynamically to reflect these changes, AI systems begin to detect inconsistencies.
In an AI-driven ecosystem where accuracy, coherence, and consistency determine inclusion, even small discrepancies can erode trust.
Manual schema management is not sustainable.
The only scalable approach is automation – using a schema management solution aligned with your entity strategy and integrated into your discovery and marketing flywheel.
Measuring success: KPIs for the generative AI era
As keyword rankings lose relevance and traffic declines, you need new KPIs to evaluate performance in AI search.
Brand visibility: Is your brand appearing in AI search results?
Brand sentiment: When your brand is cited, is the sentiment positive, negative, or neutral?
LLM visibility: Beyond branded queries, how does your performance on non-branded terms compare with competitors?
Conversions: At the bottom of the funnel, are conversion metrics being tracked and optimized?
Dig deeper: 7 focus areas as AI transforms search and the customer journey in 2026
From reading to acting: Preparing for the agentic web
The web is shifting from a “read” model to an “act” model.
AI agents will increasingly execute tasks on behalf of users, such as booking appointments, reserving tables, or comparing specifications.
To be discovered by these agents, brands must make their capabilities machine-callable. Key steps to prepare include:
Create a schema layer: Define entity lineage and executable capabilities in a machine-readable format so agents can act on your behalf.
Use action vocabularies: Leverage Schema.org action vocabularies to provide semantic meaning and define agent capabilities, including:

ReserveAction.
BookAction.
CommunicateAction.
PotentialAction.
Establish guardrails: Declare engagement rules, required inputs, authentication, and success or failure semantics in a structured format that machines can interpret.
Brands that are callable are the ones that will be found. Acting early provides a compounding advantage by shaping the standards agents learn first.
The enterprise entity deployment checklist
Use this checklist to evaluate whether your entity strategy is operational, scalable, and aligned with AI discovery requirements.
Entity audit: Have you defined your core entities and validated the facts?
Deep nesting: Does your JSON-LD reflect your business ontology, or is it flat?
Authority linking: Are you using sameAs to connect entities to Wikidata and the Knowledge Graph?
Actionable schema: Have you implemented PotentialAction for the agentic web?
Automation: Do you have a system in place to prevent schema drift?
Single source of truth (SSOT): Is schema synchronized across your CMS, GBP, and internal systems?
Technical SEO: Are the technical foundations in place to support an effective entity strategy?
IndexNow: Are you enabling progressive and rapid indexing of fresh content?
Connected customer journeys and total cost of ownership

Your martech stack must align with the evolving customer discovery journey. 
This requires a shift from treating schema as a point solution for visibility to managing a holistic presence with total cost of ownership in mind.
Data is the foundation of any composable architecture. 
A centralized data repository connects technologies, enables seamless flow, breaks down departmental silos, and optimizes cost of ownership.
This reduces redundancy and improves the consistency and accuracy AI systems expect.
When schema is treated as a point solution, content changes can break not only schema deployment but the entire entity lineage. 
Fixing individual tags does not restore performance. Instead, multiple teams – SEO, content, IT, and analytics – are pulled into investigations, increasing cost and inefficiency.
The solution is to integrate schema markup directly into brand and entity strategy.
When structured content changes, it should be:
Revalidated against the organization’s entity lineage.
Dynamically redeployed.
Pushed for progressive indexing through IndexNow.
This enables faster recovery and lower compute overhead.
Integrating schema into your entity lineage and discovery flywheel helps optimize total cost of ownership while maximizing efficiency.
A strategic blueprint for AI readiness
Several core requirements define AI readiness.

Data: Centralized, unified, consistent, and reliable data aligned to customer intent is the foundation of any AI strategy.
Connected journeys and composable architecture: When data is unified and structured with schema, customer journeys can be connected across channels. A composable martech stack enables consistent, personalized experiences at every touchpoint.
Structured content: Define organizational entity lineage and create a semantic layer that makes content machine- and agent-ready.
Distribution: Break down silos and move from channel-specific tactics to an omnichannel strategy, supported by a centralized data source and progressive crawling of fresh content.
Together, these efforts make your omnichannel strategy more durable while reducing total cost of ownership across the technology stack.
Thanks to Bill Hunt and Tushar Prabhu for their contributions to this article.

What it takes to operationalize entities and schema across large organizations, without breaking governance or increasing technical debt.

The enterprise blueprint for winning visibility in AI search

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/When-Googles-AI-bidding-breaks-–-and-how-to-take-control.jpg" class="attachment-large size-large wp-post-image" alt="When Google’s AI bidding breaks – and how to take control" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/When-Googles-AI-bidding-breaks-–-and-how-to-take-control.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/When-Googles-AI-bidding-breaks-–-and-how-to-take-control-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/When-Googles-AI-bidding-breaks-–-and-how-to-take-control-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google’s AI bidding can scale spend while eroding efficiency. Learn where to intervene to protect PPC performance.

Google’s pitch for AI-powered bidding is seductive.
Feed the algorithm your conversion data, set a target, and let it optimize your campaigns while you focus on strategy. 
Machine learning will handle the rest.
What Google doesn’t emphasize is that its algorithms optimize for Google’s goals, not necessarily yours. 
In 2026, as Smart Bidding becomes more opaque and Performance Max absorbs more campaign types, knowing when to guide the algorithm – and when to override it – has become a defining skill that separates average PPC managers from exceptional ones.
AI bidding can deliver spectacular results, but it can also quietly destroy profitable campaigns by chasing volume at the expense of efficiency. 
The difference is not the technology. It is knowing when the algorithm needs direction, tighter constraints, or a full override.
This article explains:
How AI bidding actually works.
The warning signs that it is failing.
The strategic intervention points where human judgment still outperforms machine learning.
How AI bidding actually works – and what Google doesn’t tell you
Smart Bidding comes in several strategies, including:
Target CPA.
Target ROAS.
Maximize Conversions.
Maximize Conversion Value.
Each uses machine learning to predict the likelihood of a conversion and adjust bids in real time based on contextual signals.
The algorithm analyzes hundreds of signals at auction time, such as:
Device type.
Location.
Time of day.
Browser.
Operating system.
Audience membership.
Remarketing lists.
Past site interactions.
Search query.
It compares these signals with historical conversion data to calculate an optimal bid for each auction.
During the “learning period,” typically seven to 14 days, the algorithm explores the bid landscape, testing bid levels to understand the conversion probability curve. 
Google recommends patience during this phase, and in general, that advice holds. The algorithm needs data.
The first problem is that learning periods are not always temporary. 
Some campaigns get stuck in perpetual learning and never achieve stable performance.
Dig deeper: When to trust Google Ads AI and when you shouldn’t
Google’s optimization goals vs. your business goals
The algorithm optimizes for metrics that drive Google’s revenue, not necessarily your profitability.
When a Target ROAS of 400% is set, the algorithm interprets that as “maximize total conversion value while maintaining a 400% average ROAS.” 
Notice the word “maximize.”
The system is designed to spend the full budget and, ideally, encourage increases over time. 
More spend means more revenue for Google.
Business goals are often different. 
You may want a 400% ROAS with a specific volume threshold. 
You may need to maintain margin requirements that vary by product line. 
Or you may prefer a 500% ROAS at lower volume because fulfillment capacity is constrained.
The algorithm does not understand this context. 
It sees a ROAS target and optimizes accordingly, often pushing volume at the expense of efficiency once the target is reached.
This pattern is common. An algorithm increases spend by 40% to deliver 15% more conversions at the target ROAS. Technically, it succeeds. 
In practice, cash flow cannot support the higher ad spend, even at the same efficiency. 
The algorithm does not account for working capital constraints.
Key signals the algorithm can’t understand
AI bidding works well, but it has limits. 
Without intervention, several factors can’t be fully accounted for.
Seasonal patterns not yet reflected in historical data
Launch a campaign in October, and the algorithm has no visibility into a December peak season.
It optimizes based on October performance until December data proves otherwise, often missing early seasonal demand.
Product margin differences
A $100 sale of Product A with a 60% margin and a $100 sale of Product B with a 15% margin look identical to the algorithm. 
Both register as $100 conversions. The business impact, however, is very different. 
This is where profit tracking, profit bidding, and margin-based segmentation matter.
Customer lifetime value variations
Unless lifetime value modeling is explicitly built into conversion values, the algorithm treats a first-time customer the same as a repeat buyer. 
In most accounts, that modeling does not exist.
Market and competitive changes
When a competitor launches an aggressive promotion or a new entrant appears, the algorithm continues bidding based on historical conditions until performance degrades enough to force adjustment. 
Market share is often lost during that lag.
Inventory and supply chain constraints
If a best-selling product is out of stock for two weeks, the algorithm may continue bidding aggressively on related searches because of past performance. 
The result is paid traffic that cannot convert.
This is not a criticism of the technology. It’s a reminder that the algorithm optimizes only within the data and parameters provided. 
When those inputs fail to reflect business reality, optimization may be mathematically correct but strategically wrong.
Warning signs your AI bidding strategy is failing
The perpetual learning phase
Learning periods are normal. Extended learning periods are red flags.
If your campaign shows a “Learning” status for more than two weeks, something is broken. 
Common causes include:
Insufficient conversion volume – the algorithm typically needs at least 30 to 50 conversions per month.
Frequent changes that reset the learning period.
Unstable performance with wide day-to-day fluctuations.
When to intervene
If learning extends beyond three weeks, either:
Increase the budget to accelerate data collection.
Loosen the target to allow more conversions.
Or switch to a less aggressive bid strategy like Enhanced CPC. 
Sometimes the algorithm is simply telling you it does not have enough data to succeed.
Budget pacing issues
Healthy AI bidding campaigns show relatively smooth budget pacing. 
Daily spend fluctuates, but it stays within reasonable bounds. 
Problematic patterns include:
Front-loaded spending – 80% of the daily budget gone by 10 a.m.
Consistent underspending, such as averaging 60% of budget per day.
Volatile day-to-day swings, like spending $800 one day, $200 the next, then $650 after that.
Budget pacing is a proxy for algorithm confidence. 
Smooth pacing suggests the system understands your conversion landscape. 
Erratic pacing usually means it is guessing.
The efficiency cliff
This is the most dangerous pattern. Performance starts strong, then gradually or suddenly deteriorates.
This shows up often in Target ROAS campaigns. 
Month 1: 450% ROAS, excellent. 
Month 2: 420%, still good. 
Month 3: 380%, concerning. 
Month 4: 310%, alarm bells.
What happened? 
The algorithm exhausted the most efficient audience segments and search terms. 
To keep growing volume – because it is designed to maximize – it expanded into less qualified traffic. 
Broad match reached further. Audiences widened. Bid efficiency declined.
Traffic quality deterioration
Sometimes the numbers look fine, but qualitative signals tell a different story. 
Engagement declines – bounce rate rises, time on site falls, pages per session drop. 
Geographic shifts appear as the algorithm drives traffic from lower-value regions. 
Device mix changes, often skewing toward mobile because CPCs are cheaper, even when desktop converts better. 
Time-of-day misalignment can also emerge, with traffic arriving when sales teams are unavailable.
These quality signals do not directly influence optimization because they are not part of the conversion data. 
To address them, the algorithm needs constraints: bid adjustments, audience exclusions, or ad scheduling.
The search terms report reveals the truth
The search terms report is the truth serum for AI bidding performance. 
Export it regularly and look for:
Low-intent queries receiving aggressive bids.
Informational searches mixed with transactional ones.
Irrelevant expansions where the algorithm chased conversions into entirely different intent.
A high-end furniture retailer should not spend $8 per click on “free furniture donation pickup.” 
A B2B software company targeting “project management software” should not appear for “project manager jobs.” 
These situations occur when the algorithm operates without constraints. 
Keyword matching is also looser than it was in the past, which means even small gaps can allow the system to bid on queries you never intended to target.
Dig deeper: How to tell if Google Ads automation helps or hurts your campaigns
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Strategic intervention points: When and how to take control
Segmentation for better control
One-size-fits-all AI bidding breaks down when a business has diverse economics. 
The solution is segmentation, so each algorithm optimizes toward a clear, coherent goal.
Separate high-margin products – 40%+ margin – into one campaign with more aggressive ROAS targets, and low-margin products – 10% to 15% margin – into another with more conservative targets. 
If the Northeast region delivers 450% ROAS while the Southeast delivers 250%, separate them. 
Brand campaigns operate under fundamentally different economics than nonbrand campaigns, so optimizing both with the same algorithm and target rarely makes sense.
Segmentation gives each algorithm a clear mission. Better focus leads to better results.
Bid strategy layering
Pure automation is not always the answer. 
In many cases, hybrid approaches deliver better results.
Run Target ROAS at 400% under normal conditions, then manually lower it to 300% during peak season to capture more volume when demand is high. 
Use Maximize Conversion Value with a bid cap if unit economics cannot support bids above $12. 
Group related campaigns under a portfolio Target ROAS strategy so the algorithm can optimize across them. 
For campaigns with limited conversion data or volatile performance, Enhanced CPC offers algorithmic assistance without full black box automation.
The hybrid approach
The most effective setups combine AI bidding with manual control campaigns.
Allocate 70% of the budget to AI bidding campaigns, such as Target ROAS or Maximize Conversion Value, and 30% to Enhanced CPC or manual CPC campaigns. 
Manual campaigns act as a baseline. If AI underperforms manual by more than 20% after 90 days, the algorithm is not working for the business.
Use tightly controlled manual campaigns to capture the most valuable traffic – brand terms and high-intent keywords – while AI campaigns handle broader prospecting and discovery. 
This approach protects the core business while still exploring growth opportunities.
COGS and cart data reporting (plus profit optimization beta)
Google now allows advertisers to report cost of goods sold, or COGS, and detailed cart data alongside conversions. 
This is not about bidding yet, but seeing true profitability inside Google Ads reporting.
Most accounts optimize for revenue, or ROAS, not profit. 
A $100 sale with $80 in COGS is very different from a $100 sale with $20 in COGS, but standard reporting treats them the same. 
With COGS reporting in place, actual profit becomes visible, dramatically improving the quality of performance analysis.
To set it up, conversions must include cart-level parameters added to existing tracking. 
These typically include item ID, item name, quantity, price, and, critically, the cost_of_goods_sold parameter for each product.
Google is testing a bid strategy that optimizes for profit instead of revenue. 
Access is limited, but advertisers with clean COGS data flowing into Google Ads can request entry. 
In this model, bids are optimized around actual profit margins rather than raw conversion value. 
This is especially powerful for retailers with wide margin variation across products.
For advertisers without access to the beta, a custom margin-tracking pixel can be implemented manually. It is more technical to set up, but it achieves the same outcome.
Dig deeper: Margin-based tracking: 3 advanced strategies for Google Shopping profitability
When AI bidding actually works
AI bidding works best when the fundamentals are in place: 
Sufficient conversion volume.
A stable business model with consistent margins and predictable seasonality.
Clean conversion tracking.
Enough historical data to support learning.
In these conditions, AI bidding often outperforms manual management by processing more signals and making more granular optimizations than humans can execute at scale.
This tends to be true in:
Mature ecommerce accounts.
Lead generation programs with consistent lead values.
SaaS models with predictable trial-to-paid conversion paths.
When those conditions hold, the role shifts.
Bid management gives way to strategic oversight – monitoring trends, identifying expansion opportunities, and testing new structures.
The algorithm then handles tactical optimization.
Preparing for AI-first advertising
Google is steadily reducing advertiser control under the banner of automation. 
Performance Max has absorbed Smart Shopping and Local campaigns. 
Asset groups replace ad groups. 
Broad match becomes mandatory in more contexts. 
Negative keywords increasingly function as suggestions the system may or may not honor.
For advertisers with complex business models or specific strategic goals, this loss of granularity creates tension. 
You are often asked to trust the algorithm even when business context suggests a different decision.
That shift changes the role. You are no longer a bid manager. 
You are an AI strategy director who:
Defines objectives.
Provides business context.
Sets constraints.
Monitors outcomes.
Intervenes when the system drifts away from strategic intent.
No matter how advanced AI bidding becomes, certain decisions still require human judgment. 
Strategic positioning – which markets to enter and which product lines to emphasize – cannot be automated. 
Neither can creative testing, competitive intelligence, or operational realities like inventory constraints, margin requirements, and broader business priorities.
This is not a story of humans versus AI. It is humans directing AI.
Dig deeper: 4 times PPC automation still needs a human touch
Master the algorithm, don’t serve it
AI-powered bidding is the most powerful optimization tool paid media has ever had. 
When conditions are right – sufficient data, a stable business model, and clean tracking – it delivers results manual management cannot match.
But it is not magic.
The algorithm optimizes for mathematical targets within the data you provide. 
If business context is missing from that data, optimization can be technically correct and strategically wrong. 
If markets change faster than the system adapts, performance erodes. 
If your goals diverge from Google’s revenue incentives, the algorithm will pull in directions that do not serve the business.
The job in 2026 is not to blindly trust automation or stubbornly resist it. 
It is to master the algorithm – knowing when to let it run, when to guide it with constraints, and when to override it entirely.
The strongest PPC leaders are AI directors. They do not manage bids. They manage the system that manages bids.

Google’s AI bidding can scale spend while eroding efficiency. Learn where to intervene to protect PPC performance.

When Google’s AI bidding breaks – and how to take control

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/A-3-tier-framework-for-Shopify-integrations-that-drive-conversions.jpg" class="attachment-large size-large wp-post-image" alt="A 3-tier framework for Shopify integrations that drive conversions" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/A-3-tier-framework-for-Shopify-integrations-that-drive-conversions.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/A-3-tier-framework-for-Shopify-integrations-that-drive-conversions-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/A-3-tier-framework-for-Shopify-integrations-that-drive-conversions-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Not every Shopify integration delivers value. Learn how to sequence checkout, re-engagement, and optimization tools for revenue impact.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/A-3-tier-framework-for-Shopify-integrations-that-drive-conversions.jpg" class="attachment-large size-large wp-post-image" alt="A 3-tier framework for Shopify integrations that drive conversions" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/A-3-tier-framework-for-Shopify-integrations-that-drive-conversions.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/A-3-tier-framework-for-Shopify-integrations-that-drive-conversions-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/A-3-tier-framework-for-Shopify-integrations-that-drive-conversions-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Shopify powers more than <a href="https://trends.builtwith.com/shop/Shopify" target="_blank" rel="noopener">6 million live ecommerce websites</a>, supported by a robust app ecosystem that can extend nearly every part of the customer journey. </p>



<p>Anyone can develop an app to perform virtually any function.&nbsp;</p>



<p>But with so many integrations to choose from, ecommerce teams often waste time testing add-ons that promise revenue gains but fail to deliver.</p>



<p>Having worked across a wide range of Shopify implementations, I’ve seen which tools consistently improve checkout completion, recover abandoned carts, and increase revenue.&nbsp;</p>



<p>Based on that experience, I’ve organized the most effective integrations into three tiers by priority – so you can implement the essentials first, then move on to more advanced optimization.</p>



<h2 class="wp-block-heading" id="h-tier-1-mobile-first-frictionless-buying">Tier 1: Mobile-first, frictionless buying</h2>



<p>With <a href="https://news.adobe.com/news/2025/1/adi-pr-full-season-recap" target="_blank" rel="noopener">54.5% of holiday purchases happening on mobile</a>, the ecommerce experience must be seamless and flexible.&nbsp;</p>



<p>As a result, every Shopify site should have two components integrated into its storefront:&nbsp;</p>



<ul class="wp-block-list">
<li>A digital wallet compatibility.</li>



<li>A buy now, pay later (BNPL) option.&nbsp;</li>
</ul>



<p>Without these in place, Shopify users introduce unnecessary friction into the purchase journey and risk sending customers to competitors.&nbsp;</p>



<p>The good news is that both components integrate natively with Shopify, requiring no custom development.</p>



<h3 class="wp-block-heading" id="h-why-you-need-digital-wallets">Why you need digital wallets</h3>



<p>Digital wallets, such as Apple Pay, Google Pay, and PayPal, autofill delivery and payment information with a single click, eliminating the friction of typing on a small screen.&nbsp;</p>



<p>This ease of use can shorten the purchase journey to just a few clicks between a social ad and checkout.</p>



<p>Adoption is accelerating. Up to <a href="https://capitaloneshopping.com/research/digital-wallet-statistics/" target="_blank" rel="noopener">64% of Americans</a> use digital wallets at least as often as traditional payment methods, and 54% use them more often.</p>



<h3 class="wp-block-heading" id="h-eliminate-price-objections-with-bnpl">Eliminate price objections with BNPL</h3>



<p>Beyond payment convenience, customers also expect flexibility.&nbsp;</p>



<p>BNPL providers, including Klarna and Afterpay, allow buyers to spread payments over time, reducing price objections at checkout.&nbsp;</p>



<p>These options <a href="https://news.adobe.com/news/2025/1/adi-pr-full-season-recap" target="_blank" rel="noopener">contributed $18.2 billion</a> to online spending during last year’s holiday season – an all-time high, according to Adobe.</p>



<p>Together, digital wallets and BNPL form the foundation of a modern, mobile-first checkout experience.&nbsp;</p>



<p>With these essentials in place, Shopify users can focus on tools that re-engage customers and bring them back to complete their purchases.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/shopify-seo-ai-readiness-playbook-460771">The ultimate Shopify SEO and AI readiness playbook</a></em></strong></p>



<h2 class="wp-block-heading" id="h-tier-2-the-re-engagement-power-players">Tier 2: The re-engagement power players</h2>



<p>The second tier focuses on re-engagement – tools designed to bring back customers who have already shown intent.&nbsp;</p>



<p>These integrations improve abandoned-cart recovery, increase repeat purchases, and build trust through social proof.</p>



<h3 class="wp-block-heading" id="h-re-engage-customers-with-email-and-sms">Re-engage customers with email and SMS</h3>



<p>Email remains one of the most effective channels for re-engaging customers at every stage of the journey.&nbsp;</p>



<p>Klaviyo and Attentive are strong options for Shopify users because both offer deep platform integration with minimal setup.</p>



<p>Both platforms also support SMS, allowing Shopify sellers to send automated text messages directly to customers’ mobile devices.&nbsp;</p>



<p>SMS consistently delivers higher open, click-through, and conversion rates than email, making it especially effective for re-engagement use cases such as abandoned-cart recovery.</p>



<p>Together, these tools enable targeted campaigns and sophisticated automated flows that drive incremental revenue.&nbsp;</p>



<p>However, CAN-SPAM and TCPA regulations require explicit opt-in for email and SMS marketing, respectively.&nbsp;</p>



<p>As a result, sellers can only use these channels to contact customers who have agreed to receive marketing messages.</p>



<h3 class="wp-block-heading" id="h-use-human-centered-sms-outreach">Use human-centered SMS outreach</h3>



<p>While Attentive and Klaviyo effectively reach customers who have opted in to marketing, CartConvert helps sellers engage the 50% to 60% of shoppers who have not. </p>



<p>The platform uses real people to contact cart abandoners via SMS. Because the outreach is not automated, TCPA restrictions do not apply.</p>



<p>CartConvert agents have live conversations with potential customers about their shopping experience.&nbsp;</p>



<p>They are familiar with the products and can guide buyers back toward a purchase by suggesting alternatives or offering discounts.&nbsp;</p>



<p>Running CartConvert alongside Klaviyo or Attentive ensures both subscribers and non-subscribers are included in re-engagement efforts.</p>



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<h3 class="wp-block-heading" id="h-demonstrate-social-proof-through-reviews">Demonstrate social proof through reviews</h3>



<p>Human-centered marketing also plays a role in building buyer confidence.&nbsp;</p>



<p>Today’s online shoppers rely heavily on reviews when making purchasing decisions.&nbsp;</p>



<p>When reviews are integrated directly into the shopping experience, they help establish trust and legitimacy, which in turn drive higher conversion rates.&nbsp;</p>



<p>A product with five reviews is <a href="https://spiegel.medill.northwestern.edu/wp-content/uploads/sites/2/2021/04/Spiegel_Online-Review_eBook_Jun2017_FINAL.pdf" target="_blank" rel="noopener">270% more likely</a> to be purchased than one with no reviews, research from the Spiegel Research Center at Northwestern University found.</p>



<p>Shopify users can choose from several review aggregators that pull Google reviews into product pages.&nbsp;</p>



<p>Sellers should prioritize aggregators that also sync with Google Merchant Center, which powers Google Ads.&nbsp;</p>



<p>Tools such as Okendo, Yotpo, and Shopper Approved integrate smoothly with both Shopify and Google’s ecosystem.</p>



<p>When reviews sync with Merchant Center, they can appear in Google Shopping ads, improving ad performance.&nbsp;</p>



<p>While these tools add cost, they are also proven to generate incremental revenue that offsets the investment.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/ecommerce-product-pages-ai-first-world-458629">How to make ecommerce product pages work in an AI-first world</a></em></strong></p>



<h2 class="wp-block-heading" id="h-tier-3-advanced-optimization">Tier 3: Advanced optimization</h2>



<p>The final tier includes more advanced integrations designed to help sellers optimize their sales funnel and performance at scale.</p>



<h3 class="wp-block-heading" id="h-attribution-and-analytics-triple-whale">Attribution and analytics: Triple Whale</h3>



<p>GA4’s changes to reporting, session logic, and interface have made attribution more difficult for many ecommerce teams.&nbsp;</p>



<p>As a result, sellers are increasingly seeking clearer, independent performance insights.</p>



<p>Since 2023, Triple Whale has emerged as a leading alternative to Google Analytics, offering third-party attribution tools that integrate seamlessly with Shopify.&nbsp;</p>



<p>The platform supports multiple attribution models – including first-click, last-click, and linear – along with cross-platform cost integration.</p>



<p>It also provides real-time data, which Google Analytics does not.&nbsp;</p>



<p>This capability becomes especially valuable during high-pressure sales periods, such as Black Friday, when delayed reporting can lead to missed opportunities.</p>



<p>Although Triple Whale can cost up to $10,000 annually for mid-size brands, the improved data quality often justifies the investment for teams scaling paid acquisition.</p>



<h3 class="wp-block-heading" id="h-landing-page-customization-replo">Landing page customization: Replo</h3>



<p>For sellers focused on improving conversion rates, landing page testing is essential.&nbsp;</p>



<p>While Shopify is relatively easy to use, making changes to a live storefront for A/B testing carries the risk of breaking the site.</p>



<p>Replo allows Shopify users to build custom landing pages that can be tested at scale without coding.&nbsp;</p>



<p>These pages typically provide a better user experience than default Shopify themes.&nbsp;</p>



<p>It can also use site data to personalize landing pages based on a shopper’s browsing history.&nbsp;</p>



<p>As a result, Replo-built pages often convert at higher rates than static site pages.</p>



<h3 class="wp-block-heading" id="h-tiktok-ads-integration">TikTok ads integration</h3>



<p><a href="https://searchengineland.com/tiktok-advertising-450817">TikTok</a> continues to grow as a paid media channel, but it has traditionally presented a higher barrier to entry for advertisers.&nbsp;</p>



<p>Previously, sellers needed an active TikTok account and could only purchase ads within the app, adding complexity and cost.</p>



<p>TikTok’s Shopify integration allows sellers to create ads that link directly to their websites, rather than keeping users inside the app.&nbsp;</p>



<p>This change has lowered the barrier to entry and expanded access to the platform.&nbsp;</p>



<p>Early testing shows promise for use cases such as cart abandonment, making the integration worth exploring despite its relative immaturity.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/guide/ecommerce-seo">Ecommerce SEO: Start where shoppers search</a></em></strong></p>



<h2 class="wp-block-heading" id="h-prioritizing-shopify-integrations-for-maximum-impact">Prioritizing Shopify integrations for maximum impact</h2>



<p>Shopify is a powerful platform for ecommerce, but maximizing results requires going beyond its default features.&nbsp;</p>



<ul class="wp-block-list">
<li>Start with essentials such as digital wallets and BNPL to reduce checkout friction.&nbsp;</li>



<li>Then layer in email, SMS, and review integrations to re-engage interested shoppers.&nbsp;</li>



<li>Finally, add analytics, attribution, and landing-page testing to optimize performance at scale.</li>
</ul>



<p>Sellers do not need to implement every solution at once.&nbsp;</p>



<p>Instead, conduct a quick audit of the existing stack against this framework, identify gaps, and prioritize the tools that improve conversion and re-engagement.&nbsp;</p>



<p>Shopify’s flexibility is its greatest strength, and its app ecosystem enables sellers to turn more visitors into buyers.</p>

Shopify powers more than 6 million live ecommerce websites, supported by a robust app ecosystem that can extend nearly every part of the customer journey. 
Anyone can develop an app to perform virtually any function. 
But with so many integrations to choose from, ecommerce teams often waste time testing add-ons that promise revenue gains but fail to deliver.
Having worked across a wide range of Shopify implementations, I’ve seen which tools consistently improve checkout completion, recover abandoned carts, and increase revenue. 
Based on that experience, I’ve organized the most effective integrations into three tiers by priority – so you can implement the essentials first, then move on to more advanced optimization.
Tier 1: Mobile-first, frictionless buying
With 54.5% of holiday purchases happening on mobile, the ecommerce experience must be seamless and flexible. 
As a result, every Shopify site should have two components integrated into its storefront: 
A digital wallet compatibility.
A buy now, pay later (BNPL) option. 
Without these in place, Shopify users introduce unnecessary friction into the purchase journey and risk sending customers to competitors. 
The good news is that both components integrate natively with Shopify, requiring no custom development.
Why you need digital wallets
Digital wallets, such as Apple Pay, Google Pay, and PayPal, autofill delivery and payment information with a single click, eliminating the friction of typing on a small screen. 
This ease of use can shorten the purchase journey to just a few clicks between a social ad and checkout.
Adoption is accelerating. Up to 64% of Americans use digital wallets at least as often as traditional payment methods, and 54% use them more often.
Eliminate price objections with BNPL
Beyond payment convenience, customers also expect flexibility. 
BNPL providers, including Klarna and Afterpay, allow buyers to spread payments over time, reducing price objections at checkout. 
These options contributed $18.2 billion to online spending during last year’s holiday season – an all-time high, according to Adobe.
Together, digital wallets and BNPL form the foundation of a modern, mobile-first checkout experience. 
With these essentials in place, Shopify users can focus on tools that re-engage customers and bring them back to complete their purchases.
Dig deeper: The ultimate Shopify SEO and AI readiness playbook
Tier 2: The re-engagement power players
The second tier focuses on re-engagement – tools designed to bring back customers who have already shown intent. 
These integrations improve abandoned-cart recovery, increase repeat purchases, and build trust through social proof.
Re-engage customers with email and SMS
Email remains one of the most effective channels for re-engaging customers at every stage of the journey. 
Klaviyo and Attentive are strong options for Shopify users because both offer deep platform integration with minimal setup.
Both platforms also support SMS, allowing Shopify sellers to send automated text messages directly to customers’ mobile devices. 
SMS consistently delivers higher open, click-through, and conversion rates than email, making it especially effective for re-engagement use cases such as abandoned-cart recovery.
Together, these tools enable targeted campaigns and sophisticated automated flows that drive incremental revenue. 
However, CAN-SPAM and TCPA regulations require explicit opt-in for email and SMS marketing, respectively. 
As a result, sellers can only use these channels to contact customers who have agreed to receive marketing messages.
Use human-centered SMS outreach
While Attentive and Klaviyo effectively reach customers who have opted in to marketing, CartConvert helps sellers engage the 50% to 60% of shoppers who have not. 
The platform uses real people to contact cart abandoners via SMS. Because the outreach is not automated, TCPA restrictions do not apply.
CartConvert agents have live conversations with potential customers about their shopping experience. 
They are familiar with the products and can guide buyers back toward a purchase by suggesting alternatives or offering discounts. 
Running CartConvert alongside Klaviyo or Attentive ensures both subscribers and non-subscribers are included in re-engagement efforts.
Get the newsletter search marketers rely on.
  
				
								
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See terms.
Demonstrate social proof through reviews
Human-centered marketing also plays a role in building buyer confidence. 
Today’s online shoppers rely heavily on reviews when making purchasing decisions. 
When reviews are integrated directly into the shopping experience, they help establish trust and legitimacy, which in turn drive higher conversion rates. 
A product with five reviews is 270% more likely to be purchased than one with no reviews, research from the Spiegel Research Center at Northwestern University found.
Shopify users can choose from several review aggregators that pull Google reviews into product pages. 
Sellers should prioritize aggregators that also sync with Google Merchant Center, which powers Google Ads. 
Tools such as Okendo, Yotpo, and Shopper Approved integrate smoothly with both Shopify and Google’s ecosystem.
When reviews sync with Merchant Center, they can appear in Google Shopping ads, improving ad performance. 
While these tools add cost, they are also proven to generate incremental revenue that offsets the investment.
Dig deeper: How to make ecommerce product pages work in an AI-first world
Tier 3: Advanced optimization
The final tier includes more advanced integrations designed to help sellers optimize their sales funnel and performance at scale.
Attribution and analytics: Triple Whale
GA4’s changes to reporting, session logic, and interface have made attribution more difficult for many ecommerce teams. 
As a result, sellers are increasingly seeking clearer, independent performance insights.
Since 2023, Triple Whale has emerged as a leading alternative to Google Analytics, offering third-party attribution tools that integrate seamlessly with Shopify. 
The platform supports multiple attribution models – including first-click, last-click, and linear – along with cross-platform cost integration.
It also provides real-time data, which Google Analytics does not. 
This capability becomes especially valuable during high-pressure sales periods, such as Black Friday, when delayed reporting can lead to missed opportunities.
Although Triple Whale can cost up to $10,000 annually for mid-size brands, the improved data quality often justifies the investment for teams scaling paid acquisition.
Landing page customization: Replo
For sellers focused on improving conversion rates, landing page testing is essential. 
While Shopify is relatively easy to use, making changes to a live storefront for A/B testing carries the risk of breaking the site.
Replo allows Shopify users to build custom landing pages that can be tested at scale without coding. 
These pages typically provide a better user experience than default Shopify themes. 
It can also use site data to personalize landing pages based on a shopper’s browsing history. 
As a result, Replo-built pages often convert at higher rates than static site pages.
TikTok ads integration
TikTok continues to grow as a paid media channel, but it has traditionally presented a higher barrier to entry for advertisers. 
Previously, sellers needed an active TikTok account and could only purchase ads within the app, adding complexity and cost.
TikTok’s Shopify integration allows sellers to create ads that link directly to their websites, rather than keeping users inside the app. 
This change has lowered the barrier to entry and expanded access to the platform. 
Early testing shows promise for use cases such as cart abandonment, making the integration worth exploring despite its relative immaturity.
Dig deeper: Ecommerce SEO: Start where shoppers search
Prioritizing Shopify integrations for maximum impact
Shopify is a powerful platform for ecommerce, but maximizing results requires going beyond its default features. 
Start with essentials such as digital wallets and BNPL to reduce checkout friction. 
Then layer in email, SMS, and review integrations to re-engage interested shoppers. 
Finally, add analytics, attribution, and landing-page testing to optimize performance at scale.
Sellers do not need to implement every solution at once. 
Instead, conduct a quick audit of the existing stack against this framework, identify gaps, and prioritize the tools that improve conversion and re-engagement. 
Shopify’s flexibility is its greatest strength, and its app ecosystem enables sellers to turn more visitors into buyers.

Not every Shopify integration delivers value. Learn how to sequence checkout, re-engagement, and optimization tools for revenue impact.

A 3-tier framework for Shopify integrations that drive conversions

<div><img width="1920" height="1079" src="https://searchengineland.com/wp-content/seloads/2025/12/google-nick-fox.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/google-nick-fox.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/google-nick-fox-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/google-nick-fox-1536x863.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Build great sites, great content, for your users, according to Nick Fox, SVP of Knowledge and Information at Google.

<div><img width="1920" height="1079" src="https://searchengineland.com/wp-content/seloads/2025/12/google-nick-fox.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/google-nick-fox.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/google-nick-fox-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/google-nick-fox-1536x863.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Optimizing for AI search is &#8220;the same&#8221; as optimizing for traditional search, Google SVP of Knowledge and Information Nick Fox said in a recent podcast. His advice was simple: build great sites with great content for your users.</p>



<p><strong>More details. </strong>Fox made the point on the AI Inside podcast, during an interview with Jason Howell and Jeff Jarvis. Here is the transcript from the <a href="https://youtu.be/puEyEWlp13M?si=Z5piXvmIwKyxpOUL&amp;t=1326" target="_blank" rel="noopener">22 minute mark</a>:</p>



<p>Jarvis: &#8220;Is there guidance for enlightened publishers who want to be part of AI about how they should view, should they view their content in any way differently now?&#8221;</p>



<p>Fox: &#8220;The short answer is no. The short answer is what you would have built and the way to optimize to do well in Google&#8217;s AI experiences is very similar, I would say the same, as how to perform well in traditional search. And it really does come down to build a great site, build great content. The way we put it is: build for users. Build what you would want to read, what you would want to access.&#8221;</p>



<ul class="wp-block-list">
<li>This jives with what Danny Sullivan from Google said, that <a href="https://searchengineland.com/google-danny-sullivan-good-seo-good-geo-461464">good GEO is good SEO</a>.</li>



<li>This echoes Google’s Gary Illyes advice from July – that&nbsp;<a href="https://searchengineland.com/google-says-normal-seo-works-for-ranking-in-ai-overviews-and-llms-txt-wont-be-used-459422">all you need to do is normal SEO</a>.</li>
</ul>



<p><strong>Why we care. </strong>Many of you have been practicing SEO for many years, and now with this AI revolution in Search, you should know you are very well equipped to perform well in AI Search with many, if not all, of the skills you learned doing SEO. So have at it.</p>



<p><strong>The video.</strong> <a href="https://www.youtube.com/watch?v=puEyEWlp13M" target="_blank" rel="noopener">Is AI Search Hurting The Open Web? With Google&#8217;s Nick Fox // AI Inside #104</a></p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe title="Is AI Search Hurting The Open Web? With Google&#039;s Nick Fox // AI Inside #104" width="500" height="281" src="https://www.youtube.com/embed/puEyEWlp13M?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p></p>


Optimizing for AI search is “the same” as optimizing for traditional search, Google SVP of Knowledge and Information Nick Fox said in a recent podcast. His advice was simple: build great sites with great content for your users.
More details. Fox made the point on the AI Inside podcast, during an interview with Jason Howell and Jeff Jarvis. Here is the transcript from the 22 minute mark:
Jarvis: “Is there guidance for enlightened publishers who want to be part of AI about how they should view, should they view their content in any way differently now?”
Fox: “The short answer is no. The short answer is what you would have built and the way to optimize to do well in Google’s AI experiences is very similar, I would say the same, as how to perform well in traditional search. And it really does come down to build a great site, build great content. The way we put it is: build for users. Build what you would want to read, what you would want to access.”
This jives with what Danny Sullivan from Google said, that good GEO is good SEO.
This echoes Google’s Gary Illyes advice from July – that all you need to do is normal SEO.
Why we care. Many of you have been practicing SEO for many years, and now with this AI revolution in Search, you should know you are very well equipped to perform well in AI Search with many, if not all, of the skills you learned doing SEO. So have at it.
The video. Is AI Search Hurting The Open Web? With Google’s Nick Fox // AI Inside #104

Build great sites, great content, for your users, according to Nick Fox, SVP of Knowledge and Information at Google.

Google says doing optimization for AI search is ‘the same’ as doing SEO for traditional search

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/smxa26-generic-og.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/smxa26-generic-og.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/smxa26-generic-og-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/smxa26-generic-og-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Tell us what you want to learn about and who you want to hear from at SMX Advanced taking place June 3-5 at the Westin Boston Seaport.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/smxa26-generic-og.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/smxa26-generic-og.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/smxa26-generic-og-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/smxa26-generic-og-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>We celebrated a major milestone in June: the return of <a href="https://searchengineland.com/smx/advanced/">SMX Advanced</a> as an in-person event. It was our first since 2019. </p>



<p>More than a conference, SMX Advanced 2025 was a reunion. Search marketers from around the world came together to connect, exchange ideas, and learn the most current and advanced insights in search.</p>



<p>But search never stands still. With rapid shifts in AI SEO, constant algorithm changes, and the challenge of balancing generative AI with a human touch, the need for truly advanced, actionable education has never been greater.</p>



<h2 class="wp-block-heading" id="h-help-shape-smx-advanced-2026">Help shape SMX Advanced 2026</h2>



<p>We’re committed to making the SMX Advanced 2026 program our most relevant, advanced, and exciting deep-dive experience yet. And we can’t do it without you – the expert community that makes this event legendary.</p>



<p>We’re inviting you to directly shape the curriculum for 2026.</p>



<p>Help us build a program that tackles the biggest challenges and opportunities on your radar by completing our short survey. Tell us:</p>



<ul class="wp-block-list">
<li>What advanced topics are most critical to your professional growth right now.</li>



<li>Which recent search changes or complexities are keeping you up at night.</li>



<li>Which search industry experts and innovators you need to hear from.</li>



<li>Which session formats – from deep-dive clinics to lightning talks and interactive panels – will help you learn more and retain what you learn.</li>
</ul>



<p><strong>Fill out the survey </strong><a href="https://forms.gle/UaSMAtbaeUfQT4ES9" target="_blank" rel="noopener"><strong>here</strong></a><strong>.</strong></p>



<h2 class="wp-block-heading" id="h-be-entered-to-win-an-all-access-pass">Be entered to win an All Access pass</h2>



<p>To thank you for your time and insights, everyone who completes the survey will have the opportunity to enter an exclusive drawing.</p>



<p>One lucky participant will win a coveted All Access pass to SMX Advanced 2026, taking place June 3-5 at the Westin Boston Seaport.</p>



<h2 class="wp-block-heading" id="h-submit-a-session-pitch">Submit a session pitch</h2>



<p>Beyond shaping the agenda, we also invite you to submit a session pitch. If you have a breakthrough strategy, an innovative case study, or next-level insights, this is your chance to help lead the industry conversation.</p>



<p>Read our <a href="https://searchengineland.com/smx/submit-speaking-pitch">guide to speaking </a><a href="https://searchengineland.com/smx/submit-speaking-pitch" target="_blank" rel="noopener">at</a><a href="https://searchengineland.com/smx/submit-speaking-pitch"> SMX</a> for more details on how to submit a session idea. When you’re ready, <a href="https://thirddoorevents.com/login" target="_blank" rel="noopener">create your profile</a> and send us your session pitch.</p>



<p>We look forward to your submissions and insights! If you have any questions, feel free to reach out to me at <a href="mailto:kathy.bushman@semrush.com" target="_blank" rel="noopener">kathy.bushman@semrush.com</a>.</p>


We celebrated a major milestone in June: the return of SMX Advanced as an in-person event. It was our first since 2019. 
More than a conference, SMX Advanced 2025 was a reunion. Search marketers from around the world came together to connect, exchange ideas, and learn the most current and advanced insights in search.
But search never stands still. With rapid shifts in AI SEO, constant algorithm changes, and the challenge of balancing generative AI with a human touch, the need for truly advanced, actionable education has never been greater.
Help shape SMX Advanced 2026
We’re committed to making the SMX Advanced 2026 program our most relevant, advanced, and exciting deep-dive experience yet. And we can’t do it without you – the expert community that makes this event legendary.
We’re inviting you to directly shape the curriculum for 2026.
Help us build a program that tackles the biggest challenges and opportunities on your radar by completing our short survey. Tell us:
What advanced topics are most critical to your professional growth right now.
Which recent search changes or complexities are keeping you up at night.
Which search industry experts and innovators you need to hear from.
Which session formats – from deep-dive clinics to lightning talks and interactive panels – will help you learn more and retain what you learn.
Fill out the survey here.
Be entered to win an All Access pass
To thank you for your time and insights, everyone who completes the survey will have the opportunity to enter an exclusive drawing.
One lucky participant will win a coveted All Access pass to SMX Advanced 2026, taking place June 3-5 at the Westin Boston Seaport.
Submit a session pitch
Beyond shaping the agenda, we also invite you to submit a session pitch. If you have a breakthrough strategy, an innovative case study, or next-level insights, this is your chance to help lead the industry conversation.
Read our guide to speaking at SMX for more details on how to submit a session idea. When you’re ready, create your profile and send us your session pitch.
We look forward to your submissions and insights! If you have any questions, feel free to reach out to me at kathy.bushman@semrush.com.

Tell us what you want to learn about and who you want to hear from at SMX Advanced taking place June 3-5 at the Westin Boston Seaport.

Help us shape SMX Advanced 2026. You could win an All Access pass!

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Screenshot of Google Search Console" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>After several weeks of delayed data, the report now appears to be fixed, with delays of two to six hours instead of more than 70.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Screenshot of Google Search Console" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p><a href="https://searchengineland.com/library/platforms/google/google-search-console">Google Search Console</a> appears to have fixed the weeks-long delay in Performance reports. After <a href="https://www.seroundtable.com/google-search-console-performance-reports-page-indexing-delayed-40544.html">several weeks</a> of 50+ hour lag times, the reports now seem up to date as of the past few hours.</p>



<p><strong>Now up-to-date. </strong>If you check the <a href="https://search.google.com/search-console/performance/search-analytics?resource_id=">Search Performance report</a> now, you should see a normal delay of about two to six hours. Over the past few weeks, that delay had stretched to more than 70 hours.</p>



<p>This is what <a href="https://www.seroundtable.com/google-search-console-performance-reports-fixed-40608.html" target="_blank" rel="noopener">I see</a>:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="548" height="366" src="https://searchengineland.com/wp-content/seloads/2025/12/gsc-performance-report-normal-1765881997.png" alt="" class="wp-image-466291"/></figure>



<p>The delays began a few weeks ago and took roughly three weeks to fully clear, including the backlog of data.</p>



<p><strong>Page indexing report. </strong>Meanwhile, the Page Indexing report delay we reported <a href="https://searchengineland.com/google-search-console-index-coverage-report-delayed-465464">weeks ago</a> is still unresolved. The report is now almost a month behind, and Google has not fixed it yet. Google posted a notice at the top of the report that says:</p>



<ul class="wp-block-list">
<li>&#8220;Due to internal issues, this report has not been updated to reflect recent data&#8221;</li>
</ul>



<p><strong>Why we care. </strong>If you rely on Search Console data for analytics and stakeholder or client reporting, this has been extremely frustrating. The Performance reports now appear to be updating normally, but the Page Indexing report remains heavily delayed and will continue to create reporting headaches.</p>



<p>Meanwhile, Google released a number of new features in the past few weeks, including:</p>



<ul class="wp-block-list">
<li><a href="https://searchengineland.com/google-search-console-tests-ai-powered-configuration-to-create-dynamic-reports-465637">AI-powered configuration</a> for the Search Performance report</li>



<li><a href="https://searchengineland.com/google-search-console-insights-integrating-social-channels-465776">Social channels</a> in the Insights report</li>



<li><a href="https://searchengineland.com/google-search-console-performance-reports-adds-weekly-and-monthly-views-465870">Weekly and monthly smoothing</a> in the Performance report</li>
</ul>


Google Search Console appears to have fixed the weeks-long delay in Performance reports. After several weeks of 50+ hour lag times, the reports now seem up to date as of the past few hours.
Now up-to-date. If you check the Search Performance report now, you should see a normal delay of about two to six hours. Over the past few weeks, that delay had stretched to more than 70 hours.
This is what I see:




The delays began a few weeks ago and took roughly three weeks to fully clear, including the backlog of data.
Page indexing report. Meanwhile, the Page Indexing report delay we reported weeks ago is still unresolved. The report is now almost a month behind, and Google has not fixed it yet. Google posted a notice at the top of the report that says:
“Due to internal issues, this report has not been updated to reflect recent data”
Why we care. If you rely on Search Console data for analytics and stakeholder or client reporting, this has been extremely frustrating. The Performance reports now appear to be updating normally, but the Page Indexing report remains heavily delayed and will continue to create reporting headaches.
Meanwhile, Google released a number of new features in the past few weeks, including:
AI-powered configuration for the Search Performance report
Social channels in the Insights report
Weekly and monthly smoothing in the Performance report

After several weeks of delayed data, the report now appears to be fixed, with delays of two to six hours instead of more than 70.

Google fixes weeks-long Search Console Performance report delay

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>A six-step guide to improving your ecommerce PPC strategy, inspired by a Canadian fashion leader.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div><div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final.png" alt="" class="wp-image-465983" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></figure></div>


<p>Managing large catalogs in Google Performance Max can feel like handing the algorithm your wallet and hoping for the best.&nbsp;</p>



<p>La Maison Simons faced that exact challenge: too many products and not enough control. Then they rebuilt their segmentation with <a href="https://www.channable.com/products/channable-insights?utm_medium=affiliate&amp;utm_source=search_engine_land&amp;utm_campaign=sel_sponsored_post_december_2025_us&amp;utm_content=blog" target="_blank" rel="noopener sponsored nofollow">Channable Insights</a> and turned a “black box” campaign into a revenue-generating machine.</p>



<h2 class="wp-block-heading" id="h-step-1-stop-segmenting-by-category">Step 1: Stop segmenting by category</h2>



<p>Simons originally split campaigns by product category. It sounded logical – until their best-selling sweater ate the budget and newer or overlooked products never had a chance to surface.</p>



<p>Static segmentation meant limited visibility and slow decisions.</p>



<p>Marketers stayed stuck making manual tweaks while Google kept auto-prioritizing only what was already working.</p>



<h2 class="wp-block-heading" id="h-step-2-segment-by-performance">Step 2: Segment by performance</h2>



<p>Enter Channable Insights. Product-level performance data (ROAS, clicks, visibility) now powers dynamic grouping:</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1080" height="400" src="https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Image-1-Segment-by-Performance.png" alt="Chart showing product segments: &quot;Star Products&quot; with a star, &quot;Zombie Products&quot; with a zombie face, &quot;New Arrivals&quot; with sparkles. Each has goals and strategies." class="wp-image-466107" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Image-1-Segment-by-Performance.png 1080w, https://searchengineland.com/wp-content/seloads/2025/12/Channable-SEL-Sponsored-Post-Image-1-Segment-by-Performance-768x284.png 768w" sizes="(max-width: 1080px) 100vw, 1080px" /></figure></div>


<p>Products <strong>automatically</strong> move between these segments as performance shifts – no manual work needed. As Etienne Jacques, Digital Campaign Manager, Simons, put it:</p>



<p class="has-text-align-center"><strong>“One super popular item no longer takes all the money.”</strong></p>



<h2 class="wp-block-heading" id="h-step-3-shorten-your-analysis-window">Step 3: Shorten your analysis window</h2>



<p>Instead of waiting 30 days for signals, Simons switched to a rolling 14-day window.</p>



<p>The result: faster reactions, sharper accuracy, and less wasted spend in a fast-moving catalog.</p>



<h2 class="wp-block-heading" id="h-step-4-push-the-strategy-across-channels">Step 4: Push the strategy across channels</h2>



<p>Why stop at Google? The same segmentation logic was automatically applied on:</p>



<ul class="wp-block-list">
<li>Meta</li>



<li>Pinterest</li>



<li>TikTok</li>



<li>Criteo</li>
</ul>



<p>Cross-channel consistency creates compounding optimization.</p>



<h2 class="wp-block-heading" id="h-step-5-watch-the-metrics-climb">Step 5: Watch the metrics climb</h2>



<p>Without raising ad spend, Simons unlocked:</p>



<ul class="wp-block-list">
<li><strong>ROAS growth:</strong> from ~800% to ~1500%</li>



<li><strong>CPC decrease:</strong> $0.37 to $0.30</li>



<li><strong>CTR lift:</strong> 1.45% to 1.86%</li>



<li><strong>14% </strong>increase in average order value</li>



<li><strong>1300% ROAS</strong> for New Arrivals campaigns</li>



<li><strong>Faster</strong> workflows and <strong>fewer</strong> manual tweaks</li>
</ul>



<p>Even the “invisibles” turned into surprise profit drivers once they finally got the spotlight.</p>



<h2 class="wp-block-heading" id="h-step-6-treat-automation-as-control-not-chaos">Step 6: Treat automation as control, not chaos</h2>



<p>Automation restored marketing control&nbsp;–&nbsp;it didn’t remove it.</p>



<p>Teams can finally learn from the data and influence which products grow, instead of letting PMax run everything on autopilot.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1080" height="500" src="https://searchengineland.com/wp-content/seloads/2025/12/Channable-20251216-2.png" alt="A table with a yellow header reading 'Quick Rules to Implement.' Two columns titled 'Principle' in pink and 'Why It Matters' in blue. Four empty rows beneath, with a colorful logo in the bottom left corner." class="wp-image-465888" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Channable-20251216-2.png 1080w, https://searchengineland.com/wp-content/seloads/2025/12/Channable-20251216-2-768x356.png 768w" sizes="(max-width: 1080px) 100vw, 1080px" /></figure>



<h2 class="wp-block-heading" id="h-your-action-plan">Your action plan</h2>



<ul class="wp-block-list">
<li>Classify products as Stars, Zombies, and New Arrivals.</li>



<li>Automate campaign reassignment based on real-time data.</li>



<li>Refresh product insights every 14 days.</li>



<li>Roll out segmentation logic to every paid channel.</li>



<li>Scale what wins – test what hasn’t yet.</li>
</ul>



<p>Want Simons-style ROAS gains without extra ad spend? Start by testing the quality of your product data with a <a href="https://get.channable.com/channable-us-free-feed-audit?utm_medium=affiliate&amp;utm_source=search_engine_land&amp;utm_campaign=sel_sponsored_post_december_2025_us&amp;utm_content=blog" target="_blank" rel="noopener sponsored nofollow">free feed and segmentation audit</a>.</p>



<p></p>


Managing large catalogs in Google Performance Max can feel like handing the algorithm your wallet and hoping for the best. 
La Maison Simons faced that exact challenge: too many products and not enough control. Then they rebuilt their segmentation with Channable Insights and turned a “black box” campaign into a revenue-generating machine.
Step 1: Stop segmenting by category
Simons originally split campaigns by product category. It sounded logical – until their best-selling sweater ate the budget and newer or overlooked products never had a chance to surface.
Static segmentation meant limited visibility and slow decisions.
Marketers stayed stuck making manual tweaks while Google kept auto-prioritizing only what was already working.
Step 2: Segment by performance
Enter Channable Insights. Product-level performance data (ROAS, clicks, visibility) now powers dynamic grouping:

Products automatically move between these segments as performance shifts – no manual work needed. As Etienne Jacques, Digital Campaign Manager, Simons, put it:
“One super popular item no longer takes all the money.”
Step 3: Shorten your analysis window
Instead of waiting 30 days for signals, Simons switched to a rolling 14-day window.
The result: faster reactions, sharper accuracy, and less wasted spend in a fast-moving catalog.
Step 4: Push the strategy across channels
Why stop at Google? The same segmentation logic was automatically applied on:
Meta
Pinterest
TikTok
Criteo
Cross-channel consistency creates compounding optimization.
Step 5: Watch the metrics climb
Without raising ad spend, Simons unlocked:
ROAS growth: from ~800% to ~1500%
CPC decrease: $0.37 to $0.30
CTR lift: 1.45% to 1.86%
14% increase in average order value
1300% ROAS for New Arrivals campaigns
Faster workflows and fewer manual tweaks
Even the “invisibles” turned into surprise profit drivers once they finally got the spotlight.
Step 6: Treat automation as control, not chaos
Automation restored marketing control – it didn’t remove it.
Teams can finally learn from the data and influence which products grow, instead of letting PMax run everything on autopilot.




Your action plan
Classify products as Stars, Zombies, and New Arrivals.
Automate campaign reassignment based on real-time data.
Refresh product insights every 14 days.
Roll out segmentation logic to every paid channel.
Scale what wins – test what hasn’t yet.
Want Simons-style ROAS gains without extra ad spend? Start by testing the quality of your product data with a free feed and segmentation audit.

A six-step guide to improving your ecommerce PPC strategy, inspired by a Canadian fashion leader.

How to boost ROAS like La Maison Simons by Channable

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/Google-Local-Services-Ads-vs.-Search-Ads-Which-drives-better-local-leads.jpg" class="attachment-large size-large wp-post-image" alt="Google Local Services Ads vs. Search Ads- Which drives better local leads?" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/Google-Local-Services-Ads-vs.-Search-Ads-Which-drives-better-local-leads.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/11/Google-Local-Services-Ads-vs.-Search-Ads-Which-drives-better-local-leads-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/11/Google-Local-Services-Ads-vs.-Search-Ads-Which-drives-better-local-leads-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google Ads now lets Android App campaigns optimize bidding for view-through conversions, showing a shift toward video-driven performance.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/Google-Local-Services-Ads-vs.-Search-Ads-Which-drives-better-local-leads.jpg" class="attachment-large size-large wp-post-image" alt="Google Local Services Ads vs. Search Ads- Which drives better local leads?" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/Google-Local-Services-Ads-vs.-Search-Ads-Which-drives-better-local-leads.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/11/Google-Local-Services-Ads-vs.-Search-Ads-Which-drives-better-local-leads-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/11/Google-Local-Services-Ads-vs.-Search-Ads-Which-drives-better-local-leads-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google Ads launched VTC-optimized bidding for Android app campaigns, letting advertisers toggle bidding toward conversions that happen after an ad is viewed rather than clicked.</p>



<p>Previously, VTC worked as a hidden signal inside Google’s systems. Now, it’s a clear, explicit optimization option.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1665" height="918" src="https://searchengineland.com/wp-content/seloads/2025/12/1765813237869.jpeg" alt="" class="wp-image-466261" srcset="https://searchengineland.com/wp-content/seloads/2025/12/1765813237869.jpeg 1665w, https://searchengineland.com/wp-content/seloads/2025/12/1765813237869-768x423.jpeg 768w, https://searchengineland.com/wp-content/seloads/2025/12/1765813237869-1536x847.jpeg 1536w" sizes="(max-width: 1665px) 100vw, 1665px" /></figure>



<p><strong>The shift.</strong> Google is shifting <a href="https://searchengineland.com/google-ios-app-campaigns-new-formats-ai-tools-460788">app advertising away from click-centric logic and toward incrementality and influence</a>, especially for formats like YouTube and in-feed video. This update aligns bidding more closely with how users actually discover and install apps.</p>



<p><strong>Why we care.</strong> You can now bid beyond clicks, improving measurement for video-led app campaigns and strengthening the case for upper-funnel activity.</p>



<p><strong>Who benefits most</strong>. Video-first app advertisers and teams focused on awareness, engagement, and long-term growth –&nbsp;not just last-click installs.</p>



<p><strong>What to watch</strong></p>



<ul class="wp-block-list">
<li>Increased reliance on Google’s attribution model.</li>



<li>Potential changes in CPA expectations.</li>



<li>Greater emphasis on creative quality over click-driving tactics.</li>
</ul>



<p><strong>First seen.</strong> This update was first spotted by Senior Performance Marketing Executive Rakshit Shetty when he posted on <a href="https://www.linkedin.com/posts/rakshitbshetty_googleads-appmarketing-paidmedia-activity-7406357531482120192-Y7Mo/">LinkedIn</a>. </p>


Google Ads launched VTC-optimized bidding for Android app campaigns, letting advertisers toggle bidding toward conversions that happen after an ad is viewed rather than clicked.
Previously, VTC worked as a hidden signal inside Google’s systems. Now, it’s a clear, explicit optimization option.




The shift. Google is shifting app advertising away from click-centric logic and toward incrementality and influence, especially for formats like YouTube and in-feed video. This update aligns bidding more closely with how users actually discover and install apps.
Why we care. You can now bid beyond clicks, improving measurement for video-led app campaigns and strengthening the case for upper-funnel activity.
Who benefits most. Video-first app advertisers and teams focused on awareness, engagement, and long-term growth – not just last-click installs.
What to watch
Increased reliance on Google’s attribution model.
Potential changes in CPA expectations.
Greater emphasis on creative quality over click-driving tactics.
First seen. This update was first spotted by Senior Performance Marketing Executive Rakshit Shetty when he posted on LinkedIn.

Google Ads now lets Android App campaigns optimize bidding for view-through conversions, showing a shift toward video-driven performance.

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All About Digital Marketing

Read the Latest Trends and Headlines in Digital Marketing.

Here are some of the latest headlines on digital marketing insights, search, and ecommerce:

Free Consultation

Reach out with any questions you might have regarding how RSO can help you with digital marketing.

All About
Digital Marketing