I always knew that automation was transforming PPC, but recently, I’ve seen how OpenAI’s groundbreaking tools are taking this transformation to new heights.
Automation has shaped PPC for decades, with the landscape constantly evolving. My journey started with developing the first AdWords Editor and writing about automation layering. Now, we’re seeing a new era unfold.
The way AI processes information is shifting. This change isn’t driven by traditional platforms like Google, but by pioneers like OpenAI.
AI was mostly known for handling tasks related to human language—copywriting, summarizing, reporting. But now, LLMs are delving into computer language, creating the software that boosts our efficiency.
At OpenAI’s DevDay in San Francisco, I witnessed the introduction of AgentKit, a tool that brings AI into action-handling territory. This marks a shift where PPC optimization techniques can transcend campaigns, integrating into comprehensive workflows.
Imagine if AI could manage your routine tasks, from adding client reports to your dashboard before you even access your emails, to scheduling meetings, drafting agendas, and ensuring adherence to brand guidelines while drafting ad copy.
These advancements are within reach, without the need for technical expertise.
Mainly, if you can break down tasks into actionable steps, you can set up an agent to execute them.
An AI agent is not just an algorithm; it’s a versatile aide equipped to deduce necessary actions and execute them through connected tools.
Unlike traditional, rigid software with deterministic steps, agents offer flexibility and adapt to scenarios without requiring exhaustive pre-programming.
This evolution in automated assistance is something I had glimpsed in early iterations—now, a more sophisticated agent can execute real-world tasks formulated in the virtual sandbox of GPT innovations.
The appeal of OpenAI’s AgentKit lies in its ability to transform lengthy coding sessions into quick, non-technical builds, akin to “Zapier for AI.”
Unlike traditional software, AgentKit leverages AI’s reasoning instead of fixed rules, making it an innovative tool for marketers like me aiming to automate tasks efficiently.
AgentKit provides a visual workflow built around familiar tools like Gmail and Dropbox, ensuring seamless integrations and ease of use.
I recently came across some eye-opening data about ChatGPT and its impact on driving traffic to publishers. The findings reveal a substantial gap between the visibility of ChatGPT links and actual clicks, which is quite astonishing.
A leaked document shows how OpenAI is monitoring user interactions, especially focusing on how frequently ChatGPT provides publisher links and the surprisingly low number of users who click on them.
By the numbers. ChatGPT does indeed feature links, yet they receive minimal engagement. For a top-performing page, here’s what the OpenAI data indicates:
610,775 total link impressions
4,238 total clicks
0.69% overall CTR
Best individual page CTR: 1.68%
Most other pages: 0.01%, 0.1%, 0%
ChatGPT metrics. This leaked file details each instance where ChatGPT displays links, providing a breakdown of user interactions:
Date range (include date partition, report month, min/max report dates)
Publisher and URL details (publisher name, base URL, host, URL rank)
Impressions and clicks across various locations:
Response
Sidebar
Citations
Search results
TL;DR
Fast navigation
CTR calculations for each display area
Total impressions and total clicks across all surfaces
Where the links appear. Surprisingly, the zones with the most visibility yield the fewest clicks. Here’s a performance breakdown by visibility zone:
Main response: Massive impressions, minimal CTR
Sidebar and citations: Reduced impressions but higher CTR (6–10%)
Search results: Negligible impressions, zero clicks
Why it matters. If you were hoping ChatGPT’s visibility could substitute for your lost Google organic search traffic, think again. Although AI-driven traffic is on the rise, it remains just a sliver of overall traffic and unlikely to match the behavior of traditional organic search traffic.
About the data. This fascinating data was shared on LinkedIn by Vincent Terrasi, CTO and co-founder of Draft & Goal, a company specializing in content production workflows.
Have you ever wondered which brands are thriving, which are waning, and which remain steady within AI search platforms? I’ve delved deep into Semrush’s AI Visibility Index, and I’m here to share strategies to safeguard and enhance your visibility.
AI search is a dynamic field that’s evolving rapidly. Over the past three months, it’s become clearer which brands stand out and which sources AI models prefer to trust.
In examining three months of AI Visibility Index data, particularly from ChatGPT and Google AI Mode, I’ve realized just how volatile AI search truly is, a pattern likely to persist in the near term.
Brands that come out on top are those who consistently monitor and adjust to these changes as they unfold.
The research includes a study of 2,500 real-world prompts across five crucial sectors: Business & Professional Services, Digital Technology & Software, Consumer Electronics, Fashion & Apparel, and Finance. It unveils dramatic shifts in source diversity, brand mentions, and model behavior—info no marketer can afford to ignore.
What Changed at a Model Level?
ChatGPT: Unique brand mentions fluctuated, while the number of sources cited grew by 80% in October alone, showing a move toward greater source diversity.
Google AI Mode: From August to October, brand mentions dropped by 4%, hinting at stricter recommendation controls. Source diversity saw a moderate 13% rise, indicating a more conservative stance compared to ChatGPT.
Key Trends Over Three Months
Reddit’s Correction and Resurgence: ChatGPT reduced Reddit mentions by 82% but maintained it as the fourth most-cited source. Meanwhile, Google AI Mode’s use of Reddit increased by 75%, becoming the second top source. Both platforms are recognizing Reddit’s value, albeit differently.
Brand Diversity Varies by Vertical and Model: ChatGPT noted a 20% rise in unique brand mentions in Consumer Electronics, while Finance saw a 15% decline. Conversely, Google AI Mode saw a decline across almost every vertical, underscoring the need for model-specific strategies.
Top Brands Remain Relatively Stable: Over three months, 25 new brands joined the top 100, yet only two cracked the top 50. Leading brands’ visibility changes stayed within a ~20% range, much narrower than the overall market turbulence.
Source Strategies Must Be Model-Specific: ChatGPT and Google AI Mode agree on brand mentions 67% of the time, but agree on sources only 30% of the time. Dominant sources include Wikipedia, Forbes, and Amazon for ChatGPT, while Google AI Mode favors Amazon and YouTube.
I’ve learned that maintaining AI visibility requires ongoing vigilance. Both platforms are testing diversity, adjusting for past overdependencies, and refining strategies.
What This Means for Your Strategy
In the ever-evolving world of AI search, past visibility doesn’t secure future success.
Both ChatGPT and Google AI Mode feature 61 of the top 100 brands, indicating strong brand overlap. However, source overlap is much less and has decreased from August to October.
Translation: Enhance your brand’s visibility on both platforms but customize your source strategy based on each model’s nuances.
Explore the AI Visibility Index to access full rankings, interactive leaderboards, and comprehensive trends across all five sectors. Download proven strategies to bolster your visibility in this swiftly changing domain. It’s complimentary!
As someone deeply invested in the fascinating world of agentic commerce, I’ve become curious about what really boosts product visibility in the AI shopping realm. It’s a topic worth diving into as AI rapidly transforms the way consumers make purchasing decisions.
Have you ever wondered how platforms like ChatGPT, Perplexity, and Rufus determine which products grace the digital shelves? Uncovering this process offers valuable insights into AI decision-making and gives us a competitive edge in this new era of shopping.
Let me share with you how these AI platforms evaluate and choose products, allowing us to strategically position our offerings and maximize their AI shelf presence. Understanding these dynamics empowers us to navigate and excel in AI-driven marketplaces effectively.
Why the web as we know it may fade and what AI, personal agents, and data interfaces mean for publishers, SEO, and commerce.
Every day, I’m witnessing people turn to AI for answers, product comparisons, and making quick decisions.
This shift reveals a core issue: the structure of the web wasn’t originally meant for machines.
As AI agents evolve, the way information is delivered – and the need for traditional webpages – could see dramatic changes.
The idea that the web as we know it could end, which I mentioned during a live OXD podcast in Salzburg, drew reactions ranging from thoughtful to angry.
Someone even insisted, “The web will always be there.”
Yet, those of us paying attention understand that “always” and “never” are shaky concepts in technology.
Technological history illustrates that nothing is forever.
Disruptions are noticeable only in hindsight.
Recall August 6, 1991 – could anyone foresee how Tim Berners-Lee’s World Wide Web would transform the world?
This cycle of dismissing new technology as too expensive or complex is as old as technology itself.
People pointed to existing solutions and assumed they’d last.
We also tend to judge new technologies prematurely, comparing immature models to systems we’ve heavily relied upon.
What we often fail to do is envisage the evolved state of a new technology.
This tendency clouds our future outlook.
When I’m in the market for a smartwatch, where do I usually turn for information?
Most often, I start with Google, landing on manufacturer or retailer pages.
Trying to compare the Samsung Galaxy Watch8, Classic, and Ultra to determine if the price difference makes sense is challenging.
Can I get this clarity from Samsung’s site? Probably not.
Each product page praises its uniqueness.
This forces me to jot down notes just to make basic comparisons.
I ponder over the difference between various bands and processors.
To grasp certain features, translations are sometimes necessary.
Even the “compare” function often leaves more questions than answers.
And while expectations would assume the premium model to have a specific feature, marketing priorities often arc differently.
The websites prompt more head-scratchers: Do these technical terms even matter to me?
My search broadens, throwing me onto SEO-crafted pages.
These sites often try leading me towards affiliate links.
Time is the thief here; Google requires nuanced search phrases and countless clicks.
But when I ask ChatGPT, the answer is swift and spot-on.
In less than four seconds, I get a clear comparison, making sense of all distinctions.
Follow-up questions are met with clarity.
If there are specifics to check, I am advised accordingly.
Such instances highlight the inefficiencies of web research.
Manufacturers tend to showcase products as they envision them.
But we often want straightforward comparisons.
We thrive on differences; we’re delta thinkers.
Sellers often prefer presenting products singularly.
If something isn’t present, obfuscation is the strategy.
It’s understandable, but not helpful.
Stop for a moment and try your AI for search queries.
If it’s been a while, you’re likely to be amazed.
In mere seconds, you get detailed answers.
Unsure about source reliability? Tailor your queries:
– “Only search designated expert sites.”
– “Only use well-known institutions.”
– “Give me all sources.”
The updated Google’s Gemini can produce extensive reports after an in-depth research request.
Imagine rich responses, often more comprehensive than solo human efforts.
That’s the growing strength of AI.
Using HTML makes content flexible for human consumption.
This system assists us in seeing and reading what’s online.
However, as AI usage expands, the limitations become apparent.
For example, the figures on a webpage may be clear to us, but the HTML lacks inherent semantic meaning for machines.
Structured data came as a solution but remains underused.
This impedes machine comprehension.
Apart from internal systems or large enterprises, structured data implementation is sparse.
Therefore, the primary content is still somewhat elusive to machines.
Google has worked hard to bridge this understanding gap.
Yet, AI continues to evolve, seeking innovative ways to parse and utilize data.
While AI presently gleans information through pattern matching, its potential remains vast.
Chatbots like ChatGPT offer solutions today.
The real challenge is context comprehension, which remains elusive for AI.
While both amazing and rapid, AI’s journey is just beginning.
The advances have sparked immense growth and excitement.
This era has only begun, opening doors to boundless possibilities.
Imagine a world transformed by personalized AI assistants.
The possibilities intrigue me.
These personal agents will tackle our daily routines, searching for optimal solutions.
AI might soon handle appointments, emails, and much more, offering efficiency and convenience.
Such shifts might alter how we interact digitally.
Content delivery and decision-making will evolve over time.
Our current HTML limitations challenge technological adaptability.
A new paradigm could include AIDIs assisting us with data retrieval.
Incorporating AIDIs means transitioning from HTML to structured forms.
Imagine AIDI extensions making data interpretation effortless.
Personal agents would operate even more efficiently.
The transition hinges on AI development and adoption.
Comparatively, the idea seems vast – but technological evolution often brings surprises.
Before long, our interactions may become distinctly AI-driven.
Offering a personalized touch, these agents may surpass our expectations.
I recently came across a fascinating report on AI referral traffic that’s shaking things up in the digital world. According to Conductor’s AI search benchmark report, AI-generated traffic currently makes up just over 1% of website visits across ten major industries.
AI referral traffic: It’s intriguing to see that 1.08% of all web traffic originates from AI. Among this, ChatGPT is a dominant force, accounting for 87.4% of AI referrals. Leading industries include IT with 2.8% and Consumer Staples at 1.9%, while Communication Services and Utilities are seeing the lowest shares, at 0.25% and 0.35%, respectively.
AI answer engine market share: ChatGPT is at the helm, followed by Perplexity. Interestingly, the impact varies across industries. For instance, Gemini is responsible for 21% of AI traffic in Utilities, whereas Copilot contributes 5% in Financials.
AI vs. traditional traffic: Despite the rise of AI, traditional organic search still reigns supreme. Industries like Health Care (42.4%), Communication Services (39.6%), and Industrials (33.8%) lead in organic search shares.
Why we care: While organic search remains a heavyweight, AI is emerging as a powerful channel. If a brand isn’t appearing in AI answers, it risks being invisible to its audience. While SEO strategies overlap with AI and other platforms like ChatGPT, being a Google ranking champion doesn’t guarantee AI visibility.
The brands AI cites most: Across 17 million AI responses, AI prefers different brands compared to Google. Giants like Amazon and Walmart top the list for consumer queries. In health and finance (YMYL categories), reputable sources like Mayo Clinic and NerdWallet are often cited. Meanwhile, industry stalwarts like Google and Microsoft lead in tech and B2B queries.
AI Overviews benchmarks: From an analysis of 21.9 million Google searches, 25.11% triggered AI Overviews, with categories like Health Care and Financials in the lead. The preferred content types cited are blogs, videos, and articles among others.
About the data: The comprehensive report analyzed 13,770 domains, over 3.3 billion sessions, and millions of AI interactions, offering a snapshot of the growing AI impact from May to September 2025.
