Content Archives - iPullRank

Signals in the Clickstream: Early Referral Data on Google’s AI Mode

Garrett Sussman — Fri, 26 Sep 2025 18:06:42 +0000

TL;DR: Key Referral Data Insights from the First Three Months of AI Mode Usage (May–August 2025)

External clicks from AI Mode stay under ~3%. Traditional Google Search sends far more traffic.
Clicks cluster on Reddit, YouTube, Wikipedia, Amazon, Facebook. Developer hubs like GitHub, Stack Overflow, and Stack Exchange show up.
Post-click depth from AI Mode is thinner: fewer pageviews and shorter sessions on average than visits from Google Search.
Two possible hypothetical reasons for short sessions: a) cited links are often broken, stale, or off-target, b) many users are quick-checking a claim from the AI answer and leave after confirming.
AI Mode query length trends up (roughly 7–8 words in May to 10–11+ in August). ChatGPT stays near ~70.
Sessions per user dipped, then recovered. No habit loop yet.

Note: Each of the graphs below is interactive. You can hover over them to see precise data or click on legend segments to see a different visualization of the data.

The narrative that AI Search delivers less traffic compared to traditional Google Search is entrenched. In fact, we’ve seen over 50% better conversation rates from AI referrers across all clients that we’ve analyzed this year. Semrush has claimed that AI Search traffic delivered 4.4x value compared to traditional search.

AI Mode specifically generates fewer clicks compared to classic Google Search. The clicks it does send concentrate on big, trusted, and UGC-heavy domains. Query length in AI Mode is trending up, which signals people are learning to abandon ‘keywordese’ and embrace conversational search, not that clicks will surge. Treat AI Mode as a distinct channel with low referral volume and high variance. Build presence where it already exists, and measure citation prominence and assisted impact, not just traffic.

Before diving into the data, let’s review the sequence of events since the last time we checked in.

What changed since last month

August 4 – The Google sales team is lining up AI Mode Ads for aggressive Q4 testing. Shout out to Anu Adegbola for the scoop. Agencies were briefed in early August on conversation-level targeting inside AI Mode. If those units perform, the case for a default or quasi-default experience gets stronger because the revenue model travels with it.

August 21 – Google took AI Mode global. The rollout hit 180+ countries and came with talk of agentic features like bookings and task help. I haven’t seen those live in the wild yet, which suggests staged or Labs-gated releases. Direction is clear. Scale first, deeper capability later.

September 5 – Logan Kilpatrick replied “Soon” to a post pushing for AI Mode to be the default version of search after an announcement that Google had created google.com/ai as a direct straight to the AI Mode interface destination. Momentum looked real.

September 7-8 – Then came the soft pedal. Robby Stein says not to read too much into “soon,” framing the near-term focus as easier access for people who want AI Mode, not a hard switch to default. A day later, Kilpatrick backed that and clarified he was not saying AI Mode replaces main Search right now. Signal remains. Timeline stays murky.

September 18 – Google announces that they are now building AI into Chrome on U.S. desktops.

You get omnibox entry to AI Mode, a side panel that answers questions about the page, multi-tab summaries, and deeper hooks into YouTube, Maps, and Calendar.

You get contextual search.

Now things will get interesting. Friction drops. Will usage rise? And all of this landed after the DOJ remedies phase confirmed Google would not be forced to break off Chrome, which makes the timing notable.

What this points to

Google is removing access friction, seeding usage in Chrome, testing monetization, and expanding reach. Public messaging stays cautious, yet every move increases the odds that AI Mode becomes the primary search experience in the next 6–12 months. That is the working assumption I’m planning against.

Methodology

SimilarWeb provided Elias Dabbas and our team with daily relative data points from over 100K AI Mode users between the timeframe of May 20th (AI Mode’s public launch date) to August 19th on the following metrics:

Referral Rate: The percentage of searches that led to at least one click to a non-Google site. Each search is counted once: if it triggers one or many external clicks, it qualifies as a “referred” search. (Formula: Referred searches ÷ Total searches.)
Referral Time on Site (minutes, average): The average time users spent on the external site after a referral click. Calculated across all referred visits that day. (Formula: Total minutes on referred sites ÷ Number of referred visits.)
Referral Pageviews (average): The average number of pages viewed on the external site after a referral click. Calculated across all referred visits that day. (Formula: Total pageviews on referred sites ÷ Number of referred visits.)
Referral Share (Top Referred Sites): For a given external domain, the share of all outbound clicks that landed on that domain. Each click is an event in the denominator set. (Formula: Clicks to Domain X ÷ Total outbound clicks.)
Average Query Length: The average number of words in the initial query that opened the experience. For AI Mode, only the first query is captured; follow-ups create new URLs that aren’t yet query-level trackable. In some cases, the first query may have been entered in classic Google before the user clicked into AI Mode. (Formula: Total words in first queries ÷ Number of first queries.)

We now have three months of data from May to August 2025. In our analysis, we are considering the type of person who would push past the friction to utilize the functionality. This data continues to highlight a contextual moment in time. Google is aggressively promoting AI Mode on social media, through advertising, and with disruptive pop-ups in Search. We should also understand that the novelty of it could lead to experimentation, as opposed to genuine, normal search behavior.

That was a major caveat that was addressed in our previous articles on the AI Mode data.

Revisit our initial referral report from the first month of data.

Referral Patterns in Google AI Mode: Understanding the Early Data

Google Trends: Most People Still Aren’t Searching for AI Mode

Despite all the announcements and updates, people still don’t seem to care about AI Mode. According to Google Trends data (August 2024–August 2025), “AI Mode” has one blip on the radar during the week of June 29–July 5, likely tied to the announcement of deep search and model switching capabilities via their blog.

In contrast, ChatGPT continues to dominate attention, with Gemini in the distance and Perplexity crawling behind.

Sidenote: Has anyone seen Perplexity’s recent advertisements implying people can use it for sports betting analysis and recommendations? YIKES. Bros are going to lose a lot of money. Don’t be like these bros. (H/T to iPullRank’s Lead Relevance Engineer Patrick Schofield)

AI Overviews isn’t on anyone’s radar at this point, and maybe that’s a good thing? If our UX AI Mode study is any indication, people don’t even know that’s what it’s called.

For marketers, this suggests minimal awareness or demand among everyday users. The data that follows reflects a niche user base, not mainstream behavior.

New Perplexity ad on TickTok

What the Charts Show Us (and Why It Matters)

These charts zoom in on how AI Mode actually sends traffic. The feature is tucked away, so small numbers track. The patterns still teach us.

We would expect:

Low referral volume: answer-first design keeps users in the result.
Authoritative-site dominance: clicks skew to Reddit, YouTube, Wikipedia, Amazon, Facebook.
Quicker post-click sessions: if someone does go to the site, they’re either verifying a fact or making a quick purchase.
Volume and behavior volatility: layout tweaks and entry-point friction shake the numbers week to week. People’s familiarity with conversational search may impact behavior over time.

What actually shows up, and the surprises:

CTR stays tiny (<3%) and drifts sideways. This looks like a channel for coverage and credibility, not a traffic faucet.
Developer sites surprisingly punch above their weight. GitHub, Stack Overflow, and Stack Exchange appear often, hinting at early-adopter skew and task types like troubleshooting.
Concentration risk is real. A small set of domains captures a large share of the exits, suggesting that algorithmic biases may be embedded in the model citations.
Longer prompts for AI Mode. Query length rises, indicating a change in search behavior.

Everything here remains volatile: a limited window, a promotion-heavy period, and a user mix tilted toward testers. Treat all of these insights as early signals, not a settled trend.

Referral gap

Clicks out of AI Mode sit below ~3% and drift sideways. No increase over three months of data.
AI Mode delivers significantly fewer clicks to external sites than traditional search results pages.

Implications:

AI Mode is dramatically weaker than traditional search at driving referral traffic. Similarweb’s data backs up what most of us suspected: when Google pushes users into a generative answer box, fewer clicks leave the page. It’s a different mental model for search behavior. Traditional search was already trending toward zero-click behavior. AI Mode accelerates that shift.

People still click out for three main reasons:

They want to go deeper than the synthesized answer, but that group is smaller than with classic search.
They want to verify facts and sources, especially users familiar with AI’s tendency to hallucinate.
They have intent tied to an actual purchase or direct interaction with a business.

Outside those situations, AI Mode captures the curiosity and the clicks.

Where the clicks land

AI Mode referrals show a predictable but revealing pattern. High authority, community driven, and niche expertise sites dominate the top 40% of referrals. This mix of platforms such as Reddit, YouTube, Wikipedia, Amazon, GitHub, Zillow, Healthline, and others reflects how people are using AI Mode both for mainstream topics and for specialized searches like health, real estate, and coding support. Compared to SEMrush and Ahrefs data, the AI Mode list contains fewer narrowly defined sites but more social and news outlets, pointing to shifts in both user intent and the kinds of publishers that win visibility.

Clicks cluster around large trusted ecosystems including social networks, knowledge hubs, and high authority brands, showing how AI Mode rewards broad platforms over niche ones.
Clicks underperform on specialized SEO tracked domains compared to SEMrush and Ahrefs data, signaling a potential gap in how AI Mode surfaces smaller or more targeted websites.

Semrush

Ahrefs

Post-click depth

Google Search consistently drives about six pageviews per referred visit. AI Mode averages closer to three to four pageviews, with much sharper swings. This reflects a thinner, more volatile post-click experience.

AI Mode referral sessions are about 2 pages shorter on average than Google Search sessions.
Pageview counts fluctuate widely, hinting at unstable or experimental user behavior.

Implications:

Fewer pages per visit signals “quick check” traffic or highly qualified traffic. Two opposite ends of the spectrum.

Users coming from AI Mode have already seen an AI summary and often click through to confirm or skim. Assume the content type is informational.

If it’s further down the funnel (including a homepage), these are the pages that are driving the higher rate of AI Search conversions.

Google Search referral sessions hold steady around 5 minutes. AI Mode sessions hover between 2.5 and 4 minutes with periodic spikes, but never settle into a stable pattern.

Shorter dwell times from AI Mode referrals: about half the duration of Google Search visits.
Higher volatility in session time signals mixed intent: some people test, some verify, and a few linger.

Implications:

Shorter sessions suggest issues with link quality (broken or off-target citations), anchor mismatch, or users conducting quick fact-checks before leaving. You may want to build your informational pages for fast trust by placing the cited passage above the fold, adding E-E-A-T signals early on, minimizing distractions, and offering a clear next step. This makes your site friendlier to AI Mode visitors and increases your odds of converting those brief interactions.

Prompt length

Here’s the most compelling example of change in search behavior over time (though not specifically referral-related).

AI Mode query length is growing. In June and July, the average query was around 8 words. By August it jumped to 10 or 11 words. That tells us people are starting to treat AI Mode more like a conversational interface, closer to how they use ChatGPT.

It’s nowhere near the 70-word prompts people use on ChatGPT, but the steady increase matters. Even without AI Mode as the default version of search, users are beginning to change their behavior. That shift forces a rethink of how we approach SEO. Targeting individual keywords based on search volume is losing relevance as queries get longer and more conversational.

Check out how dramatically different it feels when you only look at the AI Mode prompt length.

Engagement Frequency

Google Search stays steady at about 2.6 to 2.7 sessions per user through the period. AI Mode sits much lower at about 1.1 to 1.15 sessions per user but shows a clear rebound starting in July after an early summer dip.

AI Mode usage is still a fraction of Google Search in terms of sessions per user.
Engagement rose in late July and August which suggests new features or better visibility nudged people to come back more often.

Implications:

AI Mode has not yet built habit loops. The rise later in the period suggests that product updates or promotion can move the needle. Until access becomes default or near default, usage is likely to stay in bursts rather than a steady rhythm.

Looking at AI Mode alone, the trendline starts high in May, dips into mid June, then climbs through late July into August, reaching back toward early period highs.

AI Mode’s engagement curve reflects experimentation, friction, and partial recovery. The mid-year trough followed by a rise is consistent with a feature maturing and gaining more exposure, but it’s such a minuscule difference over such a short timeframe that the conclusion feels irresponsible.

I’ll watch how omnibox integration and global rollout influence this number. If AI Mode becomes default or quasi-default, expect a step change upward.

How are people actually using AI Mode?

Around this same period, we conducted the first-ever UX AI Mode Study with Farrah Bostic of the Difference Engine. She interviewed 23 people and had them use AI Mode to perform tasks ranging from finding a local health clinic to researching different credit card loyalty programs.

We hosted a webinar with her and shared our findings.

Since then, Francine Monahan has been diving deeper into each task to see how people use AI Mode across a variety of situations:

For each task, the conclusion was the same: AI Mode does not offer an experience that’s compelling enough to change search behavior.

People were curious and found it to be a novel experience. But many tasks weren’t appropriate given the current state of the experience and what it generated.

What this means for brands right now

AI Mode adoption is minimal. Optimizing for it is even less valuable than ChatGPT. HOWEVER. Over the next few months, as Google tests ads, you can’t afford not to pay attention. When it comes to AI Search in general, you need a strategy because it’s not just SEO.

If you don’t know where to start, we have an entire AI Search Manual for you, along with a webinar walkthrough.

What can you do in the meantime as search behavior slowly evolves to match the conversational search platform?

Calibrate expectations. AI Mode visibility is about presence and validation. Direct traffic will be small for a while (if not permanent).
Earn citations where AI Mode already looks. Reddit threads with credible answers, YouTube explainers with chapters and transcripts, reference-grade pages that define terms and steps, developer hubs if you are B2B tech. Digital PR should continue to be a big part of your organic search strategy. Omnichannel and omnimedia.
Design “confirm-and-go” landings. Assume the visitor already knows the gist. Put the proof element above the fold, surface the exact passage that was cited, and offer one low-friction next step.
Measure the right things. Channel-level citation count (we’re big fans of Profound for LLM channel monitoring), citation prominence within the answer, share of mentions vs peers, and assisted conversions for the visits you do get.

Is AI Mode going to become the default?

AI Mode shouldn’t be ignored. However, it’s not yet impactful. Optimize for being cited, for being credible when clicked, and for harvesting assisted value. Measure input signals to earn the citation, channel visibility to prove presence, and the narrow performance that follows.

Want to future-proof your business?

Learn about iPullRank's Relevance Engineering Services

The post Signals in the Clickstream: Early Referral Data on Google’s AI Mode appeared first on iPullRank.

How Anyone Can Strengthen Visibility In LLMs: A L’Oréal Case Study

Dixon Jones — Fri, 22 Aug 2025 11:00:00 +0000

Why dominating the space doesn’t always mean dominating the AI answer

Where do you learn about beauty products? Some might depend purely on YouTube, TikTok, Reddit, or…ChatGPT?

Marketers of the world’s largest brands conduct extensive research on their target audience. Beauty is purely visual. Despite your image and video channels driving traffic and visibility, brands can’t ignore the emergence of AI Search platforms. If you’re not monitoring and strategizing for AI Search, you’re opening the door for competitors to establish a stronger foundation that could hurt your brand in the long run.

As AI becomes the front door to information, brand visibility is being rewritten. It’s no longer enough for a product to appear in search results or dominate social. In large language models, the rules have changed. Visibility now depends on how well a brand is represented within the structure of the LLM’s knowledge —not just that it’s mentioned, but also the topics it’s associated with.

Even brand giants have blind spots when it comes to AI.

The Problem: You Might Be Present, But Not Relevant

When someone asks an LLM like ChatGPT about a topic, it doesn’t just repeat what it finds on the top-ranking site. It builds an answer by drawing from a web of entities and concepts: mascara ingredients, application techniques, and product performance in humidity. If your brand hasn’t clearly articulated its presence in those topic areas, it simply doesn’t appear in the response.

Some of this insight is captured by the LLMs in the training data (compiled over a long period), and some is often captured in the final mile through a search lookup, known as “Retrieval Augmented Generation” or RAG for short. If you get picked up in the training data, you stand a much better chance of your brand getting a good airing than if you have to rely on the RAG alone to get seen.

You could make the argument that Entity SEO has been a staple of a responsible Organic Search strategy for years, but it doesn’t fit neatly into the various best practice blog posts that you’ll see on the topic. But as search engines (and LLMs) increasingly depend on a semantic web driven by the relationships between words, concepts, and things, brands need more than a keyword strategy. They need an entity strategy. A way to understand how LLMs interpret them and where they’re being outplayed by competitors consistently on their underlying topics.

A Quick Example: L’Oréal Paris vs. Fenty vs. Estée Lauder

To explore how LLMs understand brands in specific product contexts, I ran a structured comparison across four leading models: Gemini, Sonar, ChatGPT, and Claude. Each was asked the same question three times, varying only the brand: What do you know about [brand] in the context of mascara? The brands tested were L’Oréal, Fenty, and Estée Lauder.

From there, I broke down each response into a knowledge graph—mapping out the key entities and topics mentioned. This allowed me to see how each brand is represented conceptually by the model, and where certain ideas or attributes are more (or less) likely to appear.

The above Knowledge Graph in table form:

A little context to explain the table below. By asking 5 LLMs what they know about Mascara in relation to three brands, we get 15 long-form responses. I go through every response, with the help of a tool like Waikay, to count every mention of every topic (by which we mean “entity” for the purists amongst you), and we tabulate the number of occurrences.

To highlight differences, I used:

Yellow to mark entities that appeared in some competitor responses but not L’Oréal’s
Red to mark entities that appeared in all competitor responses but were missing from L’Oréal’s

This approach gives a clearer view of the gaps in brand visibility across LLMs—and begins to reveal why they happen.

L’Oréal clearly holds strong authority in the mascara category, but the knowledge graph reveals some surprising gaps in how that authority is represented by LLMs. Several key entities were either inconsistently mentioned or missing altogether—including:

Of these, formulation and availability were the most significantly underrepresented.

By contrast, Estée Lauder’s responses emphasized detailed formulation benefits—things like volumizing polymers and wear time—while Fenty consistently tied its messaging to diverse skin tones, lash types, and targeted results. These aren’t just marketing angles—they act as structural cues that LLMs use to build their internal representation of the brand.

In short, brands that anchor their product narratives in specific, repeated, and semantically rich entities are far more likely to show up comprehensively in model outputs. L’Oréal has the scale and authority—but without clearer signals, key parts of its story are getting lost in generation.

Why This Happens: The Missing Pieces in L’Oréal’s LLM Presence

The results were telling. Across all three queries, most of the core entities—things like product names, application benefits, and category terms—were broadly consistent. But two important concepts showed up in both competitors’ responses and were completely absent from L’Oréal’s: formulation and price.

That’s not a random omission.

It’s a signal of how fragmented LLM knowledge really is.

Unlike search engines, LLMs aren’t pulling answers from a central index. They’re building probabilistic guesses based on whatever content they’ve encountered. For L’Oréal, that means content pulled from:

Investor pages like loreal-finance.com (which don’t talk to consumers)
Regional microsites with patchy product info
Encyclopedic sources like Wikipedia
Outdated product pages or SEO content with little contextual depth

So even though L’Oréal obviously does talk about mascara formulations and pricing across its ecosystem, that information might not be:

Consistently structured
Present in the right domains
Embedded in pages that LLMs “understand” as authoritative on mascara

That last point is key. LLMs interpret brands through the topic lens first. If your site doesn’t clearly tie the brand to the topic, here, “mascara”, in a structured and repeated way, you’re easy to skip.

This isn’t just about content volume or SEO anymore. It’s about entity clarity. If formulation and pricing aren’t surfaced in L’Oréal’s LLM presence, it’s not because they don’t exist. It’s because they weren’t expressed in ways that made them learnable.

What the LLM Should See: Filling the Topic Gaps

Using this kind of topic-level entity analysis, we generated ten concrete recommendations for how L’Oréal could improve its presence on “mascara” in LLMs:

Create a blog post on mascara formulation science, highlighting key L’Oréal ingredients
Enhance product pages with ingredient-level detail
Develop content on drugstore vs luxury positioning
Launch a mascara ingredient glossary
Address weather and humidity performance
Add clear retail availability and purchasing guide content
Improve category navigation using formulation filters
Create a product performance testing series
Develop comparison content against luxury alternatives
Fix 404 errors and broken links still being cited by LLMs

These aren’t ideas pulled from a hat. Each one reflects a topic where competitors are clearly represented and L’Oréal is not.

The Bigger Idea: Topic Ownership is the Future of Brand Visibility

This analysis isn’t just about mascara. It’s about understanding how LLMs fan out from a user query, and whether your brand is positioned to appear in that chain of reasoning. If you’re not associated with the right entities – like formulation science or retail access – you won’t be suggested, compared, or remembered.

And here’s the deeper truth: No human team can reliably spot these gaps at scale. But LLMs can. And with the right methodology, we can use their logic against them, mapping their output, identifying weaknesses, and reverse-engineering a plan to own the next query.

Want to dig deeper?

Here is the full mascara topic action report of recommendations generated for this article.

AI Search Strategy vs. SEO Strategy

L’Oréal is one of the most dominant beauty brands on earth. But when it comes to AI-generated content, dominance isn’t inherited – it’s earned, topic by topic.

The brands that understand this shift won’t just show up in LLMs. They’ll shape the conversation entirely.

The post How Anyone Can Strengthen Visibility In LLMs: A L’Oréal Case Study appeared first on iPullRank.

CMOs Are Under Pressure; Let The Right Agency Help – The CMO Series

Heather Ferris — Fri, 27 Jun 2025 11:00:00 +0000

It’s Thursday morning, 9:23am. You’ve just wrapped your board presentation.

Slack’s on mute. Your phone’s face-down. Your heart rate is finally leveling out.

But the pressure? Still lingering.

Because what looked like a simple Q2 update to the board…felt a lot bigger. It was about your strategy, your leadership, maybe even your job.

And here’s the thing – most of your external partners don’t get that. They talk in clicks and conversions, celebrate the latest KPI win, and call it a day. But they’re not in the room when you’re managing expectations, navigating politics, or defending a decision that took weeks to align.

Now imagine if they did get it. If your agency wasn’t just reporting results but actively helping you sell the story behind them. If they showed up with more than dashboards, and actually aligned with the pressures you carry every day.

The truth is, the best partners aren’t just good at marketing. They’re good at making your life easier, because they understand what success really looks like for you.

The pressure to show up not just in traditional channels, but also in emerging spaces like AI-powered search is increasing daily. In this context, the agency partners you choose can either be an anchor or a lifeline.

At iPullRank, we understand the true measure of our success is how effectively we alleviate the pressures you face every day. Thriving agency partnerships aren’t about dazzling you with more metrics; they’re about strategically supporting your internal narratives, proactively anticipating your challenges, and acting as a genuine extension of your team.

By aligning deeply with your executive-level objectives and offering clarity, foresight, and solutions before you ask, we help you turn boardroom scrutiny into confident storytelling.

Here’s how the best agencies help you breathe a little easier:

1. Build Executive-Level Reporting Assets You Can Use Internally

We know you don’t just report up, you advocate. Whether it’s to the CEO, the rest of the C-Suite, the board, or key stakeholders, you need reporting that does more than present numbers. You need narratives, context, and confidence.

The right agency designs executive-level reporting assets that go beyond the typical dashboards. You’ll want your agency to provide polished, strategic summaries tailored for internal audiences. These include:

Slide decks formatted for executive meetings
Quarterly performance recaps with emphasis on ROI and business impact
Forecasts with plain-English commentary and recommended next steps

For instance, a CMO at a global financial services firm recently trusted our team to help craft the performance story for their Q2 board meeting. We segmented organic search engine traffic by deep funnel pages that spoke directly to revenue generation, and rather than simply handing over that data, we tailored sharp, board-ready slide content, highlighted critical headline metrics, and strategically connected the dots to keep the narrative crisp, confident, and aligned.

In other words, we ensured the conversation stayed precisely where they needed it: focused, credible, and pressure-free.

2. Provide Context Around Performance, Not Just Data

Data without context creates more questions than answers. The best partner won’t just hand over performance metrics – they’ll explain what they mean, why they matter, and what actions they support.

For things like trend data for, say, a financial client, we might read earnings reports and relevant industry trade publications, as well as follow Google Trends for the client’s key topics and keywords.

This means every update delivered should include:

A breakdown of what’s moving the needle (and what’s not)
Trend analysis that anticipates market movement
Implications tailored to your KPIs and company goals

Below is a generic example:

A good agency partner translates data into decisions. When you walk into your leadership meetings, you’re guiding strategy with clarity and confidence. You’re not just citing numbers.

3. Support Internal Storytelling with Slides, Summaries, and Framing for Board Conversations

Storytelling isn’t just for customers, it’s for stakeholders. As you’re trying to align internal teams, justify budget, and frame initiatives in a way that drives consensus, your agency should be your right hand. When you’re with the best, they’ll be in these internal meetings with you, understanding the objectives and helping you tell the story.

For one of our biggest clients at iPullRank, we joined some of these meetings. Not just to report on SEO, but to be in the room where real decisions were made. It wasn’t about rankings or traffic anymore. It was about aligning with their goals, understanding the politics, and helping frame our work in a way that made sense to the C-suite.

We adjusted our language, connected our initiatives to their priorities, and focused on what really mattered to the people holding the budget. After a few weeks, we became more than just another agency; we were part of the team. And instead of just defending SEO, we helped – and continue to help – drive consensus around it.

The right partner agency will do this. From slide formatting to summary framing, you should expect:

Story arcs that communicate strategy and ROI
Executive-ready visuals and concise talking points
Positioning frameworks that show marketing as a growth engine

Another example from our work is that during a crucial product launch at a major eCommerce brand, we created a strategic deck the CMO used directly in their board update. It framed organic growth efforts in a way that showed how they underpinned demand generation and customer acquisition goals.

4. Respect and Monitor Political Dynamics and Adjust Communication Accordingly

Corporate environments are complex. Every organization has its own culture, power centers, and political dynamics. The best agencies not only pay attention to that but prioritize needs accordingly.

Picture this: you’re in the monthly senior marketing meeting. The VP of Sales tenses up the second lead volume is mentioned, and the Head of Product is going all in on a brand refresh that Sales clearly isn’t buying. You can feel the tension, and you know whatever you say next could either help smooth things over…or make it worse.

That’s exactly why transparency matters. At iPullRank, we keep a close eye on dynamics like this and stay in close, honest communication with you. If something’s getting tense internally, we talk about it. No sugarcoating, no tiptoeing. Just real conversations that help us shift our approach and keep things moving in the right direction.

Because when we’re on the same page, you’re better equipped to manage the politics, the priorities, and the pressure, with a partner who’s actually in it with you.

Communication style should adapt based on:

Who’s in the room (and who’s not)
What level of detail different stakeholders need
Where internal tensions or sensitivities might exist

When a marketing team at a Fortune 100 client was facing internal pressure over underperforming paid media, we framed our SEO performance data to show how organic was carrying the growth load. That reframing shifted the internal conversation, protected the CMO’s budget, and redirected executive focus to longer-term strategy.

5. Anticipate Friction Points and Propose Solutions Before They're Escalated

We’ve said it before and we’ll say it again: the best agency support isn’t reactive, it’s proactive. Your partner agency should be constantly scanning the horizon for potential friction points and surfacing solutions early.

This includes:

Identifying areas where results may lag and proposing pivots
Noticing shifts in market behavior that call for a strategy update
Flagging operational blockers before they impact delivery

We once helped a CMO prepare for an anticipated drop in traffic due to a Google algorithm update. Because we’d been tracking volatility and testing mitigations in advance, we were able to show up with a ready-to-go plan before questions ever hit their inbox.

Relevance Engineering Reduces the Pressure of Your Holistic Marketing Strategy

Relevance Engineering (r19g) is about more than just ranking better in search results, It’s about showing up with the right message, at the right altitude, for the right person inside your organization. It’s about internal relevance as much as external visibility.

We usually talk about Relevance Engineering as a framework for smarter marketing – connecting Information Retrieval, Digital PR, Content Strategy, AI, and UX to drive results. But it works just as well internally.

Think about it:

Information Retrieval becomes better knowledge-sharing, making sure teams can actually find and use key insights.
Digital PR is how you pitch ideas and get buy-in across departments.
Content Strategy shapes how your org documents and communicates its thinking.
AI helps teams move faster with automation and insights.
And UX? That’s the employee experience, making internal tools and comms smoother and more intuitive.

Relevance Engineering isn’t just for campaigns, it’s how great organizations align, communicate, and work better together.

A truly specialized agency doesn’t just help you win in-market. They help you win in the boardroom. That’s what makes our approach different:

We understand your success hinges on aligning internal and external narratives.
We tailor our work product to serve internal audiences as well as external ones.
We deliver insight in the formats and framing that CMOs can use instantly.

It’s Relevance Engineering, and it’s our operating system. It’s how we ensure our work delivers strategic value not only to the channels we manage, but to the teams we support.

You already carry enough. Let your agency carry the rest.

Real-World Impact: A Few Examples from the iPullRank Vault

When have we helped a client prepare for a high-stakes internal meeting?

Answer: Last quarter, for a client in consumer goods preparing for a budget renewal request, we built a case study deck mapping organic traffic gains to $4.2M in revenue.

What’s something we did to reduce stress for a CMO or marketing lead during a tough quarter?

Answer: We noticed SERP volatility impacting a core product line and jumped in with proactive simulations and revised content briefs…well before the CMO needed to escalate.

How do we tailor our updates and deliverables when we know a board presentation is coming?

Answer: We deliver condensed, visual summaries and reduce noise. We strip out jargon and highlight business implications.

In a time when everything moves faster, expectations run higher, and marketing budgets are scrutinized more than ever, the right agency is more than a vendor, they’re also a pressure valve.

Choose one that helps you breathe easier.

CMOs, your agency shouldn’t wait for you to ask the right questions - they should already have the answers.

Ready for a partner who’s already working on tomorrow? Let’s talk.

The post CMOs Are Under Pressure; Let The Right Agency Help – The CMO Series appeared first on iPullRank.

Make Sure Your Agency Knows Who They Are – The CMO Series

Heather Ferris — Fri, 20 Jun 2025 11:00:00 +0000

Chief Marketing Officers don’t need agencies that dabble. You need partners who specialize. For example, you might have tons of content but conversions aren’t hitting goals. Content calendars are packed, but performance is flat, there’s no unified strategy, and the content feels like it’s shouting into the void. Or your competitors are dominating new AI-powered search experiences, and you’re not yet on the radar. A full service agency won’t be dialing down into these specifics as well as a specialized agency..

Things are getting more complex and changing at a pretty accelerated pace lately and that’s definitely going to continue – especially in search and content strategy. The rise of AI-driven interfaces means things need to get less general and significantly more specialized.

You’re under relentless pressure to deliver results fast, with precision and confidence. Your plate is overflowing, we’re talking Thanksgiving Day serving:

Shrinking budgets.
Financial pressure to grow revenue and customers.
New lines of business. New Products. New Services. New Features.
Brand and reputation crises.

You hope the people you’ve brought on, the ones who are smarter and more specialized than you, can execute everything so you’re only burdened with the mission critical decisions that will help you jump the market leader while fending off agile grasshopper like-start ups.

You don’t have time to wait…

You don’t have time to wait for a more general agency to “figure it out” as they go. You need a strategic partner who already knows the terrain, understands the nuance (especially in the current sort of Wild West-style area of AI-driven marketing change), and brings best-in-class execution with zero hesitation.

That’s why specialization matters. Agencies that try to be everything to everyone inevitably dilute their effectiveness. The best agencies know exactly what it is they do best and double down on it, delivering exponential value because of it.

At iPullRank, specialization isn’t just a positioning strategy. It’s the engine that drives every layer of our thinking, from content creation and technical SEO to strategic consulting and Relevance Engineering (originated by our Founder and CEO, Mike King). We know exactly what we’re great at, and we’ve built deep expertise, tooling, and systems to stay great at it.

Any agency you choose to bring in should be like this; let’s talk about what this means

1. Top Agencies Stay in Their Lane

Most organizations budget across a mix of marketing channels, typically carving out funds for paid media (like PPC or social ads), brand or creative development, PR, events, and increasingly, data and analytics.

Organic Search often sits in a tricky spot: it’s critical for long-term growth, yet underprioritized in favor of faster-moving, easier-to-attribute channels. While some SEO execution lives in-house – like content production or basic site updates – many enterprises lean on agencies for high-impact support: deep technical expertise, scalable content systems, competitive analysis, and insight into rapidly evolving platforms like AI-driven search.

But here’s the truth: your SEO agency shouldn’t just “keep the lights on”; they should bring foresight, experimentation, and innovation that your internal teams don’t have time for. In today’s landscape, no one agency can, or should, own everything. The best partners are specialists who help you lead in areas where strategic depth is required, and Organic Search is absolutely one of them.

You aren’t looking for generic digital agencies – you want laser-sharp specialists with the receipts to back it up.

2. They Say No (Intentionally)

Have you ever had an agency refuse your business? That’s actually a good thing. Imagine that an agency understood your needs. You’re not a good fit. They can’t deliver what you need at this time in your maturity stage. Why go through the charge that they can? Everyone would be frustrated in the end.

The best agencies know when and how to do this. It’s not usually because they can’t figure it out, of course; it’s because they’re best at other deliverables. For example, we understand search and content at a specifically higher level, so we leave the rest to firms who specialize elsewhere.

Saying no isn’t just discipline. It’s leadership. It tells clients that we’re confident enough to focus, and humble enough to collaborate.

This approach will strengthen the relationships great agencies have with their clients – CMOs like you and your teams. You can trust your agency more when they’re protecting their lane…and yours. It signals integrity and long-term alignment.

3. They Go Deep, Not Wide

Specialization requires investment. The top agencies build their own toolsets, systems, and frameworks designed specifically for the challenges they solve best. Our ExactScience suite is a good example: a proprietary platform that allows us to analyze visibility, measure topical authority, and surface technical SEO insights tailored to enterprise sites. It helps us model out content optimizations that analyze relevance of our clients content against the search journeys that their audiences are taking, making it more likely that their brand shows up consistently throughout their searches.

Say you’re the CMO at a major mortgage lender. Interest rates are swinging, paid budgets are tight, and leadership wants results – fast. Your in-house team is stretched thin, and your current agency is giving you generic SEO reports and one-size-fits-all advice.

What you need isn’t a generalist that “does SEO,” you need a specialized partner who understands your space. One with proprietary tools built to map the full homeownership journey, spot content gaps before performance dips, and model how market shifts impact search behavior. They’re not learning on your dime, they’ve already engineered systems that work for companies like yours.

In industries like Financial Services, where trust, precision, and timing matter, specialized agencies bring foresight, technical rigor, and strategic clarity. That’s how you get ahead – and stay there.

The agency you want as a CMO won’t just simply use tools – they’ll engineer around their specialization(s). They’ll develop auditing methodologies, keyword clustering strategies, content design frameworks, and competitive analysis protocols that reflect years of focused refinement.

Every piece should be connected and every improvement should be tied to their top disciplines. This depth gives agencies like us a real edge in performance and proves value in every engagement.

For iPullRank, these specific investments we’ve made into these tools have helped us to go deeper in our niche instead of wider. That’s the kind of dedication you want as a CMO in your partner agency.

4. They Bring in the Right Partners

When you need support outside the scope of your agency – like paid acquisition, media planning, or brand storytelling – the right agency doesn’t fake it. They tap into a trusted network of experts who specialize in those areas.

Imagine you’re a CMO planning a major campaign like the Super Bowl or Black Friday. You’re coordinating months in advance across multiple teams and agency partners. Every channel, from paid media to content to SEO, must align to maximize impact.

That’s why you need specialized agencies that stay in their lane and bring in trusted partners where needed. The best SEO agencies don’t fake expertise in branding or media buying, they focus on what they do best and integrate seamlessly. In high-stakes campaigns, that kind of precision and partnership is how you unlock full-funnel performance.

At iPullRank especially, we see this as an extension of our strategy, not a limitation. Your agency’s role is to lead where they’re strongest and integrate with the best wherever else you need support. It’s a win-win-win.

5. They Align Their Point of View to Their Practice

Everything your agency publishes, whether it’s a thought leadership article, a case study, a webinar, or a content audit, should reflect the thinking behind their specialization.

Have you recently read a smart agency article that highlights a strategy that you think your team should be taking? Or has your agency put out something that you’re proud to know you’ve already got the inside track on?”

Imagine the CEO of your agency has sat in a room with your in-house team and shared all of the nuggets of their innovation custom tailored to your business. Then when they post their insights for the world, your competitors are jealous that they’re already working with you. That’s what happened when Mike King shared his insights about AI Mode. You know our clients already have strategies in place.

Our blogs don’t just share tactics; they shape the conversation around the future of SEO. Our whitepapers don’t just diagnose problems; they provide frameworks to solve them. A truly great agency is as on point with this as we are.

This alignment between POV and practice is critical. You don’t just hire an agency like us for execution – you trust us to help you navigate what’s next. And that part is especially critical right now, as so much in marketing is changing fast with AI integrations into nearly every aspect of the industry.

That trust is built on consistent, credible, specialized insight that maps directly to the challenges you face.

Why Specialization Is the Backbone of Relevance Engineering

Relevance Engineering (r19g) is a layered, dynamic approach to organic search, built on understanding how people search, how platforms deliver, and how content performs. To execute it well, you need specialists who know:

How LLMs like ChatGPT reshape search behavior
How SERP volatility reveals shifts in user demand
How to design content experiences that earn trust from both humans and machines

You can’t deliver high-context, high-performance results without deep domain expertise. When agencies try to spread too wide, they miss these nuances. Specialization ensures they don’t.

Top agencies understand they need to stay close to the signal. That means:

Tracking every shift in AI-powered search interfaces
Monitoring how competitors reposition themselves in real-time
Surfacing keyword and behavioral trends before they impact performance

Specialization lets the best agencies lead rather than react. Our specializations have helped us land clients over much larger firms specifically because we’re just that much better in these particular areas than bigger firms who don’t specialize. We are at the forefront of r19g, our founder literally coined the term, and we – and our clients – know we’re the best. That’s what you want as a CMO bringing in a top partner.

The Real-World Value of Focus

Let’s be clear: we know you aren’t just looking for a list of deliverables. You’re looking for partners who move the needle without needing to be hand-held. That means anticipating your needs, adjusting to your goals, and bringing insights before they’re even requested.

From our experience, specialization has helped us:

Deliver double-digit traffic and revenue gains for enterprise clients
Identify and fill major content gaps before competitors do
Turn down high-dollar projects to maintain trust and integrity
Build scalable, repeatable frameworks for GEO and technical SEO

Your Agency Should Know What They’re Great At

In a world full of distractions, there’s real power in staying focused. Specialization is how agencies maintain excellence, earn trust, and innovate ahead of the curve. It’s how they deliver results that generalist agencies can’t touch.

Relevance Engineering is critical at this juncture, and it’s a commitment. To strategy, to precision, and to staying sharp in the face of rapid change. That commitment only works when you know what you’re great at, and never stop getting better at it. Choose the agency that specializes, and your job as CMO gets easier.

CMOs, your agency shouldn’t wait for you to ask the right questions - they should already have the answers.

Ready for a partner who’s already working on tomorrow? Let’s talk.

The post Make Sure Your Agency Knows Who They Are – The CMO Series appeared first on iPullRank.

How to Stop the Scroll: An Introduction to Content Resonance

Fajr Muhammad — Wed, 18 Jun 2025 12:37:51 +0000

I hate to start off this way, but we have created a content problem.

There is too much content out there, and most of it isn’t very good. It’s been reported that 2.6 million YouTube videos are posted each day and 7.5 million blog posts are published every day. That’s an overwhelming amount of content.

Due to this massive flood of information and the change in search with AI, there’s no way people can pay adequate attention to everything. At this point, more content doesn’t always mean more attention for your business.

The writing is on the wall: we’re in an attention recession. Attention spans are dwindling and have declined about 70% in the past 20 years. The sheer volume of things competing for our attention has exploded and publishers, marketers and content creators have successfully trained audiences to skim and scroll.

So, what can marketers do? We can’t simply “make” more attention, we have to earn it differently now. How we do that will have to evolve as the industry and consumer habits change.

The Changing Content Landscape: 3 Shifts in Content Engagement

Users are no longer passively consuming bite-sized, empty content. They’re opting into richer, more thoughtful experiences. The rise of long-form newsletters is a telling signal, with Substack now boasting over 5 million paid subscriptions and ChatGPT and AI Mode are changing the breadth with which information is delivered. These changes reflect a shifting appetite for content that informs, entertains, or challenges perspectives in meaningful and deeper ways.

Marketers used to believe the content funnel was linear with a top, middle, and bottom. Today’s audiences don’t move neatly down a single path. They interact with brands in a multi-channel, multi-touch environment moving from search to website to social to streaming to LLMs back to website and hopefully beyond.

It’s no longer about bombarding people with content. It’s about meeting them with the right message, in the right format, on the right platform.

Here are three key shifts in content engagement happening right now:

1. Content Engagement Metrics Are Changing

Service-level metrics no longer tell the whole story. Traditional metrics like impressions and CTRs are increasingly misleading and don’t show true interest and depth of engagement.

While visits will always be necessary to move qualified prospects into the funnel, we can no longer depend on them as the primary metric of success for content efforts. What we measure tells us what matters and if we want to capture audience attention, we have to prioritize the depth of that attention and not simply the engagement itself.

Modern marketers are shifting toward behavioral and qualitative metrics:

Dwell time: How long someone stays on your content reflects actual interest.
Scroll depth: Are they consuming the entire piece or bouncing early?
Saves, shares, and replies: These indicators of resonance are more meaningful than likes.
Newsletter signups: These show long-term interest and trust.
Polls and survey responses: These reviews provide qualitative insight into how visitors are enjoying your content

These are not new metrics, but they have traditionally been deprioritized in favor of quantitative. With declining traffic across industries, prioritizing true engagement will help brands and marketers create content that meets their audiences’ needs and builds loyalty and trust.

2. Content Quality Must Be Scroll-Stopping

With attention spans at an all-time low, you need more than a hook. Stopping the scroll has always been a major factor but the sophistication of content creation is driving a new aesthetic renaissance. Content needs to be more than unique. It needs to be noteworthy.

Brands must provide powerful insights, leverage proprietary data and research to tell stories, create surprising visuals, film Oscar-worthy video, and develop stories that make your audience feel seen and heard.

It is art meets science and, while art is subjective, it begins with understanding your audience, their tastes and expectations on a deeper level.

Here’s a quick flowchart to assess your content before it goes live:

3. Post-Click Behavior Is More Valuable

In an AI world, a click is just the beginning. With now 13% of Google searches displaying an AI Overview and the full rollout of AI Mode, clicks are becoming harder and harder to get. This is making the actions a user takes post-click even more important. We can’t bank on return visits.

Post-click behavior can tell us important information about content quality:

Did they read or skim?
Did they sign up, buy, or bounce?
Did they visit another page or exit the site entirely?

Tools like heatmaps, session replays, and advanced analytics (like GA4) can help marketers understand what users do after landing on content, and that data is imperative to not only improving content engagement but driving conversions.

Speaking of conversions, how we think about conversions is also shifting. Typically, we go for the big business conversion (lead forms, application starts, etc.) but we miss small marketing conversions that can drive users into the top of the funnel. These content incentives can drive email/newsletter subscriptions to build a prospect base and email marketing still proves to be a powerful business tool with open rates up year-over-year.

While much is still TBD on how the industry will shift to accommodate generative AI results and LLMs, it’s clear that content engagement (not traffic) is moving to the front as a main KPI of content efforts.

In order to grow with our audiences, creating content that truly resonates with them is no longer a byproduct but the rule. So, what is content resonance, how do we measure it, and what can brands do today to create real and lasting content?

What Is Content Resonance?

Content resonance is the strategic architecture of content built to forge authentic, lasting connections with the audience it’s meant to serve. It’s where SEO, content, strategy, and design converge to create experiences that move people to act, share, or remember and it’s an important part of Relevance Engineering.

How to Measure Content Resonance

Resonance is not a clear-cut metric. It’s a combination of metrics that indicate user experience as well as topic authority and content relevance. While there isn’t one way to quantify resonance (yet), blended metrics including brand, search, and UX can start to directionally show us if our content is getting beneath the surface.

How to Make Your Content Resonate

Resonance is a function of connection. That’s a lofty statement but it’s true. To truly resonate with a topic, person or group, your content has to connect to their concerns, questions, and needs. It has to engage them beyond surface-level understanding, it needs to be interactive to make for two-way conversations, and it has to meet them where they are.

It’s a tall order but when done correctly, it creates lasting brand affinity, drives engagement, and creates loyalists out of passersby. Here are some frameworks and considerations for creating content that resonates with your audience:

1. Follow the R.E.A.L. Tenants

In a world driven by the artificial, real content is qualified. While LLMs can drive scale and innovation, there’s no replacement for content that adheres to human standards. R.E.AL. Content is a framework that marketers and brands can use to ensure that their efforts pass the litmus test. It’s multi-disciplinary and includes audience research, experiential and interactive design and functionality, embedded conversion and ROI, and multi-channel/platform distribution.

R.E.A.L Content is:

Resonant content that connects with the audience.
Experiential content that’s interactive and engages users.
Actionable content that provides clear value.
Leveraged content that’s repurposed and distributed strategically.

Over 225 million users engaged with Spotify Wrapped in 2023. Why? It was hyper-personal, social-ready, designed for sharing, and triggered emotion. It wasn’t just data. It was an accounting of their listening history, most played songs and artists all in a highly visual and easily distributed experience. It leveraged every pillar of R.E.A.L and is highly anticipated every year for that reason.

But resonant content isn’t only for huge brands with $10M budgets. You just need a strategy:

Solve an audience pain point
Speak their language
Build themes with empathy mapping
Survey them
Offer clear incentives
Create with atomization in mind

2. Engage Beyond the Click

We’ve said a lot about the decline in Organic Search traffic and the rise of AI. What we are going to do about it is the question we should all be asking ourselves now. Traffic is still imperative. How we get that traffic is adjusting and what we do with it is going to be key.

Content that resonates takes investment and getting visitors there is the starting point. Content now needs to be responsible for driving the visitors deeper into the experience and the top of the funnel.

Interaction and incentives turn a content experience into a built-in funnel. Here are some steps in the content conversion funnel to consider:

Click: The inflection point. They’ve landed and now we have to provide a next step
Engage: This is more than time spent, this is interaction. Provide hover and dropdown components, data visualization, input driven elements to turn visitors from passive consumer to active participants
Capture: Incentives such as more content or results help drive down funnel conversion
Nurture: Follow-up on the incentive. Offer additional incentives. Personalize to deep the connection
Convert: You’ve built the connection and can continue to drive to full conversion

Having a post-click strategy can power email campaigns, retargeting, and lead magnets and provide even more quantifiable ROI from content.

In addition to content conversions, treating content like both marketing and product can help get buy-in for resources, drive audience engagement and increase the value of your content. Consider the example of Morning Brew, where content is the marketing and the product. They grew from 100,000 to 1 million subscribers in 2 years and have industry high open rates of ~40%.

3. Design for Interaction Over Consumption

We’ve touched on this in the other elements but it can’t be understated. The days of text-based content being the dominant format are long gone. We’re living in a multi-channel/multi-format world with video and interactivity at the helm. Passive content is forgettable and if you want to drive resonance you have to invite and encourage audience participation.

Interaction triggers such as polls and quizzes encourage collaboration and a give and take relationship with your audience. You ask for their input and you provide an output. Video and audio content, while seemingly passive, is engaging and requires active listening, rewatching, and replaying.

By architecting content with interaction at the forefront, you can ensure your audience’s participation and foster a loop that your audience actively signs up for.

Steps to Take Right Now for Content Resonance

Content resonance is a step beyond engagement. It’s truly understanding your audience and developing content they want and need. Now that you understand how content resonance works, what steps can you do right now?

Understand your audience better. Review customer data, build personas, and create empathy maps to understand their pain points and needs.
Audit your current content with the new metrics and truly assess what content keeps your audience engaged and taking the next step.
Ideate new ideas, think outside the box, and tailor experiences that foster built-in interaction and participation

The future of content is no longer about just clicks, it’s about creating connections that resonate, engage and endure to build lasting community.

If you need some guidance developing your new content resonance strategy, we’re here to help. Reach out today and let’s talk about how you can create the kind of content that resonates.

Learn how you can implement a Relevance Engineering content audit at scale

Relevance Engineering at Scale: Smarter Content Pruning with Embeddings & SEO

The post How to Stop the Scroll: An Introduction to Content Resonance appeared first on iPullRank.