2026 SERP Visibility Stack: Key Updates For Local SEO, LLMs, Content & Performance

Performance Max (like the more upper-funnel Demand Gen) is different enough from other Google Ads campaigns that it requires a different approach, even if the underlying search behavior and marketing principles are the same as they’ve always been.

For what it’s worth, Performance Max is typically not the first campaign to launch in any account. We typically start with Search and/or Shopping before layering on Performance Max when it makes sense, e.g., testing and scaling.

But when the time comes to make it work, it takes a specific mindset. And if your Google Ads methods and principles are still stuck in 2015, you’re not going to get very far.

Here’s how to tailor your approach and become a mentality monster for Performance Max.

Performance Max At Its Most Basic Level

A strong mindset for modern PPC begins with knowledge and education. If you still don’t understand the fundamental differences between Performance Max and legacy campaign types (like Search and Shopping), that’s step one.

The TL;DR is simple: Performance Max is driven by algorithms, not inputs or controls. There’s a certain degree of surrendering to the system that goes with it, and trying to exert control when there’s none to claim will only end up with a large chunk of wasted spend.

If you think you can be the exception to the rule and force Performance Max into traditional campaign structures, all you’ll do is choke the algorithm and spend money on poor-quality conversions. This has a compounding effect where the system then believes those are valid conversions and will try to bring you more of the same.

Here are five core truths to keep in mind:

1. You don’t control targeting. Performance Max simply does not go where you tell it to. At best, you can provide initial direction in the form of audience signals. But it will eventually start to make its own decisions about which channels to show your ads on and which audiences to pursue. Even keywords are more about guidance than a guideline to be followed strictly.

2. You don’t decide which headlines get paired with which creatives. With Performance Max, you’ll still need to build all the pieces of your ads: responsive search ads, video and static creatives, product feeds with robust descriptors, and so on. But how those get mixed and matched isn’t up to you. Google’s system will test different combinations with different audiences before settling on what works best.

3. You don’t get full visibility into every query or placement. There’s no question that Performance Max is capable of delivering great results. If you want that, then you simply have to accept that you must give up a certain degree of visibility into where your ads show and why. You may not like it, but this campaign only works when you set things up properly and trust the system (while still supervising and verifying its output).

4. Data, not content, is king. Performance Max runs on data, and Google expects you to provide far more data than it will. Accounts with more conversion data will perform better because Google has more user signals to decode. With clearer first-party inputs, Performance Max is more likely to deliver the conversions you want. The clearer your audience signals are, the easier it is to quickly move out of the learning phase. And a more complete and accurate product feed will go a long way in getting your products in front of people who want them.

5. That being said, reporting is getting better but can still be frustrating. We only recently got access to things like asset group reporting, search terms reports and negative keywords for Performance Max. It’s far more visibility than we had a few years ago, but Google is still some distance off the ideal balance. I’d advise you to make peace with the fact that reporting won’t be perfect and attribution will be even murkier than usual.

Fortunately, there’s plenty that you can control. Those factors just happen to be broader marketing principles and strategic direction:

• Positioning, offer, and messaging strategy.
• Quality and depth of your product feed.
• Strength of your audience signals.
• Depth of your first-party data inputs, e.g., conversion tracking, customer lists, data feeds.
• Relevance of your ad copy, creatives, and landing pages.
• Bidding strategy and goals.
• Campaign and asset group structure at a high level.

Screenshot from X (Twitter), November 2025

Read more: Should Advertisers Rethink The ‘For Vs. Against’ Stance On Performance Max?

Traits Of PPC Managers Who Struggle With Performance Max

I see PPC managers every day who are so set in their ways that all they can do is complain about some part of Google’s machine learning. While it’s perfectly fine to stick with Search and Shopping, what’s not okay is bringing that mindset to Performance Max and expecting results anyway. And there are some behaviors that show up most frequently.

• They require granular control over everything. Wanting to dictate exactly how the system should operate is a red flag when managing Performance Max. These managers have a natural distrust of all things machine learning and want to deploy perfect Exact Match keywords, complicated manual bidding strategies, and specific traffic sculpting techniques.
• They believe their experience is a guarantee of success. But they don’t put in the effort to stay up-to-date on market and technological developments. These are typically old school marketers (like me) who haven’t kept up with the modern pace of Google Ads or feel entitled to success because of their tenure (unlike me).
• They specialize in Google Ads account management and little else. Modern PPC demands that account managers have a basic level of skill in areas like copywriting, landing page theory, conversion rate optimization, product feed management, market and audience research, and offer positioning. People who refuse to treat Google Ads as one piece of a wider marketing puzzle are learning this the hard way.
• They don’t have the diamond hands needed to trust their strategy. “Eyes on, hands off” is our approach. People who push back at the first sign of below-average output tend to make changes that reset the learning period, which only delays Google’s ability to start delivering good conversions. Since it can take three to six weeks (in my experience) to get to a good position with Performance Max, you need to know when not to make changes. Get early buy-in from clients (and the budget needed to ride it out) as you work through this early period.
• They take a “set it and forget it” approach to automation and machine learning. Part of exiting the learning period in Performance Max quickly is keeping an eye on early results and providing data inputs so the system learns what you want more/less of. Don’t just ride out the post-launch period without tracking what Google’s bringing to the plate.

• They expect the system to magically understand what the client wants. One of the toughest parts of modern PPC is persuading clients to provide access to data that Google needs in order to understand what success looks like on the business side. The flipside is that without this input, Google will simply make guesses until it finds something you like. This is especially true for lead-gen brands like plumbers and contractors.

Quick disclaimer: Some industries require a granular level of control, either due to regulatory and compliance mandates or because Google simply doesn’t have enough search and user volume to make informed decisions in that niche. Accounts operating in areas like pharmaceuticals, legal services, and similar niches need a higher level of control than mass market verticals like apparel or beverages.

The PPC Manager Who Wins With Performance Max

Algorithmic campaigns aren’t suitable for every account. Sometimes, it’s just better to stick to Search and Shopping. But when there is an opportunity to scale with Performance Max, there’s a specific type of person you want in charge of the process.

• They know where they’re more useful. Marketers who are willing to hand over control of ad operations to the system are able to focus on impactful areas where machines still struggle to create differentiated output: creative, ad copy, landing pages, and their UX, strategy, data sourcing and interpretation, etc.
• They accept that they’re only as good as their last campaign. Good PPC managers in the modern era don’t just treat Performance Max as its own campaign. They understand that just because one campaign worked a certain way doesn’t mean the next one will, too. What you want is someone who’s ready and willing to learn with every new project and iteration.

• They understand the value of data and how to source it. Marketers who focus on building an ecosystem of data inputs and learning get better results with Performance Max because they give Google more information to base its decisions on. Someone who knows where to find those and how to convince clients that they’re mission-critical is worth their weight in gold.
• They know how to stick to the plan. When you put in work only for a campaign to return poor results in the first week, it’s tempting to burn everything down and try something new. Marketers who build a plan for those first weeks and stick to it have the patience and confidence needed to eventually get Performance Max to a position of power.
• They excel at client communication. A lead-gen client that refuses to share its customer data is never going to get good results from Performance Max. Good marketers can see that and will recommend traditional Search instead of creating additional friction by pushing for CRM access. Another underrated trait is proactively setting expectations with clients and communicating with them throughout the campaign.

PPC-Adjacent Skills To Develop For Performance Max Success

With Google Ads demanding a more holistic marketing approach, so much of your success with Performance Max begins outside of the ad account. With the system taking over much of the button-pushing that we used to do, here’s where you should be upskilling in order to cement your future in PPC.

• Develop an understanding of marketing theory and the fundamentals that underpin all campaigns, not just in paid media or Google Ads.
• Understand the different automations in Google and how they function so that you can react appropriately in any situation.
• Learn how to set up online and offline conversion tracking so that you can impact business results, not just platform metrics.
• Understand how to set clear goals for campaigns and clients so that there’s minimal friction and maximum alignment while you focus on doing the work.
• Know all of Google’s different ad inventories and how people interact with them so that you can adapt your approach to any channel or network.

Why I’m Bullish: Performance Max Is The Start Of The Future

Added balance between machine learning and human control is Google telling us that we only have one choice: learn to work together on these algorithmic campaigns. Performance Max has changed significantly from when it was first released, and so has Google’s attitude.

Newer features in Performance Max, like negative keywords and improved reports, help refine campaigns and offer advertisers more of what we’ve been asking for. But this can be dangerous if you don’t make the right decisions – you might see that video ads are not performing as well and remove them, only to find that their role is to push certain conversions down the line.

As it stands, Performance Max today is perfectly viable for virtually any type of business – a far cry from its early use case being limited to big-budget ecommerce and retail (how viable it is for a specific business still depends on factors such as budget, expertise, risk tolerance, and data availability).

So, while you may not necessarily need it today or every day, you should be adapting to this new direction if your top priority is to protect your business, career, and clients.

More Resources:

• • Performance Max: I Was A Skeptic & Now I’m Devout (Even In Bing)
  • The State Of Performance Max: How To Optimize Google Ads In 2025
  • Google Performance Max: Everything You Need To Know

Featured Image: Master1305/Shutterstock

For this week’s Ask An SEO, the question asked was:

“Do I need to rethink my content strategy for LLMs and how do I get started with that?”

To answer, I’m going to explain the non-linear journey down the customer journey funnel and where large language models (LLMs) show up.

From rethinking traffic expectations to conducting an audit on sentiment picked up by LLMs, I will talk about why brand identity matters in building the kind of reputation that both users and machines recognize as authoritative.

You can watch this week’s Ask An SEO video and read the full transcript below.

Editor’s note: The following transcript has been edited for clarity, brevity, and adherence to our editorial guidelines.

Don’t Rush Into Overhauling Your Strategy

Off the bat, I strongly advise not to rush into this. I know there’s an extreme amount of noise and buzz and advice out there on social media that you need to rethink your strategy because of LLMs, but this thing is very, very far from settled.

For example, or most notably, AI Mode is still not in traditional search results. When that happens, when Google moves the AI Mode tab from being a tab into the main search results, the whole ecosystem is set for another upheaval, whatever that looks like, because we don’t actually know what that will look like.

I personally think that Google’s Gemini demo (the one they did way, way back, where they showed customized results for certain types of queries with certain answer formats) might be what AI Mode ends up resembling more than what it does right now, which is purely a text-based output that sort of aligns with ChatGPT.

I think Google will differentiate those two products once it moves AI Mode over from the tab into the main search results. So, things are not settled yet. And if you think they’re not. They are not settled yet.

Rethinking Traffic Expectations From LLMs

The other thing I want you to rethink is the traffic expectations from LLMs.

There’s been a lot of talk about citations and traffic – citations and traffic, citations and traffic. I don’t think citations, and therefore traffic, are the main diamond within the LLM ecosystem. I believe mentions are. And I don’t think that’s anything really new, by the way.

Traditionally, the funnel has been messy, and Google’s been talking about that for a long time. Now, you have an LLM that may be a starting point or a step in that messy funnel, but I don’t believe it’s fundamentally different.

I’ll give you an example. If I’m looking for a pair of shoes, I might go to Google and search, [Are these Nike shoes any good?]. I might look at a website, then go to Amazon and look at the actual product.

Then I might go to YouTube, see a review of the product, maybe watch a different one, go back to Amazon, have a look, check Google Shopping to see if it’s cheaper there, and then head back to Amazon to buy it.

Now, you have an LLM thrown into the mix, and that’s really the main difference. Maybe now, the LLM gives me the answer. Or maybe Google gives me the answer. Then I go to Amazon, look at the product, go to Google Shopping to see if it’s cheaper, watch a YouTube review, maybe switch things up a bit, go back to ChatGPT, see if it recommends something different this time, go through the whole process, and eventually buy on Amazon. That’s just me, personally.

It’s important to realize that the paradigm has been around for a while. But if you’re thinking of LLMs as a source of traffic, I highly recommend you don’t. They are not necessarily built for that.

ChatGPT, specifically, is not built for citations or to offer traffic. It’s built to provide answers and to be interactive. You’ll notice you usually don’t get a citation in ChatGPT until the third, fourth, or fifth prompt, whatever it is.

Other LLMs, like AI Mode or Perplexity, are a little bit more citation or link-based, but still, their main commodity is the output, giving you the answer and the ability to explore further.

So, I’m a big believer that the brand mention is far more important than the actual citation, per se. Also, the citation might just be the source of information. If I’m asking, “Are Nike shoes good?” I might get a review from a third-party website, say, the CNET of shoes, and even if I click there, that’s not where I’m going to buy the actual shoe.

So, the traffic in that case isn’t even the desirable outcome for the brand. You want users to end up where they can buy the shoe, not just read a review of it.

The Importance Of Synergy And Context With Content

The next thing is the importance of synergy and context with your content. In order to be successful with LLMs, it’s not about (and I’ve heard this before from people) that the top citations are just the ones that already do well on Google. Not necessarily.

There might be a correlation, but not causation. LLMs are trying to do something different than search engines. They’re trying to synthesize the web to serve as a proxy for the entire web. So, what happens with your content across the web matters way more: How your content is talked about, where it’s talked about, who’s talking about it, and how often it’s mentioned.

That doesn’t mean what’s on your site doesn’t factor in, but it’s weighted differently than with traditional search engines. You need to give the LLM the brand context to realize that you have a digital presence in this area, that you’re someone worth mentioning or citing.

Again, I’d focus more on mentions. That’s not to say citations aren’t important (they are), but mentions tend to carry more weight in this context.

Conducting An Audit

The way to go about this, in my opinion, is to conduct an audit. You need to see how the LLM is talking about the topic.

LLMs are notoriously positive and tend to loop in tiny bits of negative sentiment within otherwise positive answers. I was looking at a recent dataset. I don’t have the formal numbers, but I can tell you they’re built to lean neutral or net positive.

For example, if I ask, “Are the Dodgers good?” LLMs, in this case, I was looking at AI Mode, which will say, “Yes, the Dodgers are good…” and go on about that. If I ask, “Are the Yankees good?” and let’s say two or three weeks ago they weren’t doing well, it won’t say, “Yes, the Yankees are good.” It’ll say, “Well, if you look at this and you look at that, overall you might say the Yankees are good.”

Those are two very different answers. They’re both trying to be positive, but you have to read between the lines to understand how the LLM is actually perceiving the brand and what possible user hesitancies or skepticism are bound up in that. Or where are the gaps?

For instance, if I ask, “Is Gatorade a great drink?” and it answers one way, and then I ask, “Is Powerade a good drink?” and it answers slightly differently, you have to notice why that’s happening. Why does it say, “Gatorade is great,” but “Powerade is loved by many”? You have to dig in and understand the difference.

Running an audit helps you see how the LLM is treating your brand and your market. Is it consistently bringing up the same user points of skepticism or hesitation? If I ask, “What’s a good alternative to Folgers coffee?” AI Mode might say, “If you’re looking for a low-cost coffee, Folgers is an option. But if you want something that tastes better at a similar price, consider Brand X.”

That tells you something: There’s a negative sentiment around Folgers and its taste. That’s something you should be picking up on for your content and brand strategy. The only way to know that is to conduct an audit, read between the lines, and understand what the LLM is saying.

Shaping What LLMs Say About Your Brand

The way to get LLMs to say what you want about your brand is to start with a conscious point of view: What do you want LLMs to say about your brand? Which really comes down to: what do you want people to say about your brand?

And the only way to do that is to have a very strong, focused, and conscious brand identity. Who are you? What are you trying to do? Why is that meaningful? Who are you doing it for? And who is interested in you because of it?

Your brand identity is what gives your brand focus. It gives your content marketing focus, your SEO strategy focus, your audience targeting focus, and your everything focus.

If this is who you are, and that is not who you are, then you’re not going to write content that’s misaligned with who you are and what you’re trying to do. You’re not going to dilute your brand identity by creating content that’s tangential or inconsistent.

If you want third-party sites and people around the web to pick up who you are and what you’re about, to build that presence, you need a very conscious and meaningful understanding of who you are and what you do.

That way, you know where to focus, where not to, what content to create, what not to, and how to reinforce the idea around the web that you are X and relevant for X.

It sounds simple, but developing all of that, making sure it’s aligned, and auditing all the way through to ensure it’s actually happening … that’s easier said than done.

Final Thoughts

LLMs may shift how your customers find information about your brands, but chasing citations and clicks isn’t a solid strategy.

Despite the chaos in AI and search in the age of LLMs, marketers need to stick to the fundamentals: brand identity, trust, and relevance still matter.

Focus on brand identity to build your reputation, ensuring that both users and search engines recognize your brand as an authority in your niche.

More Resources:

• AI As Your Marketing Co-Pilot: How To Effectively Leverage LLMs In SEO & Content
• Building Trust In The AI Era: Content Marketing Ethics And Transparency
• State Of SEO 2026

Featured Image: Paulo Bobita/Search Engine Journal

A major category, focus, or pillar (as I have defined it for decades) of SEO is content. Influencing a range of on-page factors, but more so to develop authentic context and authority status over the years, content has been an engine of so much SEO and is a focal point in the shift from keyword-focused to visibility in the era of LLMs, AI search results, and organic search results in integrated thinking.

With a focus on content needs of today, combined with those from the past few years, a popular way to understand content’s effectiveness is to conduct SEO content audits. As we look at content auditing in a more versatile way for broader visibility, I believe it is important to address the fact that audits often fall into one of two extremes:

• Too shallow to be useful – using an automated tool and lacking data and a point of view.
• Too deep and detailed to be usable – so much data, so much crawling, and so many topics that it’s difficult for search engines and LLMs to understand the actual focus.

With AI and LLMs changing how content is discovered and interacted with, we can’t afford to rest on the content we have created in the past and to assume past performance will provide future positive results. I believe a better model is a performance and purpose-driven audit that prioritizes actions based on business impact and newer visibility models.

SEO content audits, which evolve to stay relevant in today’s search and AI environment, need to account for the fact that search behavior is shifting. I’m not going to unpack the stats or talk about search market share in this article, but trust that you’re seeing the impact in your stats and dashboards. As we shift with the market, we do have to think more about answers and authority signals.

Even if we have a finely tuned content machine that has every possible AI-driven efficiency built into it, we can’t afford wasted efforts and content bloat. Flooding search engines and LLMs with bloat, whether human-generated or AI-generated (or some combo), is wasted if it isn’t working for us. This is especially true for B2B and lead-generation-focused companies that have longer customer journeys and sales cycles.

Marketing and corporate executives expect performance and find out too late that outdated or ineffective content didn’t translate from keyword rankings to AI visibility. Leveraging a content audit that balances having enough depth, but being actionable and focused on business value, is as important as ever.

How To Conduct A Performance-Driven, LLM-Aware Content Audit

I’m advocating a modern and repeatable framework that replaces traditional SEO content audits with one that is more useful and aligned to how things work today.

1. Define Purpose

We have to start off by getting on the same page with what spurred us to do an audit and what our ultimate goal for the effort is. Whether we’re trying to clean up legacy content overall, to shift focus to LLM visibility that we want to improve, seeking to get more conversions out of existing content, or other noble goals.

It is important to understand what “good” looks like. Whether it is visibility, traffic, authority, engagement, or some other measurable outcome.

2. Segment By Type And Funnel Stage

A challenge of content reviews and analysis is how specific content is prioritized. We want to avoid a one-size-fits-all approach.

That means we need to break down the categories of content for the audit by type. That can include blog posts vs. core landing pages vs. gated assets. However you look and classify the types of content on your site and that your team creates, you’ll want to use this as a filter.

Additionally, you want to look at your content in the same way that you consider your funnel. Whether it is top, middle, and bottom-of-funnel content, or if you look in a different way at customer journeys and classifications, use this as a second important filter and prioritize what you want to analyze and why (going back to the defined purpose of the content audit).

3. Score Content 3P’s (Purpose, Performance, Potential)

This is where our audits and processes start to take a more custom approach based on the steps we’ve completed so far. You’ll need your own custom scoring system. It could be as simple as a 1-3 scale for the categories of Purpose, Performance, and Potential.

Purpose:

• What is this content meant to do?
• Is it aligned with:
  • Brand?
  • Positioning?
  • Goals?

Performance:

• How does it drive:
  • Traffic?
  • Conversions?
  • Citations?
  • Engagement?
• Does it actually:
  • Bring people in?
  • Move them forward?

Potential:

• Could it rank or be rendered in answers in AI with updates?
• Could it be:
  • Repurposed?
  • Repositioned?

As third-party tools continue to add to their data sets and measurement capabilities, you could do your own checks, combining Google Analytics 4, Google Search Console, and ChatGPT to see what content feels useful for LLMs.

4. Determine What Stays

At this juncture, it is time to add a business-focused or aligned lens. Considering content for things like it helps us get found for the right reasons, if it would resonate with our primary audience, and if it would be prominently perceived as expert and authoritative by further stakeholders (current client, journalist, industry colleagues).

For each piece of content that is reviewed within the audit and analysis, arrive at a final decision:

• Remove: With no performance, future, or purpose, this content can be removed.
• Combine: This category is typically for topics that are competing or have cannibalization.
• Update: Whether it is a topic that isn’t optimized, is misaligned in the current iteration, or needs some other type of identified improvement. LLMs prefer sources that are timely, so refreshing content on a regular basis to stay as up-to-date as possible can help improve the longevity of a piece being sourced by AI.
• Keep: This category is for content that needs no change and that you’ll keep as-is currently.

5. Optimize For Search & LLM Visibility

For the content you have determined that stays or gets updated, you’ll want to consider both search and LLMs and what they reward for your content and brand to be found.

For search engines, starting with intent can often help to not get bogged down in old-school thinking about keywords and help with thinking of topics and the opportunity that exists for visibility in organic search results.

For AI, while this article isn’t a primer for what matters for being found in LLMs, there are things like content structure, clear and authoritative answers, brand signals, and external validation (PR, etc.) that are important here, too, in the edits and updates that you make.

6. Create Prioritized Action Plan

While it might feel like, at this point, the heavy lifting is done and that you’ve got a solid spreadsheet, list, or way that you’ve organized the work so far, this is where the follow-through and implementation can get derailed quickly.

You need to work at this juncture to score or plan out what is required for implementation based on effort vs. impact. Additionally, you need to layer in your team’s capacity, skill sets, and cost (or opportunity cost) of resources. Lastly, you need to organize the effort into sprints or milestones to do over time so it doesn’t become a never-ending project or one that is too big to accomplish.

7. Track Business (Not Search) Metrics

As the content audit work wraps up and turns to implementation of the action plan, you need to make sure you’re set up to look beyond rankings and traffic.

Deeper business-aligned metrics include conversions, form submissions, and demo requests as the bridge from online to sales processes. Quality metrics and key performance indicators (KPIs) still apply as you weave in conversion rate optimization (CRO) efforts and mapping to expected aspects of the customer journey or funnel.

And, as you evolve from SEO metrics to visibility, third-party tools or your own qualification and quantification efforts in customizing GA4 or other data capture and analysis work will be important in understanding the impact of your content auditing and update efforts.

Final Thoughts

Content audits aren’t dead. However, the way we’ve done them in the past likely does need to change. There’s no such thing as a perfect process, tool, or spreadsheet, but we can leverage solid practices that integrate our own goals, potential, and value to our target audiences.

SEO this year and beyond is about visibility, usefulness, and what we can impact across search engines and LLMs.

Remembering that the right audit balances depth with being actionable, the steps I outlined and your team’s dedication and focus can help you see it through to measurable success.

More Resources:

• Create Your Own ChatGPT Agent For On-Page SEO Audits
• Agentic AI In SEO: AI Agents & Workflows For Audit (Part 2)
• Perfectly Optimized Content From Start To Finish

Featured Image: Roman Samborskyi/Shutterstock

TopRank Marketing and Ascend2 released a survey involving 797 B2B leaders. They discovered that 97% consider thought leadership as essential for achieving success throughout the entire marketing funnel.

The report frames the findings as building an “Answer Engine” for how buyers discover information across SEO and GenAI answer platforms (ChatGPT, Perplexity, AI search).

The authors analyzed differences between high-ROI and lower-performing marketers. Here’s what stands out.

What The Research Says

Respondents report strong results from original, data-driven content. 93% percent of teams that use original research say it effectively drives engagement and leads, and 48% call it “very effective.”

When asked to compare formats, 35% rated original research significantly more valuable than AI-generated content for building trust, and another 32% said it’s more impactful overall.

The study positions trusted experts and partners as part of a broader “trust system” that validates research-based content. The takeaway is quality over quantity. Partnerships work best when they add credibility and insight, not just reach.

Formats & Distribution

Marketers point to video, live or virtual events, and interactive experiences as the most effective vehicles for thought leadership.

Topic selection is guided primarily by customer signals. Direct customer feedback leads at 53%, followed by CRM/customer data and market-trend analysis at 44% each. Seasonal moments and industry events also influence planning.

High-performing teams run integrated multi-channel programs that weave SEO, advertising, experts and partners, media, email, and social into a cohesive plan.

Barriers To Success

One persistent barrier is channel concentration. About one-third cite over-reliance on a few channels or tactics as a top reason programs underperform.

Measurement is a key friction point: 41% cite difficulty proving ROI as a cause of underperforming content. High-performing programs use full-funnel analytics linking brand metrics to demand and revenue.

Why This Matters

The survey data questions two common strategies: relying on AI-generated content to foster trust and viewing SEO solely as a top-of-funnel tactic. Original research tends to be more trusted, which aligns with longer B2B sales cycles.

Additionally, successful programs link SEO to multi-channel activation and pipeline development. If your analytics don’t connect search performance with closed-won deals, that disconnect likely accounts for inconsistent ROI.

Looking Ahead

For 2026, center your plan on original research and treat search and GenAI answer platforms as connected discovery surfaces. Pair the research with credible experts, then extend it through video, events, and interactive pieces where it fits.

Featured Image: Roman Samborskyi/Shutterstock