The SEO Skills Gap: Why Technical Expertise Alone Won’t Cut It Anymore

The SEO industry has spent the last couple of decades perfecting the art of looking productive while delivering value some might describe as questionable.

Armed with an extensive suite of analytical tools, SEO is an incredibly data-rich and metric-rich industry. It was easy to generate reports that, on the surface at least, looked impressive to a C-suite eager for more of that “data-led decision making” everyone kept talking about.

These days, the C-suite is less interested in metrics like rankings, traffic, and sessions. They’re finally asking: “So what?”

It’s the same question that killed the “likes and followers” era of social media marketing. Eventually, boards stopped caring about follower counts and started demanding conversion rates, customer acquisition costs, and a measurable return on their investment.

Now it’s SEO’s turn for a reckoning. And answering that question requires a very different skill set from how many SEOs have been trained. Too many SEOs lack that wider business awareness and marketing aptitude to understand how they fit into the bigger picture.

In short, we’re faced with an SEO skills gap which, if left unaddressed, risks SEO teams and agencies falling out of step with the expectations of senior leadership and clients.

Rankings and traffic are still important, don’t get me wrong. But they’re not business outcomes; they’re contributory factors. Yet SEOs continue to cross their fingers in the hope that growth in these metrics will magically translate into sales or some other form of measurable business value. Who measures that value and how it comes about is usually someone else’s problem.

Sales and marketing can fret over the wider strategy. If the vanity metrics continue to show growth, the SEO team sits back, content they’ve done their bit.

Except, with zero-click search on the rise as customers turn increasingly to AI tools, many organizations are seeing their search traffic trending down. That focus on volume over strategy is no longer working.

Connecting The Dots To Business Outcomes

I’ve been watching this shift play out in real time. Over the past few years, I’ve noticed clients focus less on “Can you improve our rankings,” and more on “Can you prove how this contributes to our business growth.”

But as much as I’d like to trust my gut, personal experience hardly qualifies as unequivocal evidence. Unfortunately, I lack the resources to conduct a comprehensive five-year longitudinal analysis to see how employer/client expectations might have changed. So, I conducted a quick straw poll of my network instead.

It’s a small data sample, so apply the appropriate pinch of salt. I simply wanted to get a sense of whether what I’m seeing holds true beyond my business.

It seems it does.

I asked respondents how confident they were in their SEO team’s ability to explain SEO’s contribution to business outcomes like customer acquisition cost (CAC), lifetime value (LTV), and pipeline. Scored on a scale of 1 to 10, the overall average is a smidge over 6.7. Not terrible, but not great either.

But in an environment where budgets are shrinking, a score of just “okay” when it comes to demonstrating business value is potentially fatal.

Simply saying, “Trust us, it helps,” will never survive a CFO review.

SEO’s New Critical Skills

I also asked respondents which skills they consider to be most critical when hiring future SEOs. Unsurprisingly, the top result was:

1. Technical SEO (83%)

Of course, it is. You can’t tune a car without knowing your way around an engine. So no; crawling, indexing, load times, schema … none of it is going away.

But that near-ubiquitousness also means that technical SEO is the price of admission. It’s table stakes. It’s the bare minimum requirement. Being great with technical SEO will get you in the door, but it won’t keep you in the room.

What’s more telling is how many respondents selected critical skills that most SEO teams I encounter still treat as “someone else’s job.”

2. Content strategy and creation (61%)

3. Business acumen – CAC, LTV, revenue forecasting (50%)

4. Communication and stakeholder management (39%)

While the market still needs technicians, it’s increasingly hiring commercial operators. Knowing how to do something is only useful when you can also clearly articulate why.

Meanwhile, the skills that SEOs would normally consider part of their job description languished nearer the bottom of the results.

=5. Data analytics and reporting (33%)

=5. AI/machine‑learning and automation (33%)

That’s not to say SEOs don’t need to worry about these skills. It’s just that they’re less likely to sway an employer or client’s hiring decisions. Like vanity metrics, they’re simply the means to an end. An aptitude for data analytics isn’t a replacement for business acumen, but it helps inform those strategic decisions. AI and automation are useful tools, but they’re no replacement for human-led content creation.

Today, what separates high-performing teams from the rest isn’t their aptitude with technical SEO or their skill with data, but whether they can connect execution to outcomes and defend it in the language of business.

Marketing Fundamentals Matter Now More Than Ever

As SEO evolved into its own discipline, it apparently forgot that search visibility is just one component of a much larger strategic puzzle.

Most SEO teams operate as if their job is to “optimize websites.” It’s not. Their job is to help businesses grow profitably. And you can’t do that without understanding the fundamental building blocks of marketing strategy that have been hammered into every marketing graduate for over 60 years.

The four Ps of Marketing: Product, Price, Place, and Promotion.

Product: Do You Even Know What You’re Selling?

When brothers Michael and Marc Grondahl launched Planet Fitness in 1992, their strategy struck many as completely irrational. They set out to actively repel the industry’s most valuable customers.

The reason was actually quite simple. The brothers wanted to go after the 80-85% of people who didn’t belong to a gym. They realized that a gym full of well-muscled gym junkies lifting heavy weights and posing in front of mirrors is intimidating for casual users.

This insight completely shaped the gym’s launch strategy. Remove heavy weights. Ban string tank tops. No posing mirrors. And because casual users don’t overuse the facilities, gym memberships could be more affordable.

Every decision reinforced the same positioning: This is a judgment-free zone for normal people, not a stage for bodybuilders.

Most SEO teams create content without spending sufficient time trying to understand product positioning or brand messaging. With pressure on to show results quickly, they jump straight to execution, following the usual methodologies and repeatable processes to target the most obvious industry keywords.

And here’s the problem: while you can use SEO tools or AI to generate comprehensive and prioritized keyword lists, they can’t tell you who you should be selling to or how to position the product against competitors. That requires human insight, commercial understanding, and strategic thinking.

  • What problem does this product solve?
  • Who is it for (and who is it deliberately not for)?
  • What differentiates it from the available alternatives?
  • What’s the positioning strategy: premium, value, specialist, or generalist?

Price: Understanding Value, Not Just Cost

Pricing isn’t just a number. It’s a strategic signal about quality and positioning to your target market.

For example, the Van Westendorp Price Sensitivity Meter, introduced in 1976 by Dutch economist Peter van Westendorp, helps businesses to determine the price range customers will find most acceptable. It does this by asking four questions:

  • At what price would the product be too cheap to trust?
  • At what price is it a bargain?
  • At what price is it getting expensive but still acceptable?
  • At what price is it too expensive to consider?

This methodology is particularly useful when launching a new product that doesn’t (yet) have any obvious competitors. It gauges how much value consumers place on the innovation.

A pricing strategy can fundamentally change who to target and what messaging to use. Yet SEOs don’t always consider a client’s pricing strategy when deciding on an approach.

If the product is positioned as a premium expense, it makes no sense to chase high-volume keywords likely to attract price-sensitive customers. You’re bringing in people who won’t convert because they’re looking for the cheapest option, not the best option.

Place: Digital Shelves And Strategic Positioning

Place focuses on making the product available to customers in the right location and at the right time. In retail, this science is well-established.

According to recent NielsenIQ research, shoppers typically make in-store purchasing decisions in under six seconds. Hence, best-selling items are placed at eye level while less profitable products are relegated to higher or lower shelves.

Online, this decision window widens, as 44% of shoppers take at least three minutes to find a product. But while a website doesn’t have shelves, the principles are otherwise identical. By the time someone is ready to buy, they’re far more likely to default to a brand they’re already familiar with.

In search results, you’re effectively competing for digital eye level: a top three ranking, a featured snippet, an AI overview citation.

But placement extends far beyond search rankings. Can your content be cited by AI tools? Are your conversion paths obvious? Do you appear in comparison articles? Are you positioned alongside competitors in ways that favor your value proposition?

Effective placement isn’t just about identifying the channels where the business wants to be visible. It’s also about developing an interconnected content ecosystem. Just as supermarkets place complementary products together, your content should create logical pathways that guide customers forward.

Promotion: Where SEO Forgets It’s Supposed To Persuade

While Placement is about getting your content and messaging in front of the right people, Promotion is about influencing what happens next. Promotion is the persuasion part.

Imagine someone researching project management tools, comparing Asana, Monday.com, and Basecamp. A landing page titled “Asana vs. Monday.com for agencies” isn’t just informational; it’s promotional. You’re deliberately influencing how they evaluate options and steering them toward a specific conclusion.

Imagine you’re the CMO for a fictional project management tool called …  oh, I don’t know … Taskaroo. (I’m no branding expert.) Someone researching project management tools would likely want to compare Taskaroo alongside other likely options: Asana, Monday.com, and Basecamp.

Comparison pages are popular SEO tactics because they target valuable keywords at a key part of the research journey. But a landing page titled “Asana vs. Taskaroo for agencies” has even more value as a promotional tactic. The content on that page is your opportunity to shape how potential customers evaluate their options, framed to favor your own value propositions, of course, in the hope that more people will put Taskaroo into active consideration.

That’s how promotional content should work: meeting people wherever they are in the customer journey and providing the ideal information and messaging to move them forward.

The Friction That Kills Conversion

Promotion is where I see most SEO strategies fall apart. Not because SEOs don’t create content, but because they’ve forgotten that promotion isn’t the same as visibility.

When SEOs don’t think in terms of content ecosystems, mapped to the customer journey, they create unnecessary friction at exactly the moment someone might be ready to move forward.

For example, an ecommerce site publishes an article about running shoes. It’s a handy primer for anyone who’s just getting interested in running, with brief overviews of all the different types: trail running shoes, track shoes, road running shoes. It’s well-written, ranks nicely, and targets someone at the top of the funnel.

But once the reader starts wondering whether they should get a pair of trail running shoes, there’s nowhere for them to go. No suggested further reading on trail running to develop the reader’s interest; no links to guides on what to look for in trail running shoes; no connection to product recommendations. In short, there’s no next step for someone entering the consideration phase of the journey.

Actually, if there is a link, it’s probably in the form of a CTA pointing to the product page in the hope of boosting that page’s rankings. But is it really likely that someone might miraculously jump from awareness to costly conversion in a single bound after only reading a hundred heavily optimized words?

The reader has hit friction. Any further research will mean leaving your site, searching again, and potentially landing on a competitor with a better understanding of their needs. Your SEO team may have done the hard work of attracting the right audience and exciting their interest, only to abandon them at the exact moment they’re ready to go deeper.

This is why content marketing strategy and business acumen are now considered essential SEO skills. While SEO is mostly about building rankings and attracting traffic, content marketing is about nurturing and directing that traffic towards genuine, measurable business outcomes.

And that requires a comprehensive ecosystem of interlinked content spanning the entire journey from initial awareness to conversion and beyond, addressing as many relevant questions, objections, and barriers to purchase as possible along the way.

Flipping The Script On SEO

At the heart of the SEO skills gap sits a fundamental misunderstanding:

The purpose of your content isn’t to boost your SEO. The purpose of SEO is to boost your content.

SEOs use content to rank. Marketers create content to convert. If it’s possible to tell which assets were created for SEO and which were created for Marketing, then you have a problem.

When an SEO creates content purely to rank for a keyword, they’re not thinking about what the customer ultimately hopes to achieve. They’re not thinking about the journey and what happens next. They’re not anticipating what questions might arise. They’re not proactively addressing barriers and concerns that might prevent a purchase decision.

By understanding the four Ps, SEO’s role becomes much clearer. Forget chasing volume with vanity metrics. Truly effective SEO is about building experiences tailored to the customer journey, removing friction at every touchpoint, so that the next step is always obvious and effortless.

The companies that understand this don’t just rank. They convert.

Stop hiring “SEO Specialists” and start hiring growth marketers with SEO expertise who understand how their work contributes to customer acquisition efficiency, pipeline growth, and profitability.

More Resources:


Featured Image: Na_Studio/Shutterstock

How To Set Up AI Prompt Tracking You Can Trust [Webinar] via @sejournal, @lorenbaker

Getting Real About AI Visibility Tracking

If you’re on the search or marketing team right now, you’ve probably been asked some version of: “Are we showing up in ChatGPT?” or “What’s our visibility in AI Overviews?”

And honestly? Most of us are still figuring that out.

Answer engines like ChatGPT, Perplexity, and Google AI Overviews have changed how people discover and evaluate solutions. Yet, we still see a lot of teams approaching AI visibility tracking the same way they’ve approached keyword tracking, and they’re just not the same.

Improper tracking leads to bad data that’s being used to make decisions. And bad decisions can be expensive.

That’s why we’re bringing in Nick Gallagher, Sr. SEO Strategy Director at Conductor, to walk through how to set up AI prompt tracking the right way. The goal is to walk away with a tracking framework you can actually trust.

What You’ll Learn

  • How AI prompt tracking works, and why the setup matters more than the volume of prompts you’re monitoring.
  • Best practices for choosing the right topics, prompts, and answer engines to track.
  • How to avoid common mistakes that lead to inaccurate or misleading AI visibility data.

Why This Matters Right Now

A lot of the conversations I’ve been having with SEOs and in-house marketers lately come back to the same thing: they know AI search is important, but they don’t trust the data they’re getting. Nick is going to break down why that’s happening and give you a clear framework to fix it for smarter decision-making. 

If you’re trying to measure AI visibility and want to make sure you’re not building strategy on bad data, please join us.

Can’t make it live? Register anyway, and we’ll send you the on-demand recording.

15 Smarter Interview Questions For Hiring Digital Marketers In 2026 via @sejournal, @brookeosmundson

Hiring a digital marketer is no longer about finding someone who knows a few platforms well.

Most candidates can talk through Google Ads, social media, or analytics tools at a surface level. That is table stakes now. What separates a strong hire from a risky one is how they think when performance shifts, privacy rules change, or the data does not point to an obvious answer.

Marketing leaders today need people who can connect tactics to business outcomes, explain tradeoffs clearly, and adapt without panicking when the playbook changes. That is hard to uncover with generic interview questions.

The goal of this list is simple. These questions are designed to help you understand how a candidate approaches real-world problems, not just how well they have memorized terminology.

In many cases, the “why” behind their answers matters more than the answers themselves.

Here are 15 crucial interview questions to help you hire your next digital marketing teammate.

Tactical Knowledge Questions

The first set of questions focuses on an individual’s tactical knowledge of digital marketing.

1. How Do You Use AI And Automation To Improve Your Campaigns?

AI and automation aren’t just buzzwords anymore. They’re tools shaping how marketers work.

This question uncovers whether the candidate is using these tools for better performance or simply riding the hype wave.

  • What to listen for: Candidates should provide specific examples, such as using AI for bid adjustments in PPC or helping analyze campaign data for better optimizations. Red flags include vague responses or over-reliance on automation without understanding its impact.

2. What’s Your Approach To Building And Refining Audience Segments For Targeted Campaigns?

Audience targeting has become more nuanced, and it’s a skill you can’t skip.

This question dives into their strategy for reaching the right people at the right time.

  • What to listen for: Specific techniques like combining customer relationship management (CRM) data with platform insights or testing lookalike audiences. Be wary of candidates who rely solely on pre-set audience templates without customization.

3. How Do You Decide Which Channels Deserve Budget When Resources Are Limited?

This reveals prioritization, business thinking, and restraint. It also exposes whether the candidate understands incrementality, testing, and opportunity cost.

  • What to listen for: Thoughtful discussion around goals, marginal returns, test budgets, and tradeoffs. A red flag is defaulting to “we should be everywhere” without a rationale.

4. How Do You Leverage First-Party Data To Inform Your Campaigns?

First-party data is becoming increasingly valuable as the reliance on third-party cookies still remains questionable. This question uncovers how a candidate adapts to this shift of having a privacy-first mindset.

  • What to listen for: A candidate may talk about strategies like email segmentation, loyalty programs, or even how they’ve approached capturing first-party data to ensure they’re able to properly use them in campaigns. A potential red flag is relying on outdated cookie-based methods without a backup plan.

5. Can You Share An Example Of Using Cross-Platform Advertising That Has Driven Results?

As digital marketers, we know most campaigns aren’t “one and done” on a single platform. Candidates need to show how they think holistically about digital ecosystems.

  • What to listen for: Strong examples include integrating Google Ads with Meta campaigns or leveraging TikTok for awareness and retargeting on a different platform. A red flag is a candidate focusing only on one platform without considering how they interconnect and inform each other.

6. How Do You Decide What Metrics Matter Most When Reporting Performance?

Explaining results is just as important as achieving them. This question gets into their communication skills and ability to tell a story with data.

  • What to listen for: Clear alignment between business goals and metrics, plus examples of simplifying reports. Red flags include metric dumping or platform-first reporting. Examples of preferred reporting platforms and formats are a plus.

Strategic Knowledge Questions

It’s not only important to know how to do the job, but also to know why you’re doing what you’re doing.

The next set of questions allows you to dive deeper into the candidate’s mindset and see if they can put the strategic pieces together for clients.

7. How Do You Stay On Top Of Industry Changes, And What’s Something You’ve Learned Recently That Impacted Your Work?

The digital landscape changes every single day.

If someone isn’t staying current with best practices and platform changes, it can be detrimental to client success. You need to have someone on the team who is fully aware of any changes in the industry that could impact performance.

  • What to listen for: Understanding what methods a candidate uses to stay “in the know” is important. If a candidate says they’re too busy to set aside time to read up on trends, I’d consider that a red flag.

8. Have You Had To Pivot A Campaign Due To Changing Data Privacy Regulations?

Data privacy laws have changed the name of the game, especially in PPC.

This question tests how the candidate navigates regulations while keeping campaigns effective and compliant.

  • What to listen for: Look for examples like shifting to first-party data or adjusting targeting strategies in light of GDPR or CCPA. Red flags include ignoring compliance issues or struggling to adapt when audience data becomes restricted.

9. How Do You Measure Success Across Different Types Of Campaigns?

Success isn’t one-size-fits-all. The answer should show how they align goals, metrics, and performance analysis for various strategies.

  • What to listen for: Candidates should mention setting specific KPI goals based on the channel and objective of a campaign. Be wary of those who rely on vanity metrics like impressions without tying them to business outcomes.

10. How Do You Explain Complex Answers To A Client Or Someone In A C-Suite Role?

This will inevitably happen in any digital marketing role. It’s easy when you’re working as a team, and everyone knows the ins and outs of acronyms, in the weeds content.

Sometimes, you need to explain something like you’re talking to a third grader. Less is more.

  • Green flags to listen for:
    • Candidates who know how to navigate their language based on the role of the person they’re talking to.
    • When a candidate has the knowledge of basic business questions that the role cares about.
    • They know how to explain the “why” behind performance peaks and valleys.
  • Red flags to listen for:
    • Does the candidate dance around this question?
    • Is this candidate someone who might have difficulty thinking on their feet?
    • Do they believe in sharing too much data in order to avoid questions?

Culture & Fit Questions

This last set of questions is really looking at the long-term impact of your digital marketing hire.

You’re not looking to hire temporarily; you’re hiring for the long haul.

You want to feel confident in your candidate selection based on their character, the ability to collaborate with others (teams and clients), and, of course, the empathy factor.

11. What Is Your Management Style, And How Do You Ensure Alignment Within A Team?

Leadership and collaboration are critical in marketing roles.

This question helps assess how their approach complements your team dynamics.

  • Green flags to listen for: Strong candidates will mention fostering open communication, using clear goal-setting frameworks, or adapting their style to individual team members.
  • Red flags to listen for: If you notice any micro-management tendencies, or when the candidate avoids conflict resolution.

12. How Do You Balance Working Independently With Collaborating Across Departments?

Similar to the question above, digital marketers often juggle solo tasks with cross-functional initiatives.

Everyone performs their duties well in different scenarios. In some cases, digital marketers are required to work alone, on a team, or both.

This question highlights their adaptability to working together as a team versus in a silo.

  • What to listen for: Examples of successfully managing independent projects while aligning with other team departments. Be cautious of candidates who struggle to collaborate, communicate, or prefer working in silos.

13. Can You Describe A Time You Contributed To Maintaining A Positive Team Culture?

A strong company culture is key to retention and productivity.

This question reveals how they value and influence workplace dynamics.

  • What to listen for: Specific instances where they recognized a fellow colleague, facilitated team bonding, or helped resolve conflicts. Avoid candidates who dismiss culture-building as unimportant.

14. How Do You Handle Constructive Feedback, Both Giving And Receiving It?

Feedback is essential for any type of growth. This question assesses their ability to engage in productive conversations.

  • What to listen for: Look for examples of accepting feedback gracefully, acting on it, and offering constructive criticism thoughtfully. Red flags include defensiveness or avoiding difficult conversations.

15. What Are You Looking For In This Role?

Personally, I used to cringe at this question. Now, I find myself asking this to anyone I interview.

Bringing in a new person to an organization costs a lot of time and money. Think of all the training that goes into a new hire, the staffing that’s required to help train and mentor them, etc.

  • What to listen for: If they don’t have a clear answer, that’s a potential red flag. Are they simply looking for a stepping-stone position? While there’s nothing wrong with that, it’s better to know upfront to align expectations for both parties.

At the end of the day, do their motives fit in with your company’s culture and values? If not, they likely aren’t the right candidate.

The Real Goal Of These Interview Questions

Strong digital marketers are not defined by how many platforms they have used.

They stand out because they can explain their decisions, adapt when conditions change, and connect day-to-day execution back to business outcomes. Those traits rarely show up on a resume, but they surface quickly in the right conversation.

Use these questions as a framework, not a script. Listen for clarity of thought, intellectual honesty, and comfort with uncertainty.

The best candidates will not pretend to have all the answers. They will show you how they think through the hard ones.

At the end of the day, you are not hiring someone to manage channels. You are hiring someone to help steer growth.

These questions help you figure out who is actually ready for that responsibility.

More Resources:


Featured Image: Elenyska/Shutterstock

What The Data Shows About Local Rankings In 2026 [Webinar] via @sejournal, @hethr_campbell

Reputation Signals Now Matter More Than Reviews Alone

Positive reviews are no longer the primary fast path to the top of local search results. 

As Google Local Pack and Maps continue to evolve, reputation signals are playing a much larger role in how businesses earn visibility. At the same time, AI tools are emerging as a new entry point for local discovery, changing how brands are cited, mentioned, and recommended.

Join Alexia Platenburg, Senior Product Marketing Manager at GatherUp, for a data-driven look at the local SEO signals shaping visibility today. In this session, she will break down how modern reputation signals influence rankings and what scalable, defensible reputation programs look like for local SEO agencies and multi-location brands.

You will walk away with a clear framework for using reputation as a true visibility and ranking lever, not just a step toward conversion. The session connects reviews, owner responses, and broader reputation signals to measurable outcomes across Google Local Pack, Maps, and AI-powered discovery.

What You’ll Learn

  • How review volume, velocity, ratings, and owner responses influence Local Pack and Maps rankings
  • The reputation signals AI tools use to cite or mention local businesses
  • How to protect your brand from fake reviews before they impact trust at scale

Why Attend?

This webinar offers a practical, evidence-based view of how reputation management is shaping local visibility in 2026. You will gain clear guidance on what matters now, what to prioritize, and how to build trust signals that support long-term local growth.

Register now to learn how reputation is driving local visibility, trust, and growth in 2026.

🛑 Can’t attend live? Register anyway, and we’ll send you the on-demand recording after the webinar.

90 Days. 1 Plan. Improved Local Search Visibility [Webinar] via @sejournal, @hethr_campbell

A 90 Day Plan to Prepare Every Location for AI Search

AI is changing how consumers discover and choose local brands. For multi-location businesses, visibility is no longer decided only by search rankings. 

AI agents now evaluate location data, reviews, content, engagement, and brand trust before a customer ever clicks. This shift means each individual location is judged on its own signals, not just the strength of the parent brand.

Without a clear plan, enterprise teams risk silent exclusion across entire location networks, leading to lost visibility and declining demand. The challenge is not understanding that GEO matters, but knowing how to operationalize it at scale.

In this session, Ana Martinez, Chief Technology Officer of Uberall, shares a practical 90-day framework for making every location AI-ready. She will explain how AI agents surface and exclude local brands, which location-level signals matter most, and how teams can execute GEO across hundreds or thousands of locations.

What You’ll Learn

  • A phased GEO roadmap to prepare, optimize, and scale AI readiness
  • The key location level signals AI agents trust and what to fix first
  • How to operationalize GEO across large location networks

Why Attend?

This webinar gives enterprise teams a clear, actionable plan to compete in AI-driven local discovery. You will leave with a framework that protects visibility, supports demand, and prepares every location for how discovery works today.

Register now to learn how to make every location AI-ready in the next 90 days.

🛑 Can’t attend live? Register anyway, and we’ll send you the on-demand recording after the webinar.

What 1,000 Businesses Reveal About Growth in 2026 [Webinar] via @sejournal, @hethr_campbell

Learn The Signals Shaping Marketing, Efficiency, and AI Planning

As 2026 rolls on, many teams find themselves adjusting how they approach overall business and marketing growth. 

What is the most efficient use of this year’s tighter budgets? 

Priorities are shifting across industries. Understanding how peers are responding can help teams make better strategic decisions.

Join Jeff Hirz, EVP of Business Development at OuterBox, as he shares early findings from 2025 Performance Insights From 1,000 Businesses Planning for 2026

Based on survey data from nearly 1,000 businesses, this session highlights where confidence is rising, where caution remains, and how companies are balancing growth, efficiency, and focus.

What You’ll Learn

  • How business like yours will fund marketing, sales, and efficiency initiatives 
  • What AI readiness looks like in practice for businesses like yours
  • Where business confidence is increasing, and what teams are prioritizing

Why Attend?

This webinar provides a practical benchmark for evaluating your 2026 plan against peer data. You will leave with clear context and takeaways to help refine growth, efficiency, and AI strategies for the year ahead.

Register now to see what real business data says about planning for 2026.

🛑 Can’t watch live? Register anyway, and we’ll send you the recording.

Why CFOs Are Cutting AI Budgets (And The 3 Metrics That Save Them) via @sejournal, @purnavirji

Every AI vendor pitch follows the same script: “Our tool saves your team 40% of their time on X task.”

The demo looks impressive. The return on investment (ROI) calculator backs it up, showing millions in labor cost savings. You get budget approval. You deploy.

Six months later, your CFO asks: “Where’s the 40% productivity gain in our revenue?”

You realize the saved time went to email and meetings, not strategic work that moves the business forward.

This is the AI measurement crisis playing out in enterprises right now.

According to Fortune’s December 2025 report, 61% of CEOs report increasing pressure to show returns on AI investments. Yet most organizations are measuring the wrong things.

There’s a problem with how we’ve been tracking AI’s value.

Why ‘Time Saved’ Is A Vanity Metric

Time saved sounds compelling in a business case. It’s concrete, measurable, and easy to calculate.

But time saved doesn’t equal value created.

Anthropic’s November 2025 research analyzing 100,000 real AI conversations found that AI reduces task completion time by approximately 80%. Sounds transformative, right?

What that stat doesn’t capture is the Jevons Paradox of AI.

In economics, the Jevons Paradox occurs when technological progress increases the efficiency with which a resource is used, but the rate of consumption of that resource rises rather than falls.

In the corporate world, this is the Reallocation Fallacy. Just because AI completes a task faster doesn’t mean your team is producing more value. It means they’re producing the same output in less time, but then filling that saved time with lower-value work. Think more meetings, longer email threads, and administrative drift.

Google Cloud’s 2025 ROI of AI report, surveying 3,466 business leaders, found that 74% report seeing ROI within the first year, most commonly through productivity and efficiency gains rather than outcome improvements.

But when you dig into what they’re measuring, it’s primarily efficiency gains, and not outcome improvements.

CFOs understand this intuitively. That’s why “time saved” metrics don’t convince finance teams to increase AI budgets.

What does convince them is measuring what AI enables you to do that you couldn’t do before.

The Three Types Of AI Value Nobody’s Measuring

Recent research from Anthropic, OpenAI, and Google reveals a pattern: The organizations seeing real AI ROI are measuring expansion.

Three types of value actually matter:

Type 1: Quality Lift

AI can make work faster, and it makes good work better.

A marketing team using AI for email campaigns can send emails quicker. And they also have time to A/B test multiple subject lines, personalize content by segment, and analyze results to improve the next campaign.

The metric isn’t “time saved writing emails.” The metric is “15% higher email conversion rate.”

OpenAI’s State of Enterprise AI report, based on 9,000 workers across almost 100 enterprises, found that 85% of marketing and product users report faster campaign execution. But the real value shows up in campaign performance, not campaign speed.

How to measure quality lift:

  • Conversion rate improvements (not just task completion speed).
  • Customer satisfaction scores (not just response time).
  • Error reduction rates (not just throughput).
  • Revenue per campaign (not just campaigns launched).

One B2B SaaS company I talked to deployed AI for content creation.

  • Their old metric was “blog posts published per month.”
  • Their new metric became “organic traffic from AI-assisted content vs. human-only content.”

The AI-assisted content drove 23% more organic traffic because the team had time to optimize for search intent, not just word count.

That’s quality lift.

Type 2: Scope Expansion (The Shadow IT Advantage)

This is the metric most organizations completely miss.

Anthropic’s research on how their own engineers use Claude found that 27% of AI-assisted work wouldn’t have been done otherwise.

More than a quarter of the value AI creates isn’t from doing existing work faster; it’s from doing work that was previously impossible within time and budget constraints.

What does scope expansion look like? It often looks like positive Shadow IT.

The “papercuts” phenomenon: Small bugs that never got prioritized finally get fixed. Technical debt gets addressed. Internal tools that were “someday” projects actually get built because a non-engineer could scaffold them with AI.

The capability unlock: Marketing teams doing data analysis they couldn’t do before. Sales teams creating custom materials for each prospect instead of using generic decks. Customer success teams proactively reaching out instead of waiting for problems.

Google Cloud’s data shows 70% of leaders report productivity gains, with 39% seeing ROI specifically from AI enabling work that wasn’t part of the original scope.

How to measure scope expansion:

  • Track projects completed that weren’t in the original roadmap.
  • Ratio of backlog features cleared by non-engineers.
  • Measure customer requests fulfilled that would have been declined due to resource constraints.
  • Document internal tools built that were previously “someday” projects.

One enterprise software company used this metric to justify its AI investment. It tracked:

  • 47 customer feature requests implemented that would have been declined.
  • 12 internal process improvements that had been on the backlog for over a year.
  • 8 competitive vulnerabilities addressed that were previously “known issues.”

None of that shows up in “time saved” calculations. But it showed up clearly in customer retention rates and competitive win rates.

Type 3: Capability Unlock (The Full-Stack Employee)

We used to hire for deep specialization. AI is ushering in the era of the “Generalist-Specialist.”

Anthropic’s internal research found that security teams are building data visualizations. Alignment researchers are shipping frontend code. Engineers are creating marketing materials.

AI lowers the barrier to entry for hard skills.

A marketing manager doesn’t need to know SQL to query a database anymore; she just needs to know what question to ask the AI. This goes well beyond speed or time saved to removing the dependency bottleneck.

When a marketer can run their own analysis without waiting three weeks for the Data Science team, the velocity of the entire organization accelerates. The marketing generalist is now a front-end developer, a data analyst, and a copywriter all at once.

OpenAI’s enterprise data shows 75% of users report being able to complete new tasks they previously couldn’t perform. Coding-related messages increased 36% for workers outside of technical functions.

How to measure capability unlock:

  • Skills accessed (not skills owned).
  • Cross-functional work completed without handoffs.
  • Speed to execute on ideas that would have required hiring or outsourcing.
  • Projects launched without expanding headcount.

A marketing leader at a mid-market B2B company told me her team can now handle routine reporting and standard analyses with AI support, work that previously required weeks on the analytics team’s queue.

Their campaign optimization cycle accelerated 4x, leading to 31% higher campaign performance.

The “time saved” metric would say: “AI saves two hours per analysis.”

The capability unlock metric says: “We can now run 4x more tests per quarter, and our analytics team tackles deeper strategic work.”

Building A Finance-Friendly AI ROI Framework

CFOs care about three questions:

  • Is this increasing revenue? (Not just reducing cost.)
  • Is this creating competitive advantage? (Not just matching competitors.)
  • Is this sustainable? (Not just a short-term productivity bump.)

How to build an AI measurement framework that actually answers those questions:

Step 1: Baseline Your “Before AI” State

Don’t skip this step, or else it will be impossible to prove AI impact later. Before deploying AI, document current throughput, quality metrics, and scope limitations.

Step 2: Define Leading Vs. Lagging Indicators

You need to track both efficiency and expansion, but you need to frame them correctly to Finance.

  • Leading Indicator (Efficiency): Time saved on existing tasks. This predicts potential capacity.
  • Lagging Indicator (Expansion): New work enabled and revenue impact. This proves the value was realized.

Step 3: Track AI Impact On Revenue, Not Just Cost

Connect AI metrics directly to business outcomes:

  • If AI helps customer success teams → Track retention rate changes.
  • If AI helps sales teams → Track win rate and deal velocity changes.
  • If AI helps marketing teams → Track pipeline contribution and conversion rate changes.
  • If AI helps product teams → Track feature adoption and customer satisfaction changes.

Step 4: Measure The “Frontier” Gap

OpenAI’s enterprise research revealed a widening gap between “frontier” workers and median workers. Frontier firms send 2x more messages per seat.

This means identifying the teams extracting real value versus the teams just experimenting.

Step 5: Build The Measurement Infrastructure First

PwC’s 2026 AI predictions warn that measuring iterations instead of outcomes falls short when AI handles complex workflows.

As PwC notes: “If an outcome that once took five days and two iterations now takes fifteen iterations but only two days, you’re ahead.”

The infrastructure you need before you deploy AI involves baseline metrics, clear attribution models, and executive sponsorship to act on insights.

The Measurement Paradox

The organizations best positioned to measure AI ROI are the ones who already had good measurement infrastructure.

According to Kyndryl’s 2025 Readiness Report, most firms aren’t positioned to prove AI ROI because they lack the foundational data discipline.

Sound familiar? This connects directly to the data hygiene challenge I’ve written about previously. You can’t measure AI’s impact if your data is messy, conflicting, or siloed.

The Bottom Line

The AI productivity revolution is well underway. According to Anthropic’s research, current-generation AI could increase U.S. labor productivity growth by 1.8% annually over the next decade, roughly doubling recent rates.

But capturing that value requires measuring the right things.

Forget asking: “How much time does this save?”

Instead, focus on:

  • “What quality improvements are we seeing in output?”
  • “What work is now possible that wasn’t before?”
  • “What capabilities can we access without expanding headcount?”

These are the metrics that convince CFOs to increase AI budgets. These are the metrics that reveal whether AI is actually transforming your business or just making you busy faster.

Time saved is a vanity metric. Expansion enabled is the real ROI.

Measure accordingly.

More Resources:


Featured Image: SvetaZi/Shutterstock

What Google SERPs Will Reward in 2026 [Webinar] via @sejournal, @lorenbaker

The Changes, Features & Signals Driving Organic Traffic Next Year

Google’s search results are evolving faster than most SEO strategies can adapt.

AI Overviews are expanding into new keyword and intent types, AI Mode is reshaping how results are displayed, and ongoing experimentation with SERP layouts is changing how users interact with search altogether. For SEO leaders, the challenge is no longer keeping up with updates but understanding which changes actually impact organic traffic.

Join Tom Capper, Senior Search Scientist at STAT Search Analytics, for a data-backed look at how Google SERPs are shifting in 2026 and where real organic opportunities still exist. Drawing from STAT’s extensive repository of daily SERP data, this session cuts through speculation to show which features and keywords are worth prioritizing now.

What You’ll Learn

  • Which SERP features deliver the highest click potential in 2026
  • How AI Mode features are showing up and initiatives to prioritize
  • The keyword and topic opportunities that still drive organic traffic next year

Why Attend?

This webinar offers a clear, evidence-based view of how Google SERPs are changing and what those changes mean for SEO strategy. You will gain practical insights to refine keyword targeting, focus on the right SERP features, and build an organic search approach grounded in real performance data for 2026.

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Why Your Small Business’s Google Visibility in 2026 Depends on AEO [Webinar] via @sejournal, @hethr_campbell

AI Assistants Decide Which Local Businesses Get Recommended

In 2026, local visibility on SERPs is no longer controlled by traditional search rankings alone. 

AI assistants are increasingly deciding which businesses get recommended when customers ask who to call, book, or trust nearby. 

Tools like Google Gemini, ChatGPT, and Siri are shaping these decisions in ways that leave many small businesses unseen.

AI-powered search is already influencing your shoppers’ choices without a website click ever happening. 

Your future customers are relying on answer engines to surface a single recommendation, not a list of options. 

Yet most small businesses remain invisible to AI because their Google Business Profile information is incomplete, inconsistent, or structured in ways these AI chat systems cannot confidently interpret. The result is fewer calls, missed bookings, and lost revenue.

In this upcoming webinar session, Raj Madhavni, Co-Founder, Alpha SEO Pros at Thryv, will explain how AI assistants evaluate local businesses today and which signals most influence recommendations. He will also identify the common gaps that prevent businesses from being selected and outline how to address them before 2026.

What You’ll Learn

  • How to implement AEO to improve local business visibility
  • The ranking signals AI assistants use to select local businesses
  • A practical roadmap to increase AI driven visibility, trust, and conversions in 2026

Why Attend?

This webinar gives small business owners and marketers a clear framework for competing in an AI driven local search environment. You will leave with actionable guidance to close visibility gaps, strengthen trust signals, and position your business as the one AI assistants recommend when customers ask.

Register now to prepare your business for local AI search in 2026.

🛑 Can’t attend live? Register anyway, and we’ll send you the on demand recording after the session.

The State of AEO & GEO in 2026 [Webinar] via @sejournal, @hethr_campbell

How AI Search Is Reshaping Visibility & Strategy

AI search is rapidly changing how brands are discovered and how visibility is earned. 

As AI Overviews, ChatGPT, Perplexity, and other answer engines take center stage, traditional SERP rankings are no longer the only measure of success. 

For enterprise SEO leaders, the focus has shifted to understanding where to invest, which strategies actually move the needle, and how to prepare for 2026.

Join Pat Reinhart, VP of Services and Thought Leadership at Conductor, and Lindsay Boyajian Hagan, VP of Marketing at Conductor, as they unpack key insights from The State of AEO and GEO in 2026 Report. This session provides a clear look at how enterprise teams are adapting to AI-driven discovery and where AEO and GEO strategies are headed next.

What You’ll Learn

Why Attend?

This webinar offers data-backed clarity on what is working in AI search today and what to prioritize moving forward. You will gain actionable insights to refine your strategy, focus resources effectively, and stay competitive as AI continues to reshape search in 2026.

Register now to access the latest guidance on growing AI visibility in 2026.

🛑 Can’t make it live? Register anyway, and we’ll send you the recording.