Sep 3 2025
The Behavioral Data You Need To Improve Your Users’ Search Journey via @sejournal, @SequinsNsearch

We’re more than halfway through 2025, and SEO has already changed names many times to take into account the new mission of optimizing for the rise of large language models (LLMs): We’ve seen GEO (Generative Engine Optimization) floating around, AEO (Answer Engine Optimization), and even LEO (LLM Engine Optimization) has made an apparition in industry conversations and job titles.

However, while we are all busy finding new nomenclatures to factor in the machine part of the discovery journey, there is someone else in the equation that we risk forgetting about: the end beneficiary of our efforts, the user.

Why Do You Need Behavioral Data In Search?

Behavioral data is vital to understand what leads a user to a search journey, where they carry it out, and what potential points of friction might be blocking a conversion action, so that we can better cater to their needs.

And if we learned anything from the documents leaked from the Google trial, it is that users’ signals might actually be one of the many factors that influence rankings, something that was never fully confirmed by the company’s spokespeople, but that’s also been uncovered by Mark Wiliams Cook in his analysis of Google exploits and patents.

With search becoming more and more personalized, and data about users becoming less transparent now that simple search queries are expanding into full funnel conversations on LLMs, it’s important to remember that – while individual needs and experiences might be harder to isolate and cater for – general patterns of behavior tend to stick across the same population, and we can use some rules of thumb to get the basics right.

Humans often operate on a few basic principles aimed at preserving energy and resources, even in search:

  • Minimizing effort: following the path of least resistance.
  • Minimizing harm: avoiding threats.
  • Maximizing gain: seeking opportunities that present the highest benefit or rewards.

So while Google and other search channels might change the way we think about our daily job, the secret weapon we can use to future-proof our brands’ organic presence is to isolate some data about behavior, as it is, generally, much more predictable than algorithm changes.

What Behavioral Data Do You Need To Improve Search Journeys?

I would narrow it down to data that cover three main areas: discovery channel indicators, built-in mental shortcuts, and underlying users’ needs.

1. Discovery Channel Indicators

The days of starting a search on Google are long gone.

According to the Messy Middle research by Google, the exponential increase in information and new channels available has determined a shift from linear search behaviors to a loop of exploration and evaluation guiding our purchase decisions.

And since users now have an overwhelming amount of channels, they can consult in order to research a product or a brand. It’s also harder to cut through the noise, so by knowing more about them, we can make sure our strategy is laser-focused across content and format alike.

Discovery channel indicators give us information about:

  • How users are finding us beyond traditional search channels.
  • The demographic that we reach on some particular channels.
  • What drives their search, and what they are mostly engaging with.
  • The content and format that are best suited to capture and retain their attention in each one.

For example, we know that TikTok tends to be consulted for inspiration and to validate experiences through user-generated content (UGC), and that Gen Z and Millennials on social apps are increasingly skeptical of traditional ads (with skipping rates of 99%, according to a report by Bulbshare). What they favor instead is authentic voices, so they will seek out first-hand experiences on online communities like Reddit.

Knowing the different channels that users reach us through can inform organic and paid search strategy, while also giving us some data on audience demographics, helping us capture users that would otherwise be elusive.

So, make sure your channel data is mapped to reflect these new discovery channels at hand, especially if you are relying on custom analytics. Not only will this ensure that you are rightfully attributed what you are owed for organic, but it will also be an indication of untapped potential you can lean into, as searches become less and less trackable.

This data should be easily available to you via the referral and source fields in your analytics platform of choice, and you can also integrate a “How did you hear about us” survey for users who complete a transaction.

And don’t forget about language models: With the recent rise in queries that start a search and complete an action directly on LLMs, it’s even harder to track all search journeys. This replaces our mission to be relevant for one specific query at a time, to be visible for every intent we can cover.

This is even more important when we realize that everything contributes to the transactional power of a query, irrespective of how the search intent is traditionally labelled, since someone might decide to evaluate our offers and then drop out due to the lack of sufficient information about the brand.

2. Built-In Mental Shortcuts

The human brain is an incredible organ that allows us to perform several tasks efficiently every day, but its cognitive resources are not infinite.

This means that when we are carrying out a search, probably one of many of the day, while we are also engaged in other tasks, we can’t allocate all of our energy into finding the most perfect result among the infinite possibilities available. That’s why our attentional and decisional processes are often modulated by built-in mental shortcuts like cognitive biases and heuristics.

These terms are sometimes used interchangeably to refer to imperfect, yet efficient decisions, but there is a difference between the two.

Cognitive Biases

Cognitive biases are systematic, mostly unconscious errors in thinking that affect the way we perceive the world around us and form judgments. They can distort the objective reality of an experience, and the way we are persuaded into an action.

One common example of this is the serial position effect, which is made up of two biases: When we see an array of items in a list, we tend to remember best the ones we see first (primacy bias) and last (recency bias). And since cognitive load is a real threat to attention, especially now that we live in the age of 24/7 stimuli, primacy and recency biases are the reason why it’s recommended to lead with the core message, product, or item if there are a lot of options or content on the page.

Primacy and recency not only affect recall in a list, but also determine the elements that we use as a reference to compare all of the alternative options against. This is another effect called anchoring bias, and it is leveraged in UX design to assign a baseline value to the first item we see, so that anything we compare against it can either be perceived as a better or worse deal, depending on the goal of the merchant.

Among many others, some of the most common biases are:

  • Distance and size effects: As numbers increase in magnitude, it becomes harder for humans to make accurate judgments, reason why some tactics recommend using bigger digits in savings rather than fractions of the same value.
  • Negativity bias: We tend to remember and assign more emotional value to negative experiences rather than positive ones, which is why removing friction at any stage is so important to prevent abandonment.
  • Confirmation bias: We tend to seek out and prefer information that confirms our existing beliefs, and this is not only how LLMs operate to provide answers to a query, but it can be a window into the information gaps we might need to cover.

Heuristics

Heuristics, on the other hand, are rules of thumb that we employ as shortcuts at any stage of decision-making, and help us reach a good outcome without going through the hassle of analyzing every potential ramification of a choice.

A known heuristic is the familiarity heuristic, which is when we choose a brand or a product that we already know, because it cuts down on every other intermediate evaluation we would otherwise have to make with an unknown alternative.

Loss aversion is another common heuristic, showing that on average we are more likely to choose the least risky option among two with similar returns, even if this means we might miss out on a discount or a short-term benefit. An example of loss aversion is when we choose to protect our travels for an added fee, or prefer products that we can return.

There are more than 150 biases and heuristics, so this is not an exhaustive list – but in general, getting familiar with which ones are most common among our users helps us smooth out the journey for them.

Isolating Biases And Heuristics In Search

Below, you can see how some queries can already reveal subtle biases that might be driving the search task.

Bias/Heuristic Sample Queries
Confirmation Bias • Is [brand/products] the best for this [use case]?
• Is this [brand/product/service] better than [alternative brand/product service]?
• Why is [this service] more efficient than [alternative service]?
Familiarity Heuristic • Is [brand] based in [country]?
• [Brand]’s HQs
• Where do I find [product] in [country]?
Loss Aversion • Is [brand] legit?
• [brand] returns
• Free [service]
Social Proof • Most popular [product/brand]
• Best [product/brand]

You can use Regex to isolate some of these patterns and modifiers directly in Google Search Console, or you can explore other query tools like AlsoAsked.

If you’re working with large datasets, I recommend using a custom LLM or creating your own model for classifications and clustering based on these rules, so it becomes easier to spot a trend in the queries and figure out priorities.

These observations will also give you a window into the next big area.

3. Underlying Users’ Needs

While biases and heuristics can manifest a temporary need in a specific task, one of the most beneficial aspects that behavioral data can give us is the need that drives the starting query and guides all of the subsequent actions.

Underlying needs don’t only become apparent from clusters of queries, but from the channels used in the discovery and evaluation loop, too.

For example, if we see high prominence of loss aversion based on our queries, paired with low conversion rates and high traffic on UGC videos for our product or brand, we can infer that:

  • Users need reassurance on their investment.
  • There is not enough information to cover this need on our website alone.

Trust is a big decision-mover, and one of the most underrated needs that brands often fail to fulfill as they take their legitimacy for granted.

However, sometimes we need to take a step back and put ourselves in the users’ shoes in order to see everything with fresh eyes from their perspective.

By mapping biases and heuristics to specific users’ needs, we can plan for cross-functional initiatives that span beyond pure SEO and are beneficial for the entire journey from search to conversion and retention.

How Do You Obtain Behavioral Data For Actionable Insights?

In SEO, we are used to dealing with a lot of quantitative data to figure out what’s happening on our channel. However, there is much more we can uncover via qualitative measures that can help us identify the reason something might be happening.

Quantitative data is anything that can be expressed in numbers: This can be time on page, sessions, abandonment rate, average order value, and so on.

Tools that can help us extract quantitative behavioral data are:

  • Google Search Console & Google Merchant Center: Great for high-level data like click-through rates (CTRs), which can flag mismatches between the user intent and the page or campaign served, as well as cannibalization instances and incorrect or missing localization.
  • Google Analytics, or any custom analytics platform your brand relies on: These give us information on engagement metrics, and can pinpoint issues in the natural flow of the journey, as well as point of abandonment. My suggestion is to set up custom events tailored to your specific goals, in addition to the default engagement metrics, like sign-up form clicks or add to cart.
  • Heatmaps and eye-tracking data: Both of these can give us valuable insights into visual hierarchy and attention patterns on the website. Heatmapping tools like  Microsoft Clarity can show us clicks, mouse scrolls, and position data, uncovering not only areas that might not be getting enough attention, but also elements that don’t actually work. Eye-tracking data (fixation duration and count, saccades, and scan-paths) integrate that information by showing what elements are capturing visual attention, as well as which ones are often not being seen at all.

Qualitative data, on the other hand, cannot be expressed in numbers as it usually relies on observations. Examples include interviews, heuristic assessments, and live session recordings. This type of research is generally more open to interpretation than its quantitative counterpart, but it’s vital to make sure we have the full picture of the user journey.

Qualitative data for search can be extracted from:

  • Surveys and CX logs: These can uncover common frustrations and points of friction for returning users and customers, which can guide better messaging and new page opportunities.
  • Scrapes of Reddit, Trustpilot, and online communities conversations: These give us a similar output as surveys, but expand the analysis of blockers to conversion to users that we haven’t acquired yet.
  • Live user testing: The least scalable but sometimes most rewarding option, as it can cut down all the inference on quantitative data, especially when they are combined (for example, live sessions can be combined with eye-tracking and narrated by the user at a later stage via Retrospective Think-Aloud or RTA).

Behavioral Data In The AI Era

In the past year, our industry has been really good at two things: sensationalizing AI as the enemy that will replace us, and highlighting its big failures on the other end. And while it’s undeniable that there are still massive limitations, having access to AI presents unprecedented benefits as well:

  • We can use AI to easily tie up big behavioral datasets and uncover actionables that make the difference.
  • Even when we don’t have much data, we can train our own synthetic dataset based on a sample of ours or a public one, to spot existing patterns and promptly respond to users’ needs.
  • We can generate predictions that can be used proactively for new initiatives to keep us ahead of the curve.

How Do You Leverage Behavioral Data To Improve Search Journeys?

Start by creating a series of dynamic dashboards with the measures you can obtain for each one of the three areas we talked about (discovery channel indicators, built-in mental shortcuts, and underlying users’ needs). These will allow you to promptly spot behavioral trends and collect actions that can make the journey smoother for the user at every step, since search now spans beyond the clicks on site.

Once you get new insights for each area, prioritize your actions based on expected business impact and effort to implement.

And bear in mind that behavioral insights are often transferable to more than one section of the website or the business, which can maximize returns across several channels.

Lastly, set up regular conversations with your product and UX teams. Even if your job title keeps you in search, business success is often channel-agnostic. This means that we shouldn’t only treat the symptom (e.g., low traffic to a page), but curate the entire journey, and that’s why we don’t want to work in silos on our little search island.

Your users will thank you. The algorithm will likely follow.

More Resources:

Featured Image: Roman Samborskyi/Shutterstock

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Sep 3 2025
Make AI Writing Work for Your Content & SERP Visibility Strategy [Webinar] via @sejournal, @hethr_campbell

Are your AI writing tools helping or hurting your SEO performance?

Join Nadege Chaffaut and Crystie Bowe from Conductor on September 17, 2025, for a practical webinar on creating AI-informed content that ranks and builds trust.

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Aug 29 2025
Why WooCommerce Slows Down (& How to Fix It With the Right Server Stack)

This post was sponsored by Cloudways. The opinions expressed in this article are the sponsor’s own.

Wondering why your rankings may be declining?

Just discovered your WooCommerce site has slow load times?

A slow WooCommerce site doesn’t just cost you conversions. It affects search visibility, backend performance, and customer trust.

Whether you’re a developer running your own stack or an agency managing dozens of client stores, understanding how WooCommerce performance scales under load is now considered table stakes.

Today, many WordPress sites are far more dynamic, meaning many things are happening at the same time:

  • Stores run real-time sales.
  • LMS platforms track user progress.
  • Membership sites deliver highly personalized content.

Every action a user takes, from logging in, updating a cart, or initiating checkout, relies on live data from the server. These requests cannot be cached.

Tools like Varnish or CDNs can help with public pages such as the homepage or product listings. But once someone logs in to their account or interacts with their session, caching no longer helps. Each request must be processed in real time.

This article breaks down why that happens and what kind of server setup is helping stores stay fast, stable, and ready to grow.

Why Do WooCommerce Stores Slow Down?

WooCommerce often performs well on the surface. But as traffic grows and users start interacting with the site, speed issues begin to show. These are the most common reasons why stores slow down under pressure:

1. PHP: It Struggles With High User Activity

WooCommerce depends on PHP to process dynamic actions such as cart updates, coupon logic, and checkout steps. Traditional stacks using Apache for PHP handling are slower and less efficient.

Modern environments use PHP-FPM, which improves execution speed and handles more users at once without delays.

2. A Full Database: It Becomes A Bottleneck

Order creation, cart activity, and user actions generate a high number of database writes. During busy times like flash sales, new merchandise arrivals, or course launches, the database struggles to keep up.

Platforms that support optimized query execution and better indexing handle these spikes more smoothly.

3. Caching Issues: Object Caching Is Missing Or Poorly Configured

Without proper object caching, WooCommerce queries the database repeatedly for the same information. That includes product data, imagery, cart contents, and user sessions.

Solutions that include built-in Redis support help move this data to memory, reducing server load and improving site speed.

4. Concurrency Limits Affect Performance During Spikes

Most hosting stacks today, including Apache-based ones, perform well for a wide range of WordPress and WooCommerce sites. They handle typical traffic reliably and have powered many successful stores.

As traffic increases and more users log in and interact with the site at the same time, the load on the server begins to grow. Architecture starts to play a bigger role at that point.

Stacks built on NGINX with event-driven processing can manage higher concurrency more efficiently, especially during unanticipated traffic spikes.

Rather than replacing what already works, this approach extends the performance ceiling for stores that are becoming more dynamic and need consistent responsiveness under heavier load.

5. Your WordPress Admin Slows Down During Sales Seasons

During busy periods like seasonal sales campaigns or new stock availability, stores can often slow down for the team managing the site, too. The WordPress dashboard takes longer to load, which means publishing products, managing orders, or editing pages also becomes slower.

This slowdown happens because both shoppers and staff are using the site’s resources at the same time, and the server has to handle all those requests at once.

Modern stacks reduce this friction by balancing frontend and backend resources more effectively.

How To Architect A Scalable WordPress Setup For Dynamic Workloads?

WooCommerce stores today are built for more than stable traffic. Customers are logging in, updating their carts, taking actions to manage their subscription profile, and as a result, are interacting with your backend in real time.

The traditional WordPress setup, which is primarily designed for static content, cannot handle that kind of demand.

Here’s how a typical setup compares to one built for performance and scale:

Component Basic Setup         Scalable Setup
Web Server Apache NGINX
PHP Handler mod_php or CGI PHP-FPM
Object Caching None or database transients Redis with Object Cache Pro
Scheduled Tasks WP-Cron System cron job
Caching CDN or full-page caching only Layered caching, including object cache
.htaccess Handling Built-in with Apache Manual rewrite rules in NGINX config
Concurrency Handling Limited Event-based, memory-efficient server

How To Manually Setup A Performance-Ready & Scalable WooCommerce Stack

Don’t have bandwidth? Try the easy way.

If you’re setting up your own server or tuning an existing one, are the most important components to get right:

1) Use NGINX For Static File Performance

NGINX is often used as a high-performance web server for handling static files and managing concurrent requests efficiently. It is well suited for stores expecting high traffic or looking to fine-tune their infrastructure for speed.

Unlike Apache, NGINX does not use .htaccess files. Rewrite rules, such as permalinks, redirects, and trailing slashes, need to be added manually to the server block. For WordPress, these rules are well-documented and only need to be set once during setup.

This approach gives more control at the server level and can be helpful for teams building out their own environment or optimizing for scale.

2) Enable PHP-FPM For Faster Request Handling

PHP-FPM separates PHP processing from the web server. It gives you more control over memory and CPU usage. Tune values like pm.max_children and pm.max_requests based on your server size to prevent overload during high activity.

3) Install Redis With Object Cache Pro

Redis allows WooCommerce to store frequently used data in memory. This includes cart contents, user sessions, and product metadata.

Pair this with Object Cache Pro to compress cache objects, reduce database load, and improve site responsiveness under load.

4) Replace WP-Cron With A System-Level Cron Job

By default, WordPress checks for scheduled tasks whenever someone visits your site. That includes sending emails, clearing inventory, and syncing data. If you have steady traffic, it works. If not, things get delayed.

You can avoid that by turning off WP-Cron. Just add define(‘DISABLE_WP_CRON’, true); to your wp-config.php file. Then, set up a real cron job at the server level to run wp-cron.php every minute. This keeps those tasks running on time without depending on visitors.

5) Add Rewrite Rules Manually For NGINX

NGINX doesn’t use .htaccess. That means you’ll need to define URL rules directly in the server block.

This includes things like permalinks, redirects, and static file handling. It’s a one-time setup, and most of the rules you need are already available from trusted WordPress documentation. Once you add them, everything works just like it would on Apache.

A Few Tradeoffs To Keep In Mind

This kind of setup brings a real speed boost. But there are some technical changes to keep in mind.

  • NGINX won’t read .htaccess. All rewrites and redirects need to be added manually.
  • WordPress Multisite may need extra tweaks, especially if you’re using subdirectory mode.
  • Security settings like IP bans or rate limits should be handled at the server level, not through plugins.

Most developers won’t find these issues difficult to work with. But if you’re using a modern platform, much of it is already taken care of.

You don’t need overly complex infrastructure to make WooCommerce fast; just a stack that aligns with how modern, dynamic stores operate today.

Next, we’ll look at how that kind of stack performs under traffic, with benchmarks that show what actually changes when the server is built for dynamic sites.

What Happens When You Switch To An Optimized Stack?

Not all performance challenges come from code or plugins. As stores grow and user interactions increase, the type of workload becomes more important, especially when handling live sessions from logged-in users.

To better understand how different environments respond to this kind of activity, Koddr.io ran an independent benchmark comparing two common production setups:

  • A hybrid stack using Apache and NGINX.
  • A stack built on NGINX with PHP-FPM, Redis, and object caching.

Both setups were fully optimized and included tuned components like PHP-FPM and Redis. The purpose of the benchmark was to observe how each performs under specific, real-world conditions.

The tests focused on uncached activity from WooCommerce and LearnDash, where logged-in users trigger dynamic server responses.

In these scenarios, the optimized stack showed higher throughput and consistency during peak loads. This highlights the value of having infrastructure tailored for dynamic, high-concurrency traffic, depending on the use case.

WooCommerce Runs Faster Under Load

One test simulated 80 users checking out at the same time. The difference was clear:

Scenario Hybrid Stack Optimized Stack Gain
WooCommerce Checkout 3,035 actions 4,809 actions +58%
Screenshot from Koddr.io, August 2025

LMS Platforms Benefit Even More

For LearnDash course browsing—a write-heavy and uncached task, the optimized stack completed 85% more requests:

Scenario Hybrid Stack Optimized Stack Gain
LearnDash Course List View 13,459 actions 25,031 actions +85%

This shows how optimized stacks handle personalized or dynamic content more efficiently. These types of requests can’t be cached, so the server’s raw efficiency becomes critical.

Screenshot from Koddr.io, August 2025

Backend Speed Improves, Too

The optimized stack wasn’t just faster for customers. It also made the WordPress admin area more responsive:

  • WordPress login times improved by up to 31%.
  • Publish actions ran 20% faster, even with high traffic.

This means your team can concurrently manage products, update pages, and respond to sales in real time, without delays or timeouts.

It Handles More Without Relying On Caching

When Koddr turned off Varnish, the hybrid stack experienced a 71% drop in performance. This shows how effectively it handles cached traffic. The optimized stack dropped just 7%, which highlights its ability to maintain speed even during uncached, logged-in sessions.

Both setups have their strengths, but for stores with real-time user activity, reducing reliance on caching can make a measurable difference.

Stack Type With Caching Without Caching Drop
Hybrid Stack 654,000 actions 184,000 actions -7%
Optimized Stack 619,000 actions 572,000 actions -7%
Screenshot from Koddr.io, August 2025

Why This Matters?

Static pages are easy to optimize. But WooCommerce stores deal with real-time traffic. Cart updates, login sessions, and checkouts all require live processing. Caching cannot help once a user has signed in.

The Koddr.io results show how an optimized server stack:

  • Reduces CPU spikes during traffic surges.
  • Keeps the backend responsive for your team.
  • Delivers more stable speed for logged-in users.
  • Helps scale without complex performance workarounds.

These are the kinds of changes that power newer stacks purpose-built for dynamic workloads like Cloudways Lightning, built for real WooCommerce workloads.

Core Web Vitals Aren’t Just About The Frontend

You can optimize every image. Minify every line of code. Switch to a faster theme. But your Core Web Vitals score will still suffer if the server can’t respond quickly.

That’s what happens when logged-in users interact with WooCommerce or LMS sites.

When a customer hits “Add to Cart,” caching is out of the picture. The server has to process the request live. That’s where TTFB (Time to First Byte) becomes a real problem.

Slow server response means Google waits longer to start rendering the page. And that delay directly affects your Largest Contentful Paint and Interaction to Next Paint metrics.

Frontend tuning gets you part of the way. But if the backend is slow, your scores won’t improve. Especially for logged-in experiences.

Real optimization starts at the server.

How Agencies Are Skipping The Manual Work

Every developer has a checklist for WooCommerce performance. Use NGINX. Set up Redis. Replace WP-Cron. Add a WAF. Test under load. Keep tuning.

But not every team has the bandwidth to maintain all of it.

That’s why more agencies are using pre-optimized stacks that include these upgrades by default. Cloudways Lightning, a managed stack based on NGINX + PHP-FPM, designed for dynamic workloads is a good example of that.

It’s not just about speed. It’s also about backend stability during high traffic. Admin logins stay fast. Product updates don’t hang. Orders keep flowing.

Joe Lackner, founder of Celsius LLC, shared what changed for them:

“Moving our WordPress workloads to the new Cloudways stack has been a game-changer. The console admin experience is snappier, page load times have improved by +20%, and once again Cloudways has proven to be way ahead of the game in terms of reliability and cost-to-performance value at this price point.”

This is what agencies are looking for. A way to scale without getting dragged into infrastructure management every time traffic picks up.

Final Takeaway

WooCommerce performance is no longer just about homepage load speed.

Your site handles real-time activity from both customers and your team. Once a user logs in or reaches checkout, caching no longer applies. Each action hits the server directly.

If the infrastructure isn’t optimized, site speed drops, sales suffer, and backend work slows down.

The foundations matter. A stack that’s built for high concurrency and uncached traffic keeps things fast across the board. That includes cart updates, admin changes, and product publishing.

For teams who don’t want to manage server tuning manually, options like Cloudways Lightning deliver a faster, simpler path to performance at scale.

Use promo code “SUMMER305” and get 30% off for 5 months + 15 free migrations. Signup Now!

⚡ Power Up My WooCommerce Store

Image Credits

Featured Image: Image by Cloudways. Used with permission.

In-Post Images: Images by Cloudways. Used with permission.

Ecommerce MGMT 0 Comments
Aug 28 2025
Track, Prioritize & Win In AI Search [Webinar] via @sejournal, @hethr_campbell

AI search is reshaping buyer discovery. 

Every week, 800 million searches happen across ChatGPT, Claude, Perplexity, and other AI engines. 

If your brand isn’t showing up, you’re losing leads and opportunities.

Join Samanyou Garg, Founder of Writesonic, on September 10, 2025, for a webinar designed to help marketers and SEO teams master AI visibility. In this session, you’ll learn practical tactics to measure, prioritize, and optimize your AI footprint.

Here’s what you’ll walk away with

  • AI Visibility Tracking Framework: Measure mentions, citations, sentiment, and share of voice across AI engines
  • Data-Driven Prioritization: Focus on high-impact prompts and competitor gaps for the best ROI
  • 3-Pillar GEO Action Plan: Improve crawler access, craft prompt-specific content, and earn authority-building citations

Why you can’t miss this webinar:

AI-driven search is no longer optional. Your brand’s presence in AI answer engines directly impacts traffic, leads, and revenue. This session will equip you with a step-by-step process to turn AI visibility into real business results.

Save your spot now to learn actionable strategies that top brands are using to dominate AI search.

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

Ecommerce MGMT 0 Comments
Aug 26 2025
Consumer Trust And Perception Of AI In Marketing

This edited excerpt is from Ethical AI in Marketing by Nicole Alexander ©2025 and is reproduced and adapted with permission from Kogan Page Ltd.

Recent research highlights intriguing paradoxes in consumer attitudes toward AI-driven marketing. Consumers encounter AI-powered marketing interactions frequently, often without realizing it.

According to a 2022 Pew Research Center survey, 27% of Americans reported interacting with AI at least several times a day, while another 28% said they interact with AI about once a day or several times a week (Pew Research Center, 2023).

As AI adoption continues to expand across industries, marketing applications – from personalized recommendations to chatbots – are increasingly shaping consumer experiences.

According to McKinsey & Company (2023), AI-powered personalization can deliver five to eight times the ROI on marketing spend and significantly boost customer engagement.

In this rapidly evolving landscape, trust in AI has become a crucial factor for successful adoption and long-term engagement.

The World Economic Forum under­scores that “trust is the foundation for AI’s widespread acceptance,” and emphasizes the necessity for companies to adopt self-governance frameworks that prioritize transparency, accountability, and fairness (World Economic Forum, 2025).

The Psychology Of AI Trust

Consumer trust in AI marketing systems operates fundamentally differently from traditional marketing trust mechanisms.

Where traditional marketing trust builds through brand familiarity and consistent experiences, AI trust involves additional psychological dimensions related to automation, decision-making autonomy, and perceived control.

Understanding these differences is crucial for organizations seek­ing to build and maintain consumer trust in their AI marketing initiatives.

Cognitive Dimensions

Neurological studies offer intriguing insights into how our brains react to AI. Research from Stanford University reveals that we process information differently when interacting with AI-powered systems.

For example, when evaluating AI-generated product recommendations, our brains activate distinct neural path­ways compared to those triggered by recommendations from a human salesperson.

This crucial difference highlights the need for marketers to understand how consum­ers cognitively process AI-driven interactions.

There are three key cognitive factors that have emerged as critical influences on AI trust, including perceived control, understanding of mechanisms, and value recognition.

Emotional Dimensions

Consumer trust in AI marketing is deeply influenced by emotional factors, which often override logical evaluations. These emotional responses shape trust in several key ways:

  • Anxiety and privacy concerns: Despite AI’s convenience, 67% of consumers express anxiety about how their data is used, reflecting persistent privacy concerns (Pew Research Center, 2023). This tension creates a paradoxical relationship where consumers benefit from AI-driven marketing while simultaneously fearing its potential misuse.
  • Trust through repeated interactions: Emotional trust in AI systems develops iteratively through repeated, successful interactions, particularly when systems demonstrate high accuracy, consistent performance, and empathetic behavior. Experimental studies show that emotional and behavioral trust accumulate over time, with early experiences strongly shaping later perceptions. In repeated legal decision-making tasks, users exhibited growing trust toward high-performing AI, with initial interactions significantly influencing long-term reliance (Kahr et al., 2023). Emotional trust can follow nonlinear pathways – dipping after failures but recovering through empathetic interventions or improved system performance (Tsumura and Yamada, 2023).
  • Honesty and transparency in AI content: Consumers increasingly value transpar­ency regarding AI-generated content. Companies that openly disclose when AI has been used – for instance, in creating product descriptions – can empower customers by helping them feel more informed and in control of their choices. Such openness often strengthens customer trust and fosters positive perceptions of brands actively embracing transparency in their marketing practices.

Cultural Variations In AI Trust

The global nature of modern marketing requires a nuanced understanding of cultural differences in AI trust. These variations arise from deeply ingrained societal values, historical relationships with technology, and norms around privacy, automation, and decision-making.

For marketers leveraging AI in customer engagement, recognizing these cultural distinctions is crucial for developing trustworthy AI-driven campaigns, personalized experiences, and region-specific data strategies.

Diverging Cultural Trust In AI

Research reveals significant disparities in AI trust across global markets. A KPMG (2023) global survey found that 72% of Chinese consumers express trust in AI-driven services, while in the U.S., trust levels plummet to just 32%.

This stark difference reflects broader societal attitudes toward government-led AI innovation, data privacy concerns, and varying historical experiences with technology.

Another study found that AI-related job displacement fears vary greatly by region. In countries like the U.S., India, and Saudi Arabia, consumers express significant concerns about AI replacing human roles in professional sectors such as medicine, finance, and law.

In contrast, consumers in Japan, China, and Turkey exhibit lower levels of concern, signaling a higher acceptance of AI in professional settings (Quantum Zeitgeist, 2025).

The Quantum Zeitgeist study shows that regions like Japan, China, and Turkey exhibit lower levels of concern about AI replacing human jobs compared to regions like the U.S., India, and Saudi Arabia, where such fears are more pronounced.

This insight is invaluable for marketers crafting AI-driven customer service, finan­cial tools, and healthcare applications, as perceptions of AI reliability and utility vary significantly by region.

As trust in AI diverges globally, understanding the role of cultural privacy norms becomes essential for marketers aiming to build trust through AI-driven services.

Cultural Privacy Targeting In AI Marketing

As AI-driven marketing becomes more integrated globally, the concept of cultural privacy targeting – the practice of aligning data collection, privacy messaging, and AI transparency with cultural values – has gained increasing importance. Consumer attitudes toward AI adoption and data privacy are highly regional, requiring market­ers to adapt their strategies accordingly.

In more collectivist societies like Japan, AI applications that prioritize societal or community well-being are generally more accepted than those centered on individual convenience.

This is evident in Japan’s Society 5.0 initiative – a national vision intro­duced in 2016 that seeks to build a “super-smart” society by integrating AI, IoT, robotics, and big data to solve social challenges such as an aging population and strains on healthcare systems.

Businesses are central to this transformation, with government and industry collaboration encouraging companies to adopt digital technologies not just for efficiency, but to contribute to public welfare.

Across sectors – from manufac­turing and healthcare to urban planning – firms are reimagining business models to align with societal needs, creating innovations that are both economically viable and socially beneficial.

In this context, AI is viewed more favorably when positioned as a tool to enhance collective well-being and address structural challenges. For instance, AI-powered health monitoring technologies in Japan have seen increased adoption when positioned as tools that contribute to broader public health outcomes.

Conversely, Germany, as an individualistic society with strong privacy norms and high uncertainty avoidance, places significant emphasis on consumer control over personal data. The EU’s GDPR and Germany’s support for the proposed Artificial Intelligence Act reinforce expectations for robust transparency, fairness, and user autonomy in AI systems.

According to the OECD (2024), campaigns in Germany that clearly communicate data usage, safeguard individual rights, and provide opt-in consent mechanisms experience higher levels of public trust and adoption.

These contrasting cultural orientations illustrate the strategic need for contextual­ized AI marketing – ensuring that data transparency and privacy are not treated as one-size-fits-all, but rather as culture-aware dimensions that shape trust and acceptance.

Hofstede’s (2011) cultural dimensions theory offers further insights into AI trust variations:

  • High individualism + high uncertainty avoidance (e.g., Germany, U.S.) → Consum­ers demand transparency, data protection, and human oversight in AI marketing.
  • Collectivist cultures with lower uncertainty avoidance (e.g., Japan, China, South Korea) → AI is seen as a tool that enhances societal progress, and data-sharing concerns are often lower when the societal benefits are clear (Gupta et al., 2021).

For marketers deploying AI in different regions, these insights help determine which features to emphasize:

  • Control and explainability in Western markets (focused on privacy and auton­omy).
  • Seamless automation and societal progress in East Asian markets (focused on communal benefits and technological enhancement).

Understanding the cultural dimensions of AI trust is key for marketers crafting successful AI-powered campaigns.

By aligning AI personalization efforts with local cultural expectations and privacy norms, marketers can improve consumer trust and adoption in both individualistic and collectivist societies.

This culturally informed approach helps brands tailor privacy messaging and AI transparency to the unique preferences of consumers in various regions, building stronger relationships and enhancing overall engagement.

Avoiding Overgeneralization In AI Trust Strategies

While cultural differences are clear, overgeneralizing consumer attitudes can lead to marketing missteps.

A 2024 ISACA report warns against rigid AI segmentation, emphasizing that trust attitudes evolve with:

  • Media influence (e.g., growing fears of AI misinformation).
  • Regulatory changes (e.g., the EU AI Act’s impact on European consumer confidence).
  • Generational shifts (younger, digitally native consumers are often more AI-trusting, regardless of cultural background).

For AI marketing, this highlights the need for flexible, real-time AI trust monitoring rather than static cultural assumptions.

Marketers should adapt AI trust-building strategies based on region-specific consumer expectations:

  • North America and Europe: AI explainability, data transparency, and ethical AI labels increase trust.
  • East Asia: AI-driven personalization and seamless automation work best when framed as benefiting society.
  • Islamic-majority nations and ethical consumer segments: AI must be clearly aligned with fairness and ethical governance.
  • Global emerging markets: AI trust is rapidly increasing, making these markets prime opportunities for AI-driven financial inclusion and digital transformation.

The data, drawn from the 2023 KPMG International survey, underscores how cultural values such as collectivism, uncertainty avoidance, and openness to innovation, shape public attitudes toward AI.

For example, trust levels in Germany and Japan remain low, reflecting high uncertainty avoidance and strong privacy expectations, while countries like India and Brazil exhibit notably higher trust, driven by optimism around AI’s role in societal and economic progress.

Measuring Trust In AI Marketing Systems

As AI becomes central to how brands engage customers – from personalization engines to chatbots – measuring consumer trust in these systems is no longer optional. It’s essential.

And yet, many marketing teams still rely on outdated metrics like Net Promoter Score (NPS) or basic satisfaction surveys to evaluate the impact of AI. These tools are helpful for broad feedback but miss the nuance and dynamics of trust in AI-powered experiences.

Recent research, including work from MIT Media Lab (n.d.) and leading behavioral scientists, makes one thing clear: Trust in AI is multi-dimensional, and it’s shaped by how people feel, think, and behave in real-time when interacting with automated systems.

Traditional metrics like NPS and CSAT (Customer Satisfaction Score) tell you if a customer is satisfied – but not why they trust (or don’t trust) your AI systems.

They don’t account for how transparent your algorithm is, how well it explains itself, or how emotionally resonant the interaction feels. In AI-driven environments, you need a smarter way to understand trust.

A Modern Framework For Trust: What CMOs Should Know

MIT Media Lab’s work on trust in human-AI interaction offers a powerful lens for marketers. It breaks trust into three key dimensions:

Behavioral Trust

This is about what customers do, not what they say. When customers engage frequently, opt in to data sharing, or return to your AI tools repeatedly, that’s a sign of behavioral trust. How to track it:

  • Repeat engagement with AI-driven tools (e.g., product recommenders, chatbots).
  • Opt-in rates for personalization features.
  • Drop-off points in AI-led journeys.

Emotional Trust

Trust is not just rational, it’s emotional. The tone of a voice assistant, the empathy in a chatbot’s reply, or how “human” a recommendation feels all play into emotional trust. How to track it:

  • Sentiment analysis from chat transcripts and reviews.
  • Customer frustration or delight signals from support tickets.
  • Tone and emotional language in user feedback.

Cognitive Trust

This is where understanding meets confidence. When your AI explains itself clearly – or when customers understand what it can and can’t do –they’re more likely to trust the output. How to track it:

  • Feedback on explainability (“I understood why I got this recommendation”).
  • Click-through or acceptance rates of AI-generated content or decisions.
  • Post-interaction surveys that assess clarity.

Today’s marketers are moving toward real-time trust dashboards – tools that moni­tor how users interact with AI systems across channels. These dashboards track behavior, sentiment, and comprehension all at once.

According to MIT Media Lab researchers, combining these signals provides a richer picture of trust than any single survey can. It also gives teams the agility to address trust breakdowns as they happen – like confusion over AI-generated content or friction in AI-powered customer journeys.

Customers don’t expect AI to be perfect. But they do expect it to be honest and understandable. That’s why brands should:

  • Label AI-generated content clearly.
  • Explain how decisions like pricing, recommendations, or targeting are made.
  • Give customers control over data and personalization.

Building trust is less about tech perfection and more about perceived fairness, clarity, and respect.

Measuring that trust means going deeper than satisfaction. Use behav­ioral, emotional, and cognitive signals to track trust in real-time – and design AI systems that earn it.

To read the full book, SEJ readers have an exclusive 25% discount code and free shipping to the US and UK. Use promo code ‘SEJ25’ at koganpage.com here.

More Resources: 

References

  • Hofstede, G (2011) Dimensionalizing Cultures: The Hofstede Model in Context, Online Readings in Psychology and Culture, 2 (1), scholarworks.gvsu.edu/cgi/viewcontent. cgi?article=1014&context=orpc (archived at https://perma.cc/B7EP-94CQ)
  • ISACA (2024) AI Ethics: Navigating Different Cultural Contexts, December 6, www.isaca. org/resources/news-and-trends/isaca-now-blog/2024/ai-ethics-navigating-different-cultural-contexts (archived at https://perma.cc/3XLA-MRDE)
  • Kahr, P K, Meijer, S A, Willemsen, M C, and Snijders, C C P (2023) It Seems Smart, But It Acts Stupid: Development of Trust in AI Advice in a Repeated Legal Decision-Making Task, Proceedings of the 28th International Conference on Intelligent User Interfaces. doi.org/10.1145/3581641.3584058 (archived at https://perma.cc/SZF8-TSK2)
  • KPMG International and The University of Queensland (2023) Trust in Artificial Intelligence: A Global Study, assets.kpmg.com/content/dam/kpmg/au/pdf/2023/ trust-in-ai-global-insights-2023.pdf (archived at https://perma.cc/MPZ2-UWJY)
  • McKinsey & Company (2023) The State of AI in 2023: Generative AI’s Breakout Year, www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023- generative-ais-breakout-year (archived at https://perma.cc/V29V-QU6R)
  • MIT Media Lab (n.d.) Research Projects, accessed April 8, 2025
  • OECD (2024) OECD Artificial Intelligence Review of Germany, www.oecd.org/en/ publications/2024/06/oecd-artificial-intelligence-review-of-germany_c1c35ccf.html (archived at https://perma.cc/5DBS-LVLV)
  • Pew Research Center (2023) Public Awareness of Artificial Intelligence in Everyday Activities, February, www.pewresearch.org/wp-content/uploads/sites/20/2023/02/ PS_2023.02.15_AI-awareness_REPORT.pdf (archived at https://perma.cc/V3SE-L2BM)
  • Quantum Zeitgeist (2025) How Cultural Differences Shape Fear of AI in the Workplace, Quantum News, February 22, quantumzeitgeist.com/how-cultural-differences-shape-fear-of-ai-in-the-workplace-a-global-study-across-20-countries/ (archived at https://perma.cc/3EFL-LTKM)
  • Tsumura, T and Yamada, S (2023) Making an Agent’s Trust Stable in a Series of Success and Failure Tasks Through Empathy, arXiv. arxiv.org/abs/2306.09447 (archived at https://perma.cc/L7HN-B3ZC)
  • World Economic Forum (2025) How AI Can Move from Hype to Global Solutions, www. weforum.org/stories/2025/01/ai-transformation-industries-responsible-innovation/ (archived at https://perma.cc/5ALX-MDXB)

Featured Image: Rawpixel.com/Shutterstock

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Aug 20 2025
How AI Search Can Drive Sales & Boost Conversions [Webinar] via @sejournal, @brentcsutoras

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Aug 18 2025
Why The Last Year Has Been The Biggest Challenge For CMOs via @sejournal, @gregjarboe

I’ve spent 30 years navigating the turbulent waters of what was once called “internet marketing” and is now called “digital marketing.”

Based on my experience, the past year has been nothing short of a perfect storm for chief marketing officers (CMOs).

As the Director of Corporate Communications for Ziff-Davis, I helped to launch Yahoo! Europe in 1996. We faced several key challenges as the joint venture began offering customized versions of Yahoo!’s leading “Internet guide” in France, Germany, and the United Kingdom.

We had to overcome language, cultural, operational, and competitive hurdles to succeed in a rapidly evolving digital landscape with “annual growth rates in excess of 80%.”

Four years later, I was the VP of Marketing of WebCT when the dot-com bubble burst on March 10, 2000.

A month earlier, the board of directors had asked me why we had not joined the other 14 dot-com companies that spent $2.2 million to run a 30-second spot during Super Bowl XXXIV.

A month later, the board told me to cut my marketing budget in half. (So, our strategic goal flipped overnight from lighting our money on fire to slowing our burn rate.)

Yet, even with that backdrop, the confluence of challenges CMOs have faced in the last twelve months is unprecedented.

Let’s analyze why this current period has been particularly grueling and evaluate some critical data, market trends, strategic insights, fresh examples, and tactical advice for navigating these unusually rough seas.

A Perfect Storm Of Challenges

We are witnessing a surprising mix of factors:

Changing Consumer Behavior

The COVID-19 pandemic permanently reshaped consumer behaviors and preferences.

CMOs have had to rapidly adapt to increased demand for digital engagement, personalized experiences, and a heightened focus on sustainability.

Understanding and responding to these evolving expectations is paramount for maintaining brand loyalty.

Increased Competition

The digital marketing environment is more turbulent than ever, with brands fiercely competing for consumer attention across numerous channels.

CMOs are tasked with differentiating their brands in a saturated market, which necessitates innovative strategies and truly creative campaigns to stand out.

Rapid Technological Advancements

The pace of technological change continues to accelerate, with new tools and platforms emerging at a dizzying rate.

CMOs are not only expected to stay on top of these developments but also to seamlessly integrate advanced technologies like artificial intelligence (AI), machine learning (ML), and data analytics into their strategies, all while ensuring their teams are proficient in using them.

Economic Uncertainty

Global economic fluctuations, marked by inflation and supply chain disruptions, have forced CMOs to operate with tighter budgets and contend with shifting consumer spending habits.

This volatility makes forecasting marketing return on investment (ROI) and allocating resources effectively incredibly difficult.

Measurement And Accountability

As marketing becomes increasingly data-driven, CMOs face intense pressure to demonstrate the effectiveness of their strategies.

Establishing clear metrics and accountability for marketing performance is essential, yet it remains challenging in such a rapidly changing environment.

Navigating A Perfect Storm

This powerful combination of negative circumstances leads to a significantly worse outcome than if those circumstances had occurred separately. This explains why the role of the CMO has never been more complex, nor more critical.

But, how does a CMO successfully navigate a perfect storm?

In this maelstrom, Google is often seen as both a catalyst for these challenges and a beacon for solutions. So, CMOs may turn to “Think with Google,” which was recently updated to provide the equivalent of a nautical chart of “marketing in the AI era.”

The redesigned Think with Google has organized its content into five critical categories: Consumer Insights, Search & Video, AI Excellence, Future of Marketing, and Measurement.

These can provide a strategic framework for CMOs to not only weather the current turbulence but to emerge stronger, more agile, and more effective.

1. Consumer Insights: Marketing To The Predictably Unpredictable Customer

In an age of endless choice and constant connectivity, the consumer journey is anything but linear.

Understanding the “predictably unpredictable” customer is paramount. This means moving beyond demographic segmentation to truly grasp intent, context, and micro-moments.

Critical Data: New research indicates video plays a vital role in the shopping journey, especially on YouTube, where consumers seek in-depth information and trusted creator recommendations.

YouTube influences various shopping behaviors, from “rookie” to “quest for the best,” and can shorten the purchasing journey.

Shoppers turn to YouTube for product reviews and information more than other social platforms, leading to increased purchase confidence.

Market Trends: Social media drives brand awareness, but trusted recommendations boost conversions. According to a recent Traackr survey, YouTube is a top platform for product reviews.

Shoppers are increasingly relying on content from creators and honest product reviews to make their buying choices, which has, on average, cut six days off their purchasing journey, according to a Google/Material survey.

Strategic Insight: The modern consumer expects hyper-personalization without sacrificing privacy.

CMOs must build deep empathy for their audience, anticipating needs before they are explicitly stated and delivering value at every touchpoint. This requires a shift from broad-stroke campaigns to highly individualized experiences.

Fresh Example: Sephora expanded its holiday social media campaigns by collaborating with seven creators on a Shorts-only Demand Gen campaign that featured timely gift guides.

This strategy significantly increased traffic to Sephora.com, leading to an 82% rise in “Sephora holiday” searches and top-tier brand awareness.

Tactical Advice:

  • Invest in First-Party Data Strategies: As third-party cookies deprecate, building robust first-party data collection mechanisms becomes non-negotiable. This includes loyalty programs, direct customer interactions, and consent-driven data capture.
  • Map the Non-Linear Journey: Utilize analytics to understand the actual paths customers take, identifying key decision points and moments of influence, rather than relying on outdated funnel models.
  • Embrace Empathy-Driven Content: Create content that directly addresses customer pain points, aspirations, and questions, rather than simply pushing products.
  • Conduct Market and Audience Research: Both are crucial for understanding a business’s potential and success, but they differ in scope and focus. Market research explores the overall market landscape, while audience research delves into the specific characteristics and behaviors of a target group.

2. Search & Video: Meeting Customers Where They’re Searching, Streaming, Scrolling, And Shopping

Search and video are no longer distinct channels but intertwined ecosystems where consumers search, stream, scroll, and shop.

So, you must “influence audiences in all the places they go to consume content about your topic,” as Rand Fishkin says.

Critical Data: New research from Boston Consulting Group (BCG) indicates that four key consumer behaviors (streaming, scrolling, searching, and shopping) have fundamentally changed how consumers find and interact with brands.

For CMOs, it is crucial to understand each of these “4S behaviors” and adjust their marketing strategies accordingly to effectively reach, connect with, and ultimately sell to their target audiences.

Market Trends: The increasing prevalence of the “4S behaviors” creates an opportunity and a threat for CMOs.

While these behaviors make the consumer’s path to purchase more unpredictable and difficult to track, they also open new doors for brands to connect with, influence, and convert potential customers.

Strategic Insight: Visibility and discoverability are paramount. CMOs must ensure their brands are present and compelling across all forms of search and video consumption, anticipating evolving user behaviors, including voice and visual queries.

Fresh Example:Rare Beauty, founded by Selena Gomez, used AI-powered advertising to connect with Gen Z and drive business growth.

It leveraged Google AI with YouTube and Search strategies to deliver relevant messages, leading to a 7X return on ad spend as well as increased traffic and conversions through their own site and Sephora.com.

Tactical Advice:

  • Optimize for Generative AI in Search: Understand how AI-powered summaries and answers will impact organic visibility. Focus on providing comprehensive, authoritative content that AI models can readily synthesize.
  • Adopt “Search Everywhere Optimization”: Optimize content not just for text-based queries but also for voice search (conversational language, long-tail keywords) and visual search (high-quality images, structured data).
  • Master YouTube SEO and Strategy: As I outlined before, YouTube is a powerhouse. Focus on strong titles, descriptions, tags, and compelling thumbnails. Prioritize audience retention and engagement signals.
  • Embrace Shoppable Video: Integrate ecommerce directly into video content, allowing seamless transitions from viewing to purchasing.

3. AI Excellence: Transform Your Marketing With AI And Boost ROI

Artificial intelligence is no longer a futuristic concept; it is a present-day imperative for marketing transformation.

From automating routine tasks to powering hyper-personalization and predictive analytics, AI is reshaping every facet of the marketing function.

Critical Data: A recent report on AI in the Workplace by McKinsey Digital found:

“Almost all companies invest in AI, but just 1 percent believe they are at maturity. Our research finds the biggest barrier to scaling is not employees – who are ready – but leaders, who are not steering fast enough.”

Market Trends: The democratization of generative AI tools is making sophisticated AI capabilities accessible to more marketers. The focus is shifting from simply using AI to mastering AI for strategic advantage.

As I suggested previously, AI should be integrated into a continuous improvement loop, where insights from AI inform strategy, leading to better execution and further data collection.

Strategic Insight: CMOs must view AI not as a replacement for human creativity but as an indispensable co-pilot.

The strategic adoption of AI can unlock unprecedented efficiencies, enhance decision-making, and significantly boost return on investment.

Fresh Example: Jill Cress, H&R Block’s CMO, has increased AI-powered marketing tool usage by 24% by focusing on empathy and education.

Her strategy aligns AI with brand values like expertise and empathy, leading to innovations like AI Tax Assist and localized marketing efforts. This human-centered approach provides a model for AI leadership.

Tactical Advice:

  • Automate Mundane Tasks: Use AI for tasks like ad copy generation, email subject line optimization, social media scheduling, and basic content creation to free up human marketers for strategic work.
  • Personalization at Scale: Deploy AI-powered tools for dynamic content delivery, personalized product recommendations, and adaptive website experiences based on real-time user behavior.
  • Predictive Analytics for Campaign Optimization: Leverage AI to forecast campaign performance, identify optimal audience segments, and predict customer churn, allowing for proactive adjustments.
  • Ethical AI Implementation: Establish clear guidelines for AI usage, ensuring fairness, transparency, and data privacy.

4. Future Of Marketing: Lead The Charge With The Latest Innovations And Ideas

This section of the overhauled Think with Google resource for marketers, advertisers, and creatives provides the least helpful content to CMOs in an unexpected mix of events.

Why? Because articles by “Guest Thinkers” on topics like “3 strategies for navigating your marketing career to become a CMO” are worth reading.

But in a crisis, advice for how to grow your career in marketing to become a CMO is the first thing that current CMOs will toss overboard to lighten the ship.

In a crisis, time can seem to speed up. So, the perception of the “Future of Marketing” alters from 4.3 years (which is the average tenure of CMOs, according to Spencer Stuart) to 4.3 months, which is when CMOs who don’t successfully navigate economic uncertainty are likely to exit their roles.

Unfortunately for them, the most recent article from Think with Google that addresses economic uncertainty was published in 2022.

This article analyzed how economic uncertainty impacts consumer behavior and spending intentions. It also discussed how businesses need to build trust with customers in an uncertain market.

Two days later, OpenAI released ChatGPT on Nov. 30, 2022.

In November 2023, when Think with Google in Europe, Middle East & Africa published their predictions for 2024, the focus shifted to “growth” – even though economic uncertainty was predicted to continue.

Since then, the topic of economic uncertainty has only popped up in a Think with Google UK article in 2025. But it appears that Think with Google is avoiding this topic in the U.S.

So, what should CMOs in the US do?

The Economic Policy Uncertainty (EPU) Index is a good source of critical data about economic uncertainty.

But, the best source is proprietary market research, which enables a CMO to understand changing customer needs, identify new opportunities, and make informed decisions, helping them adapt and thrive in a challenging market.

In the U.S., eMarketer offers a comprehensive suite of resources, including advertising and marketing research as well as a toolkit on “Navigating Uncertainty in 2025.”

In the U.K., the IPA Bellwether Report has found marketing budgets often decrease during economic downturns, like the 2008 financial crash and the 2020 COVID-19 lockdown, showing that the willingness of British businesses to invest in their brands is closely tied to the economic climate.

Strategic Insight: Agility and a willingness to experiment are the hallmarks of future-ready marketing leaders. This involves fostering a culture of continuous learning and embracing technologies that redefine customer engagement.

Equivalent Examples: CMOs should read Tim Ringel’s article in Fast Company, where he says:

“We constantly live in uncertain times. Periods of tranquility are actually an aberration, if not an illusion.”

He adds:

“Rougher waters don’t sink all boats.”

Although his examples are from the Great Recession of 2008 and the COVID-10 pandemic of 2020, they offer “four strategic approaches for the uncertainty-conscious marketer.”

Tactical Advice:

  • Hire an Economist or Chief Economist: Susan Athey and Michael Luca of the Harvard Business Review have explained “Why Tech Companies Hire So Many Economists.” And Lydia DePillis of The Washington Post declared some time ago that  “Chief economists are the new marketers.” More CMOs should hire an economist to be their “Analysis Ninja.”
  • Build Agile Marketing Teams: Structure teams to be cross-functional and adaptable, capable of rapid iteration and quick pivots in response to market shifts.
  • Assemble All Hands on Deck: According to Spencer Stuart, 16% of Fortune 500 marketing leaders have marketing plus another function in their title (such as chief marketing and communications officer). If this function does not report to the CMO or SVP of marketing yet, then include Communications in all-hands meetings to ensure everyone is working towards a shared purpose.
  • Invest in Continuous Learning: Encourage teams to stay abreast of the latest technological advancements and marketing methodologies.

5. Measurement: Build Business Advantage With Your Data

In an increasingly data-rich environment, the ability to effectively measure marketing performance and translate data into actionable insights is the ultimate competitive advantage.

Without robust measurement, CMOs are just using dead reckoning.

Critical Data: Earlier this year, I asked, Where are the missing data holes? Back then, 67.9% of users of the Google Merchandise Store over the previous 28 days had arrived from the direct channel, according to the GA4 demo account.

Today, 77.6% of users are arriving “direct,” which means GA4 cannot determine the specific referral source of more than three out of four visitors.

Screenshot by author from GA4, July 2025

Market Trends: This month, I asked, why CMOs need to rethink attribution. I also said they should conduct brand lift studies and audience research to successfully navigate the reduced visibility that is a significant consequence of a perfect storm.

Strategic Insight: CMOs should read Avinash Kaushik’s article in The Marketing < > Analytics Intersect Newsletter. He advises shifting from activity-based marketing metrics to profit-driven outcomes like “Profit On Investment” (POI).

This innovative approach protects CMOs and secures budgets by demonstrating true business value. Kaushik also recommends cutting underperforming campaigns and retraining teams to achieve positive POI, stressing the importance of profitability even with AI Search.

Fresh Example: Lululemon used an AI-powered playbook to boost its performance marketing. This involved restructuring shopping campaigns, building a new customer acquisition engine, and strengthening measurement foundations.

The strategy led to reduced customer acquisition costs, increased new customer revenue, and an 8% boost in return on ad spend (ROAS).

Tactical Advice:

  • Implement Robust Attribution Models: Move beyond last-click attribution to multi-touch attribution models that give credit to all touchpoints in the customer journey, providing a more accurate picture of ROI.
  • Data Governance and Quality: Establish clear processes for data collection, cleaning, and storage to ensure accuracy and compliance with privacy regulations.
  • Integrate Data Silos: Break down departmental silos to create a unified view of customer interactions across marketing, sales, and service. This often involves Customer Data Platforms (CDPs) or robust data warehousing solutions.
  • Focus on Business Outcomes, Not Just Marketing Metrics: Connect marketing efforts directly to revenue, customer lifetime value, and market share, demonstrating clear business impact to the C-suite.

Conclusion: Thriving In The New Marketing Era

The digital marketing environment is indeed a perfect storm, but it is also brimming with unprecedented opportunities for those CMOs willing to adapt, innovate, and lead.

The redesigned Think with Google offers a framework to circumnavigate these challenges, even if the “Future of Marketing” team needs to recalibrate their time horizon, revise their editorial calendar, and refresh their helpful content on the topic of economic uncertainty.

By deeply understanding the predictably unpredictable customer, mastering the dynamic search and video ecosystem, embracing AI as a strategic partner, proactively exploring the future of marketing, and building a robust, data-driven measurement infrastructure, CMOs can transform their marketing organizations.

The future belongs to the agile, the data-informed, and the customer-obsessed.

By focusing on these strategic categories, CMOs can not only weather the storm but steer their brands towards unprecedented growth and sustained competitive advantage.

More Resources:

Featured Image: Roman Samborskyi/Shutterstock

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Aug 13 2025
Earn 1,000+ Links & Boost Your SEO Visibility [Webinar] via @sejournal, @lorenbaker

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Struggling to get backlinks, even when your content is solid? 

You’re not alone. With Google’s AI Overviews and generative search dominating the results, traditional link-building tactics just don’t cut it anymore.

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What You’ll Learn:

  • How to identify media trends where your expertise is in demand.
  • The step-by-step process to create studies that can earn links on autopilot.
  • How to craft a story angle journalists will want to share.

Why This Webinar is Essential:

Earned links and citations are now key to staying visible in AI search results. This session will provide you with a proven, actionable playbook for boosting your SEO visibility and building the authority you need to succeed in this new era.

Register today to get the playbook for link-building success. Can’t attend live? Don’t worry, sign up anyway, and we’ll send you the full recording.

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Aug 7 2025
How To Stay Visible in AI Search [Webinar] via @sejournal, @lorenbaker

AI search is here. Are you ready for the new rules?

The SEO game has changed. Traditional strategies are no longer enough, and some brands are getting lost in the shift to AI-powered search results.

Join Wayne Cichanski on August 20, 2025 for an exclusive webinar sponsored by iQuanti. Learn how to adapt your SEO strategy and site architecture for AI-driven queries and remain competitive in this new search era.

In this session, you’ll discover:

  • Why user experience, schema, and site architecture are now just as important as keywords
  • Practical steps to remain visible and competitive in evolving search results
  • How to position your brand for discovery in AI-driven queries, not just rankings

Why this session is essential:

With generative AI reshaping search results across platforms like Google, Bing, and ChatGPT, it is crucial to rethink how your content is structured and how people interact with your brand in AI search. Do not get left behind. Optimize for AI-driven search now.

Register today for actionable insights and a roadmap to success in the AI search era. If you cannot attend live, do not worry. Sign up anyway and we will send you the full recording.

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Aug 7 2025
Building Brand Identity: How To Define Who You Are

Brand identity is the foundation of your business, from the conceptualization of your services and products all the way to marketing.

Before you can create an effective marketing, SEO, content strategy, or even a business strategy, you need to know who you are as a brand. It’s a step many marketers and business leaders overlook, but it’s the one that makes everything else work.

This episode breaks down why identity is the starting point for your business to have impact.

Editor-in-Chief of Search Engine Journal, Katie Morton, sits down with Mordy Oberstein, founder of Unify Brand Marketing, to discuss how to develop a true brand identity so your marketing strategy has something solid to stand on.

Watch the video or read the full transcript below.

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

Katie Morton: Hey everybody, it is I, Katie Morton, Editor-in-Chief of Search Engine Journal, and today I’m sitting down with Mordy Oberstein, founder of Unify Brand Marketing. Mordy, talk to me. What’s going on?

Mordy Oberstein: Episode three! It’s a thing now. I can’t believe we’ve made it this far. Counting episodes has become a bit of a challenge, though. We might even be on number four.

Katie: Counting is definitely hard! But let’s dive in.

Why Brand Identity Matters

Mordy: Last time, we talked about brand development and the stages of brand development. The first stage of brand development is developing brand identity. So, for the sake of continuity, which is important for branding, let’s talk about how you develop brand identity this time.

Katie: That sounds fantastic. How does one develop brand identity?

Mordy: Before we get into the “how,” let’s talk about why brand identity is so essential. Identity is the foundation of everything your brand or company does. You can’t create a marketing, SEO, or content strategy without first knowing who you are. Everyone skips this step—but it’s crucial.

Also, identity is the thing that allows your audience to connect to you. There has to be a point of connection for marketing to actually be effective. And people can’t connect unless there’s a “you” to connect with.

How To Build Brand Identity

Mordy: And that, in turn, also gives you a lot of focus where brands generally go off the rails is when they start focusing on the wrong things. It’s usually because of a lack of brand identity. So, how do you actually build identity?

The first thing to understand is that identity is not a fake thing. It’s not some make-believe concept like, “Oh, brand identity, it’s a fabrication.” No, identity is a real, living, breathing thing. And because of that, it has to be tied to what you actually do, what your offering really is. There’s no way to put lipstick on a pig.

The second thing I’ll say, before we dive deeper, is that brand identity has nothing to do with your company culture. If you think, “Oh, our identity is our company culture,” you’re doing it wrong. I know that’s a hot take.

The goal of identity is to create something authentic that your audience can connect with. And it needs to have depth for that connection to happen. To have depth, there has to be almost a therapeutic process that goes on. What you’re basically engaging in therapy for your brand.

Engage In Brand “Therapy”

Mordy: What I do with clients (and what you should do internally with your own team) is tap into who you actually are and what you actually want. It’s a process of asking: Why do you do the things you do?

You need to sit down with your team and have a session where you talk about:

  • Why you do what you do.
  • How you see your industry and niche.
  • How you view your product or service.
  • How you see your space and your audience.
  • What you want for your audience, not just practically, but meaningfully.

It’s not about what your audience gets in a practical sense. It’s about the outcome for their lives in a meaningful way.

During this process, you need to take notes like a therapist. As you’re having these discussions, ask yourself: What’s landing? What’s meaningful about this? What feels like something to chew on? Listen for the things that resonate – both in what you’re saying and what your team is saying.

From Reflection To Action: Formalizing Your Brand Identity

The next step is to formalize all of that into a pathway to showcase it. You take everything you discussed, all these concepts, ideas, and meaningful points, and try to concretize them into one unified (no pun intended) concept for yourself.

This means prioritizing. You can’t focus on everything. You have to take some of the meaningful things you talked about and say, “Okay, this is secondary.” You need to decide which points will be your primary focus.

Once you have a centralized concept of who you are, what you do, and why it’s meaningful and once it’s really clear to you – the next step is execution.

Because communication about who you are isn’t in the tagline on your homepage. It’s the nonverbal stuff. It’s latent. It’s everything you do. All the content you create, the activities you engage in should all signal and speak to who you are.

Integrating Identity Into Marketing Strategy

Mordy: This is where you start integrating all the work you did in those sessions into your actual marketing strategy.

It’s a three-step process:

  1. Sit down and have deep discussions to discover what’s meaningful.
  2. Prioritize: Decide which meaningful things you’re going to focus on.
  3. Integrate: Unify those concepts into your brand actions and strategies.

Does that make sense?

Katie: So no competitive analysis at this stage?

Mordy: I would encourage you not to look at your competitors yet. All you’re trying to do is figure out…take away the idea of brand for a second, take away the company. If someone asks you who you are, you don’t answer by thinking about your competition.

Instead, you ask yourself: What’s really meaningful to me? What do I really want? What do I want people to know? What do I like to focus on? All those kind of questions and you start pulling that out.

Katie: Exactly. Authenticity should naturally help differentiate you. It should, right?

Mordy: And that’s another thing, by the way, which is a great point that you bring up. It’s technically possible that you could find an identity of who you are that’s really meaningful, that has a layer of depth, that’s not the surface-level nonsense that a lot of brands fall into. It can be super clear to you, and it can be difficult to differentiate. It could be the exact same thing as another brand, but that’s a very, very unlikely thing. It’s a technical possibility, but I don’t think it’s an existential possibility.

Katie: That makes sense. If you think of a brand as an individual human, no two humans are alike. So neither should two brands be alike.

Mordy: Exactly. If you’re doing this exercise correctly, you’ll naturally create differentiation. And if you feel like you’re not, it means you haven’t dug deep enough yet.

Brand Identity Guides Real-World Implications

Katie: Full disclosure: We actually went through this brand identity exercise with Mordy at Search Engine Journal. It was extremely helpful, and like you said, it also trickled into real world actions. It’s helping to inform some of our product strategy and other things we’re planning on doing in the real world. This branding exercise is not just empty calories, so to speak.

Mordy: Thanks for saying that. That’s awesome.

If your marketing team isn’t getting traction and feels stuck, it’s often because you’re not tapped into who you actually are. But once you are, you feel very much not stuck. You get clarity: “Here’s where our product should go. We shouldn’t go that way; we should go this way.”

It’s where you see companies go off the rails with AI, for example. They just jump on every AI thing because they don’t know who they are. They don’t have the ability to say, “That’s not us.” Or, “Yes, we should get into AI, but it should be done in a way that reflects who we are.”

This identity work also gives you focus, traction, and momentum when you’re feeling stuck. We talked about this last time: knowing who you are is very important for figuring out who you’re for.

Katie: Right. That’s a good point. So it can help target your audience as well, who do you want to help? The other thing I found it’s motivating just from a work ethic standpoint, if you feel like you’re burned out or you’re spinning your wheels or you don’t know why you do what you do, it gives you sort of a North star to really connect with other human beings, with your customer, who are you trying to serve and why?

What is that intrinsic motivation that helps you get out of bed in the morning?

Mordy: It’s super meaningful. From a practical point of view, when teams or companies talk about needing an “internal vision,” what they really mean is they need an internal identity that can be communicated across teams. That’s what I feel you’re actually trying to say.

Aligning Brand Identity: A Picture Frame Business Example

Mordy: Let me give you a weird example. Let’s say I make picture frames. That’s my business: I sell picture frames.

If your identity is just, “We’re about making cheap picture frames,” that’s not meaningful. But if you start asking why you’re doing this, you might discover something deeper. Maybe you and your team really value cherishing memories. That’s your motivation. So, your product, the frame, is a way to help people cherish their memories by displaying them.

Half my pictures are still on my phone. They are not cherished. Print them, put them in a nice frame, display them, cherish those memories. But if you say you’re all about cherishing memories and then sell flimsy, garbage frames, that would be a misalignment.

Another company might say, “We want to add artistic flair to your pictures.” Their identity is about art and design. Two totally different companies doing totally different things with their brand identity. And it’s based on who they actually are, and their products should align.

Sometimes you’ll combine concepts. Maybe you believe in cherishing memories, but you also feel that an artistic frame enhances that experience. So, your core concept becomes: “We help you cherish memories by giving them artistic design that highlights how special they are.”

So that would be taking two concepts and unifying them together to create one core concept that speaks of both aspects of who you actually are. You can do five different things with this, it all depends on who you are in reality.

Katie: I can imagine, too, that you could build entire product lines from that concept. Maybe you serve different customer segments, or maybe it’s one customer who wants variety.

Mordy: Your whole product line should be informed by that decision. If you’re saying, “Cherishing the memory means giving it a really fancy frame,” then your products need to align with that. Imagine you bought a Monet…you wouldn’t put it in a cheap poster board frame. You’d give it a beautiful frame that reflects its value. Your memories are paintings; your pictures are memories.

Your products need to align. You’d create product lines of artistic frames to match your identity. If your products don’t reflect who you are, then either that’s not your identity, or you need to change your product to match it.

Brand Identity Drives Motivation

Katie: That makes sense. As a painter, so I can relate to this example. When I don’t know why I’m creating, I stop. The times that I am aligned with this exercise of figuring out who I am and who I’m trying to connect with, and the identity behind why I would be a painter, I’m so much more motivated to show up and paint.

Any time I get lost in the grind of the work week, it often makes me not paint, because I have different identities at different times, as we all do as human beings. Sometimes my work identity will take over. If the painter identity is weak or ill-defined, I can literally go years without painting.

So to bring it back to the concrete reality of what we’re talking about, the same happens in business. It’s so easy to get off track because people have so many priorities shoved at them all the time. So it’s really easy for businesses to become idea generators. If you don’t have those north star KPIs rooted in our brand identity, it’s so easy to go chase shiny things.

Mordy: …they’re all over the place. Businesses ask, “Why should I do this? Shouldn’t I focus on conversions, revenue, traffic?” But defining your identity helps you do that. You’ll target the right people with the right message and avoid wasting time and money on products, marketing, or content that don’t align with who you are.

When you’re confused, you try everything. You waste a ton of time, resources, and money. But if you sit down for a few hours, clarify your identity, you’ll know, “We need to do this, and not that.”

Mordy: Also, identity evolves over time, just like people. Your brand, who you are, why you do what you do, it changes. That’s normal. But it always needs to be clear to you.

People are creatures of meaning. If you can’t attach meaning to what you do, your audience won’t be able to connect or resonate. You’ll face an uphill battle trying to convince people to spend money with you. On top of that, your team won’t have buy-in. You, as the owner or CEO, might be motivated, but your team needs something meaningful to connect with.

That’s why it’s critical to communicate your identity across the entire organization. Don’t stop at the C-suite or the marketing team. Start having real conversations about this with every team member.

Quick Note On ICPs And Personas

Katie: I have one last question for you, Mordy. The idea of the ICP, how much does that factor into this particular step? How would you categorize that part of this discussion in terms of the ICP and the brand identity?

Mordy: That’s a hard question, it’s a whole topic in itself. I don’t like profiling like that. I like intent-based marketing over persona-based marketing.

Katie: Not to open a can of worms late in the discussion, but talk to me briefly about intent-based versus profiling.

Mordy: I’m more interested in why people do things than which person does which thing. Generally, when you’re more intent-focused, you open up more opportunities. But when you’re persona-focused, you sometimes end up with blinders on.

That’s not to say there’s no room for persona-based marketing. There is. But going back to your question about the ICP (kind of a hot take) shouldn’t be part of this process until you’ve figured out who you are.

Should your ICP, your Ideal Customer Profile, influence who you actually are? Does it change who you are? Think of it like going on a date. Should who the other person is influence who you are as a person? That’s not a recipe for success. You are who you are.

Of course, we’re all multifaceted people, but fundamentally, you are who you are. And because of that, you decide who you should engage with, whether that’s Customer X or Customer Y. Not the other way around.

Final Thoughts

Katie: Let me just add one thing. Let’s say someone is flexible as a brand or as a dater. Imagine a scenario where someone has aspirations, whether in business or relationships. Someone who’s an inexperienced business owner who wants to target a high-value customer, but doesn’t yet have the experience to offer real value.

In that case, you have two options. One is to accept where you are, get back down into your league, and serve the customers you’re best equipped to serve right now. The other option is to level up. Get educated. Improve yourself. If you’re aiming for a target that’s currently out of your league, there are steps you can take within reason to grow into that.

But that’s a whole other business development conversation. For the purposes of this branding exercise, it’s about authenticity and being realistic. It’s about knowing where you can truly add value. And at the heart of it, it always comes back to: Who are you? Like you said, it ties back to brand development.

Mordy: To kind of end off with a very simple example, again, if you micro-level this, it all becomes much easier to see. Let’s say there are two groups I want to hang out with. Group A likes baseball games. Group B prefers the ballet or symphony. Both groups seem cool, but I love baseball. That’s my thing. So I should hang out with the baseball crowd.

I’m not a fancy person. I don’t enjoy the symphony. If you do, that’s awesome, more power to you. But it’s not me. I’m not going to force myself into that crowd. Instead, I’ll lean into the baseball group. I’ll amplify that aspect of myself. I’ll get the jersey, the gear to show them I’m part of their group. Because I actually am.

I’m not faking it. I’m just trying to amplify what I actually am to show you that’s who I am. That’s the difference. One is you’re faking it in order to show people like, “Oh, here we go, this is who I am.” Not you at all.

The other way is, this is who I am, and I’m going to try to communicate that to you by all the things I’m going to do. And I might purposely and consciously try to do things or signal to you that “I’m part of your group. I fit in. Love me.”

Katie: That’s amazing. And just from a business standpoint, when it comes to SEO and acquiring customers and traffic, it’s so important to focus on your niche. You’re not going to be all things to all people, especially now when AI is answering all the basic questions.

You need to double down on who you are and speak authentically to your niche. Stop trying to appeal to too many people. The days of the open web firehose of traffic are done. So adjust and adapt.

Mordy: If you’re for everyone, you’re for no one.

Katie: Exactly. Alright, Mordy, we’re at time. Thank you so much for sitting down with me today. I’m looking forward to the next one.

For a free consultation with Mordy, head over to unifybrandmarketing.com.

And we’re at searchenginejournal.com for more content and discussions. Mordy is also a contributor at Search Engine Journal, and any final thoughts?

Mordy: Yeah, come check out the free consultation. And check out the SEJ content.

Katie: Awesome. Until next time. Bye.

Mordy: Bye.

More resources: 

Featured Image: Paolo Bobita/Search Engine Journal

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