Beyond Google: Redefining SEO in LLMs and an AI-First World with Heather Physioc of VML

In this episode of The Simple and Smart SEO Show, host Crystal Waddell welcomes Heather Physioc, Chief Discoverability Officer at VML, for a deep dive into the evolving world of search and digital strategy. 

Heather shares her insights on why Google isn't the only search engine that matters, how AI is reshaping the search journey, and why content needs to serve users at every stage—from discovery to post-purchase. 

From structured data to customer retention via social media, this episode is packed with practical takeaways for marketers, SEOs, and business owners.

Key Takeaways:

• SEO Isn’t Just About Google Anymore: Platforms like TikTok, Pinterest, Reddit, and in-platform AI search tools are becoming vital in the discoverability ecosystem.
• AI Should Enhance, Not Replace Creativity: Use AI to eliminate repetitive tasks and streamline workflows—not to substitute authentic human communication.
• Brand Experience Matters Across the Entire Journey: From awareness to post-purchase content, every touchpoint contributes to discoverability and trust.
• Structured Data Is Critical for E-commerce SEO: Schema and well-organized product feeds prepare brands for AI-powered commerce search.
• Jobs to Be Done Framework is More Relevant Than Ever: SEO should be rooted in solving real user problems, especially in the age of contextual, compound queries.

Episode Highlights:

• "Google is not the only platform out there where people are engaging in search activities." – Heather Physioc
• "Jobs to be done isn't just a theory—it's a way to make your brand truly useful across all channels."

Listener Action Items:

1. Reevaluate Your SEO Strategy Beyond Google: Identify where your audience is searching and tailor your content accordingly.
2. Use AI Thoughtfully: Let AI handle grunt work so you can focus on creativity and strategy.
3. Audit Your Customer Journey Touchpoints: Create or improve content that supports awareness, comparison, and retention.
4. Implement Structured Data Markup: Prioritize schema to support AI discoverability in commerce platforms.
5. Map Jobs to Be Done: Understand the real problems your

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Chapters

• 0:00 Introduction and Guest Introduction
• 1:05 Heather's Role at VML
• 1:29 First Encounter and Impact
• 1:56 AI and Efficiency in SEO
• 3:56 The Evolution of Search Beyond Google
• 6:02 Brand Experience in Search
• 7:36 Retention and Social Media
• 10:08 Opportunities in E-commerce with AI
• 12:55 Connecting Data Sets for Better Insights
• 14:04 Jobs to Be Done Framework

Transcript

[00:00:00] Introduction and Guest Introduction 

[00:00:00] Heather Physioc: But the way this thing is going. That ecosystem. That discoverability ecosystem, is just bigger and more complex.

And that's not up to us, the SEO purists.

That's up to the people doing the searches.

[00:00:13] Crystal Waddell: Welcome to the Simple and Smart SEO show podcast, where we talk all things brand building SEO.

I'm your host, Crystal Waddell, here to bridge the gap between SEO strategy and real world business success.

Whether you're an entrepreneur, marketer, or SEO enthusiast, this is your place to learn, share, and build a brand that stands out. 

So grab a coffee or your favorite tea. And let's dive into Smarter SEO for your business.

[00:00:36] Crystal: welcome back to the Simple and Smart SEO show podcast. Oh my goodness. Do I have a treat for you!

It's a treat for me too. I'm so proud and excited to introduce to you Heather Physioc.

One of the most instrumental voices in SEO for me personally. Not afraid to blaze trails. 

She's not afraid of solving problems.

Heather is the Chief discoverability officer at VML. She's gonna share a little bit about what [00:01:00] she does there. And we'll jump right into the conversation.

Thanks for being here today, Heather.

[00:01:04] Heather Physioc: Thanks. 

[00:01:05] Heather's Role at VML

[00:01:05] Heather Physioc: Yeah, I've been with VML since. Gosh, 2014, now.

So, 11 years. Going on 12. And yeah, my role is Chief Discoverability Officer. So I look after how the agency goes to market for all integrated search and discoverability services.

Whatever it takes to get brands found. No matter when, where, why, or how people search for information.

So very excited to be here, finally.

We've been talking about doing this for a long time.

[00:01:29] First Encounter and Impact

[00:01:29] Crystal: we have!

It's been a couple of years since I came across your work. When I went to my first Brighton SEO conference.

It was the first time they were in San Diego.

I received tickets from Andy Holland who works for JBH out of Manchester.

And besides Andy. It has been your presentation that has just stuck with me.

And you talked all about jobs to be done. So we are gonna talk about that here in a minute.

But I did also share with you that I had been listening to you on some other podcasts.

[00:01:56] AI and Efficiency in SEO

[00:01:56] Crystal: you were talking about like the efficiency increase with [00:02:00] ai.

And how we do our jobs.

A woman who did a guest hosting podcast for me, her name's Shea Karrsing. A copywriter.

She said that she wanted AI to do more of the boring stuff. So that she could have more time to enjoy nature and create.

And not just use AI to do the creative stuff.

How do we balance those efficiencies so that we can actually create more margin in our lives versus more work?

[00:02:23] Heather Physioc: Yeah I completely agree with her position. Like the purpose of AI is not to be a substitute for our own creativity and ingenuity.

And how we as humans communicate with other humans. I don't think AI will ever be able to be a full substitute for that.

But as far as augmenting and accelerating our work. AI is something we've been waiting for a long time. To take the boring grind part out of the work.

So that runway between we have an idea. Or a need. Or an objective we need to achieve.

And actually being [00:03:00] able to actualize that. And get to work. And bring it to market.

That runway is the part that has really shortened for us.

It's things like categorizing large data sets. And drawing out meaningful insights that marketers beyond SEO people can interpret and use. And apply to their work.

AI has enabled more of that. AI has not replaced my copywriters. It's enabled them to produce more at the same high caliber. That we demand of ourselves. By removing the margin of error and the grind work in the early parts of the process.

Like gathering product SKU information. And getting it organized.

Or pressure testing after we've created content.

To make sure it aligns with what we would expect it to be able to do.

Simply generating and creating content?

It's a reductionist way to think about how to use AI to our advantage.

[00:03:56] The Evolution of Search Beyond Google

[00:03:56] Crystal: another thing I heard you say: that search isn't Google first [00:04:00] anymore. And I thought that was really interesting.

As an "SEO practitioner," I joined in this conversation as a consumer first.

I was listening to different people share their ideas on SEO. I was thinking, man. That doesn't really align with the way that I search.

These are obviously tactics that one could use. But they don't really apply to me.

So I was kind of able to enter into this, like considering my own search patterns.

And then fighting that narrative that Google was the end all be all in search.

You said, like Pinterest, and I know that Reddit's been in the news lately.

It isn't necessarily Google first anymore.

[00:04:34] Heather Physioc: Yeah, it's not Google first. It's not Google always, in all circumstances. Now, I wanna be clear.

Google's dominance by no means is projected to go away anytime soon. They have enjoyed more than 90% global market share for something like two decades now.

And that's not something that's gonna turn overnight.

And we also have to remember that Google is a competitor in the AI search game.

The core point is, I think Google was happy to let us [00:05:00] think it because they were raking in the ad dollars.

But Google is not the only platform out there where people are engaging in search activities.

That is, if we think of ourselves only as SEOs. Only about Google, only about websites. We will be obsolete.

Or already are, in many cases.

But when we take a step back. And think about what we're really trying to do here. Which is make content or brands or experiences discoverable by our customers. In the moments that they actually care to receive it.

That's the core, central human truth that never changed.

Regardless of the technology. Regardless of the platform.

But the way this thing is going. That ecosystem. That discoverability ecosystem, is just bigger and more complex.

And that's not up to us, the SEO purists.

That's up to the people doing the searches.

So if we want our brands to be discovered there, we need to understand whether and how our customers are present there.

Greatly expands your depth and breadth of ways that you can serve customers.

[00:05:58] Crystal: Yeah, and it really ties back [00:06:00] to that whole idea of brand experience. 

[00:06:02] Brand Experience in Search

[00:06:02] Crystal: And so what does that mean? What is a brand experience as it relates to search?

[00:06:08] Heather Physioc: It's such an interesting question that I think a lot of SEOs who are used to working very low in the funnel.

Convert. Drive action, et cetera.

It's something that we all have to reevaluate. The way I think about it is: in the search journey, people can enter at any point. Or any number of points along that journey.

It's not linear.

They don't go through one gate, and then another, right?

They may piece together information from a lot of different sources.

Or now through the power of ai, they may synthesize a lot of sources into one answer. To solve their problems.

So to that end, I am encouraging marketers to consider and anticipate. What their brand work will drive. Discoverability wise.

What is gonna drive people to search?

And anticipating that and preparing with the right content and experiences to pay off the promise of brand.

I am advising search people to think [00:07:00] beyond the lower funnel in the lower conversion section of the process.

And instead think about all of the different ways we can augment the work that shows up earlier in the funnel. The objective is not always a conversion or a click.

If it's high funnel awareness, it might be more visibility metrics in ai, LLMs, and traditional search results.

Or if the metric is retention, maybe their priority right now is getting a lot of engagement and action on social media. We can support all of those things and not relegate ourselves into this tiny little corner effectiveness.

[00:07:36] Retention and Social Media

[00:07:36] Crystal: that was really interesting you just said that about like retention. And using social for retention.

I deal with so many new business owners.

And a lot of the conversation is strictly, top of the funnel. It's been awareness for a long time. It's just like driving some kind of traffic, you know?

And that's where I love jobs to be done, because it finally provided a framework for like, why are we doing this?

If you're [00:08:00] creating brand awareness, what's the point of that?

What's the next step? And then what's the next step after that?

And then even more importantly, for after you've actually had the conversion.

After you have the customer.

That's really where I'm really kind of passionate about. 'cause I'm like the type of person, if I go into a grocery store and I can't find something, you know, I'm not an idiot.

So it's like if I can't find something, I ask for help.

I either I'm in a really, really big hurry or I can't find it, you know?

And so the worst thing in the world to me is when somebody's like, okay. You go way over there and, you know, three shelves down, or somewhere along that side is whatever you're looking for.

And I'm like, really? You can't help me? You can't take me over there?

Yes, exactly. Show me. And so I, I try to take that mindset into this entire experience .That entire customer experience from the beginning to the end.

And especially that after the conversion. Like, how can we make that even better?

[00:08:53] Heather Physioc: On that about like, the end of the customer journey-

[00:08:55] Crystal: yeah,

[00:08:56] Heather Physioc: conversations i'm having right now with clients that have [00:09:00] long-term investment purchases.

Large appliances, automotive. Things like that. That require a long sales cycle.

A lot of research. So we're seeing AI search have a big impact there. 'cause it shortens the runway of like comparison and research.

But about after the purchase.

There's a lot of times this fallacy that when you're creating "owner content" for people who have already purchased something, that's not gonna help you get new customers higher in the funnel.

I think we also have to consider when a piece of content or experience can serve multiple jobs to be done.

What we found is that "owner content" often helps shoppers and comparers to determine what the long term benefit or cost or risk of buying the product is.

And determine whether it's worth the hassle to begin with.

[00:09:45] Crystal: Yeah.

[00:09:46] Heather Physioc: saying don't sleep on that.

[00:09:47] Crystal: Yeah, that's such a great point because like social proof.

And getting that recommendation from another person.

TikTok is doing so well, you know. Because it feels like you're getting an actual human interpretation [00:10:00] of whatever experience they had with a particular product.

You're so right. And I'm totally taking notes on that. For some content ideas of my own. Okay, so real quick. 

[00:10:08] Opportunities in E-commerce with AI

[00:10:08] Crystal: before we get to jobs redone: where do you see some of the biggest opportunities in e-commerce with AI search?

[00:10:16] Heather Physioc: Yeah. Some of the biggest opportunities that we are going after for our commerce clients.

There's a couple things that I think are going to influence how we're able to be discovered in both the retailers themselves.

And how the retailers show up in outside search engines like Google for example. The first thing that I think we're all over indexing on is. Connecting the pipes, so to speak. It's like we're already doing a lot of different things for commerce.

But how can we connect those data sets? Connect those efforts? And connect to those people? So that work works harder for the brands?

Because we're seeing that in this landscape of AI search or conversational commerce.

Where it's [00:11:00] effectively AI search within the retailers. They have to source that information and synthesize those answers from somewhere.

And we can be the ones to provide that information.

That dependable, high quality information that can be trusted.

Or we can allow those machines to guess. And reduce the likelihood that customer's going to have the right information. Or a positive interaction with our brand.

So we're really trying to influence that as much as possible.

By making sure our product and brand store and category information is as complete as possible.

Follow that with, I think we should over index on structured data markups.

So schema. And tagging products and prices and weights and classes and things like that.

Right now it hasn't officially proven to be the magic answer to all things AI search or commerce search.

But nowhere is it more important for the information to be structured. Accurate, accessible, than commerce brands.

I think there's gonna be a lot more opportunity in the future as it pertains to product feeds, merchant feeds. And just different [00:12:00] search sales opportunities.

So don't wait to get that data cleaned up, connected and tagged.

Then the last big thing is authority, credibility, trust. So we know that these AI machines are producing masses of junk content.

All fed on content that already exists out there, right? It's just regurgitating stuff.

And so eventually the web is gonna get flooded with a bunch of junk that doesn't even compete with each other.

Although it may be able to compete right now.

And eventually, the AI search plat forms are going to be competing on which ones put out the answers you can trust the most.

They're going to be competing on trust.

Which means we need to anticipate that and make sure we are showing any signs we can of realness.

Humanity, authority. Expertise. Citations. Contact information.

Anything that is real. I think will make us more competitive in the long term.

[00:12:54] Crystal: Oh man. That's awesome. 

[00:12:55] Connecting Data Sets for Better Insights

[00:12:55] Crystal: And you made me think about the whole connecting of data sets.

I feel like [00:13:00] on the customer front side, let's use chat GPT for an example.

You know, you're right. Chat has changed the way that we synthesize information. We're able to get all those sources together versus all the tabs open.

I think I heard you say that. I think it's so true, so smart.

However, for us on the other side as business builders, the data sets are so siloed.

Even from my perspective as an e-commerce seller.

If I'm selling on multiple platforms, I have to retrieve the data from different platforms.

In order to get a full picture, in order to actually tell a data story.

And that's something also that I'm working on right now. 'cause I was like, you know what? I think other people might be having this problem too.

Because it's like, why are tools so fragmented? You know? It's like there are people who have great tools, but then it's like, but it doesn't do this one really important thing that I also need it to do.

Do you know what I'm talking about?

[00:13:47] Heather Physioc: Absolutely. That's been like the bane of my existence for 20 years.

There's always tools that get so close, but they just don't have that one thing. So yeah, we've, we're probably overinvested in too many tools in our tool stack.

[00:14:00] To get a complete robust data set. Which is not a luxury everyone necessarily has.

[00:14:04] Crystal: Right. 

[00:14:04] Jobs to Be Done Framework

[00:14:04] Crystal: when you first shared jobs be done that framework at Brighton SEO.

It completely changed and reframed how I think about search.

And it helped me see that it's not just about keywords.

It's about understanding the real jobs that people are trying to get done.

I used to say, you know, like with social media, I was like, give your social media job, like give everything that you do, every piece of technology, every tool you have, give it a job like it's an employee.

So when you were talking about jobs theory, it just resonated so much.

And so I'm kind of curious how you'd update that approach. With AI in the mix. So if you were teaching jobs to be done for the first time today, what would you do or say differently if anything?

[00:14:45] Heather Physioc: From that talk, I talk a lot about the search journey and mapping how people behave differently in different platforms.

Whether they use them, and how they use them in your space.

And one of the things I've had to do over the years is just expand what a search [00:15:00] engine means.

At first, it was an app store, then it was YouTube, then it was that, then it was this.

So we've already been expanding our idea of what a search engine even is.

We have to add AI search in there. And when we look at a new search engine to introduce into that idea of the discoverability ecosystem.

We are considering, what kinds of use cases. are for that platform? What are the most likely and common ways that people are going to use the technology to solve problems on that customer journey?

I mentioned long sales cycles, any of those large products, appliances, automotive, things like that.

That long sales cycle and complicated research and all those tabs open in your brain trying to synthesize that information.

That was really hard to do in the Google world. Which just further validates our point that it's not always the most efficient or effective way to get information or complete a task.

They can take that information that they're gathering and synthesize it very quickly with these AI tools.

Oh, by the way, those answers are gonna be [00:16:00] completely personalized and contextual, right?

It's not just a keyword anymore. It's a compound query with 15 questions in it all specific to your context.

 The work for us to do there, I think is to deeper and broader.

A greater breadth and depth of understanding of that search journey so that we are not focused only on the transactional.

But also making sure our brands are products or services are appearing in the context of the problems they have.

Their jobs to be done.

If their job is to wash laundry for, a household with five kids and two working adults, and that means there's a ton of laundry.

Then the job to be done is to help them find the right high capacity washer or something like that.

What kinds of questions that person going to ask.

And again, that brings us back to connecting the pipes.

What can we learn from social listening? What can we learn from search intelligence? What can we learn from UX testing?

Or from our conversion and purchase data? Or our call center logs? It's taking whatever you do have.

Connecting it better and getting [00:17:00] smarter about the things we put out to solve their problems.

It's all about anticipating and answering.