How 3 Brands Used AI To Personalize Content At Scale And Won | Ask An Expert

Foreign.

Welcome to another exciting and elucidating episode of the Omnitok Ask An Expert series.

I'm one of your co hosts for today's interview, Anne Mazenga.

And I'm Chris Walton, and we are.

The founders of omnitalk, the fast growing retail media organization that is all about the companies, the technologies and the people that are coming together to shape the future of retailers.

Chris, we have heard from just about every single retail executive we talked to in the last year.

When we're talking to them about Gen AI, one of the number one places they're applying that to and seeing rapid success and transformation is personalization.

Would you agree with that?

Yes, Ann.

And personalization, as you know, is my favorite word.

It is.

You're one of your favorite words.

One of them.

One of them.

I have many favorite words.

You're right.

Yes, fair.

But the reason that they are enjoying this so much is that they're able to create such special personalized content for their customers.

So we thought we'd dive even deeper to kick off this year to learn how retailers and brands are doing this successfully.

And we've brought in Contentful's Global Vice President of Solution engineering, Sarah Sullivan to help the break this down for us.

Chris.

So, Sarah, we'd like to give you a big warm welcome to omnitech.

Hello.

Well, well, hello and nice to meet you and spend some time with you.

Anne and Chris, pleasure to be here.

Hopefully everyone that's listening is coming off some really strong numbers of, you know, Black Friday and Cyber Monday deals as they think about coming into the new year here.

I hope everyone's wondering, you know, proud of what they did and trying to figure out how they're going to top it for next year.

So hopefully we can inspire them today on how they might do that.

Yeah, right.

Yeah, hopefully.

Everybody had a great close to the holiday season here as we start January, so.

And Sarah Sullivan.

I gotta, I gotta, I gotta admit, I love the alliteration of the name.

It's fitting with Omnitalk.

Sarah Sullivan.

That's a, that's a good SS dynamic there.

So.

All right, well, before we get started, just a quick reminder.

For those watching live on LinkedIn, feel free to ask your questions of Sarah and the Contentful team at any time via the chat session window in LinkedIn, which is just to the right of your screen if you're on your desktop computer.

All right, Sarah, let's get started with this.

Let's start like we always do with our guests, like give us a little bit about your Background and what Contentful does?

You bet.

Well, I'll start with Contentful.

So Contentful is a digital experience platform that now offers personalization capabilities.

So this is a perfect topic and timing for for all of us to be speaking here today.

Contentful is really about empowering brands to deliver digital experiences quickly, efficiently, at scale for what they're based on how their customers expect them to be messaged and tailored to them as an audience.

Our platform helps teams structure and manage, personalize and scale content across global brands and regions and products, all while leveraging AI.

And we work with key brands like Ikea, Ed, Vodafone, Ruggable Bang and Olufsen and a whole bunch more.

And we'll share some of those stories with the audience here today.

Awesome.

And what's your background?

Yeah, yeah, I'm based here in Los Angeles and I lead, as you mentioned, our global solution engineering team.

We're all about focusing on how customers can leverage our platform to really drive and accelerate value.

I've been with Contentful four years now, and for the last year, I've really spent a lot of time focusing on AI and how our customers can leverage it in their marketing operations to really speed things up.

So we'll try to share some ideas and examples today on how some of our customers are doing that and how organizations can be thinking about doing that here in the near future.

Sarah, that's awesome.

I mean, I think I'm almost curious, like, you've been doing this for a while and like I said in the beginning, AI is really something that we're hearing.

So many brands, so many retailers have success with, but maybe give us a little bit of kind of where it's been, where it's going, and how retailers should start to think about approaching leveraging something like AI to help them further personalize content for their customers.

Yeah, I think before any organization can even think about AI and what it means to their teams, it first starts with the foundation of how you operate today.

And because I'm hoping there's a lot of brand and creative people on the phone today, I'm going to start with.

It starts with idea generation.

Okay.

We talk to so many brand and creative folks where, you know, it's.

They come up with all of these amazing ideas of campaigns and experiences that they want to create.

And it's all about how do you drive engagement with the audiences.

But for so many brands, they talk about this idea of like, these creative ideas go to die because they don't have the solutions in place to actually bring Them to life.

Life quickly.

One of our customers is audible.

Abby McInerney there.

She's the senior brand creative director at Audible, and she was sharing with us.

Unfortunately, it's a terrible.

Not a terrible term.

I love the term.

It's a.

It's a unfortunate consequence.

She talks about the creative graveyard.

She's like, my team comes up with all of these amazing ideas, but because our solutions don't, we can't work fast enough.

We can't bring these experiences to life fast enough.

She talks about how these creative ideas go to this creative graveyard to die.

And she's like, it's so frustrating because, yeah, she's like, my team is amazing at what they do.

And so they came to us a few years ago, and this was the problem they were ultimately trying to solve.

They wanted to have a platform in place that allowed them to move faster, that allowed them to bring all of these amazing ideas live, you know, bring them to their consumers and engage with their customers in new, exciting ways.

And that's ultimately why they deployed contentful, and they've seen tremendous success as a result.

Explain that a little bit, too.

And, like, how that's like, in the day to day, like, what is that changing for the creative teams then now that you're saying work faster, but, like, if you can explain even more, like, what's the team at Audible doing now that they couldn't do before?

Well, I'll go back to one of the core challenges that a lot of these, most organizations have is that they want to be able to bring an experience to life and have it be consistent across all of their digital channels, right?

And so think about.

Think about a consumer's journey with you as a brand.

They might start on social media.

Maybe we're.

We're scrolling and we see an ad pop up that piques our interest and we click through it, right?

And as we click through it, maybe we're dropped into your brand's website, and now we're scrolling through the website, and maybe something pops up at the top that says, hey, would you like to download our mobile app?

Well, sure, yeah.

That probably creates for a better shopping experience.

So maybe I download that mobile app and now I'm scrolling through, I add the cart.

I check out, as I finish that checkout process, I get an email.

And all of a sudden, if you think about that, I've just gone through four different digital experiences.

Social, web, mobile, and email.

And for most organizations, those are four separate technologies, four separate teams, four separate experiences.

And if across those four different experiences, it's very easy for content and look and feel and experience to get out of sync because they're managed by different teams and different solutions.

And this channel is so real.

And so what I look at, like, why do customers come to Contentful?

It's because they want to have this consistent look and feel and experience across all of their digital channels and they need to be able to do it in an efficient way.

And this comes back to this very simple concept of create once, reuse everywhere.

Create once, reuse everywhere.

If you publish an experience, you should only have to create it in one place and it should automatically replicate out to all of those different channels.

And so when I look at customers like Sephora, they want a consistent experience across web, mobile and email.

When I look at Ann Taylor, they came to us because they wanted the same experience across digital as well as in store.

When you walk in one of their stores, they have big digital signs.

It's the same content being presented in both places.

Doordash, another customer of ours, they came to us because not only do they want to control the experience on the mobile app, but when they integrate with third party apps like restaurants and other ordering solutions, they want that same content to be reused across all of those different platforms.

That is a challenge for most marketing teams.

The ability to do this quickly and have it consistent is not easy for most organizations and it's because they're not set up in the right way to truly do it.

So, Sarah, the consistency part makes sense 100%.

Like, I'm totally bought in on that.

The other part of this too though, that I want to make sure that if it's happening, I want to make sure we're calling it out too.

So there's making it consistent across all the different touch points, but then there's also doing more of it as well.

Is that a piece of the contentful platform as well that you can help the retailers and brands actually get to those ideas, those creative ideas that end up in the graveyard, so to speak, that you can actually do more of them and then also make all of those additions more consistent throughout the entire user experience as well.

Is that right?

Absolutely.

And I think the biggest challenge to more is not only the creative idea part and we can talk a little bit later about, like, how does AI come into play and help help stimulate that process.

Yeah, but I actually think it comes down to scale for most organizations.

They're trying to operate across multiple brands, multiple locations, and in many cases across multiple products.

And for most organizations, organizations, there's this Kind of push and pull.

There's the corporate side of it that's saying, well, hey, we want to have a consistent brand and experience across all of our different regions and locations.

And they want a certain amount of control and governance.

But when you talk to the people in the fields that are operating in those regions and locations and products, you know, they also want to have some control.

Right?

They want to be able to take the corporate elements and then tweak them, modify them for their specific needs for the audiences that they're trying to serve.

And so you get this, this push and pull between large organizations that if you don't have the right solution in place, it's very hard to manage that consistency at scale.

A great example of this is one of our customers, UiPath.

They came to us a few years ago and at the time they were operating across 20 different product lines.

And the way they described how they internally worked is every product line operated independently.

And so if they wanted to make a change at the corporate level, maybe there was some kind of change in the way that their brand was going to be brought to life.

They had to basically set up 20 work streams, one with each product line, to go get those up sites, even just to their website.

It was a huge maintenance issue.

It was a big program management problem.

And they came to us and they said, oh my gosh, there has to be a better way to make these kind of corporate changes and, but still allow the product lines to operate in the manner that they want to operate.

Right.

They should be able to make changes to a product page without having to get developers involved.

They should be able to make a change on a product page that reflects a new feature or function or capability or value statement that's coming out.

And so they're like, we need to be able to have a solution that allows us to manage this push and pull between corporate and then, you know, the regional or the, or the product line aspects.

That's ultimately what Contentful allowed them to do, to create these things once automatically have them filter down across all of the regions, the locations, the product lines, but yet allow those, those separate entities to also have the flexibility that they need.

So, Sarah, that all seems pretty straightforward, you know, when you, when you explain it that way.

But is there anything else that keeps brands from, you know, taking action to the degree that you're describing?

I think the other challenge.

So there's obviously a technology aspect to it.

I think there's also a solution and the way that teams are structured, if you separate your teams into Web versus mobile versus email versus social.

They're going to all look at this problem differently and want to solve it in different ways.

And so when I think about themselves.

And their old medium.

Yeah, yeah.

They're not concerned about the omnichannel approach to getting to the customers.

Yeah, yeah.

And so it's like a good organizational leader will look at this and say, like, do we need to rethink how we're structured and how we operate?

And so, yes, there's a technology aspect to it, but there's also this change management aspect to it that comes into play.

The other thing that oftentimes comes to mind for me is cpg.

I think CPG oftentimes looks a little bit different than retail.

Oh, 100%.

Yeah.

So CPG is oftentimes this, you know, they're, they're operating in this mode of like B2B2C.

Right.

Where they're selling to distributors who are then selling with the end consumers on their behalf.

And we hear so many organizations come to us with this challenge of like, hey, I want to engage with my end consumer.

I want to own that first party data.

In many cases, they have no first party data at all.

No step.

Step one is get some first party data and then step two is figure out how to engage with it and get them to like, interact with you.

A few years ago, Kraft Heinz came to us with this exact problem of, you know, they knew they needed to start having a better conversation with that end consumer, but they knew they needed a solution to be able to solve this.

And so it was this combination of like cdp, like some way to actually store this first party data and then some way to be able to stand up experiences really quickly and be able to do that across all of their digital channels.

But most importantly, being able to do it in a way that they can actually talk to the audience and actually have different messages depending on who the audience is, where they're at, where they're coming from.

So that was extremely important for them when they came to Contentful to help them solve this problem.

And they've, they've had tremendous success doing it.

Well, Sarah, one of the things that, you know, we deliberately call out several brands here that you've helped, you've mentioned, mentioned several that you've helped with this.

But one of the things that you just talked about that I want to dive a little bit deeper into is the ability to, you know, at scale, create assets that then the individual, whether it's individual stores, if you're a cpg, like Kinds and you're, you're distributing content to everybody around the entire U.S.

or if you're a retailer that's really trying to personalize, you know, different messaging for your customers across different geographies across the country.

That's, that's what I'm hearing from retailers.

Like core examples, like we put a mason jar in this ad that went to our customers in the south and put the lemonade in that versus, you know, a lowball glass, which we did on the east coast, like, those kinds of messages are resonating better with some of their consumers.

So maybe if you can dive into, like highlight a couple brands here that you've really seen, can get into that regional messaging and can really, you know, see the results from, from the stuff that you're talking about here when, when they've deployed contentful craft.

Heinz.

I'll stay on that story here for a little bit.

Yeah, let's do that.

Yeah, that's similar to what you just talked about.

You talked about geo, right?

Kind of geotagging and recognizing where is the audience come from.

They had a very similar observation.

So when they came to us, one of their comments was, hey, we recognize one size does not fit all.

Like, one message is not going to work for every audience.

And it's sort of this kind of foreshadowing of where AI is going to come in.

But they came to us and they said, okay, great.

How do we set up different landing pages, different engagements, different experiences depending on these different segments of our audience.

And they specifically wanted to start with geotagging.

And what they recognize that if a consumer is coming from, say, Los Angeles, like me, maybe they want to advertise to me, I don't know, organic mayonnaise, maybe they think that product would resonate great with me.

But if an audience is coming from the east coast, for example, maybe they want to advertise their mustard.

And so what they did is they basically utilized our platform to set up different landing experiences depending on the geotag.

And then they utilized our personalization platform so they could very easily capture where is the audience coming from and serve up the right landing page, the right tailored experience based on the location of that consumer.

Like, how many are we talking about here?

Just.

Sorry to interrupt you, but, like, just how are, how many versions are we talking about people being able to do?

Like, I think East Coast, West Coast?

Sure.

But I think that's the thing that, you know, when we first started talking to you at Contentful, like, that was the thing that really shocked me.

It's like it's not just you know, four total, it's like multitudes.

Like there's so much to that you can do.

Well, I love that you asked this question because in their case they've done this for over 100 different GEOs.

Yeah.

And by doing so they saw a conversion rate grow by 78%.

Like that's a meaningful amount.

But this goes back to old school versus new school.

Old school.

Oftentimes these solutions sat into different teams.

You had to have developers involved in order to set up an experience.

You had to have marketing people creating 100 different experiences.

Yes.

Really, really time consuming and a lot of labor in order to do that.

And so organizations need a faster, more efficient, easier way to be able to set up that customized content or tailored content and be able to automatically generate those audiences on the fly.

That's where we leverage AI because our AI can actually start suggesting to a marketer hey you have a series of of your audience over here that looks like this, that has this kind of personality or this kind of of of of tagging elements to it you and then we can suggest, we think they would respond to this kind of content.

And so it starts to give the, the marketer almost like this sidekick, like a coach like hey, try this experiment with this, see if it works and if it works then deploy it at.

Scale and be able to do it.

I mean I think that's the thing.

You get a lot of teams like well like you said, ideas that go in the graveyard.

But it's like this could work or this could work and there's just, there's not.

You don't have the bandwidth to do it.

Yep.

Another great example I think you talk about team size is kind of where your mind is going.

Another one of our customers is ruggable and they looked at this for them it was a less about geo but it was more about paid ad, paid keyword searches.

A lot of organizations do this, right.

We buy Google Ads based on keywords and what they recognized.

Oh for those folks that don't know what ruggable is, it's a fantastic solution.

It's washable rugs.

I have a couple in my house.

I have cats.

Fantastic.

We're just picking the top up, throwing in the washing machine.

They wash up beautifully.

If you don't have one, I highly recommend checking it out.

And, and in their case they wanted to.

They first experimented with keyword buys on rugs for cat owners and rugs for dog owners.

Right.

If you think about it, right.

Different needs you know, right.

To different things.

And so they would buy those keywords and then drop the experience, the individuals or the consumers into landing pages tailored with content for either dog owners.

So maybe it's a picture of a beautiful rug with a dog sitting on it, or maybe it's a picture of a rug with a cat sitting on it, depending on which keyword you came in by.

And with that particular campaign set, they were, they saw conversion rates increase by 25% just by being able to leverage the keyword ads that they were buying and dropping people into customized and tailored experiences.

They do that with a team of less than two people.

And so it's just, you don't need huge teams in order to set these things up.

They can set up a new landing page in under an hour and they can then, you know, set up the, the marketing campaign or the, the personalization campaign in a couple of minutes because marketers can do it.

They don't have to get developers involved.

They can actually do it themselves right in the platform.

So where you create the content is where you also set up the experiment and the personalization campaign.

It's very simple, super easy, and it allows teams to really try things out very quickly to see what's going to work.

Yeah, that's, yeah, that, that, that is the power of AI.

So I want to, I want to get the brass tacks on that then.

Sarah.

So, like, you know, we always talk about people, technology and process on this show.

Right.

And in order to make this type of thing happen.

So, you know, you've, you've alluded to companies restructuring their teams to kind of go after this idea.

But, you know, what have you seen work in terms of the restructuring and also, like, what are the metrics that different organizations are starting to use to understand their progress in this arena?

Yeah, of course, I'm going to come back to.

It starts with the solution, right?

Like, do you have the technology in place to actually solve this?

And you know, to me, it's a modern technology platform that actually allows you to move quickly.

We hear so many organizations, organizations say they have these legacy solutions or these web page builder solutions.

Web pagers, just the name is antiquated.

Yeah.

And they have two challenges.

Guess what the first one is they're built for the web and they're not.

Built for alternative web builders.

Yeah, right.

Yeah, right, yeah.

And then the other one is they force teams to work in a siloed manner.

And you can start to hear this kind of recurring theme that we've been chatting about is like Teams can't work in silos anymore.

They have to, yes, they have to have control and governance, but they have to be able to operate as one.

And when you think about like some of these legacy solutions, there's a team that manages the web and then there's a team that sets up personalization and experimentations.

There's another team that does all the analytics and the analysis of the data.

And it's like that should be available to everybody or definitely available to the marketer.

They're the ones who are like, empower them to make decisions with good information and tools that allow them to move quickly.

And so this, this legacy mindset seems to be falling short and folding organizations back in terms of being able to do more and speak to those audiences in a tailored kind of personalized way like organizations want to.

So that's number one.

So start with the right foundation.

And then number two, I think it comes down to, is scaling how your team works.

And this, to me the answer is AI.

You know, you need a solution that actually has AI built into the platform that actually allows you to move quickly.

And I'll, I'll give you an example.

One of our customers is Klarna.

And so if you're not familiar with Klarna, it's a payment option, kind of like a pay over time option.

It's very common in retail websites as a, as a payment option when you're checking out.

Klarna came to us a couple years ago and they actually started with kind of an unnormal use case for us that like we want to stand up a knowledge base.

And a knowledge base for them was basically kind of an FAQ blog site, a place for consumers and customers to go and get answers to questions.

Great use case to start with.

So they started there and then when AI came onto the scene, they recognized that they were sitting on a ton of content that had structure and meaning that they could use to go tune an LLM.

They chose to tune a version of OpenAI so their own private LLM that's been tuned with their own content.

And as a result of tuning that LLM with their own information, what they saw is that the results that came back out were of high quality on brand.

They could tailor them with their voice and they could make sure that they were accurate and consistent.

And so because they had started with this one use case of just putting content in contentful, they now could tune an LLM very quickly.

Why?

Because we're API first.

It's very easy to extract that content out to tune an LLM.

And now they have high fidelity results coming back out of their AI engine.

And they've now used this AI engine in a variety of ways across their company.

The first use case they used it in was in a customer support option.

So what they found by putting it into their customer support operations, the first year alone, they are estimated to save over $40 million in support costs.

And how, like, what are they doing differently?

Like, yeah, what are they doing differently in their customer support function?

Now, as questions come into the customer support operations, this engine is answering 75% of them with 100% accuracy.

Got it.

So it's just, it's just cutting down the need for labor to be able to support that part of the organization.

But they haven't stopped there.

They've taken the same tuned LLM.

They use it as part of an employee bot to answer questions internally.

Their legal team is using it to write contracts.

Their marketing team is using it to do sentiment analysis.

Their marketing team is now actually leveraging it back in contentful to generate copy.

So when we talk about creating messages tailored to the audience, they're doing that why?

Because the AI engine can suggest recommendations to a marketer.

Hey, for this audience, this is what the content should look like, or here's what, the message should be tailored for that audience.

Now, their marketers are still in control, because I oftentimes get this, oh my God, is it running autonomously?

And the answer is no.

Their marketers are still in control, but they're leveraging AI, generative AI, to do 80% of the labor, the work for them so that they can look at it, review it, tweak it, modify it, and then publish.

They're using it also to translate content on their websites.

And I think if I was a marketer sitting out there going, where do I get started?

To me, translation feels like the obvious place to start.

These LLMs do translation extremely well.

And many organizations have multimillion dollar budgets in place with third party service providers that they're using to translate content.

This is a prime spot for where you could begin to leverage generative AI and save your organization a whole lot of money.

So Sarah, the former producer, project manager at a retailer and me is like thinking through the process of how this all happens.

I mean, is this, is this like a dashboard then?

So like, how is this changing?

I guess the workflows?

Because in my mind, with, you know, legal being a part of this and the brand teams and the marketing teams and all these things like putting all this data in Here and being, having all the use cases that you just outline, like how are, what does this look like for me in that producer role or project manager role?

Like am I, am I actually having people like go in here to kind of approve things too?

Like, is this, how is it, how is it working?

Well, you've nailed it, Ann.

And it's exactly that.

And so this idea of workflows becomes extremely important.

Organizations are going to demand, they're going to need a couple of things.

One, the ability for workflow to be automated to automatically engage all of these constituents along the way when they're needed in order for this to move quickly and efficiently.

And so being able to set up those workflows, number one, is really important.

But it's also things like collaboration tools that we've all become accustomed to using.

So I think about like editing a document even with you all.

As we're preparing for today, we need things like commenting right on the page that's important and essential in order to operate quickly.

That's what's built into contentful is the ability to comment, the ability to mention like, hey Chris, can you review this section that I just built out?

Does this look right for you?

Or hey, legal, I know I got some legalese terms in here.

Will you take a look at this to make sure that I haven't, you know, manipulated this in a way that's not effective.

So that's extremely important is having those collaboration tools built in.

It's got to integrate with where we all live and breathe.

So it integrates with slack Microsoft Teams because let's not get around, that's where we all spend 90% of our time most days anyway.

So like it's got to automatically alert me in my, you know, my day to day tools to let me know something to do.

Right?

Those are the collaboration tools that we know and expect and have to have in these solutions.

And then the last is the auditability.

Right?

Like at the end of the day we need to be able to track and understand who did what along the way.

And a lot of these kind of early stage solutions that we see in our space, they're great with some of these, you know, basic features, but they really struggle when you get into the corporate governance, auditability, security features.

And so this is where I encourage organizations that, hey, if you're preparing for the future, make sure you're looking for these things in your platforms.

All right, Sarah, well, let's close out with this.

And whenever we get a guest, we always like to see if we can you know, we like to tell our audience a little bit about what, what else is coming.

Like, where's this going next?

That's kind of a hallmark of how we try to end our shows wherever possible.

So, you know, in that vein, like, what would you tell people in terms of how they should prepare for what is next when it comes to the further evolution of the technology as you've been discussing it here for the last 20 or 30 minutes?

Oh, let's predict the future.

Is that what we're doing?

Yeah, of course.

100%.

Okay.

Yeah, easy, Nostradamus.

Yeah.

Well, I think the first one I'll go to, which we started to allude to, which is if you think about personalization at scale, scale, I think there's a near future not very far away.

I'm talking months, not years, where personalization is no longer going to be human to human interaction and it's going to be system to system.

And we've.

What does that mean?

Yeah, well, we've kind of coined this term of your solution needs to support infinite flexibility because we're not very far away from a future where you're going to put in a core content message and the solution will be able to at a high fidelity result, so high accurate result, be able to automatically take that content and create variations based on all of your audiences.

And so what most organizations today struggle with is being able to get beyond 4, 5, 10 audiences because it just takes too much labor to do that.

The future is near where solutions are going to be able to do personalization on a one to one basis.

That is not very far away.

The second one I is you got.

More than one prediction.

I'm still processing the first.

Yeah, yeah.

The second one is, is less about a prediction and more of the aha.

That I think a marketing leader should be careful of.

I see a lot of these marketing solutions.

If you look at a Martech stack for any organization, they probably have 5, 10, 15, 20, maybe north of 20 solutions in their marketing technology stack.

Every single one of these solutions is deploying AI.

But what's happening is behind the scenes is they're all using their own AI model.

Remember when I told you about Klarna and I said the reason they did this, they were so successful, is because they recognized day one, we are not going to go tune 20 different AI LLMs behind all of these solutions.

We're going to tune one LLM because you don't tune an LLM once, by the way.

You have to continuously tune it.

We're going to tune one LLM and every solution in our tech stack is going to point towards that LLM.

That's important because it takes a ton of time and energy to go do these to tune an LLM well and you don't want every solution to have to A, to go do that separately 20 times and B, they're going to produce very wildly erratic results if you tune each of them separately.

So I think good marketing leaders should be thinking about and asking their IT team, how are we going to tune one LLM and use that across our marketing tech stack?

Which also means when you're going out and buying marketing solutions, you have to ask, can we bring our own LLM?

Or how do you tap into and integrate with our core LLM?

Because I want to own that as a marketing leader and do that once so that I can control the consistency of the results.

So my last kind of tagline or prediction or recommendation maybe is to marketing leaders is think about your strategy and how you're going to tune one LLM versus a whole bunch of these.

That will happen.

Oh, go ahead and.

But that's like I was just going to say real quick, that's like an entirely new muscle to exercise for the average CMO too.

Like that's got to be a difficult task for them.

But go ahead.

Ann.

I'm sorry.

Oh no, I was just going to ask a simpler thing.

I was like, how many marketing leaders have even that in their vernacular?

Because that's the thing too.

Like I, I mean I think of the marketing leaders now and it's, I'm sure they're more well versed in LLMs, but like, are, are they thinking about it this way in, in the examples that you shared today, the Kraft Heinz people, the ruggable people, like, are they even prepared at that point yet?

I think the leading edge organizations, the ones that do this well and actually see the results coming in the return on investment.

This is how they're thinking and this is how operating.

They're going through the hard work of doing the change management to restructure their teams to think about how their solution works across all digital experiences, to think about how do we create content once and reuse it across all of these.

Like they're doing the legwork now to prepare them for the future.

Yeah, there's a little bit of go slow to go fast in what you're saying as well, which is also important.

So that was a great nugget drop, some great, great ending predictions there, Sarah.

So, so that was great.

So if people want to get in touch with you.

Pick your brain, learn more about Contentful.

What's the best way for them to do that?

Well, a couple of ways.

Obviously, we're on LinkedIn here, so feel free to connect with me via my LinkedIn profile.

It's Sarah S A R A.

My mom always said I was short, so I had a short name.

So sara.sullivan.

and you can also reach me via email, sarah.sullivanontentful.com awesome.

Well, that wraps us up.

Thanks to Sarah Sullivan of Contentful for sitting down with us today.

And thanks to all of you who joined us live to watch this interview on LinkedIn.

And thank you to all of you who may be listening in later as well.

And on behalf of all of us at omnitalk, as always, be careful out there.