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Index/Marketing/Marketing Beyond with Alan B. Hart
Marketing Beyond with Alan B. Hart artwork

40: Preparing marketing data for AI: Insights from jeweler David Yurman's global head of CRM, data, customer experience and loyalty, Neha Kovach

Marketing Beyond with Alan B. Hart · 2026-05-13 · 25 min

0:00--:--

Key moments - from our scoring

Substance score

56 / 100

Five dimensions, 20 points each

Insight Density12 / 20
Originality10 / 20
Guest Caliber14 / 20
Specificity & Evidence9 / 20
Conversational Craft11 / 20

Neha Kovach brings a rare combination of luxury retail, e-commerce, and data strategy expertise to the conversation around preparing organizations for agentic AI. At David Yurman, she's responsible for customer strategy, CRM, data analytics, and loyalty programs across a global luxury jewelry business. Rather than focusing on common AI use cases like customer service agents answering "where's my order," Kovach advocates for deploying agents to influence conversion, identify high-propensity customers, and proactively target retention opportunities within CDPs and data lakes. She emphasizes that successful agentic deployment requires three foundational elements: cleaning data, contextualizing information through metadata (redefining terminology like "customer engagement" to "days since last purchase"), and building a robust customer master that agents can read and act upon. Kovach also addresses the emerging complexity of agent-to-agent handoffs, particularly around MCP (Model Context Protocol) strategy, and the organizational changes required to manage agents as workforce augmentation. She references real-world examples like Riddell's success with sales coaching agents and discusses how future retail will require brands to communicate with customer agents rather than directly with consumers, fundamentally shifting how content, personalization, and commerce operate.

Key takeaways

  • →Clean data and contextual metadata layers are prerequisites for AI agents to identify patterns and opportunities; simple examples include transforming 'customer engagement' to 'days since last purchase' and contextualizing birthday data with messaging triggered weeks in advance.
  • →The highest-value agentic applications focus on revenue influence - proactively identifying top customers at risk of lapse or with high purchase propensity - rather than reactive customer service use cases.
  • →Agent-to-agent orchestration via MCP strategy is critical for seamless handoffs between data discovery agents and copy generation agents, requiring clear ownership, QA, and accountability structures within organizations.
  • →Future commerce will require brands to optimize for agent recommendation rather than direct consumer interaction, fundamentally shifting marketing content strategy and creative storytelling around customer intent rather than product features.
  • →Customer attention span and intent complexity are the central threats facing marketers; understanding how Gen Alpha consumes information instantly and contextualizing messaging around diverse customer needs will determine competitive advantage in an agentic retail environment.

Guests

Neha Kovach

Topics in this episode

Personalization at scaleDavid YurmanCRM and CDP (Customer Data Platform)Customer master dataAgentic AI and agent orchestrationMCP (Model Context Protocol) strategyData contextualization and metadataSales coaching agentsRiddell agent implementationGen Alpha consumer behavior

Questions this episode answers

What's the first step to prepare marketing data for AI and agent deployment?

Start by cleaning up your data definitions, building or auditing your customer master, and restructuring how you label information so agents can parse contextual cues - for example, renaming 'customer engagement' metrics to 'days since last purchase' so agents immediately understand customer recency status.

What's the real value unlock for agentic AI in retail beyond customer service?

The biggest value comes from using agents to proactively identify revenue opportunities - such as discovering your top 10 at-risk customers or high-propensity buyers and recommending contextual outreach - rather than just answering transactional queries like order status.

How do agents-to-agents handoffs work in a marketing context?

One agent identifies high-value customer targets with contextualized reasons (e.g., at-risk of lapse); that information then passes to a copy-generation agent that pulls relevant creative and templates; MCP strategy ensures seamless information flow and measurable execution between agents.

Who should own and manage agentic AI in an organization?

As agents function as workforce augmentation, there must be clear ownership, QA, and accountability for each agent's performance; this requires new organizational roles and disciplines to monitor, improve, and measure agent effectiveness over time.

How will agentic AI change shopping behavior next year?

Agents will become the primary decision-maker loyalty point for customers, filtering recommendations based on consumer intent rather than brand preference, meaning brands must optimize for agent recommendation rather than direct consumer persuasion.

What our scoring noted

Our reviewer’s read on each dimension, with quotes from the episode.

Insight Density

12 / 20

The episode contains useful tactical guidance on data preparation for AI (structuring metadata, contextualizing customer data with examples like 'Days since last purchase' and birthday messaging) and agent deployment strategy (identifying value unlock areas, agent-to-agent handoffs via MCPs). However, much of the runtime is spent on personal background, motherhood, neuroplasticity, and quantum physics tangents that add minimal operational value for a B2B marketer or operator. The core AI/data insights are present but diluted.

the foundations are rooted in cleaning up your data, contextualizing your information, and building a customer master
if your birthday was four weeks away, then now the message could actually read, Your birthday is four weeks away. I would love for you to come in for A, B, and C

Originality

10 / 20

The guest rehashes familiar frameworks: data cleaning, personalization, agent-to-agent orchestration, and meeting prep automation are all established concepts in martech discourse. The framing around 'talking to the agent instead of the customer' and intent-driven storytelling are reasonable takes but not particularly contrarian or first-principles. The metaphysics/quantum physics detour is novel to a B2B podcast but irrelevant to substance. Overall, recycled martech wisdom without sharp counterintuitive arguments.

How about changing that terminology from customer engagement to say, Days since last purchase, right? Because that will allow the agent to even just pick up that contextual information
message at the right time, but we haven't like, landed that plane yet. I think agents will help us get there a lot faster

Guest Caliber

14 / 20

Neha Kovach is genuinely credentialed - Global Head of CRM, Data, Customer Experience & Loyalty at David Yurman (a recognizable luxury brand), with stated experience across $1B - $10B+ revenue organizations, Salesforce implementations, and omnichannel transformation. She is a practitioner, not a consultant or pure thought-leader. However, the episode underutilizes her depth; much time is spent on personal biography and unrelated philosophy rather than extracting detailed operational wins or learnings from her actual roles.

Global Head of CRM Data, Customer Experience, and Loyalty at David Yurman
I lead customer strategy, clienteling, CRM, data analytics, and then led me to David Yurman

Specificity & Evidence

9 / 20

The episode lacks concrete data, metrics, and named case studies. Riddell is briefly mentioned as a success story (meeting prep and sales rep coaching) but zero specifics: no numbers, no timeline, no measurable lift. David Yurman's own initiatives are never quantified. Birthday messaging and 'Days since last purchase' are illustrative but not evidence-based. The guest hand-waves broad concepts like 'top 10 clients' and 'a hundred clients' without actual deployment outcomes or ROI. No revenue figures, conversion rates, or customer retention metrics are provided.

Riddell is one that, you know, just published their success story. They've been able to build an agent that builds capacity and efficiency in their sales force
if I, Neha, work at a store and my efficiency is sitting at, I'm making this up, at like 85%

Conversational Craft

11 / 20

Alan asks reasonable opening questions (career path, David Yurman overview, data preparation, AI deployment) and does follow up contextually. However, he rarely pushes back or probes for rigor. When Neha vaguely references Riddell or makes speculative claims (e.g., 'agents will change everything'), Alan accepts them without pressing for evidence or metrics. The host also allows extended digressions into personal stories, neuroplasticity, and quantum physics without redirecting to substance. Follow-ups are polite but lack sharpness; no productive disagreement or challenge to validate claims.

Yeah, and do you see a world where agents are talking to agents? Oh my gosh, yes.
A piece for all of us to figure out. It feels like there's a discipline in the middle there somewhere.

Conversation analysis

Computed from the transcript - who did the talking, and the words that came up most.

Most-used words

agent35customer29data24agents19start17show15different15experience11david11yurman11marketing11future10information10love9life8daughter8

Episode notes

What does "AI-ready data" look like in a modern marketing organization, and where can it create practical value for marketers? In today's episode Alan Hart talks with Neha Kovach about the practical work marketers may need to consider before AI can deliver real value. Neha is jeweler David Yurman's global head of customer resource management , data, customer experience and loyalty . Neha believes that getting data ready is less about volume , more about structure and context: cleaning it up, defining customers more clearly, and turning general customer data into signals that can guide action - like how recently someone purchased or how close they are to a milestone. She suggests the bigger opportunity for AI may not be routine service, but rather helping marketers improve conversion, retention, and personalization with more relevant timing and messaging. She also points to a separate operational benefit: increasing workforce capacity by helping teams work more efficiently. Looking ahead, she also explores what it might take for brands to compete in a world where AI agents may increasingly shape what customers see, consider and buy.

Full transcript

25 min

Transcribed and scored by The B2B Podcast Index.

Today on the show I've got Neha Kovach. She's the Global Head of CRM Data, Customer Experience, and Loyalty at David Yurman. She's a global omnichannel customer experience executive with a track record leading transformation across luxury retail, e-commerce, and service led organizations with revenues ranging from 1 billion to over $10 billion dollars. On the show today, we talk about David Yurman, getting your data in order for an AI journey and how AI and Agentic can be deployed to drive greater value for the business.

That, and much more with Neha Kovach. Are you ready to go beyond the basics of marketing? I'm Alan Hart, and this is Marketing Beyond, where I chat with the world's leading chief marketing officers and business innovators to share ideas that spark change and inspire you to challenge the status quo. Join us as we explore the future of marketing and its endless potential.

Welcome to the show, Neha. Thank you Alan, for having me. I'm super excited to be here. Yeah, I'm excited to talk about all things, David Yurman, but before we go there, you have had a recent big move, moving countries.

How's it going? It's been one of the most humbling experiences of my life to start over, coming from Canada to the US, building credit, building, you know, facilities with banking, finances with kids, and so it really shows how much effort it takes to start over and start a new life, and so I'm in a place of gratitude that I'm here and I can do that, but I also think about a lot of these people that do have to start over and are not able to do it in the way that I was able to, so I have a lot of humility that I've gained through this experience and this process.

It's unfortunate that it's hard, but it's good that you are learning from it. Well, you have one of the longest titles I've ever seen in my life, so I'm going to have to look down, but you are the Global Head of CRM Data, Customer Experience, and Loyalty at David Yurman. So where did you get your start in your career and how did you end up at David Yurman? So the start of the career is an interesting journey, so I'll start from, I was actually studying to be a dentist, and plans fell through and I changed my mind and then actually went from dentistry to culinary arts, as you do, a natural transition, and I became a chef trained in French cuisine, and so I learned how to cook and I worked in the kitchen for a hot minute.

Realized that was not the life that I could endure for a long period of time with the chef yelling over my head, and then I went back to school for business management, and then I'm back into business, and so I started my career off in retail, event experiential management, then moved over to merchandising, and then, you know, as opportunities kept coming, I kept saying yes to them, and then I entered the world of financial services. So, retail financial services is where I started to cut my teeth and gain a lot of experience around customer strategy, technology, operations, compliance, and then I went in over to banking, and banking was where I had fortunate mentors and sponsors that allowed me to move roles across verticals and gain so much knowledge around managing a workforce, managing customer experience, customer strategy, transformation, and that's where I led some of the work with Salesforce and implementation in a large bank.

That got me that transferable skill and then brought me back into luxury retail where I had a global mandate managing customer experience, CRM, data analytics, and then led me to David Yurman and now David Yurman, I lead customer strategy, clienteling, CRM, data analytics, all things customer related, and so, yeah, it's been an interesting journey, but what it showed me or was the breadth of experience that you can gain in every different role or aspect that you take on, and it builds that perspective.

You have a different perspective every time you take on a role, and so when you are onto the next role, you carry that with you and it's a transferable skill, so you start to think 360 really quickly, and so you have a really good appreciation for the partners and stakeholders and the workflow across the organization. I love it, I love it. Well, tell me a little bit more about David Yurman. How do I think about the business?

David Yurman is a beautiful luxury brand, really rooted in craftsmanship and our living founders, our artists, and we make, we are in the business of making beautiful jewelry, preciously curated stones, metals, and we are known for the craftsmanship that we bring to the table, and so if you don't know David Yurman, now you will. Well, I don't personally know David Yurman, but I feel like I need to go check it out. Yes, you should. We make beautiful jewelry and it's for silver, gold, precious metals, high jewelry.

We are in the business for serving a large customer base. I know my wife knows. Yeah. Anniversary's coming up, so I need to get on this.

And you should as well. We have beautiful men's jewelry as well. All right. All right.

Awesome. Awesome. Before we start to talk about AI, data is a foundational element. How do you think about what marketers in general need to do with data and preparing for AI?

Yeah, I mean, listen, I think the foundations are rooted in cleaning up your data, contextualizing your information, and building a customer master, right? So, as we think about how you start to build agents or AI solutions, your data has to be ready for it to be read by these solutions, and so the first step is to look at your definitions, look at your customer master, redefine how you look at data and definitions, and then make it easy for the agent to be able to read from.

So like one simple use case would be, you normally would get customer engagement data coming into your CDP or your data lake. How about changing that terminology from customer engagement to say, "Days since last purchase," right? Because that will allow the agent to even just pick up that contextual information, and then you'll be able to build audiences real time to say, "Hey, I haven't spoken to this customer in over 10 days, and so maybe I should prioritize this customer."

So, thinking about how you formulate your customer definition, how you think about structuring that in your master tables is going to be really critical for an agent to pick that up. Agents don't shop or browse as customers do, and so it's really important to structure that data so that agents can really, you know, identify, pick up on the cues and contextualize that, and so that's how I approach building the basic foundations so that we can enable the agents to do their jobs.

Yeah, that makes sense, and I'm assuming that that's, I mean it's a lot of metadata essentially. Like, what is the data, not just ones and zeros, but what is it intended to tell me so I can make sense of it? I mean, that's good human practice too, not just for agents. Oh, a hundred percent, like, getting to understand where the data came from, what does it mean, contextualizing it.

One of the other things that I think is so simple, but birthdays, we use birthdays as milestones, and then you, we all send happy birthday emails, and they're just so generic and you don't feel special as a customer at the end of this, but if you just took that birthday information and contextualize that, and what I mean by that is to say, if your birthday was four weeks away, then now the message could actually read, "Your birthday is four weeks away. I would love for you to come in for A, B, and C."

That changes the dialogue from saying Happy Birthday, we know, I mean, it's like going from dumb dumb to contextualized, personalized message, and that's where I think we don't have to over engineer it, we just got to get smarter with how we use the data. Yeah, no, that's a really great example. So, all right, we have got our data cleaned up, we have got the metadata layer, you know, contextualizing it. Now I'm thinking about putting AI into the mix, or agents in the mix.

What do I need to be thinking about? I think right now in the industry, which I think is probably one of my bigger pet peeves, is we all kind of go directly to the service agent. Where's my order? Where's my return?

But I think the real value on lock is, how do you influence conversion? How do you influence revenue retention? And that comes in multiple different forms, right? An agent can be looked at to scour your database, like you can have an agent in your CDP or your data lake that will proactively prompt you to say, "here is your top 10 clients that you need to target, and here is a contextualized reason as to why you should target them, they are about to go lapse, or they have a high propensity to purchase."

That's where the agent can really unlock value, so when I started thinking about the Agentic strategy, I look at where is the biggest value unlocks within the business, and then start to like print, like rank order them, and so my biggest interest and where I'm thinking about, you know, implementing some of these changes is really around data, building capacity within the workforce, and then a hyper-personalization. So how do you actually outreach to the customer where you can really take this basic data, contextualize the messaging, and then be there, and then this the concept of, we have been talking about it for a decade now, right?

Message at the right time, but we haven't like, landed that plane yet. I think agents will help us get there a lot faster. Yeah, and do you see a world where agents are talking to agents? Oh my gosh, yes.

I mean, I think it's coming a hundred percent, and I think this is where your MCP strategy is going to be so critical, and how you have agent handoff from one agent to the next agent. So as we talked about if you had an agent that was identifying opportunities within your data lake or your CDP, how do you take that information of these top say, a hundred clients, and then hand that contextual message to the next agent that's actually going to do your Gen AI copy for you? Right?

How are you using unstructured data to then recommend outreach messaging, how do you then get that agent to pull the right creative, the right template? That handoff is going to have to be very seamless, so that information continues to travel from one agent to the next, so you could actually measure like, well, what did this agent say? Did we implement what this agent said, and then what was the execution and the measurement of that? So it's going to be absolute critical.

Yeah. A piece for all of us to figure out. It feels like there's a discipline in the middle there somewhere. I don't even, I don't know if it's agent psychologists, if it's, you know, spin on human resources, but now we are talking about agents and bots or systems engineering.

I don't know how to think about it, but the, what you are laying out, the orchestration between one agent and another, and the potential for like, making sure that they're communicating correctly. A hundred percent, and I think the workforce needs to shift as a result of that, right? Like at the end of the day, who owns this agent? How do you manage and QA that agent?

I think those are all decisions that we have to make as an industry, but also then as an org design to say, well, who gets to change how this agent performs, and you know, some people it's a, some people love this theory and some don't, but agents can be looked at as an augmentation to your workforce, and so if it's like a full-time employee, how you are managing success for that agent is going to be really, really critical, and at some point, you got to drive accountability on who owns that agent, how do you continue to manage it perform and Q/A it, make it better, make it smarter, as just time goes on.

You have highlighted some use cases already, but any examples come to mind of like, how Agentic is being used today that we could think about? Yeah, I mean, there's so many cool examples, and so Riddell is one that, you know, just published their success story. They've been able to build an agent that builds capacity and efficiency in their sales force, and so one great example of that is how do you build capacity? How do you take these autonomous, like, tasks that your sales teams no longer have to do and the agents can do them on their behalf?

So simple thing like a meeting prep, if you are about to meet with a client, how can I prep that meeting for you? What is the information that you need to know right before the client walks into the door? What meeting prep do I need to do? What are the watch outs?

So if the customer was, you know, upset from the last interaction, or really happy, you know, what are the things that you can actually learn from? That would be a great, great example. The way I look at future, like near future unlock is a sales coach, and so, a great example of this could look like is, well, what are some of the best sales agents doing and how do you replicate best practices, and then make it meaningful and contextualize for that user. So, for example, if I, Neha, work at a store and my efficiency is sitting at, I'm making this up, at like 85% and I can, I have a gap of 15%, I can now tell you, based on what the best practices are and the best performing, you know, sales agents are doing, and here's the next three best actions that you can take to mimic that best sales agent's performance, and so agents can do that now, and so you build up capacity not only from a manager's perspective, but also the agents, the actual sales reps start to get these real time nudges that they don't have to go dumpster diving for that information, if that makes sense.

Yeah, no, I need a podcast agent. Yeah, hopefully there's no bad experiences I need to be told about, but like, yes, it would be helpful. We like a real Alan. Well, if you look into the future and you are thinking about customer experience, and Agentic, and AI enabled world, like what does that look like?

Where are we going? I think the future is bright and then it's also scary. We all will have agents, right? I mean, we know this, like some people already have them, and so as you have your own agent, it becomes somebody who is ingrained in your lifestyle, they know what coffee you like, how do you dress, what your, you know, travel plans look like, and where do you shop for garbage bags like that to that level of detail, and so I think today, brands and retailers talk to the consumer and in the future, we have to talk to the agent, because the agent's going to be doing a lot of the thinking, the recommendations, the actual self commercial, you know, checkouts.

The agent holds a lot of power, and so as we start to think about that, that's where the future is so, so complex, but also interesting and how we can start to build that story that the agents will be able to pick up, contextualize and then influence a customer to come to you instead of another brand or another retailer. Well, we love to get to know you even a little bit more than we already do, and I know you had a big move recently, but my favorite question to ask everyone that comes on the show is, has there been an experience of your past that defines or makes up who you are today?

Yeah. So I lost my mom when I was 18 years old and that really changed the trajectory for my life. One of the reasons why I gave up dentistry was because we were going to be in a practice together, and so I have carried that weight with me for a while, and so when I had my daughter about 11 years ago that just became a natural part of who I am in terms of being a role model, how I show up in this world, leading with empathy and humanity, and so what's been really interesting is to watch my daughter grow up and how she mimics me in like the mannerisms or, you know, on my laptop, she created this little sticker.

She's in the sticker making business now, and so she created this little sticker that says Boss Lady on it, right, and that's just the epitome of what she thinks about her mom, and that's just changed how I show up every day. So losing my mom has led me to be very mindful around the type of mother that I am to my daughter, and the types of conversations that we have, and that actually translates a lot in my work life as well, because I come from a point of we are all trying to raise good humans and nobody shows up to work, you know, wanting to be a jerk that day, so really just empathizing to understand, well, what is that perspective?

Why is your perspective different than mine? There must be a reason, and really examining that from a 360 perspective. So that entire shift of losing my mother, stepping into motherhood has turned me into more of an empathetic leader, if that makes sense. It does.

And pivotal moves in my life. Well, thank you for sharing that. Of course. I am a girl dad, so I love to hear stories about daughters that are calling out, like work is, you are a boss lady.

Yeah. So that's awesome, that's awesome. And it's also like, representation is a huge part of who I am, so my parents were immigrants in Canada, and so they had a really rough start and they, you know, they strived to give me, this life and opportunity, me and my sister, and so now I look at that as a reward and to say, what can I do to help tell the story of the legacy that was given to me? So my daughter is biracial, my husband is Caucasian, and so, you know, one of the things we always talk about is representation and retail in particular, there's not a lot of women of color that lead, you know, leadership roles, and so it's always been very important for me to make space so that she can see herself doing the things that I wasn't able to.

So growing up, it was really difficult for me to find mentors or for me to be able to emulate what my future could look like, and so I lean into that a lot as well to say, "How do I create spaces intentionally, not only for my daughter, but for others that are coming up behind me?" Well, if you were looking back on little Neha, what advice would you give her? Oh, be kind, be gentle to yourself. I think we are our harshest critic and you know, as I grow into a more mature parent, I always tell myself, "Don't tell yourself stories that you wouldn't want your daughter to tell herself".

we are always telling ourselves, you know, like, you make a mistake and you are like, "Oh, that was so stupid, I'm so stupid, I'm so dumb." It's like, but you would never say that if your daughter made that mistake. I would never go to my daughter and say, "You are so stupid. You are so dumb."

Right. So how does that, you know, how does that, why is that okay for you to speak to yourself that way? So I really, that's what I would say, it's like, just be kinder and gentler to yourself than you have been because what you say to yourself manifests in reality. I'm huge in believer of neuroplasticity, how you rewire your brain.

So I'm very much taken by this concept of the things that you tell yourself become the reality, and your energy follows the thoughts, so the thoughts should be positive, and so if you are kinder to yourself, better outcomes will happen for you. Love it. Well, most folks that come on the show are knowledge seekers, so I'm curious what you are trying to learn more about yourself right now. Yeah, oh my gosh, like, so like I just touched on, neuroplasticity is something that I'm really keenly learning, but there's an element of quantum physics within that that is a huge unlock, so I'm trying to educate myself on what does that look like and what does that mean for the future?

And if we unpack that, there's, that's where quantum physics and quantum computing is the way of the future, but then there's an element of like, you know, interstellar stuff like multiple dimensions, realities, time and space. That's what I'm trying to educate myself on, just to figure out what's the real, real? That's where I think neuroplasticity comes into play, it's like, you know, we are all energy, we all vibrate at different frequencies. So yeah, I'm trying to learn if I change my vibration and how I show up, will my outcomes change, and, you know, so far, so good, so going deeper into that.

You talk about metaphysics and quantum, and I'm curious about that. Yeah, I mean, it's like a whole, to your point, maybe another dimension, but like how things can be the same but different at the same time, and it's like mindblowing to me. It is, and you know, it touches a lot about human - within that, it touches a lot on human psychology. Yeah.

Like perspectives that, What is, is. Yeah. What is, is, and your 'is' is very different than mine is. Right.

And so we can look at the same thing, but you can have very different perspective on that, and I'm just general curious learner, so I like to take things apart and rebuild it back up, and so that's why I'm so fascinated by that whole phenomenon. I feel like there's a Sci-fi podcast in here. Yeah, I think so. That's the spinoff, Alan.

All right, all right. Well, a couple more questions. What do you think is the largest opportunity or potential threat facing marketers today? Oh man.

You know what it is? It's customer attention span. I was reading a study on Gen Alpha and how they consume information so differently than you and I, and it's that instant gratification and it's really understanding what is the message that we are trying to teach or show this consumer now, and as a consumer evolves and their expectation or experience evolves, is it going to be enough to just showcase your product? I don't think so.

I think it's like, what's the hook, right? As we start to dig deeper and deeper into customer intent, as the customers are prompting with the agents and they are asking different types of questions, our content, our marketing content, is going to need to look very different, and I use this example all the time. The pair of shoes that you and I are wearing can have so many different meanings for you. I could say I want a shoe that I can wear in work settings, but that are really comfortable, but you can say, I want something that's stylish and designer, right?

So those are two completely different use cases, but the intentions are different, and so understanding the customer intent is going to become more complex, but it's going to become interesting for marketing to be able to tell more creative stories, and so the hook no longer becomes your product. The hook becomes the stories with which you bring that consumer into the fold, if that makes sense. Yeah, it does, it does. It's a different type of creativity, but it's creativity at its core.

It is. It's very different, and we are all vying for the attention, the same customer attention, and if that attention span is like decreasing inch by inch by inch, how do you gain that market share back? I think it's going to be so, so critical, and that's a threat, but also an opportunity, and I think we can learn from that as we start to mine the data and then use that data to actually build beautiful, better stories. Love it.

All right. Well, in a sentence, what's one way Agentic AI will fundamentally change how we shop next year? The way Agentic experiences will shift within the next year is really making sure that our marketing content is showing up to the customer in the way that they want it to show up, so that intent and contextualization is going to become paramount, and so what we have talked about is, how do you prompt an agent and what you show the agent is going to become so tight that sometimes maybe your brand or your product will not show up in the top 10 because the agent has the customer's back.

The agent is loyal to the customer, and so how do you get the agent to farm out your recommendation is going to be really, really critical, and so it's going to be a pivoting point for brands to really tighten up on getting ready for Agentic commerce and AEO, GEO, all of the -EO's. Well, Neha, thank you for coming on the show. Of course, thank you for having me. Hi, it's Alan again.

Marketing Beyond is a Deloitte Digital podcast. It's created and hosted by me, Alan Hart, and produced by Sam Robertson. We have even more cutting edge marketing insights headed your way. Be sure to subscribe to our channel to stay up to date with our latest episodes.

I love hearing from listeners. Share your thoughts about the episode at the topic covered or the show by commenting on this video or emailing me at marketingbeyond@deloitte.com. If you are interested in more conversations with industry visionaries, we invite you to explore other Deloitte Digital podcasts at deloittedigital.

com/us/podcasts. There you'll find the Marketing Beyond webpage with complete show notes and links to what we discussed in the episode today. I'm Alan Hart, and this is Marketing Beyond. The views, thoughts and opinions expressed are the speaker's own and do not represent the views, thoughts, and opinions of Deloitte.

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