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AI at the helm; understanding marketing’s next frontier
In this episode of the India Insight podcast, in collaboration with CII, Digvijay Ghosh, Partner, Consumer Product and Retail, EY-Parthenon India, and Nitin Saini, Vice President of Marketing at Mondelez India, dive deep into the transformative impact of generative AI (GenAI) on marketing and consumer experiences. They discuss how AI enhances creativity, personalizes consumer interactions, and revolutionizes customer service through intelligent chatbots. The podcast also highlights the importance of leveraging first-party data for targeted marketing and the necessity of fostering a culture of experimentation within organizations. With a focus on adapting to the evolving landscape, Nitin shares valuable insights on the skills marketers need to thrive in a data-driven world. Join us as we explore the future of marketing through the lens of AI.
Digvijay Ghosh
Partner, Consumer Product and Retail, EY-Parthenon India
Nitin Saini
Vice President-Marketing, Mondelez India
Key takeaways
GenAI enhances creativity by transforming verbal concepts into engaging content, enriching brand storytelling without sacrificing authenticity.
Using first-party data enables targeted marketing, rapid performance assessment, and personalized consumer experiences, helping drive business growth.
A culture of ‘test and learn’ fosters innovation and agility, allowing brands to adapt quickly and continuously improve strategies.
AI empowers us to enhance consumer engagement through personalized experiences, revolutionizing how brands connect and respond to their audiences.
Nitin Saini
Vice President-Marketing, Mondelez India
For your convenience, a full text transcript of this podcast is available on the link below:
Digvijay: I would like to take this opportunity to welcome everyone to this CII podcast around ‘AI at the helm of understanding marketing's next frontier.’ Today, I have Nitin Saini with me, who has been with Mondelez for the last 20 years. He has been leading some of the most iconic brands like Oreo, over his career spanning multiple countries. Prior to being the VP of Marketing for India Business, he was heading this brand from a global perspective based out of US, where, among many other things, one of his key achievements was winning the coveted ‘Decade of the brand’ award at Cannes in 2022.
So, Nitin, a very warm welcome to today's episode and podcast around AI in marketing.
Nitin : Thank you, Digvijay.
Digvijay: I am Digvijay Ghosh, your host for today's podcast. I am Partner, Consumer Product and Retail, EY-Parthenon India, and it is my honor and privilege to be here to host today and have our conversations about how AI is shaping how marketing is done, how it has been impacting the way consumers are experiencing it and how brands today are learning from it and taking it forward.
Nitin, one of the things which I was thinking about is that AI is not really anything new when it comes to marketing. One of the earlier examples of this would be Google Search, which has been using fairly sophisticated algorithms over a period of time, or for that matter, the whole social media and the fields around it, which are mimicking what users’ interest is and showing up the right and the most relevant content.
In your opinion, what are the earliest examples that really caught your attention in terms of how brands should look at using AI in the way they communicate and conduct marketing as a function?
Nitin: AI is not new. It has been around for quite some time. You gave a great example with Google search, which definitely uses artificial intelligence and machine learning to provide various results whenever we search for something.
Another example that comes to mind is Google Maps, which also uses AI. Even in the world of media—advertising, marketing—brands have been using AI for some time. Chatbots, for instance, have been around for quite a while.
Additionally, personalized recommendations or content, whether on Instagram, Facebook, Google, or even travel websites or other search engines, all serve personalized feeds based on algorithms. These algorithms are grounded in your search history, and at the core of all that is AI.
What has happened is a couple of things. With digital becoming bigger and bigger, conversations around AI have become more pronounced, especially in marketing. Since people are spending so much time online, it is now possible to do a lot more with personalization, which often involves AI in some way.
Generative AI (GenAI), which gained momentum in November, gave another big push to these conversations. When I look at what Mondelez has done, we have been using AI in various forms. One area where we have really leveraged AI in a big way is personalization—to deliver delightful, personalized consumer experiences.
Digvijay: That was really well put. Reflecting on how digital marketing has evolved—the whole media buying experience has shifted towards programmatic media buying, which is also enabled by many of these technologies. Now, we are even talking about extending this to television. These are great points, Nitin.
But one of the key questions around using analytics is how to measure the impact. For example, from a traditional standpoint, there are brand or business objectives like creating awareness, driving consideration, conversions, and so on.
Is it feasible to track all of those metrics in a meaningful way, or do some of them change? Is there an equivalent set of objectives or KPIs that you measure when leveraging these analytics-enabled solutions in marketing?
Nitin: If you look at brand objectives, they typically revolve around driving brand penetration or increasing the frequency of consumption, and that is where you start. Then, you look at all the different tactics to achieve that. AI becomes a powerful tool to help deliver on these brand objectives. Therefore, anything you use AI for should ultimately tie back to what will help drive penetration.
For example, if you are building awareness—whether you are introducing a new brand or working with a brand that has existed for a long time but has not been able to build relevance with consumers—any of those drivers ultimately serve a brand objective.
The way I see it, AI is simply a means to achieve that. So, the KPIs or brand objectives themselves should not change. What AI does is provide new ways to accomplish these goals. Take, for instance, what you mentioned earlier about media buying—where you place your ads has become far more automated today. In essence, AI is about using machine learning and historical data to do a better job at these tasks, which leads to better efficiency, improved productivity, and in some cases, even better forecasting.
By leveraging AI, people can now make faster and more informed decisions about where ads should be placed in the digital ecosystem—something that would take much longer and be far less efficient if done manually.
So, in response to your question about brand objectives, I do not think they really change.
Digvijay : Fair. That is also good food for thought because, in the digital era, we often have a plethora of KPIs. And sometimes, we might lose sight of the real objectives amidst all those KPIs—forgetting the woods for the trees, if I may say so.
You touched on the topic of generative AI, and the level of excitement and conversation around AI over the last 12 months has been unprecedented, especially since the advent of generative AI. When you think about consumer goods, and broadly in marketing, there are three areas that have been most impacted by generative AI.
The first is, of course, consumer experience and personalization. How can we provide better experiences in a much more personalized manner, as you mentioned earlier?
The second area is content creation and creativity in general. How can we be more original and authentic, while still leveraging AI?
And finally, there is the service experience aspect. Over the next few minutes, it would be great to hear your views on how you see these areas being disrupted, enhanced, or transformed into something new and better for the consumer.
To start with, from the consumer experience and personalization standpoint, we would love to hear your thoughts.
Nitin: I would say that has been one of the real big benefits of AI and generative AI. One is how you can provide people with more personalized experiences, as we mentioned earlier with personalized feeds.
You are served content that is tailored to you, which is what a lot of search engines, and platforms like Google and Meta, are doing. We have also used AI in a very interesting way—creating personalized experiences that are tied to a campaign idea or brand purpose.
I can give you a few examples of what Mondelez has done with some of our brands. A few years ago, we had a campaign called Not Just a Cadbury Ad. It was during Covid when many retailers were struggling. The idea we came up with was, “Why can’t we help these retailers have their own personalized ads, featuring Shahrukh Khan as the ambassador, powered by AI?”
We used machine learning to generate numerous small ads for the retailers around Diwali, a time of celebration and generosity, so everyone could have a great Diwali. The campaign was closely tied to that sense of purpose, using AI and machine learning to create personalized ads.
Last year, we had a campaign centered around celebrations, specifically birthdays. The insight we had was that there are six billion people on the planet, but there is only one birthday song. So, if I were to sing a birthday song for you, everyone would sing the same ‘Happy Birthday to You.’ We thought, why not create a personalized birthday song?
We used generative AI to allow consumers to create a personalized birthday song and gift it to their loved ones, along with a box of ‘Cadbury Celebrations.’ The process takes a few inputs and generates a unique song for you. This is only possible through generative AI, as it has the ability to create new things.
The objective here was to build relevance for ‘Celebrations’ in the context of birthday gifting. So, you start with your brand objective, and then the idea becomes a personalized birthday song. In the execution, AI played a significant role.
Going back to what we discussed earlier about brand objectives, they do not really change. The brand objective, the human insight, and the creative idea always come first, and then technology, including AI, enhances that to create a delightful personal experience.
A couple more examples from this year: earlier on Valentine’s Day, we again used AI, allowing someone to create a personalized Valentine’s Day video. Consumers could share memories with their Valentine, giving it as a gift on the day. You can imagine the delight the recipient experiences!
Even in August, we ran a campaign where people could share personalized memories with their sisters on the occasion of Rakhi. These are the kinds of examples that enable consumers to create personalized content.
And as we discussed earlier, personalized feeds are another crucial way in which people are using AI.
Digvijay: Those are great examples. If I think back to marketers a decade ago, they could only imagine being part of so many different moments that matter from a consumer standpoint. Now, with the use of generative AI, you can actively participate in those meaningful moments.
Speaking of content, one of the things brands have always aspired to is creating high-quality content that goes beyond just experiential marketing. For example, they may want to provide research, find recipes related to their brand, or even offer insights into therapy or product knowledge. However, brands often struggle with continuously generating relevant content because consumer searches and needs evolve over time.
This challenge requires a different level of machinery to consistently churn out content that speaks to specific consumer requirements and inquiries. Where do you see this aspect getting augmented or transformed with the help of generative AI?
Nitin: Generative AI can play a significant role here. Sometimes, you need content at a very large scale—whether it is recipes or other forms of content—especially with the surge in digital commerce activities. The question is, can it be done through AI instead of relying on human intervention every time?
There are areas where creativity may not be as critical, and factors like aesthetic value, efficiency, and scale become more important. That is where a lot of work is happening today—to determine how to achieve this in a very organized way.
We are also exploring this, and it can certainly be a significant opportunity as you look at how to leverage AI. For instance, when it comes to innovation or creating scratch concepts, using AI can streamline the process and yield impressive outputs without excessive manual effort.
If you use generative AI tools and input a vision of what you want to create, you can see some really good visuals generated. I am sure you have experienced this. The output can be quite impressive.
However, there is still work needed to clarify exactly where we should use these tools. It also requires substantial effort because we need to train the AI on all the insights and learnings from the past. This training enhances the output, making it richer and more aligned with our objectives.
The final thing I will say is that, in the end, it is not an either/or situation. While you have AI-generated output, there will always be a space for human creativity. In some of the campaigns we run, AI is like the icing on the cake or the cherry on top.
You start with a creative idea grounded in strong human insight, and then AI adds that extra flair. I do not believe human creativity is going anywhere; instead, there is a wealth of output that can be generated using AI.
Digvijay: I completely agree because, at the end of the day, it is about augmenting creativity. For example, someone like me, who is really bad at drawing, might have a concept in mind but struggles to bring it to life. As you said, AI can generate something that is probably better than my verbal description. This, in no way, diminishes the authenticity or creativity that comes from the original source.
But do you also feel that this requires a degree of supervision, particularly when it comes to content from a brand standpoint? There is a level of care that needs to be applied. There are certain thresholds regarding what you can or cannot say, as well as regulatory guidelines that need to be followed. Do you think this becomes even more important now than ever?
Nitin: It does, and it requires a lot of effort in that area. Whenever we create generative AI tools for people to produce personalized content, we also have to ensure it is a safe space. We must guarantee that no copyrights are violated.
There is significant work that needs to be done, but it is all worth it in the end when we see the output. One must also be cognizant of the considerations you mentioned.
Digvijay: The third aspect I see is that generative AI is significantly impacting the service side, even if it might be somewhat removed from your core brands. For example, I know Mondelez has a gifting side, which is an exciting value proposition. But do you feel that the broader landscape of commerce is now being affected by generative AI?
As a consumer, I find it very exciting to have a single point of contact, like a chatbot, where I can express any needs related to a brand. It would be great if this could be done on platforms like WhatsApp, allowing me to address everything from shopping inquiries to customer complaints. It feels almost like having a conversation with someone from the brand or platform. That capability would be incredibly exciting and would truly enhance the consumer service experience.
Nitin: Absolutely! When you look at digital commerce, you can see that AI provides personalized recommendations based on your purchase history and what you are likely to buy in the future.
This functionality makes the shopping experience much easier and richer. We have also witnessed the rise of quick commerce, which has provided a fresh impetus to digital commerce.
I believe digital commerce can play a significant role. Brands that generate a substantial portion of their business through direct-to-consumer channels will benefit greatly from AI. They can leverage AI to deliver personalized recommendations and enhance the overall experience. It is not just about the act of buying; it is also about what happens afterward.
In terms of after-service, AI can completely revolutionize the shopping experience. The way chatbots are evolving is remarkable; they are becoming much more intelligent. To your point, if you have any queries or complaints, these chatbots can now handle them with a more human-like touch. AI is getting closer to mimicking human interaction compared to how chatbots functioned five years ago.
Previously, people would often express a strong preference to avoid chatbots and talk to a human instead. But now, that perception is changing. You are absolutely right—the entire service and commerce industry will witness significant transformations.
Digvijay: One thought I would like to leave with you is that marketers can always create a brand persona, envisioning it as if it were a real person. They can define its tonality, character, and more.
Wouldn’t it be great to create that persona and make it available for consumers to engage with? Perhaps through a chatbot, where consumers can interact and access all the fantastic features you mentioned, provided by the brand they love so much.
Nitin: Absolutely, that is a wonderful thought.
Digvijay: With all these exciting changes on the consumer side and in capability, the natural question is: how do you assess your internal capabilities and their readiness? How is that landscape changing?
Consider areas like consumer insight generation, planning, media planning, and measurement - how do you see AI opening doors and unlocking key areas, particularly in terms of consumer insights?
Nitin: AI can play a crucial role in two or three key areas. First, it can enhance our ability to listen—essentially, how we perform artificial listening. AI can synthesize all the information in one place very quickly, allowing us to gauge consumer sentiment more rapidly than relying solely on field research and direct consumer interactions.
Another area where AI can be incredibly beneficial is in data management. Every company and enterprise has a wealth of data scattered across different systems. Often, there is a significant bottleneck in consolidating all that data into one place, making it challenging to derive insights that can drive the business forward.
Sometimes, it is not the lack of data but rather the inability to convert that data into clear insights that can help the business move forward. AI can serve as a powerful enabler in this regard. If you are able to synthesize information at a rapid pace and extract insights out of it, that can serve as a competitive advantage as well.
Digvijay: I absolutely agree. In our conversations with various clients, as we have advanced in generative AI and implemented it for different clients, a recurring theme is how to empower internal teams. Generative AI can eliminate the errors associated with looking at dashboards because now you have all the data and an intelligent bot at your disposal.
You can type in your questions, and the analysis is delivered to you, eliminating the need to sift through multiple dashboards or create countless dashboards that often go unused. The way organizations approach their own data is changing.
Building on this, how do you view first-party data? I am sure Mondelez is at the forefront of harnessing it. What has been your experience with AI enabling the use of first-party data in your communication and content creation?
Nitin: We have a strong first-party data program (FDP) that we have been running for three or four years now. It allows us to understand our consumers better and reach them more effectively, enabling us to scale significantly when it comes to first-party data.
There is a lot we can do with first-party data. It empowers us to deliver personalized experiences at the right time. We aim to engage in meaningful listening with our consumers to gain insights, and AI plays a crucial role in this process, given the size of our database.
The challenge lies in organizing the data efficiently and determining how best to reach out to consumers. When we gather feedback, we must do so in an organized manner. First-party data and AI systems go hand in hand: having first-party data allows us to utilize AI effectively, and having an AI system enhances our ability to leverage our first-party data and program more efficiently. So, both elements are well intertwined.
Digvijay: In first-party data, one of the key things which often comes across is how do you leverage this data in not just in terms of creating segments that you want to share your communication with, but what are those broad areas where you see maximum value.
If you were to call out maybe two areas where you see that FPD is really impacting, the marketing metrics, what will those two areas feel?
Nitin: The first key area is the creation of targeted segments, which allows us to allocate our media and advertising budgets more effectively. By reaching more engaged audiences, we typically see a better return on investment (ROI). This targeted approach enables us to monetize our efforts more efficiently.
The second significant area would be insights generation. With our first-party data, we can quickly assess the performance of new products. For instance, if we launch a new item, we do not have to wait weeks to gauge its success. Instead, we can conduct an overnight survey with our audience to gather immediate feedback. This enables us to make necessary adjustments promptly or refine our demand forecasting. Additionally, these insights can even drive innovation by informing product development based on direct consumer feedback.
Digvijay: That is a great point. Reflecting on my own marketing days—specifically my brand management experience from about a decade ago—I see how vastly different the marketing landscape is today. If we were to have this conversation a few years from now, I am sure marketing, and the skills required will have evolved even further.
When you reflect on the changes, what do you think are the key skills or areas that have become more critical now than before? What two or three areas should every marketer focus on to stay future-ready?
That is a great question. I have reflected on this often. Before I talk about what is new, I want to highlight that some fundamental skills remain crucial for anyone aiming to be a great marketer.
Key aspects include consumer centricity, clarity of thinking, storytelling ability, and the capacity to think with both the left brain and the right brain. You need a balance of structure and creativity—those skills are still vital in marketing today.
A couple of things have obviously become more important now. With the rise of digital and data, it is essential to immerse oneself in this world and understand it as if you were a native user. For example, being well-versed in platforms like Instagram, understanding various technologies, and knowing how Customer Data Platforms (CDPs) and data systems operate has become quite crucial. The ability to navigate this digital landscape effectively is now a key skill for marketers.
Additionally, the ability to think across both ends of the marketing funnel has become increasingly critical. Building equity and awareness for your brand is essential, and that typically aligns with top-of-funnel activities, or brand building. However, with the rise of commerce, digital commerce, and direct-to-consumer (D2C) models, understanding performance marketing—essentially, full-funnel conversion—is equally important.
It is not a matter of choosing one over the other; you need to comprehend and master both areas. Furthermore, adaptability and agility have become vital qualities in today’s market. This need for flexibility and responsiveness is even more pronounced now than it was 10 years ago.
Digvijay: Reflecting on some of the ways you have articulated your thoughts, they are very precise and paint a vivid picture. The world of branding is increasingly overlapping with the world of digital product marketing. Both disciplines have evolved in ways that allow them to learn from each other.
One aspect that goes hand-in-hand with these methods is agility, as you mentioned, which involves conducting numerous experiments. It is essential to avoid viewing consumer segments as a monolith; instead, we should think of them as micro-segments, each with their unique needs and states. This approach requires room for a variety of experiments.
However, the reality is that there is often a scarcity of funds. There tends to be a crunch or a strict discipline around expense management and similar considerations. How do you create space for these experiments, and what has been your mantra in this regard?
Nitin: Again, you are absolutely right. With all these new developments, there is always some ambiguity in the beginning. A couple of things have helped us; the first is what I would call a culture of ‘test and learn.’ We try out many different things, knowing that some will not perform well. However, we learn from those experiences and improve. So, we start slowly, but we embrace this culture of experimentation. It is essential to be bold about testing, learning, and applying those lessons. We have been doing this for some time now, and it has definitely been beneficial.
The second aspect is that leadership guidance is very important in these areas. As I mentioned, there can be ambiguity because sometimes you need to invest upfront. The leadership team must provide direction and motivate the team through these challenges. This approach has proven to be quite useful. But I would emphasize that the ‘test and learn’ culture is crucial.
Digvijay: Absolutely. Without leadership skills or a culture of ‘test and learn,’ such initiatives cannot be created. Just to build on that, do you have a typical framework regarding the timeline within which an experiment needs to show results? If you follow certain principles around this, it implies that you expect results within a specific time frame. What are your thoughts on that?
Nitin: It would depend on the initiative. For some, you might set year-one milestones to determine whether you are reaching that target. Ultimately, it is about the ability to think future-back and say, "Okay, this is where we want to be three or five years from now." That is where it all begins. The synthesis of your long-term vision is critical—this is where you want to go.
From there, you conduct those ‘test and learn’ experiments, establishing the right milestones at the right times to assess whether you are moving in the right direction. Do we need to course-correct? That is what we try to do, and I believe it has certainly helped us in building digital competence within the marketing function.
In some of the examples I shared about using AI, those were experiments that, in some ways, proved to be successful. Once you achieve success with one of those initiatives, it also builds momentum.
Digvijay: That is very well said. It is a refreshing and honest way to express that success within experiments breeds more experimentation. You have to create room for that. It is great to hear that from you. We are almost at the end of our discussion today.
First of all, thank you so much, Nitin, for making the time. Your insights have been incredibly valuable. Over the last few minutes, we have discussed how AI has revolutionized marketing and the consumer experience.
We have also gained great insights into how brands are building internal capabilities and how their views of consumers are evolving. Additionally, we explored how to create a culture of learning and experimentation and build upon it. Thank you once again for your valuable insights and the time you dedicated to this discussion.
Nitin: Well, thank you. I really enjoyed the conversation with you, thank you again.
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