‘AI has helped us do things faster, fail faster, and correct ourselves faster’

At e4m TechManch'24, the session "From Data to Delight: Revolutionising Content Discovery with Hyper-Personalization" highlighted AI's role in transforming consumer experiences. As AI enhances recommendations, consumers now demand content that truly resonates, the experts shared.

Industry leaders Sujay Ray, Head-Digital Marketing, Loreal; Sairam Ranganathan, Chief Digital Officer, Wavemaker & Wavemaker NorthStar; Reena Jagtap, Lead - Digital Marketing, Henkel; Priyanka Bisen Shah, Head of Digital Marketing, Bajaj Auto; Anuja Trivedi, CMO, Shemaroo with Devika Sharma, VP & GM, India, Glance as session chair, shared insights at e4m TechManch on the future of hyper-personalization in delivering meaningful, engaging content.

Sharma set the context by discussing the importance of personalisation and how technology is playing an important role in the same. "Mobiles have become a critical part of our lives, influencing how we eat, shop, and travel, and encompassing nearly every aspect of our daily routines. As this development progresses, consumers now expect a high level of personalization. They want to see content, food, clothes, and travel options that are relevant to them, within their budget, and aligned with their preferences. Data plays a huge role in enabling this personalised experience throughout the consumer journey."

She then invited Trivedi to talk about how Shemaroo utilises data to drive content discovery and leverage personalisation. To this, Trivedi answered, "My consumer today expects that I know them very well and demand personalization. It's not just about curating the right content; it's also about the app's appearance, the notifications they receive, and the new content recommendations. The app should communicate effectively through email, the app itself, and outside the app.”

“Consumers are extremely demanding, and the data needed for this level of personalization is constantly evolving. For the OTT industry, if personalization is done right, it leads to better engagement, which in turn fosters loyalty. This loyalty can evolve into advocacy, and eventually, brand love, making consumers choose one app over another,” she added.

Enabling that entire process is critical from a business strategy perspective. Trivedi then discussed experimenting with AI for consumer engagement.

“AI has helped us do things faster, fail faster, and correct ourselves faster. We create and test more copies, including static, video, and reels-style creatives, which are used in marketing. Additionally, we leverage data on Meta and Google platforms to target and retarget our consumers. From the top of the funnel to directly selecting and targeting the right consumer, AI plays a crucial role throughout the entire funnel."

This was followed by Ray analysing the inherent human need for personalization and individual preferences. It’s the job of the marketers to provide those experiences to consumers in a differentiated way. This is where AI and data come into play.

He said, “About five or six years ago, we started acknowledging the importance of data and how it could help us offer differentiated experiences to consumers. From every touchpoint—whether it’s our D2C website, our communications, or our search results—we use data to deliver those unique experiences."

He then talked about the difference in how L'oreal is looking at the entire journey today versus five years ago, especially regarding AI. “Learning has been a constant journey for us, and with new technologies, our learning curve has steepened. As marketers, we need to continuously adapt because consumers are also learning and becoming more mindful of their choices.”

“Changes in consumer behaviour, such as content consumption on OTT platforms or search patterns, influence our go-to-market and communication strategies. For example, we analyse search trends to understand if consumers are searching for an end benefit, a problem solution, or specific ingredients. Based on these insights, we adapt our communication strategies, even down to search copy,” he further mentioned. “We leverage technologies like dynamic creative optimization, so if a consumer searches for certain things or shows specific signals based on their geography or behaviour, tailored content is shown to them. It’s about delivering the right communication and content in the right context."

From there, Shah continued the conversation. She highlighted the use of AI in hunting and farming. In hunting, they utilise different strategies to bring the consumer in. In farming, they use various strategies to sell the product. For automobiles, there's a third stage that is very critical due to the high ownership timeline.

“In the first phase, we engage in a lot of online and offline activities. For bikes, in the end, a person often needs to touch and feel the product before purchasing. This may not apply as much to two-wheelers, especially electric ones, which people buy online from platforms like Amazon. However, for most bikes, people visit showrooms. We use predictive modelling to determine showroom locations, considering over 100 parameters to ensure we attract the right audience. This includes analysing online searches, competition landscape, and market potential.”

Traditionally, these processes were slower and used fewer parameters, but with AI, the timeline has reduced, and marketers can now analyse a much larger set of data.

“The second part involves identifying the consumer. Platforms like Meta and Google have advanced AI engines that have been improving for the past 20 years, and we leverage their capabilities. The third part of AI use is in lead management. Once we capture a lead, we use AI to track their activities both online and offline. This helps us better understand their behaviour and preferences, allowing us to tailor our approach accordingly," Shah continued.

Ranganathan was the next to be invited to talk about his three pillars of personalisation. He mentioned, "For us, the intersection of personalization and artificial intelligence is crucial for helping our clients drive business outcomes. I'll structure this into three pillars. The first pillar is creating better consumer experiences. The second pillar is making better media plans. This is the core of the industry I represent, focusing on optimising the entire planning mechanism to ensure effective and efficient media strategies. The third pillar involves using AI for better optimization."

“The great thing is AI is helping us visualise dimensions we were not able to before. Imagine a programmatic planner who has to make changes in the campaign setup daily. At most, they might be able to do 18 or 19 changes. AI can easily do 10 times more changes. Based on the goal you have defined, AI can leverage historical data to make relevant changes, focusing on the desired outcome.”

Jagtap was the last to go. She highlighted how when managing a broad and diverse audience, her team focuses on supporting various strategic business units with tailored digital demand generation strategies and engaging consumers throughout their entire purchase cycle. They leverage data-driven strategies and AI tools, such as Facebook Advantage Plus, to optimise creative content and enhance their approach.

“There are several researchers that say that there are at least six decision makers for any process so it's not at all easy to convince somebody. It's not about selling a soap and shampoo is what we say to our agencies. It's really difficult to speak to these audiences and convince them. And that's where we have to understand these six key stakeholders, identify their roles in decision making, and communicate different messaging to them.”

“Since I work with global teams there are several cases where AI has helped us make 600 calls to the number of leads that are coming in so like three AI bots can make 600 calls per day. So that's the kind of ease at which we can operate due to the integration of data,
creativity and technology. This is the magic,” she concluded.