Navin Dhananjaya, Chief Solutions Officer, Ugam, a Merkle company

Navin joined Ugam as their Chief Solutions Officer in 2013. He leads solutions management and is responsible for conceptualizing and developing new, innovative solutions and taking them to market. He oversees the client delivery for overall analytics (including media, audience, site analytics) and digital commerce service lines at Ugam.  He is also responsible for conceptualizing and building Ugam’s JARVIS – a cognitive computing system. He is passionate about creating an environment that promotes personal and professional growth. His understanding of both, analytics and technology, gives him a unique edge to identify the right talent from all backgrounds and mentor them to build successful careers. He is truly Ugam’s gardener for talent – both metaphorically and literally. He brings over 25 years of experience, has held senior roles in companies such as Mu Sigma, Infosys, and Manthan.


What do customers want? They want to play their favorite song and have a ready playlist of new favorites waiting to be discovered. They want to open an online shopping website and have the home page filled with products and offers that they would seek.

And this is not news. Many brands currently provide this level of personalization to customers. Spotify auto-plays songs based on data from its customers. Amazon analyzes previous purchasing behavior, wish list, preferences, and cart among other data to understand its customers and hyper-personalize marketing campaigns to them. 

That’s how brands differentiate in an over-saturated market—through hyper-personalized experiences tailored just for their customers. And customers want this hyper-personalization. 91% of consumers say they are more likely to shop with brands that provide offers and recommendations that are relevant to them. But it’s difficult for brands to navigate through abundance of data to find ways of hyper-personalizing. 

Big data and Artificial Intelligence (AI) have been game-changers in enabling this. Brands that leverage AI to enrich customer experience are the industry leaders today. So really, the question is not about whether to hyper-personalize experiences, but how to do it.

Personalize customer experiences through AI  

With rapid digital transformation, brands have been able to gather large volumes of data from customers. However, it is often unstructured and unorganized – which can be overwhelming for internal teams to analyze. There are many useful customer footprints across first-party data that are not even harnessed. 

Using AI, brands can turn unstructured and unorganized data into meaningful insights. These insights can help formulate strategies that not only drive customer experience but also elevate their loyalty. This is enabled right through the customer journey. 

AI can analyze big data to help businesses understand market trends deeply. Using this, they can then apply a 360-degree approach for a seamless customer experience. In a business environment, where the dynamics of customer purchases keep changing, it is imperative for brands to make real-time decisions across the entire customer journey and have a deep understanding of what customers need. This is only possible by harnessing all available data, having the ability to identify customers and provide the most relevant interventions across the customer journey. 

But how can brands drive hyper-personalization and improve customer experience? 

Driving Hyper-Personalization

Hyper-personalization provides a heightened customer experience. But it is difficult to know where brands should begin. 

The first thing to do is understand the customer. If brands have limited knowledge of their customers, it limits their ability to drive impact. It’s no longer enough to know simple demographics like age and sex. Brands need to understand customers’ needs and wants. It’s imperative that they collect and analyze behavioral, psychographic, and geographic data in addition to demographics, so they can target relevant segments of their audience. 

This layered understanding of customers can be obtained from first- and well as third-party data. First-party data is already collected and owned by the brands based on interactions with customers—shopping behaviors, favorite products, etc. 

Brands can also obtain external, third-party data such as activity on social media, websites visited, income, credit scores, etc. This helps get a clearer picture of the customer and helps brands tailor their interactions with them. With plans to phase out third-party cookies by end of 2024, it is important that brands develop an AI-enabled identity solution.  

Once brands know their customers, the next step is taking care of their needs and preferences through interventions across the customer journey. The homepage of their website can use predictive analytics to offer relevant products and offers to their customer. While shopping, in-page suggestions can provide nudges whereas while checking-out they can be shown complementary products. This increases the customer engagement with the brand. At all touchpoints customers are offered a smooth and hyper-personalized customer experience. This data-led, AI-enabled approach to customer experience leads to various benefits. A few of them are listed below:  

  1. Increased efficiency: 
    Data is powerful for those who know how to use it. Brands can overlook important data due to lack of time or money. AI helps businesses work efficiently with large volumes of data. It integrates structured and unstructured data, analyzes large volumes of data and helps optimize multiple variables to get the desired insights. This helps in reducing costs and focus on data-driven insights and strategy on a continuous basis rather than spending most of their time on the raw data. 
  2. Strong brand loyalty: 
    Personalized messaging through emails, SMSs, website, etc. reduces the clutter customers have to wade through. It diminishes the burden on the customer to sort through the noise and find what’s useful for them. With hyper-personalization across the customer journey, customers get to enjoy their experience with your brand. It helps them realize that their needs are known to you and being taken care of. This improves the customer-brand relationship and loyalty. A Merkle survey found that 86% of people prefer personalized offers based on their interests and browsing or purchase history as opposed to generic mass mailers.   
  3. Higher conversion rate: 
    When you know your customer and their needs, you experience a high return on investment just by tailoring offers and deals for them. If you’re providing relevant products at appropriate touchpoints in the customer journey, you substantially increase conversion rates. And of course, as a ripple effect of improved engagement and strong brand loyalty, you can see an increased conversion.  

Hyper-personalization is no longer just useful—it is indispensable. Today’s tech-savvy customers expect personalization at every step of their buying journey. And personalization is certainly not a new concept. But with AI, brands can create hyper-personalized experiences that win over customers. 

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