This article was originally published in DataQuest India and has been reproduced here with permission.
Sometime ago, when we began thinking about personalization in marketing, it was more around the potential of broad-based targeted communication through emails and campaigns.
Soon, it evolved! By adding contextual and location-specific information, it came a step closer to being personal and relevant. Industry experts started writing about the possibilities of exploiting in real time all available customer data through analytics and machine learning (see my 2016 article When one thing leads to another). This one-to-one approach was cited as having the power to enhance brand loyalty by delivering better customer experience (CX).
Now, with AI becoming mainstream, connecting with customer journeys is a reality and is proving to be a boon for real-time personalization, or what is now being termed as Hyper Personalization.
Hyper personalization is a natural progression in digital marketing, which is built on the premise of building more relevant and personal communications with customers. Successful hyper personalization means understanding the elements of customer intent, context, time and location. Intent gives detailed insights that can power focused personalization efforts. It also means knowing the context of individual customer journeys and the probability they will buy from you, because customers not only differ on what they want to buy but also on what they would be willing to pay for.
When businesses can gather data on consumer intent, behaviours and location, it helps them deliver highly contextual messages at the right place and time. This is where AI comes in. The AI-powered applications that are used most effectively in a hyper personalization strategy are predictive analytics, user experience and content creation applications. It helps the enterprises traverse through the starting point of the customer journey from the ‘feel’ (digital) element to the ‘touch and see’ (physical) element such as in QSRs, banks or retail stores.
In short, hyper personalization facilitates the process to ensure services and products are accessible to customers both online and in the physical world. It’s ultimately about bridging the gap between marketing and commerce to turn every digital exchange into an experience that reflects customer intent, their exact context and their journey at the point of interaction.
Let’s consider an example of hyper personalization in a Quick Service Restaurant. QSRs can now quickly change menus and serve your favorites – dynamically influenced by the weather, the time of day, the traffic, and most importantly your personal choices. What’s more? As you drive through, your vehicle number plate is recognized and your ‘usual’ order served.
AI technology is also allowing the restaurant to upsell products – again using data collected from serving millions of fast-food customers – mapped to your liking, based on your location, and time. For example, it suggests items that are faster to make during peak hours to reduce service times, thereby making the job of the restaurant staff easier, but more importantly giving you more of your lunch hour to enjoy!
Add this to the existing innovations in customer service such as the mobile ordering, in-store touchscreens and table service, they really are providing a much more personalized experience.
Innovations such as the “Netflix effect” have not only driven customers’ desires to hyper personalized experiences, but have also ensured that AI is no longer alien to customers. Companies like Netflix, Amazon, and Spotify are trying to understand customers’ personal choices based on their activities and transactions, and subsequently recommend relevant content seamlessly across their mobile app or the web, or on TV. For example, Amazon’s hyper personalization approach helps it make 35% of its sales through recommendations, while Goibibo increased its conversions by 11%.
This begs the question, why can’t we (yet) get the same level of hyper personalized CX and service from a restaurant, bank or a retail store? The answer: It’s only a matter of time!
Hyper personalization thrives in a digital and connected scenario. But it can be successful as a marketing proposition only when different business entities are in sync. For example, to enable a smooth, hyper personalized offer may require agreements between a bank, credit card company, retailer, etc., where they agree to share all details of customers. Then, it leads to the bigger question of how much information will governing bodies allow to be shared, what can be shared, and whether any privacy laws are being violated.
These are hindrances no doubt, but given the irresistible force of hyper personalization and its impact on commerce, it’s expected to be a part of our everyday marketing mechanism in the next two to three years. The AI platforms needed to implement such personalization already exist. And, this is being further aided by newer and better approaches introduced by the plethora of AI-based startups. These approaches include curating and using large amounts of customer data and content with the intention of delivering real-time and personalized cross-channel experiences.
As these technologies mature, they are being bought over and integrated into existing CX platforms, thereby delivering better customer experience. Examples being Marketo acquisition by Adobe, or Datorama by Salesforce. These products are being integrated into the CX platforms to offer a seamless customer experience that is easier to implement, making hyper personalization real.
So, when you visit your bank‘s website the next time, don’t be surprised if they offer you loan for that car which you took for a test spin the previous week!