Ever since the swell of big data combined with the technological advancements of cognitive computing made giant strides in the final years of the last decade, personalized marketing suddenly became a tangible feat.
This revolution that harbored infinite possibilities led to a radical shift of businesses when it came to interacting with their customers who were ever-evolving and dynamic in their demand.
Arriving at the dawn of a new period which would later be termed as the “age of the consumer”, these advancements helped businesses provide consumers what they had always wanted. Personalization.
Before the age of the consumer kicked in, personalization used to be a marketing novelty. Today, however, both consumers and businesses see it as an indispensable part of the customer’s journey.
So much so that 84% of consumers expect brand communications to take place on a personal level. As marketers growingly recognized the power of personalization, they began investing into it as well to fulfill customer needs at scale, thus driving increased profits.
In fact, this mien of marketers is evidenced by the fact that 75% of them consider dynamic and personalized content as very important, especially in the face of the common consumer behavior, where 75% of them have proven to favor brands that offer personalized services.
The obvious conclusion this imparts is that, with consumers increasingly buying from brands that have demonstrated the ability to deliver personalized services, there is a severe need to personalize every customer touchpoint.
However, as with everything in this onerous age of the consumer, personalization has worn off its status as a novelty, with people expecting it at every touchpoint of their buyer journey nowadays.
Fortunately, AI and analytics capabilities have gotten advanced enough in recent years to meet this demand contentedly, thus giving rise to an elevated form of personalization that sets them apart from their competition.
What Is Hyper-Personalization?
This exalted status of personalization, or hyper-personalization as it is commonly known, is all thanks to machine learning and AI. However, the path to it was far from easy.
Way back in 2016, when businesses had just hopped on the chat bandwagon, personalization as a tangible service seemed only a hair’s length away. However, fiddling hastily with the scope of the technology by adopting a unilateral approach, companies saw that they gave rise to more problems than they solved for their users.
As businesses learned with time, they shook off their one-dimensional methodology and approached the creation of digital customer experiences with automation that adapted to the situation based on the user’s context.
With the help of user data like their service/product history and browsing preferences, forward-thinking businesses upped their efforts to give birth to hyper-personalization.
Hyper-personalization leveraged AI and real-time behavioral customer data to offer more appropriate content and connected services to each user — all in the spirit of diminishing the cognitive effort of the consumer.
The behavioral analysis became a key component of this exercise and entailed dividing customers into segments on the basis of their behavior. This included factors such as:
- their affinity towards your brand, product, or service
- their purchasing tendencies based on occasions
- their product or service usage behavior
- their overall knowledge of your brand and its products
The behavioral insights that were extracted from this analysis then became the pillar on which the barebone structure of hyper-personalization was formed. It utilized user data and the creative application of cognitive computing to deliver highly relevant services and content to their users at every touchpoint in their customer journey.
The Difference Between Personalization and Hyper-Personalization
As described above, hyper-personalization is an elevated form of personalization where brands tailor their marketing offerings on a per-user basis, whereas personalization is based on the information provided by users.
A classic example of personalization would be a targeted email for a product offering to an existing customer. Take, for instance, an email that has the recipient’s first/last name automatically inserted in the subject line and/or the message for a new product offering that is highly or somewhat relevant to other previous offerings.
Hyper-personalization, on the other hand, utilizes sophisticated algorithms and big data sets to infer crucial details about the customer’s desires and needs. One great example of hyper-personalizations is that of Netflix who learns the preferences of its viewers to make content suggestions.
How Hyper-Personalization Helps Brands Deliver Improved CX
The marketing landscape of today is extremely fragmented. Consumers have access to infinite media and are easily distracted while interacting with it, viewing and discarding numerous marketing messages in the process.
Hyper-personalization enables brands to sidestep this fate with service offerings and commercial messages that are customized to the minutest user detail. Brands can deploy an analytics-driven program that utilizes advanced data modeling to learn what works for their audience, thus allowing them to personalize their marketing messages and consequently enhance their customer lifetime value.
This goes to show how important hyper-personalization is today and how it makes for improved engagement rates throughout the marketing funnel. The final sale today is prefaced by several user touchpoints — and hyper-personalization can help improve the overall brand experience of everyone.
4 Ways to Provide Hyper-Personalization
AI is enabling businesses to harness user data that they have collected in the past to translate it into highly personalized experiences. Here, we will take a look at four ways that you can do just that.
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Personalized Messaging in Marketing Ads
Jared Brickman, a Marketing Strategist at Centerline Digital, long predicted that marketing personalization in the near future would be defined by hyper-specific targeted experiences.
Luke Rees, Head of Digital Marketing at AccuraCast, agreed to this and also added that “Personalization only works when it’s relevant and useful. People never mind being interrupted if the ad’s message is interesting to them.”
Many touchpoints in the buyer journey harbor potential for personalization, such as devices, interaction channels, specific times of the day when customers engage with the company, etc. However, brands can also personalize ad content, discount offers, paid media messages, and more with the help of data-driven marketing.
UK telecom provider, O2, is the perfect example of a brand utilizing this to its advantage to offer hyper-personalized marketing. The brand harvests user data and shows its customers personalized ads with custom messaging, which extends to its video ads as well.
By dynamically adapting the marketing message or offer, O2 has been able to generate more than a thousand hyper-personalized variations of the same video, all of which have resulted in a 128% better clickthrough rate than generic videos.
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Co-Browsing for Real-Time Support and Query Resolution
Customers today prefer a live chat. In fact, 75% of them would rather chat online in real-time with a support rep instead of talking to them on the phone. However, this is the furthest that most organizations’ personalization efforts go.
In fact, an Accenture report titled ‘Digital Disconnect in Customer Engagement’ found that 83% of businesses would have been better served had they delivered superior interpersonal customer service.
As mentioned above in the article, customers expect personalization at every touchpoint, even more so while using a live chat.
This is why businesses should always look for tools to equip their support team with so as to help them offer more personalized service by comprehending customer context accurately.
One such tool is co-browsing. Cobrowse technology unlocks a higher degree of personalization by combining real-time experience and human relationships. It aids your support team in gathering the customer’s query context instantly by sharing their screen so that you can offer them tailored services by guiding them through parts of the buyer’s journey that they find confusing.
Take the example of Canadian home furnishing retailer, The Dufresne Group. By deploying a co-browsing tool through their live chat, they were able to replicate their in-store experience online, resulting in 10x online sales chats in two weeks.
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Combining Elements Of the Programmatic and the Creative
Programmatic marketing is the unlikely rescuer of marketers that strive to offer hyper-personalized advertising experiences to their customers. In an age where users take a unique path to buy products or services online, programmatic marketing presents an unexpected opportunity to provide hyper-personalization by enabling a data-driven way of marketing services.
The audience targeting capacities of programmatic marketing supplement its ability to offer personalized content to unique user segments. And when combined with creativity, it allows brands to bring their users to the center of their marketing initiatives.
A great example of this is the German railway company, Deutsche Bahn. As part of their marketing campaign, ‘No Need to Fly’, the brand endorsed national travel to country natives instead of booking an expensive international flight. With the help of an AI algorithm, the brand collected the most popular destinations people wanted to travel to and identified similar-looking German landscapes and destinations.
They then juxtaposed the two destinations and offered a price comparison to travel enthusiasts by utilizing their social media customer data. When people realized that they could travel within their home country to a location that was almost identical to the international destination, they unsurprisingly opted for the cheaper train ticket, resulting in a 24% rise in sales revenue and an 850% clickthrough rate.
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Personalized Push Notifications
If your brand dabbles in mobile marketing, you have a great opportunity to deliver a hyper-personalized customer experience through push notifications. You can do this by gathering comprehensive customer information from all data points and utilize it to suggest suitable products, offer reward programs, and give away discounts or freebies as well.
Starbucks is the perfect embodiment of this. By utilizing the real-time data of their users, they have upgraded their loyalty program, which credits users for their purchase actions in terms of loyalty points. This has enabled them to create more than 400,000 variations of hyper-personalized push notifications, resulting in the formation of a persuasive tactic that will most assuredly bring customers back to the business.
Conclusion
Hyper-personalization is an iterative process, and you will have to build upon it frequentatively through structured execution and steady digital transformation.
However, the most important component of it is undoubtedly access to user data. Data is the cornerstone of emotionally intelligent and highly personal marketing, and once businesses have their strategy in concordance with technology, hyper-personalization can begin.