The COVID-19 quarantine sped up the adoption and development of digital marketing. When stores and people stopped meeting in person, businesses and customers quickly moved their operations online.
Marketers are quickly picking up the skills they need to personalize the customer experience. Customers now want even greater levels of customization, which has marketers trying to figure out how to progress from basic to hyper-personalization. Accenture found that 91% of customers are more likely to buy from companies that have actively spoken with them and presented them with deals that interest them. When done properly, personalization helps marketers stand out from the crowd. Companies like Amazon and Netflix were early adopters of personalized digital marketing.
What’s the big deal about targeted advertising?
Personalization’s advantages are better brand recognition, higher customer satisfaction, more conversations, and higher overall website metrics. According to a McKinsey study, 71% of consumers want firms to tailor their offerings to them, and more than 75% are dissatisfied when this isn’t the case. Customers become dissatisfied with a company’s product or service and look elsewhere. According to the same McKinsey analysis, businesses that implement personalization strategies claim up to 40% higher revenues and other measurable outcomes than those that don’t.
However, the rules and dynamics of the digital marketing world are continuously shifting as new problems and expectations provide a new opportunity for marketers to rethink their approach to customer engagement.
When Should You Use Personalization, and When Should You Use Hyper-Personalization?
Personalization, like hyper-personalization, aspires to provide each customer with unique content, communications, and offers.
Data, technology, and increased customization set hyper-personalization apart from standard customization.
Now, let’s examine these three key distinctions in further depth…
- Personalization based on the Data Standard relies on the most basic customer information, such as their names, demographics, locations, and purchases.
- More advanced and real-time data, including search and browsing history, purchases, consumer affinity, and sentiment, are all a part of hyper-personalization.
- Technology Standard personalization uses marketing automation, analytics, and rules-based personalization to show and promote relevant content, products, and offers.
- To collect and analyze data and provide personalized experiences, hyper-personalization employs artificial intelligence, machine learning, predictive analytics, sentiment analysis, and recommendation engines.
Customization Degree
- Conventional personalization gives customers individualized service based on their online profile information.
- Hyper-personalization goes a step further by combining information from various sources, such as online and offline transactions and the profiles of individuals with similar tastes and preferences.
- It also connects the dots between a company’s various sites of customer interaction, such as its website, mobile app, chatbot, call center, and retail locations.
- This allows for a comprehensive profile of each consumer and a personalized experience at every touchpoint.
Striking a Hyper-Personalized and Confidential Balance
- You must have noticed that we’re leaving cookies in the past. Companies are forced to get creative to gather the information they need to provide the type of service their customers want and expect.
- This difficulty initially sparked interest in, and then widespread adoption of, zero-party data. Businesses amass information about their customers, such as their profiles, buying habits, problems, and contact details.
- However, this method is not risk-free and needs to be approached carefully. Getting consumers’ permission to use their data and allowing them to revoke that permission at any moment is crucial not only from a regulatory standpoint but also from a trust and loyalty one.
Three main changes will improve the individualization process.
We should expect to see three significant changes in customization during the next five years:
- Future ‘digitized’ physical places
Our research shows that only 10% of businesses are systematically extending their use of customization outside digital channels. There’s a huge window of opportunity there. Store visits are one such area where this could have a major impact. Based on the results of our study, “offline” person-to-person interactions appear to be the next frontier for customization. CMOs predict that by 2022, 44% of frontline workers will use insights from advanced analytics to provide a personalized offering, 40% of personal shoppers will use AI-enabled tools to improve service, and 37% of facial recognition, location recognition, and biometric sensors will become more widely used.
- The capacity for empathy will grow.
Relationships thrive when both parties can empathize with one another’s feelings. The recognition and use of social cues develop trust. Digitally or in large quantities, that is challenging.
That’s starting to change as machine learning becomes significantly more adept at identifying and responding to various human emotions. More complex algorithms enable computers to understand better and process different types of data (visual, aural) and extrapolate feelings. Amazon has patented improvements to its Echo gadget that will allow it to identify signs of illness, such as a stuffy nose. Furthermore, the field of golang web development is also evolving rapidly, leveraging the power of the Go programming language to build robust and efficient web applications capable of integrating machine learning algorithms for emotion recognition and data processing.
Brands will leverage ecosystems to customize customer experiences from beginning to end.
The client experience is shared amongst multiple service providers. Many factors, including mall management, individual stores, and the branded goods available to consumers, influence the shopping experience. But they only view and affect a small part of the shopping process. The next level of personalization gives a great chance to bridge such gaps, as growing partner ecosystems allow companies to deliver more unified and consistent experiences to consumers at every point in the decision-making process. Personalization programs are getting smarter at anticipating user wants to help transition from one system (the car) to the next (the lights and heating in the home).
Ethical Implications of Highly Targeted Marketing
The advertising industry is constantly changing with the rapid development of new technologies. Thanks to hyper-personalized advertising, companies may now reach consumers with more relevant messaging and individualized offerings. This may be a win-win situation for firms and customers, but it raises some ethical questions.
- The Benefits of Highly Targeted Marketing
From a commercial perspective, hyper-targeted advertising has many advantages. Businesses can better satisfy the demands of their customers by tailoring their communications, products, and services to the specifics of each customer’s situation. This improves their advertising’s return on investment and the delight of their customers.
- The Downside of Customized Marketing
However, some ethical issues have been raised about extremely targeted marketing. Businesses can get unprecedentedly sensitive information about their clients by learning about their preferences. When this information is misused, customers can be manipulated through manipulative tactics like emotionally-charged advertisements. Concerns have also been raised over data privacy and the possibility of data abuse by companies.
Conclusion
Personalized marketing has its benefits and drawbacks. Companies gain an edge by better catering their communications and wares to individual consumers, while consumers reap the benefits of a wider selection of individualized goods and services. However, there are moral questions about how firms could exploit users’ personal information. Finally, businesses should consider the moral implications of hyper-targeted advertising and take measures to protect the privacy of their customers’ information.