Put your consumer hat on for a moment and think of the interactions you have with the brands you love. Think of the emails you receive, the app notifications on your phone, the text messages and the social media interactions. Then think of the banner ads you see as you surf the internet and the targeted ads you get when you search on Google or scroll through Instagram.
For better or for worse, marketers are learning about you. They are learning about the products you use, your interests, your buying habits and your preferred communication styles. And this trend is becoming increasingly important.
From a marketer’s perspective, personalization is about showcasing the right products and delivering the right customer experiences, to the right people, at the right time. Personalization is a core element of modern, analytics-enabled and integrated marketing strategy — central to studies in advanced degree programs like the online Master of Business Administration (MBA) – Marketing Emphasis from Southern Utah University (SUU).
Why Is Personalization in Digital Marketing Accelerating?
Broadly speaking, four primary factors are driving the ability of marketers to personalize communications to small segments of consumers: consumer demand, technology, analytics driven by big data and artificial intelligence (AI). Understanding personalization in digital marketing and the interrelated factors influencing this trend is key to accelerating any career in the field, from marketing analyst and social media management roles on up to media director and even chief marketing officer (CMO) positions.
Consumer Demand for Personalization
Consumers — for the most part — want personalization, and one-to-one marketing opportunities continue to increase as marketers use technology and big data to customize each interaction. On a weekly basis, consumers witness customer experience improvements from their favorite brands.
For instance, Amazon is the leader in online retail. Though the company sells anything and everything, from popular products available in brick-and-mortar stores to obscure items that would not do well in a physical location, the experience feels as intimate as a boutique shop. No matter your interests, Amazon can appear to each user as a store dedicated solely to you.
The more a consumer engages with the website, the more it learns about the shopper’s preferences and the better it can deliver a personalized experience. Navigating the site, finding exactly what you want, getting relevant recommendations and being able to return products easily are all in part components of personalization. And remember, it wasn’t always this way.
YouTube is another example of consumer demand driving personalization. YouTube is geared to helping consumers discover content — and products — based upon what the site learns through consumer use. Each consumer gets a personalized view that adapts to their tastes but is also designed to help expand their interests. Using algorithms to make appropriate recommendations, YouTube personalizes content and shopping experiences for the customer.
Take this simple example: If the data shows that people who have subscribed to channel A and channel B have also subscribed to channel P, then A and B channel subscribers will get exposed to content in feeds from channel P.
Consider consumer experiences with media 20 or 25 years ago. Consumers would watch cable TV, scroll through the guide and hope to find something of interest. The closest this experience came to personalization was a button to set one’s favorite channels, but the viewer had to do the work.
Now, not only can consumers quickly get to the content they want through many media providers, but the providers actively find and provide content that consumers would never find without personalization.
Technology Enables Advanced Personalization
Advances in tech have enabled marketers to continue discovering new ways to personalize marketing communications. Websites enable consumers to customize products to their liking, with tailored fits and color schemes for clothing and apparel as an example. Nike enables shoppers to customize their own shoe designs and even promote those designs via social media.
Marketing automation tools enable marketers to trigger lead nurturing campaigns based on consumer activities or engagement with their websites and social platforms. These make it easier than ever to segment audiences with unique messages that seem tailored to each individual consumer.
Mobile technologies take personalization a step further, with automated alerts triggered by customer preferences from downloaded applications and beacon technology that automatically sends messages to people within a certain geographic location — near one of the company’s stores they’ve shown interest in online, for example.
Big Data Drives Marketing Analytics
Data is behind all these consumer experiences and technologies. For example, remarketing technologies that show ubiquitous banner advertising relevant to a consumer’s prior online activities are enabled by Google’s continuously growing database. Corporate consumer databases have grown amazingly complex over the years simply by amassing information that consumers have provided.
Companies like Facebook compile behavioral databases that marketers can use to target the people most likely to be interested, based on recent prior online activities. Advanced predictive analytics technologies help companies utilize insights derived from big data to forecast trends and potential responses to personalized marketing efforts. As with every function of modern business, marketing will forevermore be data-driven.
Artificial Intelligence Is a Game-Changer
AI is not new, nor is its use in digital marketing applications like personalization. But AI technologies advanced exponentially over recent years, expanding the impact it can have in improving marketing strategy and methods. AI technologies like machine learning (ML) and natural language processing (NLP) are foundational to the software that companies use to conduct market research, analyze consumer data, personalize marketing efforts, improve the customer experience and automate marketing processes.
Moreover, the birth of generative AI opened the door to a whole new realm of AI-driven marketing applications. Generative AI expands on (and makes use of) other AI technologies and large language models (LLMs). When given appropriate training data, generative AI software — ChatGPT being a widely known example — can generate text, images, code and much more. In marketing applications, generative AI can be used to automate and scale tasks like content creation, chatbot interactions and customer relationship management.
Further, generative AI can be applied to improve personalization and branding across marketing channels while also advancing the capabilities of the analytics that drive personalization. As such, generative AI has the potential to expand personalization in both the input and output of marketing processes.
Personalization has come a long way in just a few short years, and the trend will only accelerate from here. Given how consumer demand, technology and databases do not advance on a linear curve, but rather exponentially, a fascinating future awaits those who invest in learning more about personalization in digital marketing.
Learn more about Southern Utah University’s online MBA – Marketing Emphasis program.
