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Personalization vs Individualization: Marketing Basics

December 13, 2019
5 min reading time

Excitingly, marketers now have an opportunity to change their online messaging for each consumer.  In some ways, marketers have always had some sort of strategy to react to the needs and wants of their consumers. Previously this information was best collected through focus groups and other offline metrics over long periods of time.  Now, however, we have the opportunity to react in real-time.

But how do we most effectively use the tools available to us now?  What do some of these things mean? What is personalization? And how does individualization tie in?

Personalization is a technique that uses basic customer data to tailor messages to each audience at once. Individualization speaks directly to each individual within those groups, and requires a much richer data set. 

Personalized marketing typically uses general data such as past purchases or user logins.  That data is then used to segment audiences into groups. Instead of communicating with someone based on their segment, individualization communicates directly with each person one on one.  Sometimes, messaging can be shaped by data that is entirely unique to them. 

Customers have always expected brick-and-mortar businesses to cater to their needs. Today, many technologies are able to analyze data online and customers are starting to expect online businesses to do the same.  So, simple personalization based on general data isn’t enough anymore. 

Online businesses need to accept that simple personalization is outdated. In the past, customers would expect nothing more than having their first name in the welcome line of an email. But today, nearly everyone has some version of simple personalization strategies in place. Basic personalization at that level is now an expectation, not an innovation.

Individualization vs. Personalization


Mass Marketing: 
Expensive, untargeted mass marketing messages used to tell one story to a mass audience. Although mass marketing targets a large group of people at once, it fails to segment audiences in any detailed way.  

Once newspapers came around, a company was able to sell its products directly to a mass audience.  While greatly reduced in scale and price, mass marketing campaigns still occur in printed magazines, billboards, and even the Super Bowl.

A/B Testing:  Running an A/B test is a tactic almost as old as the printing press. A/B testing occurs when marketers compare two versions of a marketing asset with only one varying element. A/B Testing makes data-driven marketing decisions based on test results that reveal user behavior and tendencies. 

The biggest difficulty with A/B Testing is the complexity of reacting to test results.  Testing tools have improved with technology. However, the best results come from a continuous process that sometimes requires constant manual oversight. 

In fact, many multivariate tests fail to deliver significant benefits. The more variants used, the more time consuming and frustrating the tests can become. Regardless, A/B testing was the first step that marketers took towards modern-day segmentation.  

Segmentation: Segmentation uses basic information to bucket prospects into similar groups based on similar interests, locations, or needs.  Through testing, marketers learned that different messages worked with different people. Segmentation allows marketers to create different designs and layouts for different segments, or to scale interfaces to suit different devices.  

While this technique created a better customer experience, this technique also requires personal information.  Unfortunately, modern marketers have amassed a scary amount of personal information as a consequence. While the individual customer benefits from a better message or product, that same customer no longer enjoys their privacy.

Personalization: Companies can now shape their messaging through personalization with a very clear picture of the consumer.  Personalized experiences can range from personalized messages on a website (“Hi Erin, welcome back”) to completely altered images and button colors.

A personalized journey can easily come across as creepy if executed in the wrong way. If done right,  personalization will offer a visitor a more humanized experience. Online personalized greetings welcome website visitors like the store owner would do at your local clothing boutique.  Personalized product recommendations find things you want just like the boutique owner showing you that cute new shirt.

Traditionally, businesses could only greet you by name or recommend a shirt when you came into the store in person.  Now, online businesses have a lot of the same information available through your past purchases or abandoned shopping carts. 

Individualization: While certain kinds of personalization can be done with a limited amount of data, individualization is a more complex variety.  To truly individualize, you must be speaking to your user as a segment of one. Online individualization is only really possible by combining a massive amount of data.

The best way to speak directly to each consumer is to leverage two separate data streams.  Firstly, continue to personalize based on what you know about that user. Secondly, collect as much of the users’s behavior as you can.  

The more data you can access, the closer you can get to true individualization.  However, all of this data would be too much for a human to collect and use at any given moment.  Fortunately, we’re doing business in an age of advanced machine learning and AI systems, which brings these marketing dreams firmly into the realm of reality.  

The data that drives individualized marketing

Individualized marketing is the most effective strategy in which marketers can reach individuals and relate to them in a timely and personalized way. An individualized marketing strategy should include a recommendation engine that recommends the most relevant products to each individual.  

The engine should look for hints and cues as to what each customer’s goals and needs are.  If you know what the customer is looking for, you will be able to show them products or content on an individual level.

A note about privacy

The methods to achieve individualization, and personalization in general, are sometimes a bit invasive. Increasingly, massive amounts of personal data is collected and used to guide marketing strategies.  LiftIgniter’s recommendation engine does not require personally identifiable information or 3rd party cookies. Instead we leverage anonymous behavioral data to produce the best results. 

However,  consumers may concede to some personal data in exchange for personalized content.

A recent study found that 52% of consumers would share personal data in exchange for product recommendations.  53% of users would do the same for personalized shopping experiences. 

What this study shows is that companies can improve the user experience using personal data in an ethical and transparent manner.  If trust is gained, consumers feel more comfortable sharing more about themselves. If your customers trust you, you can truly connect your brand to each individual.

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