Segmentation vs personalization: Segmentation is a valuable approach to marketing, but it’s severely limited compared with personalization. Marketers can take a forward step to personalize their offers using BD4’s machine-learning AI algorithms.

What is the difference between segmentation and personalization?

Too many marketers place their highest hopes on segmentation, believing they have narrowed their targets into small enough groups for maximizing efficient and effective communication. The strategy is indeed better than a blanket approach and needed for strategic planning, but it is a blunt instrument when it comes to shaping personal shopping experiences.

A much deeper strategy involves personalization which contributes to better, more informed segmentation using artificial intelligence to create individualized offers based on real-time user profiling.

Marketers have to take their cues from what consumers want. And research from McKinsey shows 71% of consumers expect personalized interactions and experiences. Companies that excel at personalization generate 40% more revenue than average, through conversion optimization.

Short attention spans and information cause rethinking from segmentation to personalization

The desire for personalization is especially true for Generation Z, or Zoomers, who make up around 40% of consumers. Not only do they have a shorter attention span than previous generations, they have a habit of juggling between various screens.

Let’s face it; today’s marketers need something special to grab consumers’ attention. Bombarded with advertisements whenever they open their inboxes and social media, consumers are experts at filtering out anything that doesn’t address their personal needs.

The three-level pyramid

A good way to think of the difference between audience segmentation and personalization is to see them as part of a pyramid with three levels: data collection, segmentation and personalization. At the base is data collection, which is integral to the higher levels.

In the middle layer of the pyramid lies segmentation, which works by taking the raw data and manually creating targeted campaigns and experiences. They tend to be based on geographic zones, demographic groups, cultural origins, behavioral and psychographic identities. They help marketers display content more accurately to the right groups.

Segmentation: A blunt instrument

But segmentation only provides a vague indicator of preferences. An example of blunt segmentation is categorizing people according to pages visited and the amount of time spent on them. It gives a rough idea of a consumer’s intentions, but no more than that.

And there are other downsides. Segmentation is hard work for marketers who need to create strict categorization rules and continually update them to react to changes in the market. There’s even a danger of the marketer’s personal bias impeding efficiency.

Personalization: Reaching for the top of the pyramid

That’s why marketers need to go a step beyond segmentation to reach the top of the pyramid and create real-time personalized customer experiences using AI on anonymous user profiles to be more user-centric.

Humans have an innate need to be recognized and valued for themselves. No wonder that when Hubspot analyzed 330,000 CTAs over six months, they found personalized CTAs brought 202% better conversion than default options.

Focusing on customer experience (CX), personalization makes it possible to deliver unique messages, content and offers in real-time based on shopping preferences. Even services can be provided at different levels. The personalization becomes constantly more precise through the machine-learning algorithms continuously analyzing the users behavior.

BD4’s AI-driven personalization case study for airlines

An example is when BD4 helped an international airline drive improved revenue using AI-driven profiling. The airline wanted to maximize revenue using incentives for existing visitors, but there was a risk of diluting revenue when some passengers were going to buy tickets anyway.

BD4’s AI allowed the airline to take the potential of segmentation to a different level in order to implement a 1:1 personalized, customer-centric approach that used real-time signals in the user journey to respond automatically to shopping behavior.

Airline case study: Increasing revenue while reducing the cost of discounts!

With BD4’s AI self-learning algorithms, the airline was able to ‘see’ and understand customer behaviors accurately for the first time in great detail. The AI made it possible to know which individuals would buy anyway and which ones would not in order to target the vouchers. The airline was also able to introduce multiple voucher types tailored to each individual.

The strategy was successful. During the trial period, revenue rose between 3% and 6% depending on seasonality and time of day. In order to achieve that result using a traditional distribution of vouchers, it would have cost the airline more than US$1M over 10 months in revenue dilution. Together, this resulted in a massively positive impact on their bottom line.

Combining AI with product insights

BD4 recently increased the power of its personalization AI by teaming up with NetMatch, the market-leading Dutch provider of online distribution solutions. They are now using the BD4 solution to combine users’ behavioral data with product insights – to produce sophisticated booking engines, showcasing personalized holiday offers.

Segmentation is omni-present in marketing, but done as a simple rules-based approach it’s a limited and outdated tool. Personalization, based on AI-driven user profiling, can smartly be connected to campaigns and online experiences targeted at user segments. That way, personalization even benefits the segmentation process.

Explore how BD4’s AI-powered 1:1 personalization can help you get a deeper understanding of what your customers want.

Find out more in this demo