How To Improve Consumer Experience With Dynamic Audience Segmentation

As consumers become more conscious about the time they spend online, it is harder than ever for brands to attain consumer loyalty. Marketers rely on a variety of processes to connect with consumers in meaningful ways, perhaps the most common of which is audience segmentation. In the best-case scenario, audience segmentation helps brands better understand consumers and deliver the right message at the right time. However, as technology evolves, consumers are outgrowing the traditional ways of audience segmentation and seeking personalized experiences. As a result, marketers need to adapt. 

The consumer journey has become more complex, and consumers’ habits, expectations, and preferences are changing quickly. Predictive personalization is the key to effective marketing because it allows marketers to deliver relevant messaging, content, and product recommendations at intent-rich moments. Audience segmentation has been the foundation of personalization, but with new technologies, the traditional means of audience segmentation do not always allow for effective personalization because it is not scalable. 

Marketers can no longer rely on a “one-to-many” approach to messaging. According to a recent report by AccentureOpens a new window , in 64% of the instances that customers shift from one brand to another, it is to seek a more relevant product, service, or experience, and this number is likely to increase. Although not as effective as one-to-one personalization, dynamic audience segmentation can help deliver more personalized and relevant experiences to consumers.

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What Is Dynamic Audience Segmentation?

Traditional audience segmentation is the practice of dividing a brand’s audience into groups that reflect common characteristics, such as demographics or psychographics. With traditional audience segmentation, the number of segments is fairly limited — marketers have a finite number of segments they can tailor messaging and experiences for, and that number is not very high. The segments require manual curation and are also static, which means they do not change in real-time while a consumer journey unfolds.

Consumer behavior and preferences now change in minutes, not months, depending on the experiences they have online and various decision points they encounter. That means the consumer experience needs to adapt quickly, ideally in real-time. This is where the “dynamic” piece comes into play. Dynamic audience segmentation allows you to adapt segments in real-time, based on more complex criteria like who your consumer is, external factors, as well as changing consumer preferences and behaviors. 

For example, if you color your hair, you would usually fall in a “colored hair” segment. You might receive product recommendations like hair dye, but realistically you will not need the hair dye for six to eight weeks. Dynamic segmentation would mean that as your hair color fades, you would receive the hair dye recommendations. But when you have just dyed your hair, you would receive only recommendations for color protection and hair care. 

Why Do Marketers Need Dynamic Audience Segmentation?

Dynamic audience segmentation is a great first step on the journey to predictive personalization. It can help you understand the consumer journey and find more complex patterns in consumer preferences and behavior that are grounded in data. Using historical data and relying only on demographics is not enough anymore. The digital landscape is so competitive, and consumers expect more relevant experiences. 

Marketers understand that all consumers are unique. At each step of the consumer journey, every person has their own context — interests, purchase habits, and other changing external factors that impact their choices. The challenge is understanding as much as possible about these behaviors and characteristics and then acting on them in a timely manner.

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Here is how dynamic audience segmentation can help:

Enables effective personalization at scale

Traditional audience segmentation is manual and quite hard to do effectively and at scale. Marketers today are restricted to tailoring messages and experiences for a few broad segments (first-time visitors, returning customers, etc.). But it often leads to poor results and over-communication among known consumers. It is impossible to do more in real-time without some help from AI-powered technology. Using AI-powered tools to enable dynamic audience segmentation can identify patterns that are difficult or time-consuming for humans to uncover and create truly relevant experiences for segments at scale. The heavy lifting does not require much involvement from marketers. 

Optimize the consumer experience in real-time

Consumers are continuously presented with an abundance of offers, messages, and invitations from brands, meaning their attention and preferences are ever-changing. Because of these shifting dynamics, more and more, the online experience is happening in real-time. If you’re unable to meet the consumer where they are and make their experience individual and relevant, they’ll simply move on to another brand. 

Dynamic audience segmentation can help you see beyond the surface and understand consumer behavior on a much deeper level. For example, a salad dressing brand might want to recommend recipes based on food trends. However, what is popular with foodies in Paris, France might differ from what’s all the rage in Miami, Florida. Traditional segments would be based on popular food searches, but wouldn’t factor in specific locations and up-to-the minute food trends in those different locales. People also have varying cooking skills and diets which is important when personalizing recommended recipes. 

Dynamic segments would allow you to provide recommendations based on more complex criteria like “recipes based on local food trends for individuals who are vegetarian”. This level of segmentation can help increase the likelihood of consumers finding exactly what they are looking for at the right time. 

Achieve business objectives and improve marketing ROI

Bottom line matters for any brand. Dynamic audience segmentation can be an easy way to see results like conversion and retention quickly. Using AI-powered tools, you can save time analyzing data and test simple use cases that accurately show end-to-end results. It is important to look for tech solutions that integrate seamlessly and quickly with your existing tools so you can execute within weeks, not months or years.  

At the end of the day, it all comes back to meeting consumer needs. Your consumers are complex individuals, and it is important to deliver experiences that acknowledge this and make them feel understood. A technology-driven approach to dynamic audience segmentation can create more relevant, personalized digital experiences while easing the burden on marketing teams — meaning consumers are more likely to be loyal, and you are able to improve business results effectively.

Have you used dynamic audience segmentation as part of your marketing strategy? What benefits have you seen? Let us know on FacebookOpens a new window , TwitterOpens a new window , and LinkedInOpens a new window .

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