Speaker 1: Have you ever wondered why companies like Amazon, Netflix, and Spotify always seem to know exactly what you want? It's not magic. Or is it? It's data segmentation. These companies gather a lot of data, and by breaking it down into smaller, more manageable chunks, companies can create personalized experiences that keep you coming back for more. In this video, I'll teach you everything you need to know about data segmentation. So buckle up, because we're going on a wild ride through the data-driven world. What's up guys, it's Bobby, and if you're wondering why I sound like I'm going through a second phase of puberty, I'm just losing my voice. But we're still gonna get this done today, I still got stuff to teach you. For instance, data segmentation is the process of dividing your data into smaller, more manageable subsets to gain a better understanding of your audience and tailor your marketing efforts. This criteria could be anything from demographics, behavior, location, and more. And some of the benefits of data segmentation are actually really cool, like improved targeting. By dividing your audience into smaller, more specific segments based on their characteristics or behaviors, you can create more targeted marketing messages that are more likely to resonate with them. Or number two, enhanced personalization. By tailoring your marketing messages to the specific needs and preferences of each segment, you can create a more personalized experience for your customers. And number three, improved customer retention. By understanding the specific needs and preferences of each segment, you can create more tailored experiences, again, and offers that keep customers coming back. And then that'll lead us on to number four, which is increased money, I mean, revenue. By creating more targeted and personalized marketing messages, improving customer retention rates, and allocating resources more effectively, businesses can ultimately drive more revenue and improve their bottom line. And there are also many different types of data segmentation, and the appropriate type depends on the specific needs and objectives of the business. One type is demographic segmentation. This type of segmentation divides the customers based on characteristics such as age, gender, income, education, marital status, and occupation. Or geographic segmentation. This type of segmentation divides customers based on their location. So like country, region, city, or zip code. There's also behavioral segmentation. This type of segmentation divides customers based on their behavior, such as purchase history, website activity, social media interactions, and email engagement. And there's even psychographic segmentation. This type of segmentation divides customers based on their attitudes, values, lifestyles, and personalities. One real-life example of data segmentation is the way people use Spotify. Spotify uses data segmentation to create a personalized music recommendation for its users. Spotify collects a vast amount of data on its users, including their listening history, playlists, and even the time of day they listen. That's a lot of personal data. I want you to know what I'm listening to at 3am. By segmenting this data based on factors such as genre, preference, listening habits, and location, Spotify can create personalized playlists and recommendations that are tailored to each user's individual taste. For example, if a user listens to a lot of classic rock, Spotify might create a segment for that user based on their genre preference within that segment. Spotify could also then further segment by artist, decade, or other criteria to create even more target recommendations. And there you have it guys, everything you need to know about data segmentation. By segmenting your data, you can gain valuable insights into your customers and create personalized experiences that not only drive engagement and loyalty, but also just bring more revenue. Money, money, money, money. I don't know why I'm trying to sing right now. And guys, you know, if you need help, you can always count on us. Just go to www.science.com. Anyways, I hope you learned something new. If you did, make sure you like the video and subscribe for more quality content so you can stay updated in everything marketing and sales related. But I'll see you guys after a nice big mug of tea. So adios.