Customer segmentation is the practice of putting customers into groups that are similar in specific ways. The goal is to tailor marketing to best meet individual needs. As a result, it improves customer satisfaction, revenue, and profitability.
There are four types of customer segmentation: Demographic, Psychographic Geographic, and Behavioral. With the rise of machine learning, artificial intelligence, personalization, and split testing, changes in customer segmentation can occur quicker with a significant impact.
Here are 6 customer segmentation case studies that show big results.
Airbnb uses machine learning to gain insights from user reviews. Then, they use this behavioral data and preference to pair hosts and guests. With A/B testing, they discover how website changes affect consumer behavior. They are able to adjust and personalize the content that users see when browsing the website.
BabyCenter (Johnson & Johnson)
For BabyCenter, Johnson & Johnson uses a Facebook Messenger App to suggest personalized advice. Through a series of questions and answers, they make targeted recommendations based on the input it receives from the user,
They look at the data to see what drove the highest levels of traffic to the website – a chatbot, email marketing, or the app. What they find is the messenger app has a read rate of 84% and a click-through rate (CTR) of 53%. The app’s overall engagement rate is 1,428% higher than email. Because it offers the greatest personalization.
DavidsTea customer segmentation
DavidsTea uses email marketing to recognize customer loyalty. When a customer reaches a specific anniversary with the company, they receive a “look back” email. It contains data on their first purchase, their most purchased teas, and how much they bought.
Therefore, by receiving this email, the customer feels unique and valued throughout their customer journey and is inclined to continue purchasing.
The Lego Group faces the challenge of marketing Lego Bricks on social media. The company identifies six distinct personas based on purchase and usage:
- Lead Users—people LEGO actively engages with on product design
- 1:1 Community—people whose names and addresses they know
- Connected Community—people who have bought LEGO and have also been to either a LEGO shop or a LEGO park
- Active Households—people who have bought LEGO in the last 12 months
- Covered Households—people who have bought LEGO once
- All Households—those who have never bought LEGO
The first three personas represent the most fertile ground. Because they share a deeper involvement with the brand. From there, Lego builds online communities on the social networks these segments use most often.
Lego takes advantage of their most valuable asset, their fans, who post pictures, videos, and provide new product ideas. This effort helps them to increase to the world’s fourth-largest toy manufacturer.
Netflix uses personalization that begins as soon as a user creates an account with Netflix and streams even just one TV show or movie. They use an algorithm that allows them to consistently and accurately A/B test and experiment with viewer preferences. Netflix’s algorithm dictates everything – the homepage layout, the recommended content, and even the visuals, or landing cards, for each piece of cinema. What’s more, Netflix personalizes the image you see based on the actors, actresses, or genres that it thinks you like. Netflix’s recommendation system saves them a massive $1Billion per year.
Olay customer segmentation
Olay creates Skin Advisor. The artificial intelligence beauty tool collects data from customers by asking them five to seven quick questions about their skin. The advisor then reveals the true age of the customer’s skin, and recommend products.
The data shows many customers are seeking Retinol based products. However, the subsequent lack of Retinol products in its range is contributing to the brand losing customers. Therefore, Olay releases Retinol 24 which has gone on to be one of the brand’s best selling products and has helped transform their sales.
Do these case studies help you see the impact of effective customer segmentation? And the tools you can apply, today?