Email marketing has been a reliable marketing channel for decades. However, with the rise of personalised and segmented email campaigns, it has become more important than ever to use data to inform your email marketing strategy. In this blog post, we’ll explore the role of data in email personalisation and segmentation and provide some best practices for using data in your email campaigns.
What is Email Personalisation?
Let’s start with an obvious question, what is email personalisation? Email personalisation involves tailoring your email content to individual recipients based on their interests, preferences, and behaviors. Personalised emails can be as simple as using a recipient’s name in the email greeting or as complex as customising the email content based on their past purchase history. Personalised emails are more effective than generic emails because they’re more relevant and engaging for the recipient.
To achieve email personalisation, marketers use data to segment their audience and tailor their email content accordingly. This is where data comes into play.
The Role of Data in Email Personalisation
Data is essential for email personalisation because it provides the information needed to create personalised content. Marketers use a range of data points to personalise their emails, including:
Demographic data: age, gender, location, etc.
Behavioural data: website browsing history, email opens and clicks, purchase history, etc.
Psychographic data: interests, values, personality traits, etc.
By analysing this data, marketers can segment their email list and create personalised content that’s relevant to each segment. For example, if you’re an online retailer, you might send different emails to customers who have previously purchased women’s clothing versus those who have purchased men’s clothing.
What is Email Segmentation?
Email segmentation involves splitting up your email list into smaller groups based on characteristics, such as age, location, purchase history, or any other data you might have. By segmenting your email list, you can send targeted emails to each group that is more likely to resonate with them.
For the automotive industry, you can become granular and segment right down to colour preferences and brands or models the customer has been looking at on your site.
The Role of Data in Email Segmentation
Data is essential for email segmentation, it really wouldn’t work out it. This is because it’s the information needed to create effective segments. By analyzing your data, you can divide your email list into smaller groups based on shared characteristics.
For example, you might create a segment of customers who have purchased in the last 30 days or a segment of customers who have signed up for your email newsletter but have never made a purchase.
Let’s be honest, we don’t want to be sending out a sale email to a customer who has just placed an order with you.
Best Practices for Using Data in Email Marketing
To create effective personalised and segmented email campaigns, it’s important to use data ethically and responsibly. Here are some best practices to keep in mind:
Collect accurate and relevant data: The quality of your data is key to the effectiveness of your email campaigns. Make sure you’re collecting accurate and relevant data that will help you create effective segments and personalised content.
Analyse your data: Once you’ve collected your data, use it to inform your email strategy. Analyse your data to identify patterns and insights to help you create more effective email campaigns.
Use data ethically and respect privacy: It’s important to use data ethically and respect your recipients’ privacy. Make sure you’re using data following GDPR regulations and other relevant privacy laws.
Case Studies of Successful Email Personalisation and Segmentation
It’s all fine and well explaining the different elements and talking through the different things you can do to use personalisation, but there isn’t anything better than real-life examples. So, here are some examples of brands that have used data effectively in their email campaigns:
Netflix: Netflix uses behavioural data to recommend movies and TV shows to its subscribers. By analysing what its subscribers have previously watched and liked, Netflix creates personalised recommendations that keep its subscribers engaged.
Adidas: Adidas uses personalization to send customised product recommendations based on customers’ past purchases and browsing history. They also send personalized emails with offers and promotions that are tailored to customers’ interests and preferences.
Starbucks: Starbucks uses personalisation to send customized emails to its customers with offers and promotions that are based on their past purchases and preferences. They also send personalized emails to customers on their birthdays and anniversaries with special offers.
Amazon: Amazon uses personalisation to recommend products to its customers based on their purchases and browsing history. They also send personalized emails with offers and promotions that are tailored to customers’ interests and preferences.
