The golden rule of sending emails is relevancy. In a “me, me, me!” society, sending emails that are relevant to your recipient is top priority. However, there’s a lot more that goes on behind the scenes for every personalized, targeted email send. Personalization in your emails is only going to ever be as specific or accurate as your data. Are you collecting the personalization data points you need to send specific, relevant emails?
Demographic
The basic level of personalization data you need to collect is demographic information. Typically, this is going to be data that doesn’t change often, so it can be used to segment and target specific groups of people over a longer period of time. Emails including offers can be specifically given to people living in a certain city, and birthday emails with special deals can be sent to contacts to help celebrate their special day and build a more personalized relationship.
Preference
If relevance is key, you need to know what interests your contacts and what they want to hear about. Preferential data such as this is typically managed by a subscription center that a recipient can use to opt into topics, products, services, newsletters, email frequency etc. based on interest. Creating a subscription center also requires a discussion of strategy. How often are you going to target people who opt into different interest areas? How often should a contact receive emails? How much content are you able to create?
However, preferential data can go out of date quicker than demographical data. Based on where you’re at right now in life or in your job, your interests could change. You might switch jobs or you might get promoted resulting in a change of what is relevant to you. Often times, when a recipient’s preferences change, they unsubscribe rather than update those preferences. To avoid unsubscribes, periodically directing users to update their preferences can be beneficial. You can also link the footer of all your emails to your subscription center making users less likely to opt-out and more likely to update.
RFM
Personalization data that is extremely valuable to any company focuses on recency, frequency, and monetization- or RFM data. This helps with identifying who your best customers are and what groups you should be targeting more to result in the biggest increase of sales. Some RFM data points to collect include first purchase date, last purchase date, total amount spent, number of purchases, average order value, and past products purchased. Utilizing this data enables you to map a customer’s relationship with your brand through their purchase history to see where they fall in their lifecycle marketing journey with your brand.
Behavior
Behavioral data focuses on a contacts direct interactions with your brand. Beyond email opens and link clicks, website traffic data is also valuable to track. A popular usage of behavioral information is capturing abandoned cart data to send targeted emails after a contact has not purchased an item. Offers and other tempting deals can be used to redirect their attention back to the website. Link clicks are also helpful in understanding general trends among all contacts of what calls to action are the most appealing, and what a specific contact is more interested in.
Collecting these data points results in pinpointed segments, personalized emails, and automated sends based on actions and interactions. Some of the most relevant emails in your inbox are likely populated with data and information specific to you. With the exploding popularity of wearables, Fitbit sends a personalized weekly email to show you visually where you’re at in reaching your goals. It encourages you to engage more with their brand and continue utilizing their product in new ways. Clothing stores often offer discounts that only certain subscribers can see based on loyalty (but more accurately, based on recency, frequency, or monetary purchasing value).
Sending the right personalized email at the right time is important to reach your audience. In fact, personalized emails deliver 6 times higher transaction rates than non-personalized emails. Personalization data is somewhat like “the man behind the curtain” who controls what you see and creates the email marketing magic that users engage with. Learn how to create your own lifecycle marketing magic by customizing and personalizing your marketing tactics!
