Email Marketing Best Practices: Creating Relevant Email Campaigns with Dynamic Content
By Megan Ouellet, Director of Marketing for Listrak
August 6, 2007
For a company’s email marketing strategy to succeed, marketers must continually update and enhance their best practices in order to keep up with new technology, subscriber demands, and the competitive landscape. More importantly, marketers must find new ways to use the tools that they already have implemented. Doing so will enhance their email campaigns while keeping costs at a minimum.
Such a case exists for dynamic content. For some companies, using dynamic content to increase the relevancy and personalization levels of their email campaigns is new. For others, dynamic content has been used in the past, but to a limited extent.
Listrak, a leading provider of email marketing solutions, has put together the following white paper to help marketers learn new ways of using dynamic content to drive the relevancy of their email marketing campaigns. This, in turn, will build stronger customer relationships and encourage higher response rates.
Collecting the Right Data
Dynamic content, also known as dynamic message assembly, is a complex mail-merge technique. It relies on a single message template with multiple customizable fields. These fields merge with the company’s subscriber database or business applications to create highly personalized and relevant customer mailings based on specific user preferences, online behavior, demographics, and personalities. Instead of sending one all-inclusive message to every subscriber, dynamic content allows you to construct multiple versions of highly-targeted, specialized messages that speak to each subscriber individually. However, because it is template-based and the content is created once, stored, and reused as needed, these messages can be created with little effort.
The collection and management of subscriber data is critical to the success of dynamic campaigns. The following attributes should be collected in your subscriber database:
Preference: Dynamic campaigns depend on the level of detail you have on each subscriber. Chances are you already know some of the preferences of your subscribers, such as HTML or plain text format preference or frequency preference, as this information is easily obtained through a survey. However, the opportunity exists to collect even more preferences.
For example, you can track the offers that each subscriber responds to. Some subscribers take advantage of emails offering free shipping while others prefer to receive a discounted price. Some like to receive the offer in the form of a special coupon code while others prefer to have the discount automatically applied during the check out process. Some want to be able to order the product online while others prefer to place their order through a phone call to a customer service representative. Knowing this information allows you to send each subscriber the offer that has the highest chance of response, and it gives you the information you need to accurately prepare for the response each campaign will generate.
If you offer more than one product or service, you should also track product preferences of each subscriber. This way, you can send targeted messages containing information that interests the recipients. For example, a woman that shops online for clothing has a higher chance of responding to an email offering coordinating purses and shoes to a recent purchase she made as opposed to an email offering a sale on men’s suits.
Demographic: For a dynamic campaign to work, you need to know as much about your customers as possible. Personal information, such as gender, age, location, income level, and hobbies, can really help you target specific groups of subscribers for different email campaigns. For example, an online department store can send email campaigns offering seasonal clothing to subscribers in different areas of the country – a campaign sent in February might offer a sale on swimwear to subscribers in Florida and a discount on fleece outerwear to subscribers in Wisconsin. However, dynamic content allows the department store to be even more specific. Using the profiling information on age, location, and income level, along with other database fields, such as product preference and shopping habits, they can target a small, specific group of subscribers to announce the availability of a new haute couture line. While the email campaign will go out to a much smaller number of subscribers, it delivers the information to the subscribers that are not only interested in reviewing the clothing, but who also have the highest chance of making a purchase.
Collecting such personal information about subscribers might, at first, seem somewhat intrusive. After all, email marketing began as a way to communicate with as many people as possible in a quick and inexpensive manner. However, subscribers want to receive emails that are personalized and specific to their needs. In a study by ChoiceStream, 80 percent of consumers said they want highly-personalized emails that are relevant to them, and 64 percent said they are willing to share preference data in order to help marketers identify their needs. However, you do not have to depend on customer surveys and profiling questions to obtain this information. Simply by following subscribers’ clickstream data, you will gain an accurate understanding of their online habits, which will help you recognize what their interests are.
History: Subscribers’ online behavior gives a level of detail that marketers need; and, thanks to integration with web tools like Google Analytics, it is easier than ever for marketers to capture this information. Web analytics is a tracking device that follows subscribers after they click-through a call to action button on an email campaign. It allows you to tie conversion rates back to a specific email address. It also tells you the average amount of page views and time that specific subscribers spent on your site, as well as landing page bounce rates. This means that you have a way to quickly identify what subscribers left your site after reviewing the information on the landing page and which ones followed through with the goal of making a purchase, downloading a white paper, requesting additional information, etc.
Gathering this information will help you build an accurate subscriber behavioral profile, including browsing habits, call center activity, and purchase history. This information will help you distinguish what your subscribers are most interested in, so you can send them offers that are relevant to their needs.
Using the online department store example, you can cross-reference a purchase that a subscriber makes with other subscribers that have purchased the same item. Then, using the purchase history from the other subscribers, you can send the purchaser a follow up email offering those items. For example, if a subscriber purchased a pair of pajamas, you can follow up with an email saying that people that purchased those pajamas also purchased this robe and these slippers. The power of suggestion works, and subscribers that receive emails like this are likely to respond positively.
Data collection is an ongoing task. It is important that the information is gathered from every interaction you have with your subscribers in order to remain current and, therefore, effective. After all, subscribers’ needs will change over time through circumstances such as marriage, children, career movement, age, geographic location, etc.
