IT Best Practices.
Highly Effective Email Marketing With Big Data
Since the 1990s, the use of email as a marketing tool has been highly effective. Although there are more fashionable marketing channels today, email marketing continues to hold its own. One reason for this is that the marketer does not have to wait for people to come to him via a website or social media platform, but can send his message directly to them. This is important because few people will remember or have sufficient motivation to go out of their way to read a marketer’s latest content unless it arrives at their inbox where they are forced to deal with the email, one way or another.
Email is also a more personal marketing medium because the recipient can choose to reply to an email. Unlike posting a comment on a blog post which is indexed by search engines and viewed by countless people, the reply email is seen by fewer eyes. This makes it a more private and therefore personal medium.
Despite these advantages, traditional email marketing has lost much of its power over the years because of over use of batch and blast email techniques. Batch and blast entails building a large list of email recipients with known interests and then relentlessly sending mass marketing emails. The process is a numbers game in which generic marketing emails and new list members are shoveled into a hopper at one end, and profits and unsubscribes come out the other end.
This technique has lost its effectiveness over the years because people are getting blasted by too many marketers as well as email spammers. Most email marketers either knowingly or unknowingly employ this strategy. They follow similar steps including sending generic emails to everyone on their list. The only difference between the “good” marketers and the abusive marketers is the frequency with which their emails are sent out.
There is a way around this diminishment of list profitability however, through the use of personalized emails. Personalized emails are custom-made to the individual characteristics of each list member. While perfect personalization is prohibitively expensive, a crude form of it is possible by segmenting a list according to its choices when put through various types of behavioral filters.
A filter can be an email focused on a specific topic or product in which those who clicked through the email and made a purchase are segmented from those who didn’t. Any situation where the list member’s interactions can be recorded and analyzed is a segmenting opportunity. After sufficient segmentation, emails are then customized and sent to profitable segments. The more finely segmented your list, the better your knowledge of your list’s behavior as individuals.
When you know someone well, it’s possible to make predictions about their purchasing behavior. The same is true with a well segmented list combined with the right analytical tools that can map behavioral patterns to purchasing patterns. There is a point where the profits derived from email list segmentation are overwhelmed by its cost. However, big data storage and analytical techniques bring this cost down and makes finely segmented lists of thousands or even millions of people highly profitable.
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