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SmartData Collective > Business Intelligence > CRM > Predictive Analytics Methodologies Could Be The Secret To Great Emails
AnalyticsCRMPredictive Analytics

Predictive Analytics Methodologies Could Be The Secret To Great Emails

Ryan Farrell
Ryan Farrell
5 Min Read
predictive analytics for emails
Shutterstock Licensed Photo - By hanss
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MIT engineer Ray Tomlinson sent the very first email back in 1971. Nearly 50 years later, we are still trying to perfect the art of using this evolving medium. New advances in data technology are helping improve the way we use email. Predictive analytics methodologies are among these game changing technologies.

Contents
Predictive Analytics is Disrupting Email Communication in Fascinating WaysPredicting Behavior of Known ContactsUsing Customer Data to Create More Holistic CRM SolutionsHelping With Threat Detection Pertaining to Email Security Risks

Predictive Analytics is Disrupting Email Communication in Fascinating Ways

Email is a rapidly changing form of communication. The technology behind it used to be very basic, but today it employs a number of features that can help facilitate better communication between users.

Predictive analytics can change the nature of email communications in a number of ways. Here are some of the things to keep in mind.

Predicting Behavior of Known Contacts

It takes time to get to know anybody. It can be even more challenging online. People tend to be less inhibited when writing over the Internet, which means they are more likely to respond the way they feel like, without censoring themselves like they do in the real world.

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This means that you need to take time to understand the behavior of people you communicate with. The best place to start is by studying their historical responses to various statements. Predictive analytics will be able to help people draw interesting insights that they would not reach on their own. This is easier to do with tools like Unibox, which help you organize messages by a single recipient.

Using Customer Data to Create More Holistic CRM Solutions

Customer relationship management (CRM) technology has been around since the mid-1950s, a couple of decades before the first email was ever sent. However, predictive analytics technology has dramatically increased its effectiveness over the last few years.

Customer data can now be uploaded directly to a CRM database. Previous CRM models focused primarily on engagement statistics, which forced administrators to draw open-ended conclusions. Predictive analytics gives a much more granular overview of the users in your CRM tool. It can also draw industry-specific conclusions. As the CRM collects more detailed data on behavior of customers from a variety of brands in a given industry, the tool will be able to make very nuanced predictions of their future behavior.

Helping With Threat Detection Pertaining to Email Security Risks

Email security is a major concern today. The growing number of digital security breaches has caused people to become more concerned with guarding against malware and social engineering strategies.

The good news is that there are a lot of predictive analytics solutions that can help fight against malware. The technology has made some improvements over the last few years, but still have a ways to go. In 2016, FireEye warned that current email threat detection algorithms weren’t sophisticated enough to combat online fraud and privacy risks, writing:

“Ninety-one percent of cyber attacks begin with a spear-phishing email…Email gateways that rely on commodity intelligence, anti-spam filters and antivirus software aren’t purpose built for advanced threat protection. Advanced threats such as ransomware and spear-phishing emails easily bypass the signature-based and reputation-based prevention mechanisms that traditional security solutions use. This means emails that contain malicious URLs and malware-laden attachments are delivered to users.”

Over the two years since that report was written, a number of new predictive analytics features have been added to fight against email security threats. These include:

  • Determining the likelihood that an email is sent for fraudulent purposes based on its country of origin or association with a suspicious IP address (such as a known Tor or VPN IP.)
  • Identifying the words that are most commonly used in spam emails and using them to create a fraud score of an email in your inbox. Modern email fraud scoring algorithms are notoriously effective.
  • Looking for patterns between an email and previous emails sent for malicious purposes.

Combatting fraud will be one of the biggest priorities in the years to come. Brands in every industry will need to take a close look at the predictive analytics fraud scoring solutions companies offer to avoid ransomware and other security risks. Fortunately, technology keeps evolving to help us make this happen.

TAGGED:email analyticspredictive analyticspredictive analytics methodologies
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