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Write Better Email Subject Lines with Machine Learning and Oracle Responsys

By Preethika Sathyamangalam Kalyanasundaram

As a marketer, you likely dedicate a lot of creative energy to drafting copy that captures the curiosity or interest of the recipient – especially when it comes to email subject lines.

Many marketers use multivariate testing (MVT) to narrow in on the best subject lines for their subscribers. But what if you could use machine learning to predict how well your subject line will perform – even before sending?

Testing email subject line impact

The Subject Line Prediction feature – part of Advanced Intelligence for Oracle Responsys – uses a machine-learning algorithm to analyze your written subject line, predict open rates, and suggest improvements. You can check numerous variations of your subject line and choose the best one so that your recipients receive only the most engaging version.

This means that Oracle Responsys Campaign Management users can now get a prediction for subject lines used in every email campaign prior to deployment.

This feature provides a collection of capabilities to help you optimize each subject line, including:

  • Insight into whether the subject line is “good” or “poor”
  • Predicted open rate and the lift compared to the average open rate
  • Key phrases that are likely to have an impact on the subject line
  • Suggestions on what aspects of the subject line worked and did not work
  • Insight into top-performing key phrases in your account with their average open rate and usage frequency
  • Subject lines that are similar to the given subject line from the historical data along with their corresponding average open rate
  • Predictions not only for English subject lines, but Spanish, Chinese, Hebrew, French, and more

How it works

The data science implementation of the Subject Line Prediction feature contains two parts: the learning phase, which happens behind the scenes, and the prediction phase.

During the learning phase, the algorithm will consider the data present in your account and identify “good” and “poor” historical subject lines based on their open rates. Then, the algorithm analyzes the words and phrases in each subject line and builds a data science classification model.

After a model has been built, a marketer can request predictions for subject lines they provide from the message designer. In the below example, the subject line “Bored with the usual? Designer wear you will love, curated especially for you” was processed and fed into a model which has already been trained on this account’s historical subject lines.

Based on the indication pictured, this subject line is predicted to result in a “good” open rate.

Responsys will display subject lines that are similar to the given subject line from the historical data along with their corresponding average open rate. This can help marketers gain insight into how similar subject lines have performed in the past.

In addition to providing the predicted open rate and similar subject lines, Responsys will also provide insight into top-performing phrases along with the average open rate and usage frequency. This provides insight into the top-performing phrases you can use in crafting new subject lines, as well as how frequently they’ve been used.

Key capabilities are highlighted in the screenshot below.

Key takeaway

Email subject lines continue to be a fundamental aspect of winning consumer attention. Marketers can deploy emails with higher confidence by infusing machine learning and the scientific method into the art of copywriting.

For more information about Subject Line Predictions, visit our resource page.

Whether you’re a B2B or B2C marketer, or both, we have more resources for you.

Download the Personalized Marketing for B2B Marketers ebook here.

Download the Personalized Marketing for B2C Marketers ebook here.

Or, to find out more about the tools needed to succeed as a digital marketer, check out Oracle Marketing.

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