Get Personal In Your Marketing Emails With Machine Learning

With Email Open Rates Declining, is Personalization your Best Way to Improve Performance?
When it comes to connecting with your customers and driving sales, there’s no channel more cost-effective than email. But as the number of marketing emails sent to inboxes each day continues to climb, and open rates continue to decline, consumers are becoming fatigued with too much information and too many offers. Now, according to top experts in the field, capturing the attention of your audience takes a more sophisticated, more personalized approach.
 
The Case for Personalization
Research shows that the vast majority of companies that use some form of personalization see boosts in their open and click-through rates. And studies show that customers like it too. 73% of consumers say they prefer to do business with companies that use personal information to make more relevant offers, while 80% of shoppers say they like emails that recommend products based on previous purchases. The statistics support the obvious conclusion: people want to see information and offers that are relevant to their interests.
 
What do the Experts Say?
“The best brands will be capturing behavior across channels (and) using it to improve customer targeting,” email marketing consultant Tim Watson says of the top marketing trends for 2016. While creating highly targeted campaigns, top brands will also turn to a more personalized approach to emails, Watson says, especially with items like discount offers.
 
How Machine Learning Can Help Personalization Keep Pace With Your Changing Audience
To achieve true one-to-one personalization in email on a mass scale, you must utilize high levels of automation that can only be achieved with the use of machine learning. Top email marketing influencer Kath Pay lays out how machine learning can be a major advantage for marketers:

Systems that use machine learning to analyze data can generate insights that constantly adjust and refine the content sent to different customers based on their different characteristics and behavior.

Instead of sending messages based on one point of past behavior, these systems continually take in data, analyze it and use those insights to personalize messaging without requiring marketers or their IT cohorts to keep tinkering under the hood to keep up with changes.

With the ability to continuously absorb and adjust to new data, high speed computing that leverages machine learning can be used to optimize subject lines, delivery times, copy, newsletters, and other content in real-time without losing time in lengthy A/B testing programs. The end result is a unique email that engages each individual customer, and ultimately, drives more sales.
 
The Results Speak for Themselves
Brands that use personalization in their email campaigns are seeing impressive results. And research shows that marketers who tailor their digital strategies to individual customers with custom content can benefit in a big way:
  • More than 90% of marketers who use some form of personalization see an increase of opens and click-through rates
  • 84% of companies that combine A/B testing with personalization see increased conversion rates (source: Econsultancy)
  • Marketers see an average increase of 20% in sales when using personalized web experiences.
  • One company, BustedTees, saw an 8% lift in revenue and a 17% increase in their email response rate simply by personalizing the time of email delivery
  • 78% of CMOs think custom content is the future of marketing.
 
Step 1 to Personalizing: Put your customer data to work
Most marketers have loads of data about their customers but they can’t put the data to work in a meaningful email campaign. The tools exist today to use this data and while the remarketing technologies for display ads use it effectively on your websites and display ads, this trend has not made its way to email yet. Using a pattern matching engine can unlock valuable insights about your audience that can be used to effectively personalize your email messaging.
 
Step 2:  Pair Customer data with Contextual Data
Marketers get a multiplier effect when pairing “known” customer data with “learned” first-party data gathered at the time of engagement. This learned data, also referred to as “contextual data”, includes location, time of day, weather, email client information, and device type of the user. Knowing these items and using them in the content decision process, you can dramatically improve the relevancy and effectiveness of your emails.
 
Don’t Get Overwhelmed by the Data – Put the Machines to Work
Using all of the available data about your customers is too much for marketers alone to manage. Many will fall back on simple personalization techniques like using a customer’s name in the email. However, with today’s advances in machine learning there are solutions that can crunch the numbers and give you meaningful data insights in real-time that can be used to tailor your email down to the individual level.
 
Is Personalizing Email a Requirement today?
Answer- Yes.
The experts recommend it and your customers have requested more relevant content. Personalization is no longer optional if you want to keep your customers happy. Creating unique, personalized emails takes a lot of work but the results show that the added effort pays for itself.
 
About Wylei
At Wylei, we use machine learning to deliver Adaptive Content™–a whole new level of personalization for companies looking to breathe new life into their email campaigns. Wylei’s machine learning technology finds subtle patterns in your campaign performance that identify the best content to present, in real-time, to each individual. Our clients average a 27% increase in Click-to-Open rates, a 10X ROI and a correlated increase in sales and conversions. To learn more about Wylei please visit www.wylei.com