2 minute read

3 Ways Machine Learning Can Improve Your Email Campaigns

It is not news to anyone that the Retail and Financial Services landscapes are changing. For marketers, it is no longer sufficient only to send scheduled campaigns based around a marketing calendar, and reaching today’s consumers with the right messaging requires the assistance of machine learning to identify the moments and devices of highest engagement.

You may be wondering, how can you incorporate this into your marketing strategy? Here are three ways you can use machine learning to improve your email campaigns:

1. Understand where your audience is coming from and why that is important.

The number of people with smartphones is ever increasing with up to 88% of adults in the US, age 30-49 now using a smartphone. What are those people doing when they visit your site from a mobile device? Are they browsing for items to buy later when they get home, making that last minute purchase they forgot, looking up more details on an ad they saw, or comparing prices while in your brick and mortar? It’s pertinent that you as a marketer understand how a customer is interacting with your site so you can understand them better and message to them accordingly.

2.  Identify your high value customers.

Customers are also more savvy about scheduled sales and promotions. While there are still seasonal events such as back-to-school, Black Friday, and other holiday shopping promotions, they are becoming less dependable because making purchases online is much more convenient. Using data science generated models, it is possible to recognize the difference between the shoppers that come to your site or brick and mortar only for promotions, and the high value customers that buy with you repeatedly. Not only do you want to message to them differently, but ultimately turn the former group into the latter. This includes managing the post purchase relationship and the lead-up for both groups.

3. Personalize the experience.

Of course, the pinnacle of digital marketing is delivering a more personalized experience. By knowing whether buyers are browsing or buying, or better yet, if the browser would be a buyer with just a little nudge (perhaps free shipping or discounted price), a more personalized message can be crafted. Add in, things like “complete the look”, combining aspects of what the customer is viewing/carting and algorithmic cross-category correlation, and the proper call to action to purchase in-store or online and you have a recipe for success.

By applying machine learning to your marketing email programs, you stand a better chance of reaching your target group with the right message at the right time. According to Dean Abbott, Chief Data Scientist here at SmarterHQ, “machine learning can uncover patterns of behavior that would be impossible for marketers to find themselves--there are far too many combinations of behaviors to assess." Ultimately, this allows you to create the best, most personalized experience for your customers to keep ahead of the rising tide of digital competition.

For more details about product recommendations, check out Product Recommendations from the Eyes of a Data Scientist