Online retailers are sending out too many irrelevant marketing emails that will never get opened. As a result, businesses lose money, sender reputation goes down, and subscribers opt out from communications they see no value in.
The AI-based Frequency Recommendation Engine (FRE) by eSputnik predicts whether a subscriber will open an email or not, based on the available data on the subscriber’s opens and clicks.
- FRE helps optimize email frequency and send more relevant content for better customer engagement and higher ROI.
- Increased customer engagement translates to higher sender reputation, and more emails reach the recipients’ Inbox.
eSputnik Frequency Recommendation Engine in Action
One of the eSputnik’s clients, an online shopping club for fashion and lifestyle, was sending up to 65 million of emails per month. In doing so, each subscriber was receiving 1 to 3 emails a day. To narrow down the audience for their email marketing campaigns, the company tried filtering out recipients who hadn’t opened any of the emails for 6 months. Still, the subscribers were receiving too many promotional and triggered emails while only few of the emails got opened or clicked. Our clients were looking for an easy way to target their audience using a wider range of parameters, including subscribers’ behavior in emails.
How This Works
To help eSputnik clients improve the efficiency of their email campaigns, the eSputnik Data Science team has developed an AI-powered Frequency Recommendation Engine (FRE). The engine utilizes machine learning algorithms to suggest the optimal email frequency for bulk and triggered campaigns, based on the calculated probability that the emails will get opened. To do this, FRE analyzes the already-collected user data on a number of different parameters.
This includes, among others:
- The total customer lifetime,
- The total number of emails received by a user within a campaign,
- The types of emails they opened the most often,
- The time since the last relevant open.
In this way, FRE helps identify the recipients who are most likely to be interested in receiving a particular message, and suggests filtering out those who’re likely to unsubscribe or simply ignore the email.
Actual tests have proven that using FRE can boost email click rate by about 63% through sending 40% fewer emails with only less than 2% fewer email opens.
- The eSputnik Frequency Recommendation Engine helps you boost your email performance ROI and improve sender reputation, by minimizing emails sent to subscribers who don’t want them.
- Machine learning algorithms behind FRE ensure that you can reduce your email marketing spend by up to 40% while improving your business performance.
- The eSputnik AI algorithms do most of the work, and you don’t need to spend much time and effort to achieve the results you want. All you need do is select a segment for your email campaign, and FRE will filter out the contacts who are unlikely to engage with the campaign.
eSputnik's Frequency Recommendation Engine is available on demand. If interested, please contact us at email@example.com.