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Normalize inflated iOS 15 Email Open Rates with Unsupervised ML

Happy Holidays. In September 2021, Apple rolled out iOS 15. For high volume email senders, Apple Mail now essentially tracks every email sent as an "open." Seemingly if you are a campaign engineer, high volume sender or ESP, this change can radically affect 25% - 45% of your email subscriber base, across both B2B, B2C or D2C. Inside your email analytics platform, you should see the specific percentage of Apple Mail users in your database, thus a significant rate of change ( delta) regarding inflated "open rates." more

RealTimeML:  Email Send Time Optimization for Supply Chain Bottlenecks

Look for this trio of email-related organizations MessageGears, Validity, Vidi-Emi, to become trailblazers in the RealTimeML Email landscape. This article will examine the nascent concept of utilizing RealTimeML to optimize for open rates and ultimately engagement rates by using a SendTime Email Optimization model. The model will infer RealTimeML predictions for optimal engagement rates, which provides enormous value throughout your current supply chain. Additionally, we will share ongoing time trials to serve the model efficiently. more

JD Falk – a Decade Afterwards

I can still hear it. ‘Hee hee’. That’s good. We all have unique laughs, but few are distinctive. Fewer yet belly the true nature of the human being issuing them. British insult comedian Jimmy Carr has one such laugh, a tri-tone ‘dah dah DUH,’ rising on the third expulsion. It has a bell-like quality, ringing, embodying the deft touch that Don Rickles had of insulting while loving, something Carr has mastered. It lets you know that despite him having just said something shocking and horrid, he is laughing with, never at, reassuring the target, ‘all is well.’ more

RealTimeML Email Recommendation Engine Part V: Sentiment Analysis

In our continuing series on RealTime machine learning recommendations for email, we will discuss the importance of Sentiment Analysis in RealTime for Email. The initial feedback we've received from the field to develop a Sentiment Analysis model has been extraordinary. We initially want to dissect why we feel this model is essential, determine the components needed to serve real-time machine learning recommendations for higher engagement rates before the campaign send, and tailoring sentiment to the types of emails companies send. more

MailChimp Not Quite Ready for PrimeTimeML

With perhaps the most coveted valuation in the Email Industry at close to $10B, MailChimp is considered the most forward-thinking ESP on the planet boasting 12M customers, with outstanding brand recognition and an incredible leadership suite. But when it comes to installing RealTimeML, it's lollygagging mainly because it has not justified the actual value to productionalize RealTimeML across its client base. And also, because it is a challenge to execute! more

Real-Time Email Recommendation Engine Part IV: Image Optimization

Before we dive into optimizing predictive analytics for images using #RealTimeML, at our neighborhood Email Service Provider, there are a few people we need to acknowledge. First, we would like to recognize the Stanford Digital Economy Lab and its managing director Christie Ko. Christie reached out to us to potentially write articles for them, and we talked about several topics in the world of Machine learning (ML). She found our blog here on CircleID and ... more

How Does the Acceptance of All Domain Names in Open-Source Software Look in 2021?

A recent study carried out by Governance Primer on behalf of the Universal Acceptance Steering Group (UASG) identified trends in the acceptance of all domain names in software hosted at Github, the largest open-source repository globally. This research builds on top of previous efforts aimed at identifying the underlying issues that result in problems when different applications need to handle Internationalized Domain Names (IDNs) and new gTLDs, particularly when it comes to email addresses. more

Email Recommendation System-Abstract: Deployment Considerations (Part III)

Perhaps, one of the most thrilling moments of any machine learning project for a data science team is learning that they get to deploy the model in a production environment. However, this can be a daunting task or a simplified one, if all the tools are readily available. Machine-learning (ML) models "require" deployment to a production environment to deliver optimal business value, and the reality is that most models never make it to production. more

Email Recommendation Engine for ESPs – Text Length Optimization (Part II)

Popular email editors today have no way to optimize for text length. An email marketer may attempt to build her content but has no idea whether that content is optimized related to word count for a specific industry/client. As it relates only to text length, does the email have too many or too few words. Currently, there is no built-in predictive model to inform her. Well, until now. Last month we described an evolutionary real-time data-driven process for email campaign builders to have at their disposal. more

Vendor Selection Matters in the Domain Registrar Ecosystem

Domain name abuse is one of the most dangerous and under-regulated issues in digital business security today. Many of the largest companies in the world still lack basic domain security protocols, making them prime targets for bad actors. An attack on a domain can lead to the redirection of a company's website, domain spoofing, domain and domain name system (DNS) hijacking attacks, phishing attacks, network breaches, and business email compromise (BEC). more