At more than 40 years old, email marketing is still the marketing channel with the highest ROI--especially when it's personalized. Among the many emails that enter inboxes each day, it's no surprise that triggered messages, sent in response to specific consumer behaviors, account for 77% of email ROI, according to the Data & Marketing Association. Every year, personalized marketing automation technology provider Sailthru analyzes 250 retailers' shopping experiences and ranks them based on personalization prowess. The 2019 Retail Personalization Index shows that the retailers with the best email personalization are generally those with strong lifecycle-centric email marketing programs. Welcome emails have a significantly higher open rate than other marketing messages, and the brands that performed best in the Retail Personalization Index know how to capitalize on them.

Want to see better marketing results? You might want to jump on the artificial intelligence bandwagon. A February 2017 study of 200 businesses showed that retailers plan on expanding their marketing, particularly social media and mobile marketing, and incorporating artificial intelligence to better personalize the customer's journey as well as analyze results. The study was conducted by Sailthru, a cross-channel management platform company. When discussing what marketing channels best met marketing goals, 56 percent of businesses surveyed said their websites generate the most online revenue, with email marketing and mobile coming in next at 18 percent and 7 percent.

Machine learning is the new game changer in business technology. In a world where digital information volumes are doubling every two years on average, machine learning allows organizations to extract highly valuable information from enormous data stores at heretofore unimaginable speeds. Building and deploying machine learning solutions can be expensive, requiring investment in servers and storage, expanded networks, and data scientists. Alternatively, companies can invest in none of the above and turn to one of the many new machine learning as-a-service solutions. Getting started with machine learning in this way basically requires what virtually every organization is awash in today: data.

Machine learning is the new game changer in business technology. In a world where digital information volumes are doubling every two years on average, machine learning allows organizations to extract highly valuable information from enormous data stores at heretofore unimaginable speeds. Alternatively, companies can invest in none of the above and turn to one of the many new machine learning as-a-service solutions. Getting started with machine learning in this way basically requires what virtually every organization is awash in today: data. The "machine" in question here is a computer.

If you don't understand machine learning (ML), it's time to give yourself a crash course--especially as it relates to marketing. Just as SEO, programmatic buying, and other new technologies have revolutionized certain aspects of the marketing industry, ML figures to change the whole process, from how we handle simple marketing tasks to how we approach the larger task of telling brand stories. First, though, it's important to dispel common misunderstandings. Instead of developing the cognitive capabilities to rival or even surpass human intellect, ML is more about optimizing certain problem-solving processes. ML, in other words, is just a very advanced tool.

If you don't understand machine learning (ML), it's time to give yourself a crash course--especially as it relates to marketing. Just as SEO, programmatic buying, and other new technologies have revolutionized certain aspects of the marketing industry, ML figures to change the whole process, from how we handle simple marketing tasks to how we approach the larger task of telling brand stories. First, though, it's important to dispel common misunderstandings. Instead of developing the cognitive capabilities to rival or even surpass human intellect, ML is more about optimizing certain problem-solving processes. ML, in other words, is just a very advanced tool.

If you don't understand machine learning (ML), it's time to give yourself a crash course--especially as it relates to marketing. Just as SEO, programmatic buying, and other new technologies have revolutionized certain aspects of the marketing industry, ML figures to change the whole process, from how we handle simple marketing tasks to how we approach the larger task of telling brand stories. First, though, it's important to dispel common misunderstandings. Instead of developing the cognitive capabilities to rival or even surpass human intellect, ML is more about optimizing certain problem-solving processes. ML, in other words, is just a very advanced tool.

Machine-reengineering is a way to automate business processes using machine learning. Although machine-reengineering is new, companies are already seeing striking results with it, particularly in boosts to speed and efficiency. Studying 168 early adopters, we've seen speed improvements of two times or more for most business processes -- and some organizations are reporting speed improvements of 10 times or more. How do companies do it? Our study found that organizations are using machine-reengineering to establish new forms of human-machine collaboration that break through the bottlenecks of complex digital processes.

This post is a general overview of my thoughts on the future of marketing technology. In 2011, I was introduced to a startup called Sailthru. Back then, they were a young, Series A startup that had a neat "Forward to a Friend" email feature that was pivotal in our young daily deals startup (pre-IPO Groupon/LivingSocial). Later on, they grew into a full-service email marketing platform solution, an ambitious contender to market incumbents such as ExactTarget (pre-Salesforce), Responsys, Silverpop,etc. What sold me was results, and their core belief in data science to power 1:1 email personalization, beyond the first name.